The Relationship Between Counselor Educator Technology Self-Effic

Chapter 1: Introduction to the Study

Introduction

Although it has been nearly 2 decades since professional counseling organizations

began to recognize the need for training to include the impact of technology in

counseling, there has been little attention given to training counseling students in this area

(Anthony, 2015; Pipoly, 2013). The field of distance counseling is recent, and research

regarding counselor training in distance counseling is also new (Anthony, 2015). The

limited research available indicates that mental health professionals often lack training

and information on distance counseling (Blumer, Hertlein, & VandenBosch, 2015; Bruno

& Abbott, 2015; Cabaniss, 2002; Finn & Barak, 2010; Glueckauf et al., 2018; Tanrikulu,

2009). Considering the evolution of the counseling profession towards the use of distance

counseling, Callan, Maheu, and Bucky (2017) described the lack of training in telemental

health as a crisis.

The need for counselors trained in distance counseling is growing as the use of

distance counseling is expected to continue to increase. However, based on what

counselors report they are not receiving adequate training in distance counseling.

Research indicates counselors lack training and that the training available is often

postgraduate and can be costly (Anthony, 2015). The lack of training among counselors

may extend to counselor educators as well, a possible explanation for the training deficit

(Trepal, Haberstroh, Duffey, & Evans, 2007). The use of technology in counseling is an

important part of professional development and should be included in master level

counselor preparation programs (Anthony, 2015; Blumer et al., 2015; Cabaniss, 2002;

Cartreine, Ahern, & Locke, 2010; Callan et al., 2017; Finn & Barak, 2010; Glueckauf et

al., 2018; Kozlowski & Holmes, 2017; Pipoly, 2013).

The use of technology is an essential component of distance counseling. Prior use

of counseling related technology and past use of distance counseling has been associated

with a more positive attitude towards distance counseling (Simms, Gibson, & O’Donnell,

2011). Prior research on technology integration in education indicates that intrapersonal

factors such as self-efficacy play an important role in technology integration (Davis,

1989; Niederhauser & Perkmen, 2008). In addition, self-efficacy is understood to be a

significant factor in motivation and behavior (Bandura, 1977). The influence of self-

efficacy on technology integration can be applied to distance counseling training as well.

Technology is used in distance counseling and training is preferable to include a hands-

on approach (Anthony, 2015; Hilty et al. 2017; Holmes, Hermann, & Kozlowski, 2014;

Manring, Greenberg, Gregory, & Gallinger, 2011; Shandley et al. 2011). Counselor

educators’ perceptions of their skills could have an impact on their confidence and their

teaching behavior.

In this study, I investigated the self-efficacy of counselor educators in relation to

distance counseling instruction. This study provides additional insight into this area of

counselor education that has been largely ignored. Counselor training for distance

counseling in master programs is an important area to investigate, in order to better

understand the training deficit in this area. Distance counseling does have the potential to

increase access for rural areas and underserved communities (Flaum, 2013), but it must

be done in accordance with professional standards (Richards & Vigano, 2013; Hilty,

Maheu, Drude, & Hertlein, 2018). The training of counseling students is an essential step

in that process, yet little has been investigated. I began this search by investigating

intrapersonal factors of counselor educators that might impact training. Specifically,

counselor educator self-efficacy with technology and the relationship of this intrapersonal

variable on distance counseling instruction.

This chapter will provide background information on the research study;

examining counselor educators self-efficacy with technology integration and teaching

master level students distance counseling skills. In this study, I reviewed past research

relevant to training in distance counseling and then discussed why this problem is

important to study. In addition, I describe the methodology that was used and variables

that were explored. I also explained the theoretical basis for the study and assumptions

and limitations of the study. Finally, I clarify definitions to that were used.

Background

Technology has changed the way people work, play, form relationships, and

communicate. The field of mental health has also been impacted by evolving

technological advances. It has become more important for the mental health field to adapt

to the widespread use of technology, both by counseling professionals and their clients,

and to keep up with technological advances (Anthony, 2015; Mallen, Jenkins, Vogel, &

Day, 2011). However, the counseling profession has not been responsive to the changes

resulting from technological advances, especially regarding counselor training to utilize

technology for distance counseling (Allenman, 2002; Anthony, 2015; Callan et al., 2017;

Cartreine et al., 2010; Pipoly, 2013; Reljic, Harper, & Crethar, 2013). There have been

growing concerns that counselors are unprepared for the evolution of technology in

counseling.

There is no definitive terminology used regarding the use of technology to

provide counseling services; many terms are used to describe distance counseling. The

American Counseling Association (ACA) defined distance counseling as “the provision

of counseling services by means other than face-to-face meetings, usually with the aid of

technology” (ACA, 2014, p. 20). Distance counseling includes synchronous and

asynchronous methods of communication that include texting, email, chat, bulletin

boards, smartphone applications, or videoconferencing (Myers & Turvey, 2013). I used

the term distance counseling throughout this study.

The use of distance counseling is expected to continue to grow (Barnett, 2011;

Backhaus et al., 2012; Cartreine et al., 2010; Haberstroh, Parr, Bradley, Morgan-Fleming,

& Gee, 2008; Layne & Hohenshil, 2005; Menon & Rubin, 2011; Richards & Vigano,

2013; Shandley et al., 2011). It is important that counselors have appropriate training to

provide distance counseling services (Cartreine et al., 2010; Hilty et al, 2018; Glueckauf

et al., 2018; Maheu et al., 2017). There has been a growing body of research on distance

counseling; however, little research has been done regarding training (Anthony, 2015).

The few studies that have been conducted indicate that online practitioners often lack

training for distance counseling but provide services online regardless (e.g. Blumer et al.,

2015; Bruno & Abbott, 2015; Finn & Barak, 2010; Chester & Glass, 2006; Maheu &

Gordon, 2000). Further, counselors reported they feel undertrained regarding distance

counseling (Bastemur & Bastemur, 2015; Benavides-Vaello, Strode, & Sheeran, 2013;

Blumer et al., 2015; Cipolletta & Mocellin, 2017; Santhiveeran, 2009; Shaw & Shaw,

2006; Simms et al., 2011). The practice of distance counseling is expected to continue to

increase and there is a gap in training that must be addressed (Anthony, 2015; Callan et

al., 2017; Pipoly, 2013). There have been concerns that counselor training programs have

not been meeting the needs of students concerning distance counseling (Anthony, 2015;

Blumer et al., 2015; Pipoly, 2013). The use of technology in counseling requires training;

however, many counselors have reported they lack training in this area.

Professionals have been calling for master programs to include distance

counseling training (Anthony, 2015; Blumer et al., 2015; Callan et al., 2017; Glueckauf et

al., 2018; Pipoly, 2013). There have been concerns that counseling programs have not

been preparing students for the current and future work environment (Anthony, 2015;

Cabaniss, 2002; Callan et al., 2017; Glueckauf et al., 2018; Maheu et al., 2017; Pipoly,

2013). The need to train counselors regarding technology in counseling has also been

recognized by The Council for Accreditation of Counseling and Related Educational

Programs ([CACREP], 2001, 2009, 2016) and The Association for Counselor Education

and Supervision ([ACES], 2007; ACES Technology Interest Network, 1999). Counselor

training programs are obligated to include distance counseling in their programs, but they

do not appear to be meeting the needs of students. Counselors must be prepared to work

in a technology supported environment (Glueckauf et al., 2018; Maheu et al., 2017).

Mental health practitioners are expected to have the skills necessary to work as a member

of an integrated team that utilizes technological tools (Maheu et al., 2017). In addition,

the practice of distance counseling is a viable career option (Pipoly, 2013). There are

practitioners who have been working online for years (Haberstroh & Duffey, 2011).

Counseling students have expressed interest in learning about distance counseling.

When asked, students have reported that they would like more information on distance

counseling practices (Bastemur & Bastemur, 2015; Blumer et al., 2015, Tanrikulu, 2009).

Despite the need for and student interest in distance counseling training, training is

lacking.

If training for distance counseling should occur in counselor education programs,

why is it not occurring? One explanation may be barriers with technology integration.

Distance counseling uses various technological tools. Student trainees and clients

reported technical problems were a significant factor in their distance counseling

satisfaction (Haberstroh, Duffey, Evans, Gee, & Trepal, 2007). Practitioners must have

adequate skills and knowledge of the technologies used for distance counseling to

practice, to train (Haberstroh et al., 2008), or to supervise others in distance counseling

(Haberstroh & Duffey, 2011).

Haberstroh et al. (2007) noted that few counselors are trained in distance

counseling which may be indicative that few counselor educators are trained in distance

counseling as well. Experience or training with distance counseling has been associated

with clinicians’ attitude about distance counseling (Simms et al., 2011). The lack of

training could impact a counselor educator’s attitude about distance counseling, including

self-efficacy, ultimately influencing counselor educator classroom behavior. Past research

in technology integration has found an association between self-efficacy and technology

integration (Anderson, Groulx, & Maninger, 2011; Bunch, Robinson & Edwards, 2012;

Niederhauser & Perkmen, 2008; Perkmen & Pamuk, 2011, Perkmen, 2014). Counselor

educator self-efficacy could be a barrier to technology integration relating to distance

counseling.

Technology integration has been researched in education to better understand

barriers to integrating technology into classrooms. The research indicated that teacher

attitudes and beliefs were found to influence teacher technology integration (e.g. Bunch

et al., 2012; Ertmer, Ottenbreit-Leftwich, Sadik, Sendurur, & Sendurur, 2012; Gu, Zhu,

& Guo, 2012; Holden & Rada, 2011; Hew & Brush, 2007; Kim, Kim, Lee, Spector, &

DeMeester, 2013; Niederhauser & Perkmen, 2008). There are differences between

student and educator levels of comfort with technology. In fact, Geer and Sweeney

(2012) found that students had concerns about teachers’ abilities to use technology in the

classroom. Nearly 100% of young adults, especially college students, use the internet

regularly (Pew & Pew, 2018). The college student population is more comfortable with

using the internet and technology than other groups. Indeed, students may be more

comfortable with technology than educators.

With this study, I investigated one possible factor for the deficit in training,

counselor educator self-efficacy with technology. It has been understood that technology

acceptance, which includes self-efficacy and outcome expectation, is influential in the

implementation of distance counseling (Bruno & Abbott, 2015; Simms et al., 2011;

Terpstra et al., 2018). There is a body of research supporting the importance of perceived

self-efficacy as influential in technology integration in the classroom (Anderson et al.,

2011; Bunch et al., 2012; Ertmer et al., 2012; Gu et al., 2012; Holden & Rada, 2011; Hew

& Brush, 2007; Kim et al., 2013; Niederhauser & Perkmen, 2008, Perkmen & Pamuk,

2011, Perkmen, 2014, Perkmen & Surmelioglu 2016, Tezci, 2011a, 2011b). Considering

the importance of technology in distance counseling and the need for integrating the

technology into the classroom in order to teach distance counseling, self-efficacy with

technology was an appropriate construct to explore. In this study, I examined one

possible deficit, intrapersonal factors relating to self-efficacy with technology among

counselor educators, and the relationship with distance counseling skills in clinical skills

courses.

Problem Statement

Distance counseling is becoming more commonplace in the field of mental health

practice but despite the increasing use of technology in counseling, counselor training is

not keeping up with the demand (Anthony, 2015; Callan et al., 2017; Hilty et al., 2018;

Pipoly, 2013). Although counselors have been practicing online, the available research

indicates a majority of providers have been doing so without adequate training (Bruno &

Abbott, 2015; Chester & Glass, 2006; Maheu & Gordon, 2000; Shaw & Shaw, 2006) and

not adhering to ethical standards of professional organizations (Chester & Glass, 2006;

Finn & Barak, 2010; Heinlen, Welfel, Richmond, & Rak, 2003; Maheu & Gordon, 2000;

Santhiveeran, 2009; Shaw & Shaw, 2006). The evolution of technology in counseling is

an important aspect of counseling practice and counselor training. The Council for

Accreditation of Counseling and Related Educational Programs (CACREP) accreditation

requirements include the need to address the impact of technology in counseling,

however, students have reported that they had not received training in this area

(Benavides-Vaello et al., 2013; Blumer et al., 2015; Bruno & Abbott, 2015; Tanrikulu,

2009). There has been concern that the lack of attention paid to training in distance

counseling has led to counselors unable to meet the demands of the future marketplace

(Anthony, 2015; Callan et al., 2017; Gilkey, Carey, & Wade, 2009; Hilty et al., 2018;

Pipoly, 2013). Although training students in the area of distance counseling is necessary,

based on the scant research available, students reported they have not received the

training needed to prepare them adequately in this area.

Researchers who have examined distance counseling have reinforced the

importance of training counselors in distance counseling practices (Abbott, Klein, &

Ciechomski, 2008; Anthony, 2015; Finn & Barak, 2010; Gentile & Liu, 2008; Haberstroh

et al., 2008; Hilty et al, 2018; Kozlowski & Holmes, 2017; Shandley et al., 2011; Simms

et al., 2011; Tanrikulu, 2009; Trepal et al., 2007). The practice of distance counseling

requires an understanding of the unique characteristics of counseling via the use of

technology. The face-to-face skills are not wholly transferable in the online world where

non-verbal communication is absent, and communication may be exclusively text-based

and asynchronous (Haberstroh et al., 2007; Haberstroh & Duffey, 2011; Johnson, 2017;

Shandley et al., 2011; Trepal et al., 2007). Training is necessary, unfortunately it is

available in post-graduate settings and may be expensive, costing hundreds of dollars

(Anthony, 2015).

Counselors themselves have reported that they lack the training required to

provide competent distance counseling services (Benavides-Vaello et al., 2013; Finn &

Barak, 2010; Hertlein, Blumer & Smith, 2014; Santhiveeran, 2009; Simms et al., 2011;

Shaw & Shaw, 2006; Tanrikulu, 2009). In fact, counselors may be unaware of the unique

aspects of distance counseling and feel confident to practice without understanding the

complex legal and ethical requirements or practice issues relevant to distance counseling

(Trepal et al., 2007). This lack of knowledge or training is of concern, the lack of training

could result in client harm (Goss & Anthony, 2009; Holmes, 2008; Shandley et al., 2011;

Terpstra et al., 2018). Allenman (2002) has also expressed concerns that unethical

practices have a negative impact on the reputation of the counseling profession. There are

consequences to clients, clinicians, and to the counseling professions legitimacy resulting

from the deficit in counselor training.

Unfortunately, the research indicated that a variety of online mental health

practitioners have been failing to meet ethical and legal standards. There has been some

research into the practice of distance counseling; through interviewing practitioners or

examining websites of online practitioners. The findings indicated that a majority of

mental health professionals conducting distance counseling services were not adhering to

ethical standards established by professional organizations including the ACA, (2014)

and the National Board for Certified Counselors ([NBCC], 2016b) (Chester & Glass,

2006; Finn & Barak, 2010; Heinlen et al., 2003; Maheu & Gordon, 2000; Santhiveeran,

2009; Shaw & Shaw, 2006).

The organization that is instrumental in counselor education, CACREP,

responded to the influence of technology in counseling practice by updating counselor

training to include the impact of technology on counseling into curriculum (CACREP,

2001, 2009). As a result, the CACREP standards were updated to incorporate

technological influence on the counseling profession into counseling curriculum

(CACREP, 2009; CACREP, 2016). Counselor education programs have the

responsibility of preparing students to be competent to practice, including with regards to

the impact of technology in counseling services (CACREP, 2016). However, counselor

educators have the choice on how, if, or to what degree they implement distance

counseling into their curriculum (CACREP, 2016).

Similarly, the ACES Technology Interest Network developed competencies

regarding technology and the use of technology in the field of counselor education nearly

two decades ago (ACES, 2007). ACES (2007), recognized the impact of technology on

varying aspects of the counseling profession and developed Technical Competencies for

Counselor Education Students: Recommended Guidelines for Program Development in

1999 (ACES, 1999). Specifically, ACES (year) proposed technology competencies “be

infused throughout counselor education curriculum at the masters’ and doctoral program

levels” (p. 1). However, based on student reports and past research on practice, this does

not appear to be occurring (Blumer et al., 2015; Cabaniss, 2002; Hilty et al., 2015;

Tanrikulu, 2009).

Despite the call to integrate technology into counselor training, there has been

little research done regarding training counseling students to use technology (Anthony,

2015; Fitzgerald, Hunter, Hadjistavropoulos, & Koocher, 2010; Kozlowski & Holmes,

2014; Shandley et al., 2011). It is concerning that few counselors possess NBCC distance

counseling certification (DCC), conduct distance counseling, or to provide the necessary

training to counseling students (Trepal et al., 2007). The DCC has been changed to Board

Certified Telemental Health Provider (BC-TMH)

The need for counselors trained to provide online services is increasing; however,

counselors report they lack the skills and training. The need for graduate training

programs to include distance counseling into counseling programs is necessary to ensure

counselors are prepared to work with the unique aspects of distance counseling upon

graduation (Anthony, 2015; Blumer et al., 2015; Callan et al., 2017; Glueckauf et al.,

2018; Hertlein, Blumer, & Mihaloliakis, 2014; Hilty et al., 2017; Mallen, Vogel, &

Rochlen, 2005; Pipoly, 2013). The use of technology in counseling has become

widespread and all students should be provided with the necessary skills to ensure ethical

and legal practice. There is a training crisis that must be addressed (Callan et al., 2017).

The information gained through this study can be used to support counselor educators

training needs to ensure that students are prepared for the impact of technology on the

counseling profession. Investigating counselor educators’ self-efficacy can provide

insight into the training needs of counselor educators as well.

Counseling students, counselors, other mental health professionals, and

professional organizations agree that training for distance counseling should occur in

master level counselor education programs (Anthony, 2015; Blumer et al., 2015;

Cardenas, Serranno, Flores, De LaRosa, 2008; Glueckauf et al., 2018; Hertlein, Blumer,

& Smith, 2014; Hilty et al., 2017; Mallen et al., 2005; Pipoly, 2013, Trepal et al., 2007).

However, based on prior research on practice and experience this training is reportedly

not occurring. I explored one possible area related to lack of training; specifically,

counselor educators perceived self-efficacy with technology. Past research into

technology integration has indicated that intrapersonal factors, such as self-efficacy have

an influence on technology integration in the classroom (Kim et al., 2013; Ertmer et al.,

2012). This study considered one variable which may be related to counselor educator’s

incorporation of distance counseling training into the classroom, the impact of counselor

educator’s technology self-efficacy in relation to distance counseling skills instruction in

the master level classroom.

In addition to self-efficacy, demographic variables were included in statistical

analysis. Both correlation and regression models were developed to determine which, if

any, demographic variables were significant predictors of including distance counseling

skills in their class.

Purpose of the Study

The purpose of the study was to examine if there was a statistically significant

relationship between counselor educators’ self-efficacy with technology and counselor

educator inclusion of distance counseling instruction in the master level classroom. In

addition, the study also examined if there were any significant demographic factors that

predicted the inclusion of distance counseling skills instruction in the skills-based

classroom of master level counseling programs. Counselor educator self-efficacy with

technology was be measured using three subscales from the Intrapersonal Technology

Integration Scale (ITIS), and the full score of the ITIS as well. Specifically, the self-

efficacy (SE), outcome expectations (OE), and interest (INT) subscales. The inclusion of

distance counseling skills was based on counselor educator self-reports. Finally,

demographic data was collected using an online survey, along with the ITIS questions.

Research Questions and Hypotheses

In this research study, I examined if there was a relationship between counselor

educators’ self-efficacy with technology, as measured by the full score of the ITIS and

each of the individual subscales; self-efficacy, outcome expectations, and interest, and

counselor educator’s instruction of distance counseling skills in the master level

classroom.

RQ1: Is there a relationship between the level of perceived self-efficacy with

technology as measured by the Intrapersonal Technology Integration Scale (ITIS) and the

inclusion of distance counseling skills in the skills-based courses in which they are an

instructor, as measured by self-report?

H11: There is a statistically significant correlation between counselor educator

self-efficacy with technology, based on scores on the self-efficacy, outcome expectations,

and interest subscales and the total score from the ITIS and teaching distance counseling

skills in the classroom based on self-report.

H01: There is not a statistically significant correlation between counselor educator

self-efficacy with technology, based on scores on the self-efficacy, outcome expectations,

and interest subscales and the total score from the ITIS and teaching distance counseling

skills in the classroom based on self-report.

RQ2: Which, if any demographic variables are predictive of counselor educator

inclusion of distance counseling skills in the skills-based courses in which they are an

instructor, as measured by self-report?

H12: There is a relationship between demographic variables, counselor educator

self-efficacy with technology, based on scores on the self-efficacy, outcome expectations,

and interest subscales and the full score from the ITIS, and teaching distance counseling

skills in the classroom based on self-report.

H02: There is a not a relationship between demographic variables, counselor

educator self-efficacy with technology, based on scores on the self-efficacy, outcome

expectations, and interest subscales and the full score from the ITIS, and teaching

distance counseling skills in the classroom based on self-report.

Theoretical and/or Conceptual Framework for the Study

Bandura’s theory of self-efficacy is the framework for the study. Self-efficacy, in

short, is one’s belief in his or her ability to perform a task (Bandura, 1977, 1997). The

development of perceived self-efficacy is a process that includes the person, behavior,

and environment. The individual’s beliefs in his or her ability are formed through a

process of environment interaction and successes or failures in completed tasks (Bandura,

1989). Self-efficacy beliefs are a substantial factor in motivation and behavior. Bandura

included two components: self-efficacy expectations and outcome expectations (Resnick,

2011). Both factors influence the performance of activities (Resnick, 2011). Self-efficacy

has been found to be associated with several behaviors (Renick, 2011) and is also

important in motivation to change or adopt a behavior (Bandura, 1977).

The theory of self-efficacy has been applied to many tasks, including technology

integration. Technology is an important component of distance counseling and in training

counselors to practice distance counseling (Myers & Turvey, 2013). Distance counseling

requires the use of various hardware and software. Technological tools such as

computers, smart phones, webcams, and the accompanying software require knowledge

to use effectively, especially regarding the competent delivery of therapy services. Given

the importance of perceived self-efficacy and outcome expectation on behavior and the

relevance to technology integration, it is an appropriate starting point to examine

counselor educator technology integration in the form of distance counseling training and

skills development in the classroom

Nature of the Study

I used an anonymous online survey to collect quantitative data on counselor

educator self-efficacy with technology and their inclusion of distance counseling skills in

master level skills-based classes they taught. Self-efficacy with technology has been

examined in education to better understand barriers to technology integration that are

intrapersonal in nature. I examined the variables, counselor educator self-efficacy with

technology and teaching distance counseling skills in the master level classroom, as a

starting point in understanding barriers to training students in distance counseling skills.

Self-efficacy and outcome expectation are recognized as significant predictors of

behavior (Bandura, 1989) and a logical starting point in examining counselor educator

behavior regarding instructional habits in the classroom.

A correlation study was selected to understand the relationship better, as it occurs

in an educational setting, between counselor educator self-efficacy with technology and

their inclusion of distance counseling skills training in the master level classroom. The

problem exists in the educational environment and examining the problem in the natural

setting provides insight into the issue and hopefully can be used to better prepare

counseling students for the changing landscape in mental health practice. Similarly, the

study is designed to collect data directly from counselor educators with experience in

training counselors. An online survey was selected to collect data from a wider

geographic area which provided information on a more significant number of counseling

programs across the united states. Based on the results of the correlation, a logistic

regression analysis was performed using the subscale scores, full scale score, and the

demographic data collected to examine if any of the demographic data was predictive of

counselor educator inclusion of distance counseling skills in their master level skills-

based class.

Definitions

Asynchronous: Not simultaneously, asynchronous communication methods refer

to communication methods that do not occur in real time such as email (Perle, Langsam,

& Nierenberg, 2011).

Distance counseling: NBCC (2016a) defined distance counseling as professional

services delivered through electronic means which includes telephone, secure e-mail,

chat, videoconferencing, or stand-alone programs. There is no agreement on terminology

nor definitions regarding distance services.

Internet supported psychological interventions (ISPIs): Defined by Bruno and

Abbott (2015) to include a variety of web-based interventions including self-guided

intervention, synchronous and asynchronous communication methods, therapeutic

software, and other online activities such as blogs or self-help groups.

Online counseling: Richards and Vigano (2013) defined online counseling as a

therapeutic intervention facilitated through computer-mediated communication

technologies conducted by a trained professional, either stand-alone or as an adjunct to

other services.

Self-efficacy: One’s belief in their own ability to “exercise influence over events

that affect their lives” (Bandura, 1994, p. 71). It can be simply stated as one’s belief in

their own ability.

Synchronous: At the same time, concurrent. Synchronous communication

methods refer to communication in real time such as using video, instant messaging, or

instant chatroom (Perle et al., 2011).

Telemental health: The general delivery of mental health services via technology

(Zur, 2018). The services are provided by mental health professionals.

Videoconferencing: A synchronous communication method through the use of a

webcam and associated software the use of video to transmit and receive video and audio

(Yellowless, Shore, & Roberts, 2009).

Assumptions

In this study, I had assumptions that individuals responding to the survey would

respond appropriately. For example, it was assumed that all participants answered the

questions truthfully and to the best of their ability. A survey method was selected to

ensure anonymity because some of the content might be perceived as sensitive by

counselor educators, especially regarding their level of confidence with technology. It

was also assumed that counselor educators have the information required to answer

questions about online therapy and counselor education. It was expected that counselor

educators had at least a basic knowledge of distance counseling and accurately reported

their teaching of distance counseling skills.

In addition, I assumed, based on validation studies, that the ITIS (Niederhauser &

Perkmen, 2008) is a valid measure. Niederhauser and Perkmen (2008) determined that

each subscale has strong internal consistency and each subscale is a distinct construct.

Factor validity and internal consistency support the instrument. However, although the

validity of the ITIS is established, the ITIS was developed for use in education and the

use in counselor education is a new use of the scale. The ITIS has been used in other

education-related studies and the validity accepted (Bunch et al., 2012; Benigno, Chifari,

& Chiorri, 2014).

Scope and Delimitations

There is a deficit in distance counseling training in university counseling

programs. I explored one possible factor: counselor educator self-efficacy with

technology. Technology is an important part of distance counseling work and problems

with using technology can result in both clients and counselors feeling unhappy and

unsatisfied with distance counseling (Trepal et al., 2007).

The importance of technological knowledge on the distance counseling process

can be applied to counselor training in distance counseling skills as well. To train

counselors on the skills required to conduct distance counseling, the counselor educator

may benefit from self-confidence in their knowledge and skills. Past research in

technology integration confirms the impact self-efficacy has on integrating technology in

the classroom (Bunch et al., 2012; Hew & Brush, 2007; Kim et al., 2013; Niederhauser &

Perkmen, 2008; Perkmen & Pamuk, 2011).

I examined the relationship between self-efficacy with technology and the

instruction of distance counseling skills in the master level classroom. There is a body of

research that supports intrapersonal factors, including self-efficacy, exerting influence

over technology integration in an educational setting (Ertmer et al., 2012; Holden &

Rada, 2011). The integration of technology is an important factor in distance counseling

skills. There are different technologies utilized in distance counseling and having the

technical knowledge to use the technological tools effectively has been found to be an

important aspect of distance counseling practice (Trepal et al., 2007; Haberstroh et al.,

2008).

Counselor educators who have experience in teaching a counseling skills class

such as practicum or internship were surveyed through an online survey for this study. I

examined intrapersonal factors that were hypothesized to be associated with technology

integration, specifically self-efficacy, and also related factors included in the ITIS,

outcome expectation and interest. The availability of technology in the classroom was

also important to know and was included in the survey. However, past research has found

that the availability of technology in the educational environment does not wholly explain

barriers to technology integration (Hew & Tan, 2016). Prior use of distance counseling

and prior training have also been noted to be associated with greater acceptance of

distance counseling (Simms et al., 2011) so those questions were included as well.

The sample was drawn from counselor educators throughout the United States

from both CACREP accredited and nonaccredited master counseling programs. The

findings may not be generalizable to all counselor educators because of the diversity

among counselor educators. In addition, participants were contacted by e-mail and

invited to participate in an online survey. Because the survey is online, it introduced the

possibility that nontechnology savvy individuals were excluded.

Limitations

There are always limitations in research studies; this study is no exception. An

online survey was used which required some technical knowledge and ability to

complete. An internet survey was chosen because it is easy to access and complete and

the geographic reach was broad. However, the data collected is representative of the

sample group and may not be truly representative of all counselor educators.

The study examined the relationship between self-efficacy with technology and

counselor educator training students in distance counseling. The participants were self-

selecting and likely had comfort with technology which may have introduced sampling

bias. However, to access and complete the survey was not technologically challenging,

the skills required were not much greater than responding to an email or surfing the

internet. The prevalence of internet usage among the population of the United States is

high, many Americans know how to surf the web (File & Ryan, 2014). However, it must

be considered that the ability to complete an online survey may have excluded

participants with lower levels of technology self-efficacy simply because it requires basic

technical skills to complete.

Significance

There are several reasons why distance counseling is growing and is expected to

continue to grow (Anthony, 2015; Barnett, 2011; Finn & Barak, 2010; Simms et al.,

2011; Hilty et al., 2013). Distance counseling has the capacity to improve access to

mental health care and is a workable career option. Distance counseling is being used to

increase access to psychotherapy services to a larger population such as rural

communities, prisons, retirement homes, individuals who are homebound, people who

suffer from social anxiety, or individuals who are deaf (Benavides-Vaello et al., 2013;

Crowe, 2017; Hilty et al., 2013; McGinty, Saeed, Simmons, & Yildirim, 2006; Reljic et

al., 2013; Swenson, Smothermon, Rosenblad, & Chalmers, 2016; Toscos et al., 2018). In

addition, it is possible to practice exclusively online in the current marketplace, an online

practice is a realistic career option for counselors today (Pipoly, 2013). Ensuring that

practitioners are aware of the unique requirements and skills is an important aspect of

counselor preparation and training.

The use of online counseling is beneficial for clients and counselors alike. Online

therapy can be a way to augment a therapy practice providing additional income. In

addition, online counseling is a way to provide mental health services to underserved

communities and to reach individuals who are unable or unwilling to attend face-to-face

counseling. At the heart of this endeavor is educating counseling professionals to provide

services that are ethical, efficacious, and adhere to the law. The education of counselors

is where this knowledge is provided, so it is essential to determine if counselor educators

are meeting this requirement and examining possible barriers. The information gained in

this study can be used to improve training for counseling students in distance counseling.

Ensuring counseling students are prepared to the meet the evolving demands of the

profession can have a positive impact on increasing access to needed mental health

services. The information gained from this study can be used to better understand self-

efficacy as a factor in distance counseling training in master level counseling programs,

and counselor educators teaching distance counseling skills.

Summary

There is a call for training mental health providers in distance counseling,

preferably during their master level education (Anthony, 2015; Callan et al., 2017;

Cartreine et al., 2010; Glueckauf et al., 2018; Pipoly, 2013). Distance counseling is

recognized as an effective tool in providing care to underserved areas and populations.

Some practitioners have embraced the online domain exclusively and others use online

services to augment their private practice or an adjunct to face-to-face therapy. There are

a small number of research studies that explored the practice of distance counseling. The

limited research that has been conducted indicates that mental health providers are failing

to live up to core ethical and legal standards for online practice (Hertlein, Blumer, &

Mihaloliakos, 2014). There are unique aspects to distance counseling such as the

asynchronous nature of communication, lack of non-verbal cues, reliance on written

language, informed consent, and how to manage a crisis with a client in a distance

location (Abbott et al., 2008; Barnett, 2011; Cartreine et al., 2010). The topic is rapidly

evolving, and the laws are complex or often lacking, making training vital for ethical,

legal, and evidence-based practice (Pennington, Patton, Ray, & Katafiasz, 2017). There is

a desire for training and recognition among mental health professionals that they lack the

knowledge and skills necessary to adequately practice in this area (Bruno & Abbott,

2015). However, given past research, it is evident that practitioners are using technology,

many, without the information required to do so (Finn & Barak, 2010; Glueckauf et al.,

2018; Pipoly, 2013).

The topic of training in distance counseling is recent since distance counseling

itself is new. However, the research available confirms the need for training and the

support among professionals and students for training in distance counseling (Anthony,

2015; Callan et al., 2017; Glueckauf et al., 2018; Pipoly, 2013). Professional associations

such as CACREP and ACES also recognize the need to train counseling students

adequately, so they have the skills to work ethically with an understanding of the impact

of technology on the lives of clients and the counseling profession.

The practice of distance counseling requires the use of technology such as

smartphones, computers, and web cameras. Distance counselors are expected to have the

knowledge, skills, and abilities required to utilize distance counseling technology

ethically, legally, and effectively. Further, they must be able to help clients with the

technology as well. Researchers have found that prior use or training in distance

counseling is associated with greater acceptance and use of distance counseling (Simms

et al., 2011). Training students in distance counseling should incorporate hands-on

opportunities to conduct distance therapy (Anthony, 2015; Hilty et al., 2017; Manring et

al., 2011; Shandley et al., 2011). There are not a high number of counselors that are

trained as BC-TMH which could mean that counselor educators also lack the specific

training for distance counseling. Understanding the deficit in training is important to

ensure that counselors are prepared to work in the evolving counseling environment. Past

research on technology integration has found that internal and external factors impact

teacher technology integration (e.g. Ertmer et al., 2012). There are interpersonal factors

such as self-efficacy and a component of self-efficacy, outcome expectation, which are

influential in technology integration (Harrell & Bynum, 2018; Niederhauser Perkmen,

2008; Niederhauser, Perkmen, & Toy, 2012). I examined if there is a relationship

between counselor educator self-efficacy with technology, and the inclusion of distance

counseling skills in the master level classroom. In the coming chapter, I will review the

relevant research in more detail.

Chapter 2: Literature Review

Introduction

The rapid evolution of technology has impacted the counseling profession in

many ways, particularly in the use of technology to provide counseling services. Distance

counseling is becoming more commonplace in the field of mental health practice but

despite the increasing demand for the use of technology in counseling, counselor training

is not keeping up (Anthony, 2015; Callan et al., 2017; Glueckauf et al., 2018; Pipoly,

2013). Although the research regarding distance counselor practice and training is

limited, what is evident is that mental health providers are working online but are failing

to adhere to professional standards (Chester & Glass, 2006; Finn & Barak, 2010,

Gassova, 2016; Heinlen et al., 2003; Maheu & Gordon, 2000; Murphy, McFadden, &

Mitchell, 2008; Shaw & Shaw, 2006). Further, providers are often not trained to work

online, reportedly not received training as part of their education (Finn & Barak, 2010;

Pipoly, 2013). Counselor training has not kept up with the evolution of technology-

related practices. This deficit in training has become a significant problem in the field of

counseling (Anthony, 2015; Callan et al., 2017; Glueckauf et al., 2018; Pipoly, 2013).

Professional organizations took steps to address the influence of technology in

counseling more than 20 years ago. For example, The NBCC (2016b) developed specific

ethical guidelines for distance counseling as early as 1997. The ACA, and the American

Mental Health Counseling Association (AMHCA) followed in 1999, and 2000,

respectively by updating their ethical codes to address the new medium (ACA, 1999;

AMHCA, 2000; Attridge, 2004; Centore, & Milacci, 2008). Despite the inclusion of

distance counseling into professional standards and ethical codes, the counseling

profession continues to be divided on the topic of integration of technology in counseling

due to unclear laws and concerns for privacy (Harris & Birnbaum, 2014).

The growing demand for technology-related services has had an impact on

counselor training as well. CACREP updated the requirement for accredited educational

programs to include the impact of technology on the counseling profession into the 2009

and 2016 CACREP Standards (CACREP, 2009; 2016). ACES also acknowledged the

need for training counselors to work with technology and developed technology

competencies for counselors as early as 1999 (ACES, 2007; ACES Technology Interest

Network, 1999). Although professional organizations have developed standards in

training, it seems that counseling programs have not kept up with training counseling

students to use and work with the diverse technological applications in counseling

practice (Anthony, 2015; Finn & Barak, 2010; Haberstroh et al., 2007; Pipoly 2013;

Trepal et al., 2007). Counselors report that they are not feeling adequately trained in

distance counseling (Anthony, 2015; Blumer et al., 2015; Cabaniss, 2002; Pipoly, 2013).

Anthony (2015) and Callan et al. (2017) reported that there are legitimate concerns that

training programs are not adequately preparing students for the current and future work

environment.

Training counselors to provide distance counseling requires counselor educators

who also have the necessary training and skills in the topic. The practice of distance

counseling is complex and evolves rapidly (Anthony, 2015). The topic of distance

counseling is broad with several practice related concerns and unique ethical and legal

issues. In addition, the practice of distance counseling uses various types of technology

and the provider must be adept enough to provide technical support to clients in some

cases. Technological issues are a factor in the satisfaction of distance counseling for both

clients and clinicians (Haberstroh et al., 2011). Given the low number of BC-TMH

professionals certified through NBCC (Haberstroh et al., 2011), counselor educators may

lack the knowledge and skills to teach distance counseling. Researchers found that mental

health professionals who had received training in distance counseling were more likely to

utilize or to consider utilizing distance counseling (Finn & Barak, 2010; Simms et al.,

2011). Applying the theory of self-efficacy, a counselor educator may be unsure of their

own abilities, low self-efficacy, to provide training in this domain if they lack the training

and experience themselves.

Findings from research into the integration of technology in the educational

setting indicate intrapersonal factors including self-efficacy and outcome expectation

may have an influence on technology integration (Anderson, et al. , 2011, Bunch et al.,

2012; Hew & Brush, 2007; Kim et al., 2013; Niederhauser & Perkmen, 2008;

Niederhauser, Perkmen, & Troy, 2015; Perkmen & Pamuk, 2011, Perkmen, 2014,

Perkmen & Sulmelioglue, 2016). Self-efficacy with technology is also related to

perceived ease of use and perceived usefulness, which are also related to outcome

expectations, regarding technology integration in the classroom (Davis, 1989;

Niederhauser & Perkmen, 2008). Self-efficacy beliefs are influenced by feedback from

the environment as well. Specifically, if a person believes in his or her ability, they are

likely to feel they have the skills needed to complete the task. Further, if done

successfully, further attempts are increased, by contrast, if done unsuccessfully then

future attempts are reduced (Bandura, 1977). Technology integration in counselor

training is not well understood, especially regarding training in distance counseling.

However, given the research on technology integration in educational settings, it is

certainly possible that counselor educators who have low levels of perceived self-efficacy

with technology could be hesitant to include technology-related counseling skills in their

classroom. Self-efficacy has been noted to be a relevant factor in technology integration

in education. It is possible to apply this information to counselor education as to examine

the impact of self-efficacy on distance counseling instruction.

The demand for skills in distance counseling is an expectation for graduates and

counseling programs have standards and competencies in place (ACES Technology

Interest Network, 1999; CACREP, 2016). Unfortunately, there is little research in

counselor training programs and training counselors regarding distance counseling skills.

This study fills a gap that exists regarding possible factors that impact counselor training

regarding distance counseling skills. Specifically, in this study I investigated one aspect

of training, counselor educator self-efficacy with technology, and the influence on

distance counseling training in master level counselor training programs. I examined the

impact of counselor educator self-efficacy with technology and inclusion of distance

counseling skills in counseling skills classes.

The purpose of the study was to examine if there was a relationship between self-

efficacy with technology, as measured by the ITIS (Niederhauser & Perkmen, 2008) and

counselor educators’ distance counseling skills instruction in master level skill-based

classes. There is currently little research on training counselors in distance counseling

and no current research on counselor educator technology integration in counseling

programs.

Synopsis of Current Literature

In this literature review, I synthesized research relevant to the training of

counselors to provide distance counseling retrieved from various sources. The use of

technology in counseling is new to the field and research is limited (Anthony, 2015).

Similarly, training counselors to practice distance counseling is also a newer aspect of the

profession and research is also very limited (Anthony, 2015). The literature available on

distance counseling includes the practice of distance counseling and training counselors

to practice with the use of technology. In addition to the important research on distance

counseling training, research on clinical practice has been included. The research

available on practice provides insight into what practices have been occurring in the field

by counselors and other mental health professionals and provides insight into what

practitioners know and what training they did or did not have prior to undertaking

distance counseling work. Further, the information on practice is useful in better

understanding what distance counseling professionals should know if they are to provide

services via technology.

Researchers investigating professional practices have collected information two

ways; either by examining websites (e.g. Gassova, 2016; Heinlen et al., 2003; Recupero

& Rainey, 2006; Santhiveeran, 2009; Shaw & Shaw, 2006) or collecting information

from practitioners directly (e.g. Bruno & Abbott, 2015; Bambling, King, Reid, &

Wegner, 2008; Chester & Glass, 2006; Finn & Barak, 2010; Maheu & Gordon, 2000;

Menon & Rubin, 2011; Simms et al., 2011). The research is not exclusive to counseling,

other professions with similar practices such as marriage and family therapy (e.g.

Gassova, 2016; Hertlein, Blumer, & Mihaloliakos, 2014; Hertlein, Blumer, & Smith,

2014), social work (e.g. Santhiveeran, 2009), psychology (e.g. Wangberg, Gammon &

Spitznogle, 2007), or a mixed group of online practitioners (e.g. Bruno & Abbott, 2015;

Chester & Glass, 2006; Finn & Barak, 2010; Menon & Rubin, 2011) provided insight

into current practices. Information collected included the types of technology mental

health practitioners had been using, adherence to ethical standards, and the unique aspects

of counseling practice with the use of technology. This information provided insight into

services practitioners had been providing to the public and the standard of care provided.

In some cases, information on practice was also collected as to whether the providers had

been trained to provide distance counseling services.

The training of related mental health practitioners to use technology appropriately

for counseling is also relevant to this study. The research available in this area includes

similar professions such as social work (e.g. Mishna, Levine, Bogo, Van Wert, 2013),

psychology (e.g. Cardenas et al., 2008) school counselors (e.g. Gentile & Lui, 2008), or a

group of mixed professionals (e.g. Murphy et al., 2008). There are a handful of studies in

which training programs for counselors were developed and then feedback obtained on

the experience from the participants (e.g. Haberstroh et al., 2008; Kozlowski & Holmes,

2017; Trepal et al., 2007). The research on training, although very limited, supports the

importance of training to provide distance counseling services. Participants who have had

training support the need for training due to the unique aspects of technology related

services versus face-to-face counseling.

Regarding the topic of technology integration or related topics, only two studies

were located. Quinn, Hohenshil, and Fortune (2002), and Myers and Gibson (1999). The

ACES Technology competencies were published in 1999, soon after, researchers set out

to ascertain baseline data on the ACES competencies in counselor education.

Myers and Gibson (1999) asked respondents collected from the CESNET-L, to

self-rate their level of competence on the 12 ACES competencies (ACES Technology

Interest Network, 1999). Competency 10, knowledge about web-counseling, was rated

11th on the list of competencies, meaning that the counselor educators rated their

competency low. Myers and Gibson (1999) found that there was not a consistently high

level of technology competency in the sample. Despite the low ratings on web-

counseling, about 96% reported that they actively seek opportunity to develop their

technology skills.

Quinn et al. (2002) investigated technology use in counselor education as well,

the technology that CACREP programs were using. This study was drawn from

CACREP programs across the United States, a group of counselor educators were asked

which technology they were using in their schools (Quinn et al., 2002). The findings

indicated that counselor educators used technology mainly in the areas of research, and

teaching or training (Quinn et al., 2002). The technologies that were reported as being

used, such as interactive satellite, were about teaching or training, not as a mode of

counseling (Quinn et al., 2002). The counselor educators in the study felt satisfied with

their training in the use of technology, 65.9% felt their training was adequate, 27.3% said

they had training but that it was not adequate. 39% of the counselor educators did report

that they use the ACES competency guidelines in the teaching (Quinn et al., 2002). To

summarize, although a majority of counselor educators reported satisfaction with their

training to use technology; the technology used by counselor educators was used for

teaching or training.

Research on training counselors to provide distance counseling is lacking. Related

topics include the current practices of online mental health practitioners and a handful of

studies on training mental health practitioners to use technology-related services. Based

on available research, mental health providers online practices are not meeting

professional standards (Bruno & Abbott, 2011; Finn & Barak, 2010; Glueckauf et al.

2018; Santhiveeran, 2009; Shaw & Shaw, 2006). The research available examines the

practices of different providers including social work (Santhiveeran, 2009; Mishna,

Levine, Bogo, Van Wert, 2013), psychologist (Glueckauf et al., 2018; Hilty et al., 2017)

family therapists (Hertlein, Blumer, & Smith, 2014; Hertlein, Blumer & Mihaloliakos,

2014 and counselors (Bruno & Abbott, 2011; Finn & Barak, 2010; Trepal, et al., 2007).

The research presents a trend of poor ethical online practice with practitioners in most of

the cases not adhering to the standards of their professional organizations (Bruno &

Abbott, 2015; Finn & Barak, 2010; Glueckauf et al., 2018, Simms et al., 2011).

There are a few pioneers in counselor training in distance counseling such as

Anthony (2013), Haberstroh (2009), and Trepal et al. (2007), Barak & Grohol, 2011

Murphy et al. (2008), and, specific to group distance counseling, Kozlowski and Holmes

(2017). Other researchers have also contributed to the field of distance counseling

including Hertlein, Blumer & Smith (2014) in marriage and family therapy, Mishna,

Levine, Bogo, Van Wert (2013) in social work, Maheu et al. (2017) in psychology, and

Hilty et al. (2018) in psychiatry. All have been proponents of advancing training for

professionals to ensure the quality of services available to the public as well. It is the

insights and research of these pioneers that encourages researchers to look further and

continue to better understand how best to train counseling students to prepare them for

the future of distance counseling.

The barriers that counselor educators face regarding training counselors in

distance counseling are not well understood due to the lack of research in this area.

Similarly, research on counselor educator self-efficacy in distance counseling is relatively

unexplored and worth examining as self-efficacy is established as an important factor in

the integration of technology in the teaching setting

Sections in this Chapter

In this chapter I provide a review of the existing literature on or relating to

training clinicians in distance counseling. Specifically, I have begun by laying out the

strategy used to find available literature on the topic. Next, research on the practice of

distance counseling is discussed to provide insight into the practice of clinicians and the

need for training. The insight from clinicians who are or have practiced distance

counseling provides a greater understanding of the unique aspects of the medium and the

specific practice issues and legal and ethical concerns relevant to distance counseling.

Researchers have collected information through counselors and other mental health

professionals directly and by examining websites for compliance to professional

organization ethical codes and state laws. The research from both approaches in included.

The next section includes research on training programs that have been undertaken and

the information gleaned by these programs. And finally, a short discussion on the

professional organization's positions on training in distance counseling.

Literature Search Strategy

A search of the recent literature was conducted using several sources available

including the PsycARTICLES, PsychINFO, ERIC, and EBSCO databases, and Google

Scholar. In addition, journals specific to the field of telemental health and counselor

education were also included in the literature search. There is a lack of consensus in

terminology for distance counseling, as a result keyword searches included telemental

health, teletherapy, online counseling, online therapy, distance counseling, e-therapy,

web counseling, or web therapy. Although I focused primarily on research after 2008, due

to the limited research available I included some early studies including Maheu and

Gordon (2000) and Chester and Glass (2006), which were significant research studies in

an under researched area specific to the practice of distance counseling. I also searched

for research on counselor education and technology integration. There is little research

concerning practitioners’ practice of distance counseling and even less in the training of

counselors to provide distance counseling services. Although more recent research is

preferable, the lack of research in the recent past was augmented by later research. The

gap in the literature relating to counselor training and counselor educators training in

distance counseling skills to master level students illuminates the need for research in this

area.

The topic of distance counseling has been examined by other doctoral students.

For example, some dissertations explore various aspects of distance counseling such as

school counselors’ intention to use online counseling (Golden, 2017), and ethics of

websites of marriage and family therapists (Gassova, 2016) counselor beliefs, intentions,

and self-identification relationship to the intention to practice distance counseling

(Holmsten, 2018), and clinicians experience conducting psychotherapy using Skype

video conferencing (Stanard-Kinnaird, 2014)

There was almost no recent research in counselor educator training specifically

relating to distance counseling skills in master level programs found despite an

exhaustive search on the subject. Trepal et al. (2007) reported their experience in training

a group of master level counseling students, and the students also shared their

experiences of learning web counseling. In addition, there has been some attention paid

to training counselors to provide distance group counseling (Kozlowski & Holmes, 2017)

which is another exciting area open for exploration.

The need for more research in distance counseling is recognized, yet the area of

training counseling students in distance counseling has not seen the same attention. There

have been related studies such as training social work students (Mishna, Tufford, Cook,

& Bogo, 2013), school counselors (Gentile & Lui, 2008), psychologists (Cardenas et al.,

2008) or marriage and family therapists (Hertlein, Blumer, & Smith, 2014). In addition,

there is increasing recognition for the need for competencies across domains to ensure

that the mental health profession is providing a high level of care in this expanding

medium (Maheu et al., 2017; Hilty et al., 2018).

Theoretical Foundation

The theoretical foundation for this study was Bandura’s theory of self-efficacy.

Self-efficacy is succinctly described as one’s belief in their ability to achieve a specific

course of action such as a task or behavior (Bandura, 1977, 1997). Self-efficacy includes

four major processes, cognitive, motivational, effective, and selection (Bandura, 1993).

One’s self-efficacy beliefs are the result of several factors including motivation, prior

experience, feedback from the environment, and knowledge and training (Bandura,

1994). Bandura (1993) proposes that perceived self-efficacy is a strong influence on

thinking, feeling, and doing. Self-efficacy beliefs are influential in motivation, self-

regulation, persistence, and resiliency to accomplish a task (Bandura, 1993). Self-efficacy

beliefs are the result of interaction with the environment and are shaped by the self-

evaluation and self-reflection of the individual based on past successes and failures, not

only their own but also vicariously.

Self-efficacy has been established to be a factor in the development of skills and

in the ability to perform a variety of functions. For example, self-efficacy has been

associated with counselor skill development and ability (Larson & Daniels, 1998),

teaching and learning (Zee & Koomen, 2016), and computers and technology integration

(Celik & Yesilyurt, 2013; Tweed, 2013). In fact, self-efficacy can be used to predict

whether one will carry out a specific behavior (Bandura, 1977 & 1997). Perceived self-

efficacy is an integral aspect of behavior, and is well established as a strong predictor of

behavior (Sang, Valcke, van Braak, & Tondeur, 2010)

Researchers have also examined self-efficacy in counseling. Counselor self-

efficacy (CSE) is used to describe the counselor’s belief in their capabilities to provide

effective counseling services (Larson & Daniels, 1998). Bandura’s (1977) theory of self-

efficacy, applied to counseling supports the belief that a counselor’s beliefs would impact

the “choice of counselor responses, effort expenditure and persistence in the face of

failures, and risk-taking behavior” (Larson & Daniels, 1998, p 180). Research on self-

efficacy in counseling includes CSE in relation to the level of training, age, hours of

supervision, and developmental level (Larson & Daniels, 1998). In addition, Schiele,

West, Youngstrom, Stephan & Lever (2014) found that counselor self-efficacy predicted

the quality of practice, knowledge of evidence-based practices, and use of evidence-based

practices. Self-efficacy has been noted to have an impact on the student’s abilities in

many areas (Schiele et al., 2014). This extends to counseling student learning as well. For

example, Watson (2012) examined student counselor self-efficacy beliefs in relation to

counseling ability for students who participated in online instruction. Schiele et al. (2014)

examined counselor self-efficacy and quality of services and knowledge of evidence-

based practices. In addition, Tsai (2015) examined the relationship between self-efficacy

in student counselors and anxiety. In general, findings support self-efficacy as influential

in skills development and counselor practice. Counselor self-efficacy is an important

aspect of counselor training and can influence the counselor’s ability to provide

appropriate services.

The principles of self-efficacy have also been researched in the field of education.

For example, self-efficacy has been examined for teachers in a variety of domains

including teacher well-being (Skaalvik & Skaalvik, 2007), teacher effectiveness

(Holzberger, Phillip, Kunter, 2013), level of performance (Ross, 1998), student

achievement (Capara, Barbaranelli, Steca, & Malone, 2006), providing student feedback

(Motley, Reese, & Campos, 2013), higher learning goals (Wolters & Daugherty, 2007),

and most relevant to this study, technology integration (Bunch et al., 2012; Curts,

Tanguma & Peña, 2008; Morales, Knezek & Christensen, 2008; Niederhauser &

Perkmen, 2008; Stewart, Antonenko, Robinson, & Mwavita, 2013). The research

supports the importance of educator self-efficacy beliefs and the impact of these beliefs

on both educators and students. Self-efficacy impacts educators in many ways including

technology integration.

Self-efficacy has also been examined as a variable impacting the integration of

computers and technology into classrooms. Past research in education, has supported

self-efficacy with technology as a factor related to the integration of technology in the

classroom (Celik & Yesilyurt, 2013; Curts et al., 2008; Morales et al., 2008;

Niederhauser & Perkmen, 2008; Stewart et al., 2013). I propose it is applicable to

distance counseling because distance counseling methods generally require utilization of

technology. Both synchronous and asynchronous methods utilize technology ranging

from texting, computer chat rooms, or video conferencing platforms. The ability to utilize

these technologies is essential for counselors and the counselor educators who train them

(Anthony, 2015; Trepal et al., 2007). Given past research, it is possible that counselor

educators’ self-efficacy with technology could be related to distance counseling

instruction provided by the counselor educator. The basic tenets of self-efficacy theory

propose that one’s perceived beliefs in their own abilities will influence their behavior

including their cognitions, motivations, affective states, and selection (Bandura, 1977).

Currently, there is no research on factors that might correlate with counselor educator

inclusion of distance counseling. However, given past research on learning and teaching,

self-efficacy is a logical starting point.

Measuring technology integration has also been a focus of research. Davis

(1989) developed the technology acceptance model (TAM) to examine factors that

predict user acceptance of computers in the business field. Davis (1989) determined that

two factors, (a) perceived usefulness and (b) perceived ease of use, were important

factors in the acceptance of information technology. Perceived ease of use is also noted to

be a component of motivation in relation to self-efficacy. Two research studies on

counselor use of distance counseling have used an adapted TAM to examine the variables

that impact technology integration by mental health professionals or students (Bruno &

Abbott, 2015; Simms et al., 2011). Bruno and Abbott (2015) found that perceived

usefulness, perceived ease of use, and attitude toward internet supported psychological

interventions influenced study participants willingness to use Internet supported

psychological interventions (ISPIs). Similarly, Simms et al. (2011) found that mental

health provider attitude and perceived ease of use were influential in willingness to use

telemental health. Simms et al. (2011) also found providers who received training were

more likely to use telemental health. The limited research available supports the

importance of educator self-efficacy beliefs and the impact of these beliefs on the

integration of technology (Celik & Yesilyurt, 2013; Ertmer et al., 2012; Holden & Rada,

2011; Hsu, 2010; Niederhauser & Perkmen, 2008; Niederhauser & Perkmen, 2010;

Perkmen & Pamuk, 2011; Saade & Kira, 2009).

Counselor educators, like educators, are influenced by the principles of self-

efficacy. The theory of self-efficacy supports the idea that an instructor that has low self-

efficacy regarding his or her ability to utilize distance counseling resources would be less

likely to attempt to attempt such tasks. It can be surmised that an instructor who lacks

self-efficacy in an area would also be hesitant to teach the topic area. Distance counseling

utilizes different types of technology including smartphones, tablets, or computers. Saade

& Kira (2009) have explored computer self-efficacy, they report that the level of self-

efficacy “plays a significant role in mediating the impact of anxiety on perceived ease of

use” (p 177). Knowledge of and practice using technology are important factors in

technology integration as well (Potter & Rockinson-Szapkiw, 2010). It is possible that

counselor educators’ level of computer self-efficacy has an impact on their motivation to

include computer-related counseling tools in their classroom. Bruno and Abbott (2015)

and Simms et al. (2011) found that perceived ease of use influenced the use of distance

counseling (Bruno & Abbott, 2015; Simms et al., 2011). Examining the relationship

between self-efficacy and counselor educator teaching behavior in distance counseling

skills can provide insight into current training.

Review of the Literature

The Growth of Distance Counseling

Counseling, like many other professions, has evolved in response to advances in

technology. Mental health practitioners have been providing online services and the

practice of distance counseling continues to expand (Cartreine et al. 2010; Finn & Bruce,

2008; Perle et al., 2011). There are several benefits to distance counseling such as

increasing access to care, anonymity, a larger pool of practitioners, and in some cases

lower costs (Ostrowski & Collins, 2016; Richards & Vigano, 2013). For a majority of

Americans in rural areas, distance counseling is not just an alternative form of

counseling, it is the only feasible option (Center for Credentialing and Education Global

[CCE], 2018). The use of distance counseling is a feasible option to address a variety of

presenting problems, the efficacy has been researched and distance counseling is found to

be comparable to face-to-face counseling for many conditions (Hilty et al., 2013) and

even superior in some cases (Kiluk et al, 2018). The profession is moving online and is

expected to increase in the future.

Distance Counseling as a Profession

The goal of counselor training programs is to provide counseling students with the

knowledge and skills to practice as a counseling professional. Distance counseling skills

are an important tool for counselors to have. Distance counseling is a viable career option

for clinicians (Pipoly, 2013). The growth of online counseling has opened the door for

clinicians to practice exclusively online. It is essential that counseling programs include

distance counseling material into their counselor preparation programs (Anthony, 2015;

Haberstroh et al., 2009; McAdams & Wyatt, 2010; Myers & Gibson, 1999; Pipoly,

2013). Unfortunately, counselor preparation programs do not appear to be meeting the

needs of students (Anthony, 2015; Callan et al., 2017). As technology continues to

evolve, so must counselor training. Despite the increasing use of distance counseling,

counselor training programs are not providing the necessary training to ensure counselors

have the knowledge and skills necessary to provide services in this domain (Anthony,

2015; Callan et al., 2017; Goss & Anthony, 2009). It is essential to better understand the

deficit in training to address the deficit and better prepare counselors for practice online.

Research on Current Practice

It is important to obtain information on current practices in distance counseling to

better understand professional use of distance counseling and practice related issues.

Researchers have used two approaches to collect information, they have surveyed

practitioners or evaluated practitioner websites. Researchers set out to better understand

the attitudes and practices of providers by collecting information directly from

professionals themselves such as Bruno and Abbott (2015), Finn and Barak (2010),

Hertlein, Blumer, Mihaloliakos (2014), Hertlein, Blumer, & Smith (2014), Menon and

Rubin (2011), Simms et al. (2011), Wangberg et al. (2007) or from websites of providers

(Heinlen et al., 2003; Recupero & Rainey, 2006; Santhiveeran, 2009; Shaw & Shaw,

2006). The research is limited and much of it dated more than a decade ago.

Unfortunately, due to the evolution of technology, especially in teleconferencing

software, much of it does not provide insight into current practices. However, the

research does provide limited information on practices and the training of clinicians in

distance counseling.

Research on Distance Counseling Practices

Research on the practice and training of distance counseling is limited and

includes different mental health professionals such as social workers, psychologists,

marriage and family therapists, and counselors. Research on the training experiences of

counselors using technology is also scant. The distance counseling tools utilized vary

which makes comparison difficult. Different tools that are under the umbrella of distance

counseling including self-directed online tools, telephone, email, chatrooms, or video

conferencing. There are a small number of studies, and often the technology utilized is

not consistent. The research available is difficult to compare as the variables measured

vary as well.

Glueckauf et al. (2018) and Bruno and Abbott (2015) are the most recent

researchers to investigate the use of technology in mental health practice. Glueckauf et al.

(2018) conducted an online survey including practitioners from various mental health

fields throughout the U.S. The survey is unique in that it asked about current use and also

attitudes about what technologies they considered useful for distance counseling. The

findings in Glueckauf et al. (2018) contrasted with past research; e-mail was used by only

37.8% and video-conferencing was used by 25.61%. The percentage of clinicians using

e-mail was lower than other researchers such as Finn and Barak (2010) and Simms et al.

(2011) reported. In addition, the percentage of participants using video-conferencing was

much higher than reported by other researchers such as Centore and Milacci (2008) who

reported 1.2% of the practitioners using video conferencing, and 4.48% reported by

Chester and Glass (2006). The percentages reported regarding attitudes was higher with

72.56% considering video-conferencing to be useful for distance counseling (Glueckauf

et al., 2018). The shift from e-mail to videoconferencing could be the result of advances

in video conferencing platforms.

Bruno & Abbott (2015) surveyed mental health providers in Australia about their

use of what they refer to as internet supported psychological interventions (ISPIs); ISPIs

including everything from self-directed internet tools to video-conferencing. The

participants in the Bruno and Abbott (2015) study reported they used one or more forms

of ISPIs with clients (69.8%). The most prevalent was self-guided web-based therapeutic

interventions and web-based educational interventions (45 %). Only 17.4 % reported

using online counseling and therapy which included therapist contact via email, instant

messaging, or video; therapist contact was reported as a single variable. Although

practitioners were using ISPIs, only 23% had received training. Further, of the 23% who

had training, they reported the training they received lacked opportunities to practice.

(Bruno & Abbott, 2015). The research done by Bruno and Abbott (2015) indicated that

despite what could be characterized by limited training, practitioners are using distance

counseling tools.

Telephone, e-mail, chat, or video conferencing are the primary modes of distance

counseling. However, some of the research was conducted more than a decade ago when

video-conferencing software was not as prevalent nor HIPAA compliant. Centore and

Milacci (2008) found 73.8% of practitioners used the telephone for therapy, 28.1% used

email, 5.6% used text chat, and only 1.2% used video conferencing. Hertlein, Blumer &

Smith (2014) asked MFT’s about their use of email, 83.4 % used email to communicate

with clients. Finn and Barak (2010) recorded 87% of providers used e-mail. Simms et al.

(2011) had similar findings with 72 % of their sample communicating with clients via e-

mail. E-mail use has been common among mental health professionals, but the past

research indicates that video-conferencing has not been widely used. Chester and Glass

(2006) also found participants in their study were using email (71%) and chat (17%)

mainly to communicate with clients and to provide services. However, the most current

research from Glueckauf et al. (2018) report that only 37.8% of psychologists surveyed

use email. Although the numbers seem to have decreased, practitioners are utilizing

distance counseling and have been for over a decade. The shift seems to be moving to the

use of synchronous video technology.

The limited research confirms that providers, often educated, licensed

professionals, are utilizing distance counseling. Unfortunately, research indicates

providers have not been practicing within ethical standards or sometimes within the law.

For example, Maheu and Gordon (2000) collected information about online practitioners

including their professional background, the technologies used, and clinical interventions

employed. The study participants were predominately licensed (93%), yet nearly half of

the practitioners did not have arrangements in place to deal with the crisis, and less than

half (48%) employed a consent form for treatment. It is troubling when a majority of

online practitioners fail to meet a basic ethical and legal standards of client care. Chester

and Glass (2006) had similar results. A significant majority of providers were licensed

(87%), but many did not use encryption (42%), and a majority of the providers surveyed

were practicing outside of the state of their license. The research reveals concerns about

the distance counseling services available online.

Website Analysis

Researchers have also collected information available publicly on websites.

Consumers turn to the internet for therapy and researchers have set out to better

understand what consumers might find. The analysis of websites supports the findings

that practitioners were not adhering to appropriate ethical and legal standards. Providers

online should provide the prospective client with information about online therapy

including possible risk, the provider's credentials, and education, the state they practice

in, information relating to informed consent, the use of encryption, treating minors, and

how a crisis is managed (AAMFT, 2017; NBCC, 2016b). Websites were examined

regarding best practices and ethical standards.

The findings indicate that providers are not meeting the standards based on the

information available on websites. Gassova (2016) recently examined websites of

marriage and family therapists (MFT). Most websites did not have documents such as

crisis services, informed consent, or information on privacy. Only 37% had information

available. When Gassova (2016) analyzed the websites for compliance with the AAMFT

ethical principles for practice online, only a single website met all the principles. Seven

websites did not meet a single principle. One interesting finding in this study is the

decrease in email use and the increase of video conferencing use for therapeutic contact,

similar to the findings of Glueckauf et al. (2018). What was also concerning is that

providers were utilizing video-conferencing. 57% listed the service, but the providers

reportedly were utilizing skype (42%) which does not meet the encryption standards

necessary for distance counseling (Gassova, 2016). Shaw and Shaw (2006) conducted

similar research but used the ACA code of ethics as the standard. The findings were also

concerning, only 32% of the websites required clients to sign a waiver for services and

only 38% had an intake procedure. In addition, less than half (45%) required the client to

provide their full name and address and only 46% required the client to provide a date of

birth to confirm their age. There were also deficits in protecting client data, only 27%

used secure site or encryption software and only 33% indicated there is a risk when

communicating via the internet. This is concerning, especially considering the education

level and licensure status of the clinicians presented on the websites.

Support for Training in Distance Counseling

Unfortunately, the studies of practice did not always inquire into the training of

practitioners. Finn and Barak did include the question, 94%, reported that they did not

receive training in their training programs (Finn & Barak, 2010). Most had read up on the

topic themselves (92%), only 20% had attended a workshop and only 16% had attended a

training program. Of interest is the e-counselors from the United States were less likely to

have received formal training, only 10% of U.S counselors reported having received

training. The need for training was agreed upon by 44%, with those who had training

more likely to support training (Finn and Barak, 2010). In addition, most participants

(56.5%) had not received supervision while doing e-counseling. An additional 41.3%

received informal supervision from colleagues, only 6.5% received formal paid online

supervision from another online therapist (Finn & Barak, 2010). The study confirmed that

training and supervision were lacking among practicing e-counselors.

Counselors or other mental health professionals who have either received training

or have practiced distance counseling support training prior to utilizing distance

counseling (Chęć et al., 2016; Finn & Barak, 2010; Murphy et al., 2008; Simms et al.,

2011; Wangberg et al., 2007). There are a small number of studies on providing distance

counseling training to mental health professionals (Anthony, 2015; Finn & Barak, 2010;

Gentile & Liu, 2008; Haberstroh et al., 2008; Trepal et al., 2007). The limited research

findings do indicate there are significant ethical and legal concerns among clinicians who

practice distance counseling, reinforcing the importance of training counselors prior to

implementing distance counseling practices (Anthony, 2015; Coursol & Lewis, 2003;

Finn & Barak, 2010; Gentile & Liu, 2008; Haberstroh et al., 2008; Shandley et al., 2011;

Simms, et al., 2011; Tanrikulu, 2009; Trepal et al., 2007).

This lack of knowledge or training revealed in the practice research, is of concern.

A lack of training may result in negative client outcomes (Barnett, 2011) such as client

harm (Goss & Anthony, 2009; Holmes, 2008; Pennington et al., 2017; Shandley, et al.,

2011; Terpstra et al., 2018) or ethical or legal violations (Barnett & Kolmes, 2016b; Finn

& Barak, 2010; Maheu & Gordon, 2000). Distance counseling tools, especially email, are

used by a majority of counseling professionals (Chester & Glass, 2006; Finn & Barak,

2010; Heinlen et al., 2003; Leibert, Archer, Munson, & York, 2006; Murphy et al., 2008;

Pelling, 2009; Simms et al., 2011). However, counselors are utilizing email and other

available online tools absent of training (Finn & Barak, 2010).

Although the research is limited, it is evident that there are certain concerns

regarding the training of practitioners providing online therapy and adherence to

professional ethical codes or state laws. It is also evident that many online practitioners

have little if any training to practice distance services. Researchers found that a majority

of mental health professionals who were providing distance counseling services are not

adhering to the ethical guidelines established by the ACA (2014), the NBCC (2016b), or

other professional organizations (Chester & Glass, 2006; Finn & Barak, 2010; Heinlen et

al., 2003; Maheu & Gordon, 2000; Recupero & Rainer, 2006; Santhiveeran, 2009; Shaw

& Shaw, 2006). Further, counselors may not be aware of the unique aspects of distance

counseling and may wrongly feel confident to practice without understanding the legal

and ethical requirements or practice issues relating to distance counseling (Trepal et al.,

2007). Distance counseling skills must be included in counselor training programs to

ensure that counselors have the skills needed to practice within the law and ethical

standards required for counselors.

Research on Training for Distance Counseling

Educational programs focus on the provision of face-to-face skills but may be

neglecting the unique skills to work in a technologically connected world (Anthony,

2015; Callan et al., 2017; Glueckauf et al., 2018; Mishna, Levine, Bogo, & Van Wert,

2013; Pipoly, 2013). Failing to address the unique aspects of online counseling might

lead some students to believe no special skills are needed and they can do online therapy

the same as face-to-face therapy which is not accurate. Prior research has confirmed that

practitioners who have gone through training for distance counseling agree that training is

necessary to provide distance counseling to clients (Cardenas et al., 2008; Haberstroh et

al., 2008; Gentile & Lui, 2008; Mishna, Bogo, Root, Sawyer, & Khoury-Kassabri, 2012;

Mishna, Levine, Bogo, & Van Wert, 2013, Misha, Tufford, Cook, & Bogo, 2013;

Murphy et al., 2008). The lack of visual and other nonverbal cues, present in some forms

of distance counseling, requires more dependence on language (Trepal et al., 2007). The

process is different than face-to-face counseling and it is often neglected in traditional

training programs.

The overall consensus is that training is important in order to appropriately,

ethically, and effectively provide distance counseling (Abbott et al., 2008; Baker &

Bufka, 2011; Barnett & Kolmes, 2016a, 2016b; Bastemur & Bastemur, 2015; Cardenas et

al., 2008; Carlisle, Hays, Pribesh, & Wood, 2015; Gentile & Lui, 2008; Haberstroh et al.,

2008; Hertlein, Blumer, Mihaloliakos, 2014; Hertlein, Blumer & Smith, 2014; Gentile &

Lui, 2008; Mishna et al., 2012; Langarizadeh, Tabatabaei, Tavakol, Naghipour, &

Moghbeli, 2017; Menon & Rubin, 2011; Mishna, Levine, Bogo, & Van Wert, 2013;

Mishna, Tufford, Cook & Bogo, 2013; Murphy et al., 2008; Nelson & Duncan, 2015;

Kozlowski & Holmes, 2014; Simms et al., 2011; Yuen, 2012). The legal and regulatory

guidelines for online counseling are often complex and difficult to understand (Zur,

2016). Training in the ethics and laws relating to distance counseling is needed to

navigate the ethical codes and relevant laws (Haberstroh, Barney, Foster, & Duffey,

2014).

Researchers agree on specific ethical concerns that are unique to online therapy.

Specifically, informed consent, verifying client identity, privacy, competency, duty to

protect, jurisdictional issues, and therapist transparency in advertising (Abbott et. al.,

2008; Barnett & Sheetz, 2003; Finn & Barak, 2010; Fitzgerald et al., 2010; Hertlein,

Blumer, Mihaloliakos, 2014; Hilty et al., 2017; Hughes, 2000; Richards & Vigano, 2013;

Ross, 2016; Shaw & Shaw, 2006; Mallen et. al., 2005; Wells, Mitchell, Finkelhor &

Becker-Blease, 2007). Support for training is prevalent, especially among those who have

experience or training in distance counseling (Finn & Barak, 2010; Simms et al., 2011).

Experience and training for therapeutic methods in face-to-face counseling are not

adequate for practicing distance counseling (Haberstroh et al., 2008; Murphy et al., 2008;

Mishna, Levine, Bogo, & Van Wert, 2013, Mishna, Tufford, Cook, & Bogo, 2013).

There are ethical, legal, and practice issues unique to the online setting (Maheu et al.,

2017). Counseling students have not been learning the skills necessary for distance

counseling in their educational programs (Murphy et al., 2008; Cardenas et al., 2008).

Research supports the need for training, specifically hands-on training with technology

(Anthony, 2015; Manring et al., 2011; Mitchell, Myers, Swan-Kremeier, & Wonderlich,

2003; Goss & Anthony, 2009; Haberstroh et al., 2008; Hilty et al., 2017; Shandley et al.,

2011). There is a call for this training to be provided during the field experience

component of therapist preparation, a key time for skill development (Cardenas et al.,

2008).

Training in distance counseling has an impact on the counselor’s willingness to

use distance counseling tools (Finn & Barak, 2010; Simms et al, 2011). Researchers also

found that training increased practitioners’ self-efficacy beliefs (perceived ease of use

and perceived usefulness) and influenced providers use of distance counseling (Lazuras

& Dokou, 2016; Simms et al., 2011). Training has an impact on both self-efficacy with

technology and willingness to use technology in counseling.

Call for Training in Distance Counseling

Despite the growing interest in and need for training, there was no research

located regarding how distance counseling skills are included in master programs. There

are professionals calling for distance counseling training in graduate training programs to

ensure counselors are prepared to work with the unique aspects of distance counseling

upon graduation (Anthony, 2015; Blumer et al., 2015; Haberstroh et al., 2008; Kozlowski

& Holmes, 2017; Maheu et al., 2017; Mallen et al., 2005; McAdams & Wyatt, 2010;

Pipoly, 2013; Shandley et al., 2011). Training is necessary to ensure that counselors are

competent to perform the day to day clinical practice that is inclusive of technological

advances (Maheu et al., 2017). Counselor preparation programs should be meeting this

need but based on research findings, they are not.

Counseling students report an interest in learning about distance counseling

(Blumer et al., 2015; Hertlein, Blumer, Mihaloliakos, 2014; Tanrikulu, 2009) as do

practicing counselors (Bastemur & Bastemur, 2015; Zamani, Nasir, & Yusoof, 2010).

Research findings also show that students are not only interested in training (Finn &

Barak, 2010; Tanrikulu, 2009; Teh, Acosta, Hechanova, Garabiles, & Aliana, 2014) but

also in becoming certified in cyber-based practices (Hertlein, Blumer, Mihaloliakos,

2014). In addition, students agree that graduate programs should be including information

about the use of technology in supervision (Hertlein, Blumer, Mihaloliakos, 2014). There

is interest among students on the topic, however educational programs are not addressing

this issue of distance counseling training (Anthony, 2015; Callan et al., 2017; Hertlein,

Blumer, Mihaloliakos, 2014; Pipoly, 2013)

The practice of distance counseling requires an understanding of the unique

characteristics of counseling via the online environment such as the unique visual and

verbal components (Holmes & Kozlowski, 2015; Kozlowski & Holmes, 2014; Menon &

Rubin, 2011; Murphy et al., 2009). Distance counseling methods utilize a greater reliance

on the written and oral communication between counselor and client because there is a

lack of visual cues and nonverbal communication that is present in face to face

counseling (Anthony, 2015; Finn & Barak, 2010; Gentile & Liu, 2008; Haberstroh et al.,

2008; Kozlowski & Holmes, 2014; Menon & Rubin, 2011; Shandley et al., 2011;

Tanrikulu, 2009; Trepal et al., 2007). Videoconferencing platforms can improve the

visual aspect of distance counseling but the technology itself can be challenging for both

client and counselor (Haberstroh et al., 2011). However, new counselors are not being

trained in distance counseling practices. Trepal et al. (2007) propose that because few

counselors are trained specifically in distance counseling, they lack the knowledge to

train in distance counseling. Counselor educators may lack the specific training in

distance counseling which could impact their beliefs in their own abilities. This study

investigated one possible barrier to distance counseling training, counselor self-efficacy

with technology.

Professional Organizations Positions on Training

As technology use in counseling grew, professional organizations established

standards for professionals as well as training practices. Professional organizations such

as the NBCC, the ACA, and the American Mental Health Counseling Association

(AMHCA) began addressing the impact of technology on counseling in 1995, 1999, and

2000, respectively (Attridge, 2004; Centore, & Milacci, 2008; ACA, 1999; AMHCA,

2000; NBCC, 2016b). In addition, the American Association of Marriage and Family

Therapy (AAMFT) recently developed best practices for the use of technology-assisted

professional services (Caldwell, Bischoff, Derrig-Palumbo, & Liebert, 2017). Ethical

guidelines have been established to ensure adherence to core principles consistent with

counseling standards that ensure client protections. The ethical mandates support the use

of technology if the professional is competent, provides appropriate informed consent,

and meets the professional standards protecting client data and privacy (ACA, 2014;

NBCC, 2016b; AAMFT, 2016). Professional organizations have adapted the ethical

codes and practice guidelines to include technology in counseling.

The recognition that the use of technology in counseling was growing extended

into counselor education as well. The Council for Accreditation of Counseling and

Related Educational Programs (CACREP) recognized the need for training counselors in

distance counseling and required that counseling programs include the impact of

technology on the counseling profession into the CACREP Standards in 2009 (CACREP,

2009). However, counselor educators have the choice of how and to what degree they

implement technology’s impact on counseling into their curriculum (CACREP, 2016). Of

concern is the fact, there are not many counselors NBCC certified in distance counseling

to provide the necessary training to counseling students (Trepal et al., 2007). Counselor

education programs have the responsibility of preparing students to be competent to

practice, including with regards to the impact of technology in counseling services

(CACREP, 2016).

In addition, ACES (2007) recognized the impact that technology had on varying

aspects of the counseling profession such as counselor education. Nearly two decades ago

in 1999, ACES Technology Interest Network developed a set of technology competencies

for counselor education students to have upon graduation, regarding technology and the

use of technology in the field of counselor education (ACES, 2007). Two of these

competencies relate directly to distance counseling. Specifically, competency (9) Be

knowledgeable of the legal and ethical codes which relate to counseling services via the

internet, and (10) be knowledgeable of the strengths and weaknesses of counseling

services provided via the internet. ACES proposed technology competencies “be infused

throughout counselor education curriculum at the masters’ and doctoral program levels”

(p. 1). Based on student reports and past research on practice, this does not appear to be

occurring (Anthony, 2015; Blumer et al., 2015; Cabaniss, 2002; Pipoly, 2013).

After an exhaustive search for research regarding the technological competence of

counselor educators, only two studies were found. Myers and Gibson (1999) surveyed

counselor educators on their self-reported level of competency in the ACES technological

competencies just established at that time. Quinn et al. (2002) examined the utilization of

technology in CACREP accredited counselor education programs also many years ago.

Since then the topic of technology in counselor training has been studied in the areas of

supervision and distance learning but not on distance counseling training.

The most recent ACA code of ethics addresses online therapy in Section H:

Distance Counseling, Technology, and Social Media (ACA, 2014). The online

environment has unique ethical issues including privacy online, duty to warn and duty to

protect clients who are in a different geographic location, ensuring the age and identity of

the client, ensuring the appropriateness of distance therapies for clients, training and

competence, and ensuring the appropriate use of technologies (ACA, 2014). The online

environment creates unique ethical and legal issues separate from face-to-face

counseling.

In an effort to validate counseling training in distance counseling the NBCC

offers a Board Certified-TeleMental Health Provider (BC-TMH) credential for those

trained in providing distance services (CCE, 2016). They define distance professional

services as counseling adapted for delivery through electronic means including telephone,

secure e-mail, chat, video conferencing, or stand-alone programs. (NBCC, 2016a). The

BC-TMH credential is available to mental health professionals from a variety of

disciplines and is a way to indicate that one has received appropriate training on the

practical aspects involved in the safe and effective provision of distance counseling

services (CCE, 2016).

The NBCC includes guidelines in the code of ethics and also has a specific policy

for distance counseling (NBCC, 2012, 2016a). The NBCC ethical code sets forth

guidelines for the use of social media and record keeping related to the use of technology

in counseling. In addition, the NBCC policy on distance counseling services provides

guidelines on best practices to ensure ethical practice of distance counseling. The policy

document is based on three main concepts, that (a) counseling through a distance presents

unique ethical dilemmas for professional counselors, (b) the technology continues to

advance and become used more frequently by professionals, and (c) the use of technology

continues to evolve in the field of counseling (NBCC, 2016a). It is necessary for

counselors to be aware of the impact technology has on the profession, and the lives of

clients (Anthony, 2015). Unfortunately, counselor education programs are not preparing

counselors for the changing landscape of the counseling profession and technology

related services.

Considering these multiple professional standards, it would seem that training

new counselors in the practice of distance counseling would be common. However,

research shows that counselors are not trained in distance counseling (Anthony, 2015;

Bastemur & Bastemur, 2015; Benavides-Vaello et al., 2013; Cipolletta & Mocellin, 2017;

Finn & Barak, 2010; Glueckauf et al., 2018; Hertlein, Blumer & Smith, 2014; Pipoly,

2013; Santhiveeran, 2009; Shaw & Shaw, 2006; Simms et al., 2011; Tanrikulu, 2009). Of

further concern is the fact that counselors are providing distance counseling services

often without training and frequently not adhering to the appropriate ethical and legal

requirements (Chester & Glass, 2006; Finn & Barak, 2010, Gassova, 2016; Heinlen et al.,

2003; Maheu & Gordon, 2000; Shaw & Shaw, 2006).

Despite these professional and educational standards, the training of counselors to

provide distance counseling services has not been well researched (Anthony, 2015;

Fitzgerald et al., 2010; Shandley et al., 2011). Advances in technology and the increasing

use of online counseling warrants continuing research to understand distance counseling

training practices (Haberstroh et al., 2008; Backhaus et al., 2012). To better understand

this deficit in training, this study was undertaken to investigate one possible barrier to

training, counselor educator self-efficacy with technology and the relationship with

distance counseling training in counselor education programs.

Summary

Although distance counseling is a growing field the research on training is limited

to a handful of studies not limited to training counselors. Research supports the efficacy

of distance counseling and the usefulness of distance counseling to increase access to

underserved areas, especially in rural communities which often lack professional

services. However, research on training master level students in the skills of distance

counseling is limited despite an exhaustive search. Other professions such as social work,

psychology, and marriage and family therapy also have limited research and the findings

indicate distance counseling requires unique skills and the importance of training to

provide distance counseling services. The need for training is supported by those who

have experience in the field and those who have obtained training in distance counseling.

Further, the limited research examining the practice of distance counseling has found that

the professionals in practice are mostly untrained and are not meeting the ethical and

legal requirements of their profession. Professionals are utilizing distance counseling

tools, although they may not identify as distance counselors or even be aware, they are

practicing distance counseling. Behavioral health professionals are utilizing technology

and often failing to meet the acceptable ethical standards set forth by professional

organizations ethical codes. The lack of training is a problem that must be addressed,

preferably in master level programs to ensure counselors are prepared to work with

technology in counseling upon graduation.

The training deficit has not been examined directly in relation to counselor

educator’s behavior. The available research does indicate that students are interested in

receiving training in distance counseling however they are not receiving it in their

counseling programs. The gap in understanding what is getting in the way of training

counseling students is worth examining. Self-efficacy with technology has been

examined in the field of education for many years. The integration of technology in

education has been noted to involve different factors, self-efficacy being a strong

indicator of an educator’s motivation, willingness, and behavioral intention to integrate

technology into the classroom. The utilization of technology is an important aspect of

distance counseling and self-efficacy with technology may be influential in a counselor

educator’s integration of technology in the master level skills-based class.

Chapter 3: Research Method

Introduction

I set out to examine the relationship between counselor educator’s self-efficacy

with technology and their inclusion of distance counseling skills training in the master

level classroom. Self-efficacy with technology was be measured by the SE, OE, and INT

subscales, and the overall score of the ITIS. The distance counseling skills instruction

was determined by self-report. The variables were analyzed to determine if there was a

statistically significant relationship between the variables of interest. Demographic

information was also collected and was analyzed to determine if any of the demographic

variables were predictive of teaching distance counseling skills.

In this chapter, I discuss the research method that was used for this study. I began

with selection criteria for the population of the study and the sampling procedure used. I

provided information on the procedures used in recruitment, participation, and data

collection. I also clarify the specific instrumentation that was used and how the variables

were operationalized by the instrument. The next section describes how the data was

analyzed for this study. Threats to validity have been considered and how they relate

specifically to this study as well. In addition, the ethical procedures followed are included

followed by a summary.

Research Design and Rationale

In this study. I examined the relationship between self-efficacy with technology

among counselor educators and distance counseling instruction in the classroom. Little is

known about this emerging field of training and this research study collected important

data that can be used to better understand the behavior of counselor educators and levels

of self-efficacy with technology integration. The variables of interest included counselor

educator inclusion of distance counseling skills in their master level skills-based class and

counselor educators’ self-efficacy with technology. Counselor educator self-efficacy with

technology was measured by the ITIS, including a full score and scores for the three

subscales: SE, OE, and INT (Niederhauser & Perkmen, 2008). The dependent variable

was the inclusion of distance counseling skills in the classroom. Demographic data was

collected as was data on counselor educator training in distance counseling and

experience using distance counseling. The information collected was reported, providing

baseline data for future research in this area.

The design of the study was quantitative, using an anonymous online descriptive

survey. A correlation study was used to explore the current teaching environment and the

prevalence of distance counseling training. The data was then statistically analyzed to

examine the relationship between counselor educators’ self-efficacy with technology,

measured by their total and individual scale scores on the SE, OE, and INT subscales of

ITIS and the inclusion of distance counseling instruction in the master level classroom for

skill-based classes. A correlation analysis was used in order to explore relationships

between variables that are observed as they occur without interference from the

researcher. Correlation studies can be used to examine a behavior as it is occurring

without manipulation providing information as to current practices (Creswell, 2012;

Creswell & Creswell, 2013). Based on the correlation findings, a regression analysis was

performed to see if demographic variables had any relationship with teaching distance

counseling skills and to further examine which demographic variables and scale scores, if

any, were predictive of distance counseling instruction.

This study sample was drawn from three sources but was focused on a single

sample group, counselor educators, for the data collection. The first source was (a) an

email list was created by the researcher of publicly available contact information

available from university websites in the United States, (b) the CESNET-L an email

listserv for ACES members, and the (c) ACA Connect call for study participant email

group list, a counseling newsletter for ACA members specific to request for research

participants.

The data was collected using an online survey that was made available for 7

weeks. Two reminders were sent after the initial request for participation, one after 3

weeks and an additional reminder 5 weeks after initial contact. The second reminder

informed the contacts that the survey would close in 2 weeks and provided a specific

date. An online survey was selected because of the ability to reach a larger number of

counselor educators in different geographic locations. Although geographic data was not

collected, I contacted universities across the United States and requested their

participation. The data I collected provided information that can be used to better

understand if counselor educators are including distance counseling skills in their

classrooms. In addition, information on counselor educator training and the use of

distance counseling was also collected.

I analyzed the survey data using a correlation to ascertain if there is a statistically

significant relationship between counselor educator self-efficacy with technology, as

measured by the SE, INT, and OE subscales and the total score on the ITIS, and inclusion

of distance counseling skills. The sampling frame included areas throughout the United

States to provide a more diverse sample to better understand counselor educator behavior

in distance counseling skills training.

Methodology

This section will provide information on my collection of data including how

participants were selected and how the data was collected. I will also discuss why the

population for the study was selected. I will describe in detail the methods used to collect

the sample data.

Population

The population for the study was counselor educators who have experience

teaching skills-based counseling classes in master level counseling programs within the

United States. This includes counselor educators of various education levels, from either

CACREP-accredited programs or nonaccredited programs, and counselor educators who

are currently teaching a skills-based course or have in the past taught a skills-based

course to master level students. The exact number of counselor educators in the United

States is unknown. One prior study sampled counselor educators from CACREP

accredited programs which were found to include just over 1,500 counselor educators

(Brown-Rice & Furr, 2016). The CESNET-L has 4,475 subscribers and the unedited list

collected of probable counselor educators I collected totaled 4,699. The exact number of

counselor educators is unknown but could be several thousand.

Sampling and Sampling Procedures

The sampling used a nonprobability purposive sample. I solicited participation

through email contact. The sampling was drawn from several sources: (a) CESNET-L, a

listserv for ACES members, (b) the ACA connect call for study participant email group,

CACREP accredited programs available through the CACREP website, and (d)

university contacts from master level clinical counseling programs within the United

States obtained by an internet search. Participants self-selected to participate in the

survey.

The first step was to collect email contact information from master level

counseling programs in the United States. A list was obtained from the CACREP website

of all CACREP accredited programs, past, current, and in the process. I then visited all

the websites listed on the CACREP list. The university website was searched for

counseling faculty or counselor education faculty. If email addresses were publicly listed

the email address was recorded in an excel spreadsheet along with the state, the name of

the university, and the first and last name of the faculty member. A similar process was

followed to collect information from nonaccredited programs. An internet search for non-

accredited counseling programs was done for all 50 states using Google. Once a

university was found, the website was located, and the same process of collection was

followed. The university site was viewed and counseling faculty or counselor education

faculty that were publicly listed, including email, state, university, and first and last name

were recorded in an excel spreadsheet. In both cases, the information obtained was based

on what was available to the general public. The lists were then be combined into one

master list with both CACREP and non-CACREP accredited programs to include contact

information obtained from the various university websites. Once a list was created, I

initiated e-mail contact to counselor educators.

The first sampling email sent was a general email requesting participation

(Appendix B). The email was sent to the three sources: (a) the CESNET-L listserv, (b)

the ACA connect call for study participant email group list, and (a) directly to individuals

from the university email contact list via SurveyMonkey. Approval to submit on the

CESNET-L had been obtained earlier (Appendix A); permission is not required but the

list manager does request that he is contacted prior to posting on the listserv. In addition,

posting on the ACA connect call for study participant email group list required joining

the list prior to submission, I had joined the list prior to initiating sampling. The emails

collected through public information listed on university websites, were uploaded to

Surveymonkey and the survey was sent out (Appendix B). The process was adjusted

based on feedback then repeated after 3 weeks and again after 2 additional weeks.

The sampling frame was comprised of counselor educators who have either

current or past experience teaching a skills-based class to master students. Skills-based

classes will be defined as a practicum or internship as described in Section 3.

The sample size required was calculated based on alpha level, power, and effect

size (see Field, 2013, Trochim, 2006). The alpha level represents the probability of a

Type I error or rejecting a null hypothesis that is true. For this study, an alpha level of .05

was selected. Psychological research generally uses α=.05 (Trochim, 2006). This is an

acceptable level for research and will allow for a smaller sample size. The power level of

.90 was proposed. This is also an acceptable level for research (Rea & Parker, 2014).

The effect size was estimated based on past research on the topic. There are few

studies on instructional content relating to self-efficacy. Perkmen and Pamuk (2011)

examined the variables included in the ITIS, (a) SE, (b) OE, and (c) INT. There was a

medium effect size for SE and a large effect size for OE. Based on these findings, a

medium effect size was applied.

Finally, using Cohen’s effect size, a medium effect size, d= .3, was used. Using

these parameters, the sample size is calculated using GPower (see Faul, Erdfelder, Lang,

& Buchner, 2007) with a power of .90, α= .05, two-tailed, with a medium effect size of

d= .3 the sample required is 109. A regression analysis was included based on the

findings of the correlation. It is generally accepted practice to limit the regression model

to 10 participants per variable (Concato, Peduzzi, Holford, & Feinstein, 1995), this was

followed in the regression analysis with no more than six variables included in any

model.

Rea and Parker (2014) considered the size of the population when determining

sample size in survey research. There is no specific data on the number of counselor

educators in the United States. Past research on counselor educators has estimated

counselor educators in CACREP programs to number approximately 1,500 (Brown-Rice

& Furr, 2016). Rea and Parker classified populations less than 100,000 as small, the

number of counselor educators likely falls into this category given the numbers estimated

for CACREP programs by Brown-Rice and Furr (2016). For a sample size based on a

population of 3,000 with a confidence level of 95% of and confidence interval of .10, the

recommendation is 94 (Rea & Parker, 2014). A sample of 109, as calculated based on

power, was sufficient based on the small population using a survey to collect the data.

Procedures for Recruitment, Participation, and Data Collection

Recruitment was done by direct email contact. A contact list was generated based

on data obtained from the CACREP program list and from internet searches for

universities with master level clinical mental health counseling programs. Individuals on

the created lists were contacted directly via email with a description of the proposed

study, the time required for participation, the requirements to participate, and a link for a

SurveyMonkey survey (Appendix B). The same email was distributed on the CESNET-L

listserv, and the ACA connect call for study participant email group list for the first

contact. The informed consent form was provided on the initial landing page of the

survey.

Information was provided in the contact form (Appendix B) that described the

purpose of the study, the commitment required, the requirements to participate, and the

participants’ rights around participation. The email included specific information for

consent including the right to be informed of the outcome of the research study and a

right to receive a copy of the findings. The participants were provided the protection of

anonymity and a right to withdraw from the study at any time. My contact information

was provided to participants including the opportunity to contact the researcher to

withdraw or with any concerns or questions. It was not expected that the nature of the

data collected would result in any client harm. However, to ensure participants are

provided adequate support, there was information provided for talkspace.com, an online

counseling forum that can be accessed at any time from any location. In addition, given

the population of the study, counselor educators training master level clinical counseling

students, it was expected the sample would have the ability to access resources if they

deemed it necessary.

A statement of privacy was provided on the landing page of the survey. The first

page stated that the information was collected anonymously. In order to ensure

anonymity, a random number was assigned to participants. In addition, SurveyMonkey

has an option to not track participants, SSL encryption is used on the site, and data are

kept securely. I set the security settings on SurveyMonkey to no tracking and to not

collect any identifying information. Although anonymous data was stored on

SurveyMonkey servers in the United States., the data did not contain any information that

can be used to identify survey respondents. The data was a protected while on the

SurveyMonkey server and during transfer by TSL cryptographic protocols. The physical

servers are always monitored and protected from intrusion or physical damage

(SurveyMonkey, 2019). SurveyMonkey uses procedures to ensure the privacy and

confidentiality of the data obtained including SSL encryption and no tracking of

participants (SurveyMonkey, 2018). Finally, to protect all data obtained, I stored the data

securely using encryption to secure the electronic data. The devices I used are secure,

password protected, and antivirus software was maintained throughout the research study.

The equipment I used is not available for access by any person, other than me. The data

will be kept for the required 5 years and then destroyed.

Based on feedback from the institutional review board (IRB), the second sampling

emails were adapted to include how the contact information had been obtained. The

updated email was again sent out on the CESNET listserv (Appendix D), the ACA

connect call for study participant email group list (Appendix E) and sent directly to the

contacts obtained through the online searches and CACREP (Appendix F). In addition,

the email list created from public data was edited based on feedback from the previous

sampling, for example some of the contacts emailed me directly to indicate they were not

eligible, and the names were removed from the list. Similarly, if someone indicated they

had already participated they were removed from the contact list as well.

The third and final email soliciting participation was edited to specify it was a

third and final request, and a final date for the survey was added then it was sent to the

three sources (a) CESNET-L, (b) ACA connect call for study participant email group,

and (c) the university email contact list. When possible, the emails were personalized, as

recommended by Dillman (2014) in an effort to increase participation. The

SurveyMonkey email list allowed for the input of first and last names and this was done

on both the second and final sampling but was not done on the first.

The anonymous online survey was created through the website SurveyMonkey.

Participants had the ability to exit the survey at any point. In addition, each question

included the option to not respond. Email contact was provided in the letter requesting

participation and several people contacted me with questions and the request for further

information. The emails were recorded, and I responded to the questions or requests

accordingly. I will provide the completed dissertation to the participants who requested

the final results.

The data was collected from counselor educators who have taught or were

teaching a skill-based counseling class in a master level clinical program during the time

of the survey. The survey questions relied on self-report for the information. The survey

included questions to collect demographic information including are (a) age, (b) gender,

(e) CACREP accreditation status of the university teaching occurred, (f) matriculated

university CACREP accredited status, (g) prior training in distance counseling, (h) past

experience using distance counseling, (i) availability of technology at teaching university,

(j) reported use of technology in the teaching setting, and (k) the inclusion of distance

counseling skills in the classroom.

The survey also included 21 items adapted from the Intrapersonal Technology

Integration Scale ([ITIS], Niederhauser & Perkmen, 2008) (Appendix H). Permission to

use and adapt the scale was obtained from both Dr Perkmen and Dr. Niederhauser

(Appendix G). The adaptations were done to clarify that the questions were related to

distance counseling technology as opposed to instructional technology as had been stated

on the original ITIS. For example, in each question the stem items will were replaced the

broader term of instructional technology to distance counseling technology. Item 23 has

an additional clarification, the question from the original ITIS has been adapted from I

have an interest in listening to a famous instructional technologist speaking about

effective use of instructional technology in the classroom to I have an interest in

listening to a famous distance counselor speaking about the effective use of distance

counseling technology in the classroom.

To clarify, the subscales that relate to self-efficacy, specifically the SE, OE, and

INT were included, with rephrasing to relate to counselor education, in order to collect

information on technology self-efficacy and technology integration specific to counselor

education. The subscale behavioral intentions (BI) was not included, only 21 of the 25

items of the ITIS will be included to collect scores on self-efficacy, outcome expectations

and interest in technology integration. The BI subscale was not included because actual

behavior, in this case teaching distance counseling skills in the counselor educator’s

classroom was the variable to be measured as the outcome variable, not intention to

utilize technology in the future.

Each subscale was scored individually, not including the BI subscale will not

affect the other subscale’s validity or reliability. Perkmen and Pamuk (2011) conducted

research on social cognitive predictors in pre-service teachers and technology integration

using only the self-efficacy subscale and the outcome expectation subscale and found the

subscales to be valid and reliable when used alone. Each subscale has been examined for

factorial validity and the SE subscale items ranged from .05 to .75, the OE items loading

ranged from .62 to .83. Perkmen and Pamuk (2011) determined that SE and OE were

indeed representative of two separate constructs and the scales distinct.

The information collected will provide baseline data on the number of counselor

educators who include information on distance counseling in the master level classroom,

their training and use of distance counseling, and additional demographic data that was

reported. Given the scarcity of any data on the topic, it will shed some light on this little-

researched domain of counselor education.

Instrumentation and Operationalization of Constructs

The instrument used in the study is the Intrapersonal Technology Integration

Scale ([ITIS] Niederhauser & Perkmen, 2008). In this section I will describe the scale and

discuss the reliability and validity of the ITIS. In addition, I include sample questions and

discuss the adaptation of the scale to apply to counselor educators.

The Intrapersonal Technology Integration Scale (Niederhauser & Perkmen, 2008).

The Intrapersonal Technology Integration Scale ([ITIS] Niederhauser & Perkmen, 2008)

was used to collect information on counselor educator self-efficacy with technology for

this research study. The ITIS was created to better understand intrapersonal cognitive

variables that affect preservice teacher’s integration of technology in their teaching. The

ITIS was originally used with pre-service teachers but has also been used with Turkish

primary school teachers (Perkmen & Surmelioglu, 2016), and in a university agricultural

program (Bunch, et al., 2012). The ITIS was developed to examine the variables of self-

efficacy, outcome expectations and performance goals and “the manner in which they

may jointly function to predict technology integration performance” (Perkmen, 2008, p.

vi).

The variable of interest in this study was counselor educator self-efficacy with

technology. The ITIS was selected because it has been used to measure self-efficacy with

technology integration and has a legacy in research on self-efficacy and technology

integration. The ITIS self-efficacy subscale is drawn from a scale that is also established

in the study of self-efficacy and technology integration, the Computer Technology

Integration Survey ([CTIS],Wang, Ertmer, & Newby 2004).

Perkmen (2008) developed the Intrapersonal Technology Integration Scale (ITIS)

scale as a dissertation study (Perkmen, 2008). The original ITIS included 25 questions

which include the self-efficacy (SE), and outcome expectation (OE) subscales, and one

question to assess performance goal setting (PG). The ITIS included questions that had

been adapted from other scales. Specifically, the self-efficacy subscale was adapted from

the CTIS (Wang, Ertmer, & Newby 2004). In fact, the stems are nearly the same, the

language is modified from the word computer in some cases, to be more consistent with

teaching. The outcome expectations subscale in unique as it was developed to include

three aspects of outcome expectation, performance outcome expectation (POE), social

outcome expectation (SOE), and self-evaluative outcome expectation (SEOE) (Perkmen,

2008). Outcome expectation is also referred to as perceived usefulness in some measures

and is related to the perceived results of carrying out the task (Perkmen, 2008). The ITIS

was selected as it measures self-efficacy with technology integration in education, the

construct which was examined in this study.

Niederhauser and Perkmen (2008) adapted the scale further. In their validation

study, the complete ITIS was comprised of 25 items including four subscales. The four

factors were, self-efficacy, outcome expectation, interest, and behavioral intention

(Niederhauser & Perkmen, 2008). These four factors are measured in four such named

subscales (a) self-efficacy (SE), (b) outcome expectation, (OE), (c) interest (INT), and (d)

behavioral intention (BI). The questions were scored on a five-point Likert Scale, 1=

strongly disagree, 2= disagree, 3= neither disagree nor agree, 4= agree, and 5= strongly

agree. The subscale scores were calculated by totaling the subscale question responses.

Higher scores indicate higher levels of self-efficacy, outcome expectation, interest, and

intention to integrate technology. The three subscales, SE, OE, and INT were analyzed

against the inclusion of distance counseling skills.

The subscales have been used independently as well as combined with other

constructs to measure technology integration. For example, Perkmen (2014) conducted a

study using the SE and OE scales along with school climate and personality factors to

examine technology integration among a group of Turkish pre-service teachers. The SE

and OE scales were also combined again with school climate by Perkmen, Antonenko, &

Caracuel (2016) to explore technology integration intentions of pre-service teachers in

Turkey, Spain and the United States. The subscales were treated as independent scales in

a study conducted by Perkmen & Surmelioglu (2016), the SE and OE scales were found

to measure unique constructs both relating to motivational factors of technology

integration. Finally, the OE scale was also evaluated independently by Niederhauser and

Perkmen (2010). The researchers determined that the construct of outcome expectation

was effectively measure by the scale. The subscales have been used independently and

the validity and reliability have been confirmed.

The ITIS is used to measure self-efficacy, and performance and outcome related

constructs found to contribute to educators’ integration of technology in the classroom.

For this study, the questions were altered slightly to be more consistent with counselor

education and the behavior intention subscale was not be used. The ITIS has been slightly

altered for other use as well. For example, Bunch et al. (2012) replaced the term

instructional technology with IWB meaning interactive whiteboard and the validity was

not impacted. The adapted scale was pilot tested, and construct reliability was confirmed.

Cronbach’s alpha coefficients for the SE=0.93, OE=0.91, and INT=0.89 (Bunch et al.,

2012). In addition, the adjusted instrument was reviewed by a panel of experts and face

validity was determined as well (Bunch et al., 2012). The slight alteration made to the

scale in this study is similar to the Bunch et al (2012) study where only the terminology

specific to the industry was used in the place of instructional technology.

In addition, Perkmen et al. (2016) recently translated and adapted the ITIS in a

study to validate the ITIS in Spanish and Turkish in Turkey, Spain and the United States.

The interest scale was not used in this study, the SE and OE were used and found to be

valid and reliable to measure self-efficacy and outcome expectation for technology

integration in education (Perkmen et al. 2016). The researchers translated the ITIS into

both Spanish and Turkish and the construct validity, factorial validity, and reliability

were confirmed.

The ITIS subscales have also been used separately or in combination with other

scales to further explore the variables of SE and OE as they relate to technology

integration for teachers Niederhauser & Perkmen, 2010; Niederhauser et al., 2012;

Perkmen et al., 2016; Perkmen & Pamuk, 2011; Perkmen & Surmelioglu, 2016). The

subscales, SE and OE, and the constructs, self-efficacy and outcome expectation, are

separate and each scale measures the construct as supported by past validation studies

(Niederhauser & Perkmen, 2010; Perkmen & Pamuk, 2011; Perkmen & Surmelioglu,

2016).

Operationalization

The two most important factors in predicting behavior are self-efficacy and

outcome expectation (Bandura, 2006). Self-efficacy is the result of many factors

including interaction with the environment (Bandura, 1997). Self-efficacy is not a global

trait but varies within the individual for different subjects (Bandura, 2006). The

integration of technology, as is necessary for distance counseling, is highly dependent on

factors related to self-efficacy with technology (Anderson et al., 2011; Bunch et al., 2012;

Ertmer et al., 2012; Gu et al., 2012; Holden & Rada, 2011; Hew & Brush, 2007; Kim et

al., 2013; Niederhauser & Perkmen, 2008, Perkmen & Pamuk, 2011, Perkmen, 2014,

Perkmen & Surmelioglu 2016, Tezci, 2011a, 2011b, Wang, Ertmer, & Newby, 2004).

The interaction of the variables SE and OE were found to be influential in the

Niederhauser and Perkmen (2008) scale for technology integration and in the technology

assistance model (TAM) as well (Venkatesh & Davis, 2000). Outcome expectation is an

important factor in teacher motivation to integrate technology in the classroom

(Niederhauser & Perkmen, 2010). Outcome expectation can be explained as the belief

that it is worthwhile to do, the “why one should” put for the effort to integrate technology

into the classroom. Similarly, Vankatesh and Davis (2000) include perceived usefulness

as part of their TAM which in quite similar to the outcome expectation in the ITIS.

The ITIS contains four subscales, self-efficacy (SE), outcome expectation (OE),

interest (INT), and behavioral intention (BI). The subscales provide a broader picture of

self-efficacy as it includes the additional factors (a) interest and (b) outcome expectation

which are influential factors in self-efficacy, motivation, and behavior (Niederhauser &

Perkmen, 2008). The ITIS provides information on the intrapersonal beliefs of educators

that have been found to be influential in the decision-making process to integrate

technology into the classroom.

The subscales together give a picture of the intrapersonal factors that enhance or

inhibit an educators’ integration of technology. Three of the four subscales are used to

measure educators’ self-perceptions of their technology integration in their classroom.

Specifically, the SE subscale was used in this study to collect data specific to counselor

educators’ self-reported confidence regarding their use of technology in the classroom.

The OE subscale includes three dimensions of outcomes, (a) performance, (b) self-

evaluation, and (c) social. The OE measures the expected benefits in the domains

mentioned regarding the use of technology in the classroom. The expected outcome of

the behavior considered has been found to be related to self-efficacy (Sang et al., 2010).

The third subscale, INT, measures the interest in integrating technology related activities.

Bandura viewed interest and self-efficacy to be influential to each other, a certain amount

of self-efficacy is needed to spark interest and self-efficacy required to generate interest

(Bandura, 1986). The three concepts of self-efficacy, interest, and outcome expectations

are related and interrelated factors that contribute to action. The individual’s interest in

integrating technology into the class can also have an influence on their motivation which

also in turn influences behavior. The BI scale measures future intention, as the study was

focused on current behavior and not future intention, the BI scale was not included. This

study examined if the factors were related to the inclusion of skills-based instruction in

the counselor educator’s classroom.

The ITIS has been validated and found to be valid and reliable in English

(Niederhauser & Perkmen, 2008; Perkmen, 2008), Italian (Benigno et al., 2014), and

Turkish and Spanish (Perkmen et al., 2016). The ITIS was first developed as a

dissertation study of Perkmen (2008). The ITIS developed in the dissertation study

included three subscales, self-efficacy (SE), outcome expectation (OE), and interest

(INT), the three that will be used for this study. In a follow-up study, the ITIS was

validated, the concurrent validity of the subscales and the overall scale was found to be

Cronbach’s alpha coefficients for the three constructs: SE = 0.93; OE = 0.91; INT = 0.89

(Niederhauser & Perkmen, 2008). The latest use of the measure was a study to validate

the SE, OE scales in addition to a measure of perceived school climate, as factors

affecting technology integration (Perkmen et al., 2016). The SE and OE subscales were

used, and the subscale validity confirmed as a reliable measure of self-efficacy with

technology and outcome expectation of integrating technology in education (Perkmen et

al., 2016).

In addition to the ITIS, counselor educators were asked, “Do you include any

component of distance counseling skills in your skills-based class? The question will

require a yes or no response. The variable was dummy coded for analysis. No=0 and

Yes=1.

The data was collected through the use of an online anonymous websurvey

through SurveyMonkey. The ITIS is administered to participants through the websurvey.

The full score for the subscale and the full ITIS, a total of the three subscales, was

calculated and entered into a table for analysis using SPSS. In addition to the ITIS

questions, the survey also collected demographic data including (a) age, (b) gender, (c)

years of experience as a counselor educator, (d) level of education, (e) CACREP status

of the university they graduated, (f) the availability of technology, (g) their use of

technology in the teaching setting, (h) CACREP accreditation status of the university

where teaching occurred, (i) past use of distance counseling and (j) prior training in

distance counseling. The questions all rely on self-report.

Data Analysis Plan

The survey data was retrieved from SurveyMonkey after the survey was closed.

The data was securely downloaded and was stored securely on an encrypted flash drive

for analysis. The data was cleaned, incomplete responses were viewed to determine if key

data was missing, specifically if question 11, “I include distance counseling skills in my

classroom” was missing, the response was omitted from the analysis. In the case of

missing data on the ITIS questions, when possible the data was averaged and assumed,

incomplete forms where an average score for any one of the three subscales could be

calculated was used and analyzed. Specifically, if more than 1 response from a single

subscale was missing, then the survey was removed from the analysis. If only one score

is missing on a subscale, the average score was calculated, the average score was filled in

for the missing response and the response was used in the analysis. In the same way, any

cases that contained more than 3 blank responses on the three subscales overall, were

rejected. Outliers, values that were +/- 3 standard deviations (SD) from the mean, will not

be included in the statistical analysis but may be reported on if they provide information

relevant to the study.

The demographic data was reported in a table including frequencies and

percentages for some of the nominal data and mean, range and standard deviation for

other variables. Specifically, the survey response data reported was entered into a table

and placed into demographic categories. The demographic variables were (a) age (b)

gender (c) highest level of education completed, (d) years of experience as a counselor

educator, (e) CACREP accreditation status of the university teaching occurred, (f)

matriculated university CACREP accredited status, (g) prior training in distance

counseling, (h) past experience using distance counseling, (i) availability of technology at

teaching university, (j) reported use of technology in the teaching setting, and (k) the

inclusion of distance counseling skills in the classroom. Measures of central tendency for

the ITIS scores were reported in Figure 1.

The construct of self-efficacy with technology, was assessed through the ITIS.

Specifically, the full ITIS score, and the total SE, OE, and INT subscales. Counselor

educator self-efficacy with technology was compared to counselor educator’s teaching

distance counseling skills in any master level skills-based class that they have taught. A

correlation was conducted on the inclusion of distance counseling skills and average

scores on the SE, OE, and INT subscales of the ITIS. The assumptions of correlation

were not met for the data, so a logistic regression was also done to examine if the

subscale and full score for the ITIS were predictive of counselor educator teaching

distance counseling skills.

Point-biserial correlation can be used with dichotomous dependent variables

(Field, 2013). Since counselor educator’s instruction used a yes or no scale a point-

biserial correlation was appropriate as the dependent variable, yes or no to teaching

distance counseling skills, is dichotomous. The point-biserial correlation will be

conducted using SPSS version 24. The inclusion of distance counseling skills was

dummy coded, 0 for no teaching skills and 1 for yes teaching skills. The ITIS uses a five-

point Likert scale and the subscale score were summed and reported for the analysis. The

subscales were summed individually and as a total score for the ITIS. The total subscale

scores and the full ITIS scores were analyzed.

The statistical analysis was done with a power of .95, alpha level of .05, two-

tailed, with a medium effect size of .3. Psychological research often uses a α=.05

(Trochim, 2006). A power of .95 is an acceptable level for research as well (Rea &

Parker, 2014). The effect size, d=.3 is based on past research done in the area of self-

efficacy and instructional content (Perkmen & Pamuk, 2011). Pearson’s rpb was

calculated to determine if there was a statistically significant relationship between

counselor educator’s self-efficacy with technology and their distance counseling

instruction behavior. Correlation studies, such as a point-biserial correlation, measure the

association between to variables, the value of rpb can range from -1 to +1 with + or - 1

indicated the two variables are perfectly correlation and 0 indicating there is no

correlation. The + or – indicates the direction of the association, if the variables both

increase or decrease in the same direction. In a point-biserial correlation the positive or

negative correlation is also influenced by the coding of the dichotomous variable (Field,

2013).

The assumptions of point-biserial correlation are similar to a Pearson’s

correlation, with an additional requirement that the dependent variable being

dichotomous. Specifically, the Pearson’s correlation has the assumption of normality.

Another assumption is that the variables have equal variance (Field, 2013). This was

tested using Levene’s test of equal variance. The findings are reported in Chapter 4.

Threats to Validity

The nature of the study, a correlation study, is not a true experimental design

which introduces threats to validity. The nature of a correlation study is to collect

information as it occurs naturally without manipulation. In this case, to collect

information on technology integration for counselor educators in the current work setting.

The goal was not to determine cause and effect but to examine the relationship between

variables. As such, the non-experimental nature of the study will introduce threats to

validity.

External Validity

External validity relates to the generalizability of the research. In this case, a

small sample of 176 counselor educators may not be representative of all counselor

educators. The population of counselor educators is somewhat diverse and is represented

in all many different states, so this sample may not be truly representative of the

population. However, the sampling included universities across the U.S. in order to

collect a more diverse sample than a limited geographic area would provide.

Another concern was the survey used an online format and the topic was related

to technology integration. To complete the survey required that participants had a level of

skill with technology which could have limited the sample group by excluding

participants that lacked the technological skills required to complete an online survey.

Similarly, two of the sampling sources were online email list services, indicating a level

of acceptance in the use of technology as a resource for communication and information

for the sample source.

Internal Validity

There were also internal threats to validity including confounding variables and

sampling. In this study, the variables examined could have been influenced by unknown

and unmeasured variables or confounding variables. In addition, there was also a threat of

self-selection bias. The sampling for the survey was purposive so participants self-

selected. Another concern was the survey used an online format and the topic of the study

was related to the integration of technology. To complete the survey required that

participants had a level of skill with technology which could have limited the sample

group by excluding participants that lacked the technological skills required to complete

an online survey.

Construct Validity

Construct validity refers to a test measuring the construct it is reported to

measure. In regard to the construct validity of this study, the instrument that was used, the

ITIS has good construct validity and concurrent validity (Niederhauser & Perkmen, 2008;

Perkmen, 2008). Chronbach’s alpha for the full scale was .96 (Niederhauser & Perkmen,

2008). In addition, the variables examined, self-efficacy, outcome expectation, and

interest were found to have internal consistency (Niederhauser & Perkmen, 2008).

Chronbach’s alpha for each subscale were .90 for SE subscale, .93 for the OE subscale,

and .89 for the INT subscale. The subscales have been validated independently as well.

Ethical Procedures

The research study met the appropriate ethical standards, in accordance with IRB

approval. IRB approval was granted, IRB 11-29-18-0081056 (Appendix C). The

procedures followed regarding participant confidentiality and privacy, informed consent,

and data protection were consistent with ethical standards required for human subjects.

Specifically, the survey clearly stated the voluntary nature and included information that

the participant may stop and leave the survey prior to submission. Each question provided

an option to not answer the question in order to respect the participants’ right to withhold

information as they wish. Because the survey did ask about gender the option to self-

identification was included, as was the option stating that the participant prefers not to

answer. Several sources support expanding the binary choices for gender in survey

research to respect those who may identify as a non-binary identity (Bauer, Braimoh,

Scheim, & Dharma, 2017). In addition, to ensure confidentiality and privacy, the data

collected was made anonymous by assigning numbers with no specific identifying factors

assigned to the number. The data was protected throughout the process and was coded to

ensure no identifying information could be gleaned from the data.

The email soliciting participation (Appendix B) contained the necessary

requirements notifying prospective volunteers of the nature of the survey including the

voluntary nature of participation, the anonymous collection of the data and the right to

refuse participation at any point. Information to report any concerns was included for the

researcher, the dissertation chair, and the Walden University IRB. In addition, the

information was repeated on the landing page of the survey, consent was required in

order to access the survey.

No adverse effects, nor requests to avail of the Talkspace therapy were reported;

however, a person from one university that was contacted, did initiate a complaint to the

IRB to incorrectly report the whole university had been sent the solicitation email. The

IRB was informed that the procedures that had been stated in the application, publicly

available emails were collected and only faculty in the counseling, or related department

were contacted, and the problem was resolved. The university was removed from further

sampling at that point. After feedback from the IRB, the solicitation email was updated

for the second and third sampling to include how their information was obtained

(Appendices D, E, F,).

Summary

The dissertation study examined the relationship between self-efficacy with

technology and counselor educator teaching of distance counseling skills in the master

level skills-based class. The sample was drawn from universities across the U.S. and

email group lists in order to find counselor educators with experience teaching a skills-

based class at the master’s degree level. The sampling was purposive, direct contact was

made through (a) publicly available email contact information from universities in the

US, (b) the CESNET-L listserv, and the (c) ACA Connect call for study participant email

group list.

The email contained the appropriate information necessary when working with

human subjects such as the voluntary nature of the study, the ability to end participation

at any time, the protection and storage of the data and protection of participant identity

using anonymous data collection procedures. An anonymous online survey was used,

through the SurveyMonkey website, encryption and data protection procedures were set

to ensure that participants were not tracked, nor any data collected from participants,

other than the survey responses. The data was stored securely on an encrypted flash drive

and will be store for 5 years as is required.

The data was cleaned, and incomplete responses were ignored. There were 223

total responses, of those 176 were considered complete responses as they had completed

all the subscale questions and question 11, I include distance counseling skills in my

class. The remaining responses were dummy coded as appropriate, and statistically

analyzed using both a point-biserial correlation analysis and a logistic regression analysis.

The findings of the analysis are discussed in detail in Chapter 4.

Chapter 4: Results

Introduction

The purpose of the study was to examine if there was a statistically significant

relationship between counselor educator self-efficacy with technology, and inclusion of

distance counseling skills instruction in their skills-based class. A correlation analysis

was performed on the data collected in the online survey. Based on the findings of the

correlation, an additional analysis, a logistic regression, was included. The additional

analysis explores if self-efficacy with technology was predictive of distance counseling

instruction in the master level skills-based class and, were any demographic variables

strong predictors of counselor educator teaching distance counseling skills in their class.

The data was collected using an online survey, which included demographic

questions and the items from the ITIS which included three subscales, SE, OE, and INT.

Subscale scores and a full-scale score were used in a logistic regression models to

determine if the variables were predictive of counselor educator inclusion of distance

counseling instruction in their class. The outcome variable, Question 11 on the survey,

was self-reported as either yes or no. Demographic variables were analyses and any

significant variables were included in logistic regression models until a best-fitting model

was found.

The original hypothesis of the study was whether there is a statistically significant

correlation between counselor educator self-efficacy with technology and their inclusion

of distance counseling skills in skills-based classes they teach. Because the survey data

provided demographic variables that were understood to be influential in technology

integration, the demographic variables were included in correlation and regression

models to examine if any of the demographic variables, in addition to self-efficacy with

technology, would be related to their inclusion of distance counseling skills in the skills-

based class taught. A second hypothesis was included: At least one of the demographic

variables is associated with counselor educator inclusion of distance counseling skills in

their class.

This chapter provides information on how the data was collected including the

time frame and the characteristics of the sample. Information including response rates

and sample demographics have been provided in this chapter as well. The results of the

statistical analysis have also been included and discussed. A summary of the findings

concludes the chapter.

Data Collection

The data collection procedures, as discussed in Chapter 3, were followed with

slight adaptions. Specifically, as planned, the email list was generated based on publicly

available information. I obtained publicly available email contacts from universities

across the United States that were found to have master level counseling programs, both

CACREP accredited, non-CACREP accredited, and also several in the process of

obtaining accreditation. I observed that several programs housed counseling psychology

programs, rehabilitation counseling programs, and school counseling programs as well,

which at times were difficult to distinguish from the overall counseling department and

associated faculty. The first list developed included 4,699 email contacts. The list was

edited based on feedback from the IRB and from individuals who had been contacted

requesting removal or notifying the researcher that they were not counselor educators. In

addition, several participants notified the researcher they had completed the survey and

those individuals were removed from the list as well. This was done after the first and

second solicitation emails were sent.

In addition to the researcher generated email list, the CESNET-L and the ACA

Connect call for study participant email groups were contacted through the list

administrator. The two email list groups were all contacted at the same time. However,

there was a delay in the dissemination of the email groups which resulted in an

approximately 2-day gap between the groups receiving the email.

A second email was sent approximately 3 weeks after the first email was sent.

The researcher compiled email list was reduced to 2,143 after revising the list. A third

email was sent 2 weeks after the second email, which was approximately 5 weeks after

the first email informing participants that it was the final call and that the survey would

close after 2 weeks from the time they received the email.

The total number of responses was 223, however only 176 participants answered

all the ITIS questions and Question 11, I include distance counseling skills in my

classroom. Surveys which did not have a response to Question 11 were excluded from

the statistical analysis. The response rate was quite low; it is difficult to calculate the

exact number of individuals contacted because there were likely individuals on the

CESNET-L or ACA Connect call for study participant group emails that were also

contacted through the university email list I created. I generated an email list included

4,699 individuals; the CESNET-L lists 4,475 members, and the ACA Connect call for

study participant email group lists 287 members, it is likely that some individuals were

contacted through more than one source.

The email generated list was the primary source of responses, 133 participants

who had been contacted by the researcher generated list responded to the first email, an

additional 51 responded through the weblink provided in the emails sent to the CESNET-

L and ACA connect group, the second email solicitation collected 23 responses and the

final call collected an addition 16 responses. The number of responses exceed the

minimum number required so the survey was closed approximately 7 weeks after the

sampling began. Most participants, 172, were from the researcher-generated email list.

Results

Descriptives

There is little research on counselor educator demographic information, however

one study by Sangganjanavanich and Balkin (2013) collected demographic data for

counselor educators. Sangganjanavanich and Balkin (2013) sampled 220 counselor

educators and of the participants, 68% were women, 32% were men, the average was

46.95 years old and the average time as a faculty member was 8.53 years. The participant

demographics in this sample were similar: 64.8% were women, 33.5% were male, the

majority were in the age group 45-54 (26.7%), and the average time as a counselor

educator was 11.02 years. In addition, the majority held a doctoral degree (85.8%), the

majority were teaching in CACREP accredited universities (90.3%) and a majority had

graduated from CACREP accredited PhD programs (60.8%) (Table 1). When it comes to

distance counseling specifically, 55.7% did not have training in distance counseling,

54.5% did not have experience using distance counseling and a 57.4% did not include

distance counseling skills in their classroom (Table 1). Nearly all the participants used

technology in the classroom (97.7%) and 67.6% reported having technology available to

teach distance counseling (Table 1). The results show that counselor educators are using

technology; however, it does not seem to be technology for distance counseling. The

findings show that a majority of highly educated counselor educators in primarily

CACREP accredited programs are not teaching distance counseling skills in their

classroom (Table 1).

Table 1

Demographic Data Frequencies and Percentages

Variable

Frequency

Percent

Age

25-34

16.5

35-44

23.9

45-54

26.7

55-64

65+

7.4

Gender

Male

33.5

Female

114

64.8

Highest Level of Education

Bachelor’s degree

0.6

Master’s degree

11.9

Doctoral Degree

151

85.9

Teaching University is CACREP Accredited

Yes

159

90.3

8.5

University Graduated from is CACREP

Accredited

Yes

107

60.8

38.1

Have Had Training in Distance Counseling

Yes

43.8

55.7

Have Experience Using Distance Counseling

Yes

54.5

45.5

Teaching University has Technology

Available to Teach Distance Counseling

Yes

119

67.6

31.3

Use Technology in Teaching Setting

Yes

172

97.7

2.3

Include Distance Counseling Skills in my

Classroom

Yes

42.6

101

57.4

Assumptions

A point-biserial correlation was conducted on the survey data. The assumptions of

a point-biserial correlation include (a) one of the variables is measured on a continuous

scale, (b) one of the variables is dichotomous, (c) there should not be any outliers, (d) the

continuous variable should be approximately normally distributed, and (e) the continuous

variable should have equal variances (Field, 2009). When testing the full-scale score and

each of the subscale scores, the assumptions were not all met. For example, the Shapiro-

Wilk test was significant for all three subscales and for the full-scale (Table 2) but the

histograms for the full scale (Figure 1) and the OE subscale show a nearly normal

distribution (Figure 2). The SE (Figure 3) and INT subscales (Figure 4) were both

skewed right.

Table 2

Test of Normality Subscale Scores

Tests of Normality

Shapiro-

Wilk

Statistic

Sig.

Self-Efficacy Subscale

Total Score

0.918

176

Outcome Expectation

Subscale Total Score

0.973

176

0.002

Interest Subscale Total

Score

0.902

176

Full Scale Score

0.972

176

0.001

Figure 1. ITIS full-scale score distribution

Figure 2. Outcome expectation subscale score distribution

Figure 3. Self-efficacy subscale score distribution

Figure 4. Interest subscale score distribution

The Levene’s test was not significant for the OE, INT and full-scale score; however, it

was significant for the SE subscale.

The assumptions for a binary logistic regression are (a) the dependent variable is

binary, (b) independent observations, (c) little or no multicollinearity, (d) linearity of

independent variables and log odds, (d) large sample size, generally 10 cases for each

independent variable in the model (Htway, 2018). The assumptions for binary logistic

regression were met, the correlations of the independent variables were all less than 1,

and the variable inflation factor for all independent variables were under 5. The sample

size was n=176 and no models included more than seven independent variables.

Statistical Findings

The initial research question was, Is there a relationship between counselor

educator self-efficacy with technology and their inclusion of distance counseling skills in

the classroom? The correlation was found to be significant; there was a positive

correlation between the full-scale ITIS score and including distance counseling skills in

the skills-based class. n=176, rpb=.343, p< .001. Similarly, there was a significant

relationship between self-efficacy subscale total scores and the inclusion of distance

counseling skills in the classroom, n=176, rpb=.403, p< .001, the outcome expectation

subscale total scores and the inclusion of distance counseling skills in the classroom,

n=176, rpb=.240, p= .001, and the interest subscale total scores and the inclusion of

distance counseling skills in the classroom, n=176, rpb=.191, p= .011. The SE subscale

total score was the most highly correlated subscale.

Scatterplot diagrams for the full-scale ITIS (Figure 5), the SE (Figure 6) subscale,

the OE subscale (Figure 7), and the INT subscale (Figure 8) respectively, with the

inclusion of distance counseling skills in the classroom show there is a positive

correlation between self-efficacy with technology and including distance counseling

skills in the classroom.

Figure 5. Scatterplot full-scale ITIS score and inclusion of distance counseling skills in

the classroom

Figure 6. Scatterplot SE subscale total score and inclusion of distance counseling skills in

the classroom

Figure 7. Scatterplot OE subscale total score and inclusion of distance counseling skills

in the classroom

Figure 8. Scatterplot INT subscale total score and inclusion of distance counseling skills

in the classroom

100

In addition to the ITIS full-scale scores and the three subscale total scores, a

correlation analysis was done on the demographic variables to determine if there were

any significant variables from the demographic information collected. The variables

found to be significantly correlated with inclusion of distance counseling skills were, (a) I

have had training in distance counseling, n=176, rpb=.372, p< .001. (b) I have experience

using distance counseling n=176, rpb=.436, p< .001., and (c) The university where I teach

has technology available to teach distance counseling n=176, rpb=.385, p< .001. Based

on the findings from the correlation, a logistic regression analysis was done including the

significant demographic variables to examine relationships further.

A logistic regression was done with the outcome variable, I include distance

counseling skills in my classroom, and all the demographic variables to determine which

demographic variables were significant in the different models. The variables I have

experience using distance counseling p=.001, The university where I teach has

technology available to teach distance counseling p<.000, and about how many years

have you been a counselor educator p=.049, were all found to be significant, these

variables were included in future models. In future models that included I have

experience using distance counseling, I have had training in distance counseling, and the

university where I work has technology available to teach distance counseling, the

predictor variable, about how many years have you been a counselor educator was not

significant. This was true for models which included the self-efficacy subscale score

only, the full ITIS score, and the three subscales together. The variable was removed

from further models.

101

Regression models were run using the outcome variable, I include distance

counseling skills in the class, and each of the total subscale scores and the full ITIS score

(Table 3). First the full ITIS scale scores were run in a model with the outcome variable,

inclusion of distance counseling skills. The full ITIS score was found to be significant

(Table 3). Next, a model was run with all three subscale score totals were analyzed, only

self-efficacy was significant in the model with the three subscale scores with the outcome

variable, inclusion of distance counseling skills (Table 3). The further models were run

using only the full-scale ITIS and the SE subscale.

Table 3

Logistic Regression Models with Inclusion of Distance Counseling Skills and ITIS Full-

Scale and Subscale Scores

S.E.

Wald

Sig.

Exp(B

)

95% C.I.for

EXP(B)

Lowe

Uppe

Correc

-2 Log

likelihoo

Cox &

Snell

Squar

Nagelkerk

e R

Square

Self-

Efficacy

Subscale

Total

Score

0.15

0.03c

18.97

0.00

1.166

1.088

1.249

67.6

205.776a

0.177

0.238

Outcome

Expectatio

n Subscale

Total

Score

0.03

0.029

1.866

0.17

1.040

0.983

1.101

Interest

Subscale

Total

Score

0.01

0.045

0.184

0.66

0.981

0.898

1.071

Full Scale

Score

0.05

0.012

18.04

0.00

1.054

1.029

1.079

64.2

217.364a

0.121

0.163

Based on the findings of the correlation, three variables were included in

regression models, (a) I have had training in distance counseling, (b) I have experience

using distance counseling, and (c) the university where I teach has technology available

102

to teach distance counseling. The three variables were significant predictors in each of

the models. Additional models were run that included all the three demographic variables

as predictor variables individually (Table 4) and together (Table 5), with either the full

ITIS scores or the self-efficacy subscale total score alone.

Table 4

Logistic Regression of Inclusion of Distance Counseling Skills and ITIS Full-Scale and

Subscale Total Scores with Significant Predictors Individually

S.E.

Wald

Sig.

Exp(B

)

95% C.I.for

EXP(B)

Lowe

Uppe

Correc

-2 Log

likelihoo

Cox

Snell

Squar

Nagelkerk

e R

Square

ITIS Full

Scale

Score

0.04

0.01

10.46

1.00

0.00

1.042

1.016

1.068

69.7

202.325a

0.189

0.254

I have

had

training

distance

counselin

1.27

0.34

13.58

1.00

0.00

3.586

1.819

7.072

ITIS Full

Scale

Score

0.03

0.01

8.834

1.00

0.00

1.039

1.013

1.066

73.9

195.650a

0.223

0.300

I have

experienc

e using

distance

counselin

1.60

0.35

20.61

1.00

0.00

4.982

2.491

9.964

ITIS Full

Scale

Score

0.05

0.01

15.81

1.00

0.00

1.053

1.026

1.080

70.1

189.607a

0.240

0.322

The

university

where I

teach has

technolog

available

to teach

distance

counselin

1.90

0.44

18.52

1.00

0.00

6.711

2.820

15.96

Self-

Efficacy

Subscale

Total

Score

0.12

0.03

14.08

0.00

1.138

1.064

1.218

70.3

197.227a

0.212

0.285

103

I have

had

training

distance

counselin

1.08

0.36

9.025

0.00

2.952

1.457

5.981

Self-

Efficacy

Subscale

Total

Score

0.12

0.03

12.79

0.00

1.130

1.057

1.209

73.9

190.641a

0.245

0.329

I have

experienc

e using

distance

counselin

1.47

0.36

16.72

0.00

4.390

2.161

8.919

Self-

Efficacy

Subscale

Total

Score

0.13

0.03

16.26

0.00

1.149

1.074

1.230

75.3

189.067a

0.242

0.325

The

university

where I

teach has

technolog

available

to teach

distance

counselin

1.63

0.44

13.32

0.00

5.118

2.130

12.30

Table 5

Logistic Regression of Inclusion of Distance Counseling Skills and ITIS Full-Scale and

Subscale Total Scores with Significant Predictors Together

S.E.

Wald

Sig.

Exp(B

)

95% C.I.for

EXP(B)

Lowe

Upper

Correc

-2 Log

likelihoo

Cox &

Snell

Squar

Nagelkerk

e R

Square

ITIS Full

Scale

Score

0.03

0.01

8.093

0.00

1.039

1.012

1.067

78.6

169.845a

0.319

0.428

I have

experienc

e using

distance

counselin

1.38

0.44

9.629

0.00

3.982

1.664

9.53

I have had

training in

distance

0.34

0.44

0.599

0.43

1.416

0.587

3.417

104

counselin

The

university

where I

teach has

technolog

available

to teach

distance

counselin

1.72

0.47

13.34

5.6

2.222

14.11

Self-

Efficacy

Subscale

Total

Score

0.10

0.03

7.859

0.00

1.106

1.031

1.187

75.1

170.213a

0.317

0.426

I have

experienc

e using

distance

counselin

1.38

0.44

9.526

0.00

3.997

1.658

9.634

I have had

training in

distance

counselin

0.27

0.45

0.359

0.54

1.315

0.536

3.227

The

university

where I

teach has

technolog

available

to teach

distance

counselin

1.55

0.47

10.72

0.00

4.714

1.864

11.92

The regression models that included both I have experience using distance

counseling and I have had training in distance counseling showed that when experience

using distance counseling was included in the model, having had training in distance

counseling was no longer a significant predictor (Table 5).

The best fit model was found to contain the two predictor variables the university

where I teach has technology available to teach distance counseling and I have

experience using distance counseling. The full-scale ITIS score and the SE subscale total

105

score varied only slightly in the models (Table 6). The full ITIS score was clearly driven

by the SE subscale score primarily.

Table 6

Logistic Regression Models Full-Scale Scores with Significant Variables and Self-

Efficacy Subscale with Significant Variables

Variables

Wald

Sig

Exp(B

)

95%

C.I.for

EXP(B

)

Lower

Upper

Correc

-2 Log

likelihoo

Cox &

Snell

Squar

Nagelkerk

e R

Square

I have

experienc

e using

distance

counselin

1.47

0.38

15.10

0.00

4.380

2.079

9.227

74.1

173.494a

0.307

0.413

The

university

where I

teach has

technolog

available

to teach

distance

counselin

1.52

0.46

10.59

0.00

4.601

1.836

11.53

Self-

Efficacy

Subscale

Total

Score

0.10

0.03

8.739

0.00

1.110

1.036

1.189

I have

experienc

e using

distance

counselin

1.51

0.37

16.03

0.00

4.539

2.165

9.519

The

university

where I

teach has

technolog

available

to teach

distance

counselin

1.72

0.46

13.60

0.00

5.582

2.239

13.92

ITIS Full

Scale

Score

0.04

0.01

9.061

0.00

1.041

1.014

1.069

79.3

172.973a

0.309

0.415

106

The model which included the full-scale ITIS score was more accurate in the

percent correct, 79.3% correct as compared to 74.1 % correct in the model which

included the SE subscale score only, however the pseudo R2 values were much closer

with the full-scale ITIS model ranging from 30.9 - 41.5 % of the variance a result of the

full score and the self-efficacy only model findings with 30.7-41.3 % of the variance

explained the scores. The self-efficacy subscale was clearly contributing to the full-scale

score and the inclusion of distance counseling skills.

The model including the full-scale ITIS also shows that the variable, the

university where I teach has technology available to teach distance counseling has a

higher odds ratio, Exp(B)=5.38 than the SE subscale model Exp(B)=.4.601. The variable I

have experience using distance counseling also varied between the two models, the full-

scale ITIS score odds ratio was Exp(B)=4.539, in the SE subscale only model,

Exp(B)=4.3. Meaning those with experience are about 4 times more likely to be in the

group that did include distance counseling in the classroom. What is clear from the

models, self-efficacy, experience, and having the technology available were significant

predictors of including distance counseling skills in the classroom.

Summary

The research question was, is there a relationship between counselor educator

self-efficacy with technology, as measured by the ITIS, and their inclusion of distance

counseling skills in the master level skills-based classroom. The correlation analysis

confirmed a significant relationship between the full-scale score on the ITIS and the

dependent variable, I include distance counseling skills in the classroom. Based on the

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correlation and regression analysis, there is a relationship between counselor educator

self-efficacy with technology and their inclusion of distance counseling skills in the

skills-based classroom. Further, having experience using distance counseling, the

university having technology available to teach distance counseling were also

significantly correlated and were significant predictors of including distance counseling

instruction in the master level skills-based classes taught by these counselor educators.

The findings of the study are consistent with past research on counselor practice

and the importance of prior experience with using distance counseling. The availability of

technology to teach distance counseling skills is also a contributing factor to teaching

distance counseling skills. Past research in the area of technology integration confirms

that although availability of technology is a factor, it alone does not explain technology

integration (Hew & Tan, 2016) The results and analysis of the findings is contained in

Chapter 5.

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Chapter 5: Discussion, Conclusions, and Recommendations

Introduction

This research study was conducted to examine if a statistically significant

relationship exists between counselor educator self-efficacy with technology and their

teaching distance counseling skills in master level counselor skills-training classes. Based

on the findings of this study, there was a significant relationship between the scores on

the ITIS and inclusion of distance counseling skills in the skills-based class.

Based on the findings of significance in the correlation analysis, the data was

further explored using logistic regression. To better understand the relationship between

counselor educator self-efficacy with technology and teaching distance counseling skills,

demographic variables were included in the analysis. Demographic variables were

examined to determine which, if any, were significantly correlated with counselor

educator inclusion of distance counseling skills in skills-based master level classes.

Significant demographic variables were included in a logistic regression model that

included the ITIS full-scale score, and the self-efficacy scale alone. From the regression

analysis it was found that the demographic variables (a) have had experience using

distance counseling, (b) the university where I teach has the technology available for me

to teach, and (c) I have had training in distance counseling were all found to be

significant predictors of teaching distance counseling skills, along with self-efficacy.

The study findings support that self-efficacy with technology, as measured by the

ITIS full-scale score and the SE subscale score, was significantly correlated with the

teaching of distance counseling skills in master level skills-based class. In addition to

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self-efficacy, prior experience using distance counseling, having prior training, and the

availability of the technology needed to teach distance counseling were found to be

significant predictors of including distance counseling skills in the skills-based class.

Using a regression analysis, it was determined that self-efficacy with technology

was predictive of counselor educator teaching distance counseling skills in their skills-

based class. Further, experience using distance counseling and the university having

technology available to teach distance counseling were the most significant predictors in

counselor educator and including distance counseling skills in their skills-based class. I

discuss how these findings related to past research in this chapter.

Relating to Past Research

There is limited research on counselor education and teaching distance counseling

skills in master level programs, and very limited information specific to skills-based

classes. There is some information on the importance of training and experience (e.g.

Holmes et al., 2014; Lazuras & Dokou, 2016; Potter & Rockinson‐Szapkiw, 2012) and

availability of technology regarding technology integration (e.g. Eickelmann, 2011). The

findings of this study are consistent with research in that area. There are several factors

that seem to influence teacher technology integration: (a) self-efficacy and related

concepts such as perceived usefulness and perceived ease of use, (b) past experience, and

& Bynum, 2018). The process of technology integration is impacted by factors which are

intrapersonal and environmental. This study confirms this as well.

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Consistent with prior research on counselors and distance counseling training,

counselors who had received training in distance counseling were more likely to use

distance counseling and had a more positive attitude about distance counseling (Simms et

al., 2011). They were also more likely to recommend training (Finn & Barak, 2010;

Simms et al., 2011).

The percentage of participants in this study who reported including distance

counseling skills in the classroom is a minority, 42.6%. No prior research could be found

which collected information on the number of counselor educators who are including

distance counseling skills in the classroom, so the information from my study provides a

starting point in understanding the impact of technology in distance counseling

instruction. The data obtained in this study can provide a baseline count of counselor

educators who are including distance counseling skills in their master level skills-based

class.

Interpretation of the Findings

The participants in this survey were mainly from CACREP accredited programs,

most had a doctoral level degree, and nearly all use technology in their class. The sample

was not diverse regarding level of education, accreditation status of the university where

they teach, or the counselor educator self-reported use of technology in teaching. This is

the first survey that has directly asked counselor educators if they were including distance

counseling skills in their classroom so there is no way to directly compare these findings

to past findings. However, some findings can be compared to what has been looked at in

the areas of education, counseling, and technology integration.

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The findings of the study support that self-efficacy is related to counselor

educator teaching distance counseling skills in their skills-based class. The full score and

the SE subscale alone models were only slightly different which indicates that SE is the

contributing factor to the full-scale score. Self-efficacy alone does not fully explain the

relationship if demographic information is included in the model. Prior experience and

the university having technology available to teach distance counseling were also found

to be significant predictors of including distance counseling skills in their skills-based

class. In some of the regression models, it was four times more likely that the respondents

with experience would be including distance counseling skills in their skills-based class.

One interesting finding of this study was that when both experience and training

were included in the logistic regression models, experience was significant while training

was not significant, indicating that experience using distance counseling technology

accounted for counselor educator technology integration to a higher degree than training

alone. This also confirms prior research in the use of distance counseling by students who

were conducting distance counseling as part of their counselor training (see Simms et al.,

2011). Similarly, this was found in regard to practice with counselors who had experience

using distance counseling having a more positive attitude about distance counseling (see

Simms et al., 2011). In addition, prior experience was a significant predictor of teaching

distance counseling, which supports the need for hands-on skills included in training, (see

Anthony, 2015; Holmes et al., 2014; Manring et al., 2011; Mitchell et al., 2003; Goss &

Anthony, 2009; Haberstroh et al., 2008; Hilty et al., 2017; Shandley et al., 2011).

112

Training is important but experience is more important; training that includes experience

is a preferable method of training.

One aspect of the findings that is concerning is the lack of training that counselor

educators have received themselves. The research supports that counselors who have

experience are more likely to use distance counseling (see Simms, et al., 2011). Training

can increase self-efficacy beliefs (Lazuras & Dokou, 2016) and use of distance

counseling (Finn & Barak, 2010). Training and experience both are significant, but

experience is more significant in predicting including distance counseling skills in their

skills-based class.

The demographic information collected indicates that counseling programs are

still not meeting the needs of counseling students. The last research study that examined

the use of technology by counselor educators was focused mainly on how technology was

utilized in teaching specifically (see Quinn, 2001). One finding of the Quinn (2001)

dissertation was that 39% of respondents used the ACES Technical Competencies with

their students. The main uses of technology reported by the respondents was for email

communication, listservs, reading online journals, and participating in chat rooms

(citation). The use of the internet in these programs was focused on communication and

research related functions.

This study found that most counselor educators are not trained in, do not have

experience in, and are not including distance counseling skills in their skills-based master

level classroom. However, the numbers were close to the 50% range in most of the areas.

It is a positive finding that 45.5% of the counselor educators who responded to the survey

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report having experience using distance counseling. It is also positive that a majority,

68.4%, of the respondents said that the university where they teach has the technology

available to teach distance counseling. Given the findings that prior experience, the

university having the technology available, and self-efficacy are important factors related

to including distance counseling skills in the master level skills-based classroom, the

availability of technology reported by a majority of counselor educators is a positive

finding. The findings of this study confirm the importance of prior experience, self-

efficacy, and the availability of technology as important factors to predict the inclusion of

distance counseling skills instruction.

Theoretical Framework

The data collected from this survey confirmed the relationship between self-

efficacy with technology and counselor educator teaching distance counseling skills. In

addition, self-efficacy was determined to be an important factor in predicting teaching

distance counseling skills along with prior experience, prior training, and having the

technology available. The study confirms that counselor educator self-efficacy with

technology has a significant relationship with counselor educator including distance

counseling skills in their skills-based class.

Although not all of the subscales had a significant relationship with including

distance counseling skills in the classroom, there is likely some interconnectedness

between the variables of prior training, past experience, and self-efficacy. Training can

have a positive influence on self-efficacy beliefs (Lazuras & Dokou, 2016), and also on

use of distance counseling (Lazuras & Dokou, 2016; Simms et al., 2011). The theory of

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self-efficacy proposes the process of decision making and the role of self-efficacy is

complex and changes in response to an interaction with the environment. The findings of

this study support the hypothesis that there is a statistically significant relationship

between counselor educator self-efficacy with technology as measured by the

Intrapersonal Technology Integration Scale (ITIS), and their including distance

counseling skills in the master level skills-based class they have taught.

Limitations of the Study

There are some limitations to the study. The study utilized an anonymous online

survey, this required participant to self-select. This self-selection could have introduced

bias into the study. In addition, the survey request was sent by email, this required a

minimal level of ability to use technology which could have excluded counselor

educators who do not use email to communicate.

In addition, it is important to remember that counselor educators may not share

the characteristics of the sample group and the results may not be applicable to all

counselor educators. The group sampled for this study was drawn from multiple sources,

however the results of this study may not be applicable to all counselor educators. The

group sampled may not be representative of all counselor educators in the United States.

Recommendations

There is a lack of research in the area of counselor training to provide distance

counseling. The increasing use of technology in the field of counseling, both by

counselors and by their clients, are areas that researchers are only beginning to explore.

Technology is being used in several ways including self-guided therapy, virtual reality, or

115

professionally guided therapy. These are just some of the uses of technology in therapy.

The diversity in technological based interventions has made understanding the research

more difficult as well. There are many areas of study that need further study.

Based on the lack of training that has been occurring in counseling programs,

training counseling students, is an area in need of more research as well. Further studies

providing information on the practice of distance counseling and training in distance

counseling would be useful to better understand what is being practiced in the

marketplace, and the training experiences of counselors, especially the training

experiences of counselors who practice online.

This study provided some insight into the practices of counselor educators in

master level counseling programs. Although the findings indicate that counseling

programs are not including distance counseling skills training in all cases, the results are

positive in two ways. The number of counselor educators who have experience is nearly

half and approximately 2/3 of the counselor educators who responded to the survey,

reported that the university where they teach has the technology available. The findings

of this study indicate that these two factors are both significant predictors of including

distance counseling skills in the master level skills-based class. In order to make the most

of training, there should be hands-on opportunities to use the technology in a simulate

environment. Training that includes experience provides an added aspect that is superior

to training alone.

Training should include hands-on opportunities to use the technology. The

relationship between experience and inclusion of distance counseling skills supports that

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training that includes experience is the most effective approach. Training that is hands on

provides opportunities for using the technology and allows for vicarious learning.

Training counselors should include a hands-on opportunity for learning to be most

effective (Anthony, 2015; Manring et al., 2011; Mitchell et al, 2003; Goss & Anthony,

2009; Haberstroh et al., 2008; Hilty et al., 2017; Shandley et al., 2011).

What is also confirmed is the importance of universities in providing the

technology to faculty and students, to be skilled and trained to practice distance

counseling. Having technology available was found to be the most significant predictor

of including distance counseling skills in the master level classroom.

Implications

The counseling field is moving online, there are many reasons why, for both

counselors and clients. What we can be sure of, is the field continues to grow. Distance

counseling offers many benefits and may be available in many places where in person

counseling is not. The reach of a counselor is now literally across the world. The need for

counselors, all counselors, to have at least basic knowledge in distance counseling is

imperative given the integration of technology and counseling. Not knowing basic

information on practice, ethics, and legal issues regarding distance counseling could lead

to violations of ethical and legal protections and could cause client harm.

Ensuring that counseling students are receiving the appropriate training needed to

navigate the online world is no longer something to think about, it is here now. The

findings from this study can be useful in better understanding counselor educator’s

behavior regarding distance counseling instruction, in practice. One important finding of

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this study is to have a baseline number of counselor educators who are including distance

counseling skills in their classrooms. This study also provided more data on the

prevalence of counselor educators who have training in distance counseling. This

information is beneficial for counseling programs to better understand the needs for not

only counseling students to receive training consistent with CACREP standards, but to

support counselor educators by providing support such as training opportunities and

technical support in the classroom. The findings of this study confirm that training,

experience, and availability of technology, are important factors in predicting teaching

distance counseling skills in the master-level skills-based classroom.

Conclusion

This study extends the knowledge of technology integration into counselor

education. The future of behavioral health care will require the ability to utilize

technology, in a number of ways, in accordance with appropriate ethical and legal

standards. Master level counselor training programs are overall not including distance

counseling into their curricula, if we depend on student or professional report (Blumer et

al., 2015; Bruno & Abbott, 2011; Finn & Barak, 2011; Pipoly, 2013 It is interested that

the findings in this study show different information from counselor educators than from

students as to training in the classroom. Counselor educators were close to 50% reporting

that they include distance counseling skills. In the research available where counselors or

students are asked, a large majority, often in the 70-80% range, state they never received

information on technology or related distance counseling topics (Blumer et al., 2015;

Bruno & Abbott, 2011; Finn & Barak, 2011; Pipoly, 2013).

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The availability, quality, and necessity of distance counseling are just some of the

reasons why it continues to grow. The lack of access to behavioral healthcare has moved

onto the web, beyond self-help into professional help. Therapy has partnered with the

internet in reducing the stigma behind therapy and making therapy available to people

around the world. The public are using distance counseling, counselors are using distance

counseling and ethical codes have specific guidelines, as do educational programs, on the

key areas to know in order to practice. The importance of distance counseling, as a tool in

the fight to increase access to mental healthcare, requires that it be used appropriately.

The findings of this study support prior studies, hands-on training is preferable and that it

is imperative that the university has the technology available in order to teach distance

counseling.

This study can provide another layer of support for factors that are associated with

technology integration in education. In this case in the area of counselor education and

distance counseling skills. The findings support self-efficacy as significant in predicting

distance counseling skills instruction. Two demographic variables, the university having

the technology available and having had experience using distance counseling, were the

only two factors that were significant predictors of distance counseling instruction in the

regression models with the self-efficacy measures.

119

References

Abbott, J. A. M., Klein, B., & Ciechomski, L. (2008). Best practices in online therapy.

Journal of Technology in Human Services, 26(2-4), 360-375.

doi:10.1080/15228830802097257

Allenman, J.R. (2002). Online counseling: The internet and mental health treatment. E-

Journal of Psychotherapy: Theory, Research, Practice, Training, 29(2), 199-209.

doi:10:1037/0033-3204.39.2.199

American Counseling Association. (2014). Code of ethics. Retrieved from

https://www.counseling.org/resources/aca-code-of-ethics.pdf

Anderson, S. E., Groulx, J. G., & Maninger, R. M. (2011). Relationships among

preservice teachers’ technology-related abilities, beliefs, and intentions to use

technology in their future classrooms. Journal of Educational Computing

Research, 45(3), 321–338. https://doi.org/10.2190/EC.45.3.d

Anthony, K. (2015). Training therapists to work effectively online and offline within

digital culture. British Journal of Guidance & Counseling, 43(1), 36-42.

http://dx.doi.org/10.1080/03069885.2014.924617

ACES Technology Interest Network. (1999). ACES guidelines for online instruction in

counselor education. Retrieved from

https://www.acesonline.net/sites/default/files/ACES%20Guidelines%20Online%2

01999.pdf

Association for Counselor Education and Supervision (April, 1999). Technical

competencies for counselor education students: Recommended guidelines for

120

program development. Retrieved from

https://acesonline.net/sites/default/files/2007_aces_technology_competencies.pdf

Association for Counselor Education and Supervision [ACES]. (2007). Technical

competencies for counselor education: Recommended guidelines for program

development. Retrieved from

https://acesonline.net/sites/default/files/2007_aces_technology_competencies.pdf

Attridge, W.C. (2004). Current practices & future implications for internet counseling. In

G.R. Walz & C. Kirkman (Eds.), CyberBytes: Highlighting Compelling Uses of

Technology in Counseling (pp. 87-103). ERIC Document Reproduction Service

No. ED478221.

Backhaus, A., Agha, Z., Maglione, M. L., Repp, A., Ross, B., Zuest, D., ... & Thorp, S.

R. (2012). Videoconferencing psychotherapy: A systematic review. Psychological

Services, 9(2), 111. https://doi.org/10.1037/a0027924

Baker, D. C., & Bufka, L. F. (2011). Preparing for the telehealth world: Navigating legal,

regulatory, reimbursement, and ethical issues in an electronic age. Professional

Psychology: Research and Practice, 42(6), 405–411.

https://doi.org/10.1037/a0025037

Bambling, M., King, R., Reid, W., & Wegner, K. (2008). Online counselling: The

experience of counsellors providing synchronous single‐session counselling to

young people. Counselling and Psychotherapy Research, 8(2), 110-116.

https://doi.org/10.1080/14733140802055011

Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change.

121

Psychological Review, 84(2), 191. Retrieved from

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.315.4567&rep=rep1&t

ype=pdf

Bandura, A. (1986). The explanatory and predictive scope of self-efficacy

theory. Journal of Social and Clinical Psychology, 4(3), 359-373.

https://doi.org/10.1521/jscp.1986.4.3.359

Bandura, A. (1989). Human agency in social cognitive theory. American

Psychologist, 44(9), 1175. https://doi.org/10.1037//0003-066x.44.9.1175

Bandura, A. (1993). Perceived self-efficacy in cognitive development and

functioning. Educational Psychologist, 28(2), 117-148.

https://doi.org/10.1207/s15326985ep2802_3

Bandura, A. (1994). Self-efficacy. In V. S. Ramachaudran (Ed.), Encyclopedia of human

behavior (Vol. 4, pp. 71-81). New York: Academic Press. (Reprinted in H.

Friedman [Ed.], Encyclopedia of mental health.) San Diego: Academic Press.

Bandura, A. (1997). Self-efficacy: The exercise of control. New York, NY: Freeman.

Bandura, A. (2006). Guide for constructing self-efficacy scales. Self-efficacy beliefs of

adolescents, 5(1), 307-337. Retrieved from

http://www.uky.edu/~eushe2/BanduraPubs/BanduraGuide2006.pdf

Barnett, J. E., & Scheetz, K. (2003). Technological advances and telehealth: Ethics, law,

and the practice of psychotherapy. Psychotherapy: Theory, Research, Practice,

Training, 40(1-2), 86. https://doi.org/10.1037/0033-3204.40.1-2.86

Barnett, J.E. (2011). Utilizing technological innovations to enhance psychotherapy

122

supervision, training, and outcomes. Psychotherapy, 48(2), 103-108.

https://doi.org/10.1037/a0023381

Barnett, J. E., & Kolmes, K. (2016a). Avoiding a disconnect with telemental health.

Monitor on Psychology, 47(5), 48–55. Retrieved from

http://www.apa.org/monitor/2016/05/ce-corner.aspx

Barnett, J. E., & Kolmes, K. (2016b). The practice of tele-mental health: Ethical, legal,

and clinical issues for practitioners. Practice Innovations, 1(1), 53-66.

https://doi.org/10.1037/pri0000014

Bastemur, S. & Bastemur, E. (2015). Technology based counseling: Perspectives of

Turkish counselors. Procedia - Social and Behavioral Sciences, 176, 431–438.

https://doi.org/10.1016/j.sbspro.2015.01.493

Bauer, G. R., Braimoh, J., Scheim, A. I., & Dharma, C. (2017). Transgender-inclusive

measures of sex/gender for population surveys: Mixed-methods evaluation and

recommendations. PLOS ONE, 12(5), e0178043.

https://doi.org/10.1371/journal.pone.0178043

Benavides-Vaello, S., Strode, A., & Sheeran, B. C. (2012). Using technology in the

delivery of mental health and substance abuse treatment in rural communities: A

review. Journal of Behavioral Health Services & Research, 40(1), 111–120.

https://doi.org/10.1007/s11414-012-9299-6

Benigno, V., Chifari, A. & Chiorri, C. (2014). ICT adoption in schools: a scale for

measuring teachers’ attitudes and beliefs. Italian Journal of Educational

123

Technology, 22(1), 59-62. Retrieved from

https://www.learntechlib.org/p/183311/.

Blumer, M.K., Hertlein, K.M., & VandenBosch, M.L. (2015). Towards the development

of educational core competencies for couple and family therapy technology

practices. Contemporary Family Therapy, 37(2), 113-121.

https://doi.org/10.1007/s10591-015-9330-1

Brown-Rice, K., & Furr, S. (2016). Counselor Educators and Students with Problems of

Professional Competence: A Survey and Discussion. Professional

Counselor, 6(2), 134-146. https://doi.org/10.15241/kbr.6.2.134

Bruno, R. & Abbott, A. (2015). Australian health professionals’ attitudes toward and

frequency of use of internet supported psychological interventions. International

Journal of Mental Health, 44, 107-123.

https://doi.org/10.1080/00207411.2015.1009784

Bunch, J. C., Robinson, J. S., & Edwards, M. C. (2012). Measuring the relationship

between agriculture teachers' self-efficacy, outcome expectation, interest, and

their use of interactive whiteboards. Journal of Agricultural Education, 53(1), 67-

80. https://doi.org/10.5032/jae.2012.01067

Cabaniss, K. (2002). Computer-related technology use by counselors in the new

millennium: A Delphi study. Journal of Technology in Counseling, 2(2).

Retrieved from http://techcounseling.net/Archive/vol2_2/cabaniss/cabaniss.htm

Caldwell, B.E, Bischoff, R.J., Derrig-Palumbo, K.A., & Liebert, J.D. (2017). Best

practices in online practice of couple and family therapy. Retrieved from

124

https://www.aamft.org/Documents/Products/AAMFT_Best_Practices_for_Online

_MFT.pdf

Callan, J. E., Maheu, M. M., & Bucky, S. F. (2017). Crisis in the behavioral health

classroom: enhancing knowledge, skills, and attitudes in telehealth training.

In Career paths in telemental health (pp. 63-80). Switzerland: Springer.

Capara, G. V., Barbaranelli, C., Steca, P., & Malone, P. S. (2006). Teachers’ self-efficacy

beliefs as determinants of job satisfaction and students’ academic achievement: A

study at the school level. Journal of School Psychology, 44, 473–490.

https://doi.org/10.1016/j.jsp.2006.09.001

Cárdenas, G., Serrano, B., Flores, L. A., & De la Rosa, A. (2008). Etherapy: A training

program for development of clinical skills in distance psychotherapy. Journal of

Technology in Human Services, 26(2-4), 470–483.

https://doi.org/10.1080/15228830802102180

Carlisle, R. M., Hays, D. G., Pribesh, S. L., & Wood, C. T. (2017). Educational

technology and distance supervision in counselor education. Counselor Education

and Supervision, 56(1), 33–49. https://doi.org/10.1002/ceas.12058

Cartreine, J. A., Ahern, D. K., & Locke, S. E. (2010). A roadmap to computer-based

psychotherapy in the United States. Harvard Review of Psychiatry, 18(2), 80–95.

https://doi.org/10.3109/10673221003707702

Celik, V., & Yesilyurt, E. (2013). Attitudes to technology, perceived computer self-

efficacy and computer anxiety as predictors of computer supported education.

125

Computers & Education, 60(1), 148–158.

https://doi.org/10.1016/j.compedu.2012.06.008

Center for Credentialing and Education Global (2016). BC-TMH Board Certified-

TeleMental health provider. Retrieved from http://www.cce-

global.org/Credentialing/BCTMH

Center for Credentialing and Education Global (2018). Best practices in video telemental

health. Retrieved from https://learn.cce-global.org/mod/scorm/player.php

Centore, A., & Milacci, F. (2008). A study of mental health counselors' use of and

perspectives on distance counseling. Journal of Mental Health Counseling, 30(3),

267-282. https://doi.org/10.17744/mehc.30.3.q871r684n863u75r

Chęć, M., Ligocka, M., Maciejewska, M., Samochowiec, J., Łodygowska, E., &

Samochowiec, A. (2016). On-line psychological support in the evaluation of

specialists and future specialists in Poland. Computers in Human Behavior, 64,

703–709. https://doi.org/10.1016/j.chb.2016.07.015

Chester, A., & Glass, C. A. (2006). Online counselling: A descriptive analysis of therapy

services on the Internet. British Journal of Guidance & Counselling, 34(2), 145–

160. https://doi.org/10.1080/03069880600583170

Cipolletta, S. & Mocellin, D. (2017): Online counseling: An exploratory survey of Italian

psychologists’ attitudes towards new ways of interaction. Psychotherapy

Research, 1-16. https://doi.org/10.1080/10503307.2016.1259533

Council for Accreditation of Counseling & Related Educational Programs. (2001). The

2001 Standards. Retrieved from

126

Council for Accreditation of Counseling & Related Educational Programs. (2009). 2009

CACREP standards. Retrieved from http://www.cacrep.org/wp-

content/uploads/2013/12/2009-Standards.pdf

Council for Accreditation of Counseling & Related Educational Programs. (2016). 2016

CACREP standards. Retrieved from http://www.cacrep.org/wp-

content/uploads/2016/06/2016-Standards-with-Glossary-rev-2.2016.pdf

Coursol, D. & Lewis, J. (2003). Counselor preparation for a cyber world: Curriculum

design and development. In J.W. Bloom & G.R. Walz (Eds.), Cybercounseling

and Cyberlearning: An Encore (19-34). Greensboro, NC:CAPS Press.

Creswell, J.W. (2012). Educational research: Planning, conducting, and evaluating

quantitative and qualitative research. 4th ed. Boston: Pearson.

Creswell, J. W., & Creswell, J. D. (2013). Research design: Qualitative, quantitative, and

mixed methods approaches. 4th ed. Los Angeles: Sage publications.

Crowe, T. V. (2017). Is telemental health services a viable alternative to traditional

psychotherapy for deaf individuals? Community Mental Health Journal, 53(2),

154-162. https://doi.org/10.1007/s10597-016-0025-3

Curts, J., Tanguma, J., & Peña, C. M. (2008). Predictors of Hispanic school teachers' self-

efficacy in the pedagogical uses of technology. Computers in the Schools, 25(1-

2), 48-63. https://doi.org/10.1080/07380560802157766

Davis, F.D. (1989) Perceived usefulness, perceived ease of use, and user acceptance of

information technology. MIS Quarterly, 13(3), 319–340.

https://doi.org/10.2307/249008

127

Dillman, D. A. (2014). Internet, Phone, Mail, and Mixed-Mode Surveys: The Tailored

Design Method. 4th ed. Hoboken, NJ: John Wiley & Sons.

Eickelmann, B. (2011). Supportive and hindering factors to a sustainable implementation

of ICT in schools. Journal for Educational Research Online/Journal für

Bildungsforschung Online, 3(1), 75-103. Retrieved from

https://www.pedocs.de/volltexte/2011/4683/pdf/JERO_2011_1_Eickelmann_Sup

portive_and_hindering_factors_S75_D_A.pdf

Ertmer, P. A., Ottenbreit-Leftwich, A. T., Sadik, O., Sendurur, E., & Sendurur, P. (2012).

Teacher beliefs and technology integration practices: A critical relationship.

Computers & Education, 59(2), 423–435.

https://doi.org/10.1016/j.compedu.2012.02.001

Faul, F., Erdfelder, E., Lang, A. G., & Buchner, A. (2007). G* Power 3: A flexible

statistical power analysis program for the social, behavioral, and biomedical

sciences. Behavior research methods, 39(2), 175-191.

https://doi.org/10.3758/bf03193146

Field, A. (2013). Discovering statistics using IBM SPSS statistics, 4th ed. London: Sage

Publications.

File, T., & Ryan, C. (2014). Computer and internet use in the united states, 2013. US

Department of Commerce, Economics and Statistics Administration, US Census

Bureau. Retrieved from https://www.census.gov/history/pdf/acs-internet2013.pdf

128

Finn, J., & Barak, A. (2010). A descriptive study of e-counsellor attitudes, ethics, and

practice. Counselling and Psychotherapy Research, 10(4), 268–277.

https://doi.org/10.1080/14733140903380847

Finn, J., & Bruce, S. (2008). The LivePerson model for delivery of etherapy services: A

case study. Journal of Technology in Human Services, 26(2-4), 282-309.

https://doi.org/10.1080/15228830802096820

Fitzgerald, T.D., Hunter, P. V., Hadjistavropoulos, T., & Koocher, G. P. (2010). Ethical

and legal considerations for internet-based psychotherapy. Cognitive Behaviour

Therapy, 39(3), 173–187. https://doi:10.1080/16506071003636046

Flaum, M. (2013). Telemental health as a solution to the widening gap in between supply

and demand for mental health services (pp. 11-25). New York, Elsevier.

Gassova, Z. (2016). Characteristics and ethics of e-therapy websites with marriage and

family therapists (Unpublished doctoral dissertation). University of Kentucky.

Geer, R., & Sweeney, T. (2012). Students’ voices about learning with technology.

Journal of Social Sciences, 8(2), 294–303.

https://doi.org/10.3844/jssp.2012.294.303

Gentile, T., Liu, L. (2008). Online training to prepare counselors for online counseling:

New strategies and tools. In G. Marks, and A. Rodssett (Eds.) E-Learn in

Corporate, Government, Healthcare and Higher Education Annual 2008 (p.

1579-1586). Las Vegas, NV:AACE

Glueckauf, R. L., Maheu, M. M., Drude, K. P., Wells, B. A., Wang, Y., Gustafson, D. J.,

& Nelson, E.-L. (2018). Survey of psychologists’ telebehavioral health practices:

129

Technology use, ethical issues, and training needs. Professional Psychology:

Research and Practice, 49(3), 205–219. https://doi:10.1037/pro0000188

Golden, S. H. (2017). Factors that Influence School Counselors' Intent to Use Online

Counseling (Unpublished doctoral dissertation). Walden University, MN.

Goss, S. & Anthony, K. (2009). Developments in the use of technology in counselling

and psychotherapy. British Journal of Guidance & Counselling, 37(3), 223-230.

https://doi.org/10.1080/03069880902956967

Gu, X., Zhu, Y., & Guo, X. (2013). Meeting the" digital natives": Understanding the

acceptance of technology in classrooms. Journal of Educational Technology &

Society, 16(1), 392. Retrieved from https://search-ebscohost-

com.ezp.waldenulibrary.org/login.aspx?direct=true&db=a9h&AN=85178218&sit

e=ehost-live&scope=site

Haberstroh, S., Duffey, T., Evans, M., Gee, R., & Trepal, H. (2007). The experience of

online counseling. Journal of Mental Health Counseling, 29(3), 269–282.

https://doi:10.17744/mehc.29.3.j344651261w357v2

Haberstroh, S., Parr, G., Bradley, L., Morgan-Fleming, B., & Gee, R. (2008). Facilitating

online counseling: Perspectives from counselors in training. Journal of

Counseling & Development, 86(4), 460–470. https://doi:10.1002/j.1556-

6678.2008.tb00534.x

Haberstroh, S. (2009). Strategies and resources for conducting online counseling. Journal

of Professional Counseling: Practice, Theory & Research, 37(2), 1-20.

https://doi.org/10.1080/15566382.2009.12033857

130

Harrell, S., & Bynum, Y. (2018). Factors Affecting Technology Integration in the

Classroom. Alabama Journal of Educational Leadership, 5, 12-18. Retrieved

from https://files.eric.ed.gov/fulltext/EJ1194723.pdf

Harris, B., & Birnbaum, R. (2014). Ethical and Legal Implications on the Use of

Technology in Counselling. Clinical Social Work Journal, 43(2), 133–141.

https://doi:10.1007/s10615-014-0515-0

Heinlen, K. T., Welfel, E. R., Richmond, E. N., & Rak, C. F. (2003). The scope of

WebCounseling: A survey of services and compliance with NBCC Standards for

the ethical practice of WebCounseling. Journal of Counseling & Development,

81(1), 61–69. https://doi.org/10.1002/j.1556-6678.2003.tb00226.x

Hertlein, K., Blumer, M.L., & Mihaloliakos, J (2014) Marriage and family counselor’s

perceived ethical issues related to online therapy. The Family Journal, 23(1), 5-

12. https://doi.org/10.1177/1066480714547184

Hertlein, K.M., Blumer, M.L., & Smith, J.M. (2014) Marriage and family therapists’ use

and comfort with online communication with clients. Contemporary Family

Therapy, 36(1), 58–69. doi:10.1007/s10591-013-9284-0

Hew, K. F., & Brush, T. (2007). Integrating technology into K-12 teaching and learning:

Current knowledge gaps and recommendations for future research. Educational

technology research and development, 55(3), 223-252. https://doi.

10.1007/s11423-006-9022-5

Hew, K. F., & Tan, C. Y. (2016). Predictors of information technology integration in

secondary schools: Evidence from a large scale study of more than 30,000

131

students. PLOS ONE, 11(12), e0168547.

https://doi:10.1371/journal.pone.0168547

Hilty, D. M., Ferrer, D. C., Parish, M. B., Johnston, B., Callahan, E. J., & Yellowlees, P.

M. (2013). The effectiveness of telemental health: a 2013 review. Telemedicine

and e-Health, 19(6), 444-454. DOI: 10.1089/tmj.2013.0075

Hilty, D. M., Crawford, A., Teshima, J., Chan, S., Sunderji, N., Yellowlees, P. M., … Li,

S.-T. (2015). A framework for telepsychiatric training and e-health: Competency-

based education, evaluation and implications. International Review of Psychiatry,

27(6), 569–592. doi:10.3109/09540261.2015.1091292

Hilty, D.M., Maheu, M.M., Drude, K.P., Hertlein, K.M, Wall, K., Long, R.P., & Luoma,

T.L. (2017) Telebehavioral health, telemental health, e-Therapy and e-Health

competencies: The need for an interprofessional framework. Journal of

Technology in Behavioral Science, 2(3-4), 171-189. doi: 10.1007/s41347-017-

0036-0

Hilty, D. M., Maheu, M. M., Drude, K. P., & Hertlein, K. M. (2018). The Need to

Implement and Evaluate Telehealth Competency Frameworks to Ensure Quality

Care across Behavioral Health Professions. Academic Psychiatry, 42(6), 818–824.

doi:10.1007/s40596-018-0992-5

Holden, H., & Rada, R. (2011). Understanding the influence of perceived usability and

technology self-efficacy on teachers’ technology acceptance. Journal of Research

on Technology in Education, 43(4), 343-367.

https://doi.org/10.1080/15391523.2011.10782576

132

Holmes, C. (2008). How ethically we practice online: An exploration of potential online

provider liability. Annual Review of CyberTherapy and Telemedicine, 6, 97-102.

Retrieved from

https://www.researchgate.net/profile/Roy_Kimble/publication/43508466_The_de

velopment_of_a_paediatric_pain_management_device/links/09e4150e8bf539515f

000000/The-development-of-a-paediatric-pain-management-device.pdf#page=97

Holmes, C., Hermann, K., & Kozlowski, K. (2014). Integrating Web 2.0 technologies in

educational and clinical settings: An isomorphic perspective. Journal of

Technology in Human Services, 32(1-2), 65-80.

https://doi.org/10.1080/15228835.2013.860363

Holmes, C. M., & Kozlowski, K. A. (2015). A preliminary comparison of online and

face-to-face process groups. Journal of Technology in Human Services,33(3),

241-262. DOI10.1080/15228835.2015.1038376

Holmsten, J.E. (2018). Exploring distance counseling: Counselor beliefs, intentions,

behaviors, and self-identification. (PhD dissertation). Retrieved from ProQuest.

(10784237).

Holzberger, D., Philipp, A., & Kunter, M. (2013). How teachers’ self-efficacy is related

to instructional quality: A longitudinal analysis. Journal of Educational

Psychology, 105(3), 774–786. https://doi:10.1037/a0032198

Hsu, S. (2010). The relationship between teacher's technology integration ability and

usage. Journal of Educational Computing Research, 43(3), 309-325.

https://doi.org/10.2190/ec.43.3.c

133

Htway, Z. (2018). Logistic Regression series part 1: Simple logistic regression.

[PowerPoint Slides]. via email

Johnson, S. M. (2017). E-Counselling: A Review of Practices and Ethical

Considerations. Antistasis, 7(1). Retrieved from

https://journals.lib.unb.ca/index.php/antistasis/article/download/25160/29509

Kiluk, B. D., Nich, C., Buck, M. B., Devore, K. A., Frankforter, T. L., LaPaglia, D. M.,

… Carroll, K. M. (2018). Randomized clinical trial of computerized and clinician-

delivered CBT in comparison with standard outpatient treatment for substance use

disorders: Primary within-treatment and follow-up outcomes. American Journal

of Psychiatry, 175(9), 853–863. doi:10.1176/appi.ajp.2018.17090978

Kim, C., Kim, M. K., Lee, C., Spector, J. M., & DeMeester, K. (2013). Teacher beliefs

and technology integration. Teaching and Teacher Education, 29, 76–85.

https://doi:10.1016/j.tate.2012.08.005

Kozlowski, K.A., & Holmes, C. (2014). Experiences in online process groups: A

qualitative study. The Journal for Specialists in Group Work, 39(4) 276-300.

https://doi: 10.1080/01933922.2014.948235

Kozlowski, K. A., & Holmes, C. M. (2017). Teaching online group counseling skills in

an on-campus group counseling course. The Journal of Counselor Preparation

and Supervision, 9(1), 162-190. https://doi:10.7729/91.1157

Langarizadeh, M., Tabatabaei, M., Tavakol, K., Naghipour, M., & Moghbeli, F. (2017).

Telemental health care, an effective alternative to conventional mental care: A

134

systematic review. Acta Informatica Medica, 25(4), 240.

https://doi:10.5455/aim.2017.25.240-246.

Larson, L. M., & Daniels, J. A. (1998). Review of the counseling self-efficacy

literature. The Counseling Psychologist, 26(2), 179-218.

http://dx.doi.org/10.1177/0011000098262001

Layne, C. M., & Hohenshil, T. H. (2005). High tech counseling: Revisited. Journal of

Counseling & Development, 83(2), 222–226. https://doi.org/10.1002/j.1556-

6678.2005.tb00599.x

Lazuras, L., & Dokou, A. (2016). Mental health professionals' acceptance of online

counseling. Technology in Society, 44, 10-14.

https://doi.org/10.1016/j.techsoc.2015.11.002

Leibert, T. Archer, J., Munson, J., & York, G. (2006). An exploratory study of client

perceptions of internet counseling and the therapeutic alliance. Journal of Mental

Health Counseling, 28(1), 69-83.

https://doi.org/10.17744/mehc.28.1.f0h37djrw89nv6vb

Maheu, M.M., Drude, K.P., Hertlein, K.M., Lipschutz, R. Wall, K. & Hilty, D.M. (2017).

An interprofessional framework for telebehavioral/ health competencies. Journal

of Technology in Behavioral Science, 2(3-4), 190-210. https://doi:

10.10007/s41347-017-0038y

Maheu, M.M. & Gordon, B.L. (2000). Counseling and therapy on the internet.

Professional Psychology: Research and Practice , 31(5), 484-489.

https://doi:10.1037/0735-7028.31.5.484

135

Mallen, M. J., Vogel, D. L., & Rochlen, A. B. (2005). The practical aspects of online

counseling: Ethics, training, technology, and competency. The Counseling

Psychologist, 33(6), 776-818. https://doi.org/10.1177/0011000005278625

Mallen, M. J., Jenkins, I. M., Vogel, D. L., & Day, S. X. (2011). Online counselling: An

initial examination of the process in a synchronous chat environment. Counselling

and Psychotherapy Research, 11(3), 220–227.

https://doi.org/10.1080/14733145.2010.486865

Manring, J., Greenberg, R. P., Gregory, R., & Gallinger, L. (2011). Learning

psychotherapy in the digital age. Psychotherapy, 48(2), 119.

https://doi.org/10.1037/a0022185

McAdams, C. R., & Wyatt, K. L. (2010). The regulation of technology-assisted distance

counseling and supervision in the United States: An analysis of current extent,

trends, and implications. Counselor Education and Supervision, 49(3), 179–192.

https://doi:10.1002/j.1556-6978.2010.tb00097.x

McGinty, K. L., Saeed, S. A., Simmons, S. C., & Yildirim, Y. (2006). Telepsychiatry and

e-mental health services: Potential for improving access to mental health care.

Psychiatric Quarterly, 77(4), 335–342. https://doi:10.1007/s11126-006-9019-6

Menon, G. M., & Rubin, M. (2011). A survey of online practitioners: Implications for

Education and Practice. Journal of Technology in Human Services, 29(2), 133-

141. https://doi: 10.1080/15228835.2011.595262

136

Mishna, F., Bogo, M., Root, J., Sawyer, J.-L., & Khoury-Kassabri, M. (2012). “It just

crept in”: The Digital Age and Implications for Social Work Practice. Clinical

Social Work Journal, 40(3), 277–286. https://doi:10.1007/s10615-012-0383-4

Mishna, F., Levine, D., Bogo, M., & Van Wert, M. (2013). Cyber Counselling: An

Innovative Field Education Pilot Project. Social Work Education, 32(4), 484–492.

https://doi:10.1080/02615479.2012.685066

Mishna, F., Tufford, L., Cook, C., & Bogo, M. (2013). Research note—A pilot cyber

Counseling course in a graduate social work program. Journal of Social Work

Education, 49(3), 515–524. https://doi.org/10.1080/10437797.2013.796855

Mitchell, J. E., Myers, T., Swan‐Kremeier, L., & Wonderlich, S. (2003). Psychotherapy

for bulimia nervosa delivered via telemedicine. European Eating Disorders

Review: The Professional Journal of the Eating Disorders Association, 11(3),

222-230. https://doi-org.ezp.waldenulibrary.org/10.1002/erv.517

Morales, C., Knezek, G., & Christensen, R. (2008). Self-efficacy ratings of technology

proficiency among teachers in Mexico and Texas. Computers in the Schools,

25(1-2), 126–144. https://doi:10.1080/07380560802158004

Motley, V., Reese, M. K., & Campos, P. (2014). Evaluating corrective feedback self-

efficacy changes among counselor educators and site supervisors. Counselor

Education and Supervision, 53(1), 34–46. https://doi-

org.ezp.waldenulibrary.org/10.1002/j.1556-6978.2014.00047.x

Murphy, L., McFadden, R., & Mitchell, D. (2008). Cybercounseling online: The

development of a university-based training program for e-mail counseling.

137

Journal of Technology in Human Services, 26(2-4), 447–469. https://doi-

org.ezp.waldenulibrary.org/10.1080/15228830802102081

Murphy, L., Parnass, P., Mitchell, D. L., Hallett, R., Cayley, P., & Seagram, S. (2009).

Client satisfaction and outcome comparisons of online and face-to-face

counselling methods. British Journal of Social Work, 39(4), 627–640.

https://doi:10.1093/bjsw/bcp041

Myers, J. E., & Gibson, D. M. (1999). Technology Competence of Counselor Educators.

Retrieved from https://files.eric.ed.gov/fulltext/ED435049.pdf

Myers, K., & Turvey, C. L. (Eds.). (2013). Elsevier insights. Telemental health: Clinical,

technical, and administrative foundations for evidence-based

practice. Amsterdam, Netherlands: Elsevier.

National Board for Certified Counselors. (2016a). National board for certified counselors

(NBCC) policy regarding the provision of distance professional services.

Retrieved from

http://www.nbcc.org/Assets/Ethics/NBCCPolicyRegardingPracticeofDistanceCou

nselingBoard.pdf

National Board for Certified Counselors. (2016b). Code of Ethics. Retrieved from

www.nbcc.org/Assets/Ethics/NBCCCodeofEthics.pdf

Niederhauser, D. S., & Perkmen, S. (2008). Validation of the intrapersonal technology

integration scale: Assessing the influence of intrapersonal factors that influence

technology integration. Computers in the Schools, 25(1-2), 98–111.

https://doi:10.1080/07380560802157956

138

Niederhauser, D. S., & Perkmen, S. (2010). Beyond self-efficacy: Measuring pre-service

teachers’ instructional technology outcome expectations. Computers in Human

Behavior, 26(3), 436–442. https://doi.org/10.1016/j.chb.2009.12.002

Niederhauser, D., Perkmen, S. & Toy, S. (2012). Valuing technology integration: The

role of outcome expectations in promoting preservice teachers’ acceptance of

technology. In P. Resta (Ed.), Proceedings of SITE 2012--Society for Information

Technology & Teacher Education International Conference (pp. 2015-2020).

Austin, Texas, USA: Association for the Advancement of Computing in

Education (AACE). Retrieved

from https://www.learntechlib.org/primary/p/39885/.

Ostrowski, J., & Collins, T. P. (2016). A comparison of telemental health terminology

used across mental health state licensure boards. The Professional Counselor,

6(4), 387–396. https://doi:10.15241/jo.6.4.387

Pelling, N. (2009). The use of email and the internet in counselling and psychological

service: What practitioners need to know. Counselling, Psychotherapy, and

Health, The Use of Technology in Mental Health Special Issue, 5(1), 1-25.

Retrieved from

https://www.researchgate.net/publication/228486169_The_Use_of_Email_and_th

e_Internet_in_Counselling_and_Psychological_Service_What_Practitioners_Nee

d_to_Know

Pennington, M., Patton, R., Ray, Amber, Katafiasz, H. (2017). A brief report on the

ethical and legal guides for technology use in marriage and family therapy.

139

Journal of Marital and Family Therapy, 43(4), 733-742.

https://doi.org/10.1111/jmft.12232

Perkmen, S. (2008). Factors that influence pre-service teachers' technology integration

performance. Theses and Dissertations. 15804. Retrieved from

https://lib.dr.iastate.edu/rtd/15804

Perkmen, S. (2014). The role of personality and school climate on pre-service teachers’

motivation towards technology integration. E-Journal of New World Sciences

Academy, 9(4), 380-393. http://dx.doi.org/10.12739/NWSA.2014.9.4.1C0625

Perkmen, S., Antonenko, P. & Caracuel, A. (2016). Validating measure of teacher

intentions to integrate technology in education in Turkey, Spain, and the USA.

Journal of Information Technology for Teacher Education, 24(2), 215-241.

Retrieved from

https://www.researchgate.net/profile/Pavlo_pasha_Antonenko2/publication/30793

3216_Validating_a_Measure_of_Teacher_Intentions_to_Integrate_Technology_i

n_Education_in_Turkey_Spain_and_the_USA/links/585145ae08aef7d0309d029e/

Validating-a-Measure-of-Teacher-Intentions-to-Integrate-Technology-in-

Education-in-Turkey-Spain-and-the-USA.pdf

Perkmen, S. & Pamuk, S. (2011). Social cognitive predictors of pre-service teachers’

technology integration performance. Asia Pacific Education Review, 12(1), 45–

58. doi:10.1007/s12564-010-9109-x

Perkmen, S & Surmelioglu, Y. (2016). Measurement of teachers’ self-efficacy and

outcome expectations for technology integration in education. [Special Issue] The

140

Turkish Online Journal of Educational Technology. 88-94. Retrieved from

https://www.researchgate.net/publication/312127166_Measurement_of_teachers'_

self-

efficacy_and_outcome_expectations_for_technology_integration_in_education

Perle, J. G., Langsam, L. C., & Nierenberg, B. (2011). Controversy clarified: An updated

review of clinical psychology and tele-health. Clinical psychology review, 31(8),

1247-1258. https://doi:10.1016/j.cpr.2011.08.003

Pipoly, L. (2013). Counselor education curriculum and online counseling. Journal of

Instructional Research, 2, 48-57. Retrieved from

https://files.eric.ed.gov/fulltext/EJ1127652.pdf

Potter, S. L., & Rockinson‐Szapkiw, A. J. (2012). Technology integration for

instructional improvement: The impact of professional development. Performance

Improvement, 51(2), 22-27. https://doi.org/10.1002/pfi.21246

Quinn, A.C. (2001). Utilization of Technology in CACREP Approved Counselor

Education Programs. (Doctoral dissertation). Retrieved from ProQuest.

(3022238)

Quinn, A.C., Hohenshil, T. & Fortune, J. (2002). Utilization of Technology in CACREP

Approved Counselor Education Programs. Journal of Technology in Counseling,

2(2). Retrieved from https://www.learntechlib.org/p/95643/.

Rea, L.M. & Parker, R.A. (2014). Designing and Conducting Survey Research: A

Comprehensive Guide. San Francisco, CA: John Wiley and Sons.

141

Richards, D., & Viganó, N. (2013). Online counseling: A narrative and critical review of

the literature. Journal of Clinical Psychology, 69(9), 994–1011.

https://doi:10.1002/jclp.21974

Reljic, R., Harper, A., & Crethar, H. (2013). Using technology creatively to empower

diverse populations in counseling. American Counseling Association, VISTAS

Online (2013): 1-14. Retrieved from https://www.counseling.org/docs/default-

source/vistas/using-technology-creatively-to-empower-diverse-populations-in-

counseling.pdf?sfvrsn=57116101_12

Resnick, B. (2011). Theory of self-efficacy. In S.J. Peterson & T.S. Bredow (Eds).

Middle range theories: Application to nursing research 3rd ed (197-223). New

York: Springer.

Ross, J. A. (1998). The antecedents and consequences of teacher efficacy. In J. Brophy

(Ed.), Advances in research on teaching (pp. 385–400). Greenwich, CT: JAI

Press.

Ross, W.R. (2016). Web-based counseling: Evaluating efficacy in light of ethical

challenges and therapeutic advantages. The Online Journal of Counseling and

Education, 5(2), 35-49. Retrieved from https://search-ebscohost-

com.ezp.waldenulibrary.org/login.aspx?direct=true&db=eue&AN=115546489&si

te=eds-live&scope=site

Recupero, P. R., & Rainey, S. E. (2006). Characteristics of E-Therapy Web Sites. The

Journal of Clinical Psychiatry, 67(09), 1435–1440.

https://doi:10.4088/jcp.v67n0915

142

Saadé, R. G., & Kira, D. (2009). Computer anxiety in e-learning: The effect of computer

self-efficacy. Journal of Information Technology Education, 8(1), 177-191.

Retrieved from

https://www.researchgate.net/profile/Raafat_Saade/publication/228672834_Comp

uter_anxiety_in_e-learning_The_effect_of_computer_self-

efficacy/links/0deec538e89483fc64000000.pdf

Sangganjanavanich, V. F., & Balkin, R. S. (2013). Burnout and job satisfaction among

counselor educators. The Journal of Humanistic Counseling, 52, 67–79.

https://doi:10.1002/j.2161-1939.2013.00033.x

Sang, G., Valcke, M., van Braak, J., & Tondeur, J. (2010). Student teachers’ thinking

processes and ICT integration: Predictors of prospective teaching behaviors with

educational technology. Computers & Education, 54(1), 103–112.

https://doi:10.1016/j.compedu.2009.07.010

Santhiveeran, J. (2009). Compliance of social work e-therapy websites to the NASW

code of ethics. Social Work in Health Care, 48(1), 1-13,

https://doi.org/10.1080/00981380802231216

Schiele, B. E., Weist, M. D., Youngstrom, E. A., Stephan, S. H., & Lever, N. A. (2014).

Counseling self-efficacy, quality of services and knowledge of evidence-based

practices in school mental health. The Professional Counselor, 4(5), 467–480.

https://doi:10.15241/bes.4.5.467

Shandley, K., Klein, B., Kyrios, M., Austin, D., Ciechomski, L., & Murray, G. (2011).

Training postgraduate psychology students to deliver psychological services

143

online. Australian Psychologist, 46(2), 120-125. https://doi.org/10.1111/j.1742-

9544.2011.00034.x

Shaw, H. E., & Shaw, S. F. (2006). Critical Ethical Issues in Online Counseling:

Assessing Current Practices with an Ethical Intent Checklist. Journal of

Counseling & Development, 84(1), 41–53. https://doi:10.1002/j.1556-

6678.2006.tb00378.x

Simms, D. C., Gibson, K., & O'donnell, S. (2011). To use or not to use: Clinicians'

perceptions of telemental health. Canadian Psychology/Psychologie canadienne,

52(1), 41. https://doi.org/10.1037/a0022275

Skaalvik, E. M., & Skaalvik, S. (2007). Dimensions of teacher self-efficacy and relations

with strain factors, perceived collective teacher-efficacy, and teacher burnout.

Journal of Educational Psychology, 99, 611–625. https://doi:10.1037/0022-

0663.99.3.611

Stanard-Kinnaird, K. (2014). Qualitative study of clinicians' experience conducting

psychotherapy using Skype (Doctoral dissertation). Retrieved from ProQuest.

(3581154)

Stewart, J., Antonenko, P.D., Robinson, J.S, & Mwavita, M. (2013). Intrapersonal factors

affecting technological pedagogical content knowledge of agricultural education

teachers. Journal of Agricultural Education, 54(3), 157-170.

https://doi.org/10.5032/jae.2013.03157

SurveyMonkey (2018). Security statement. Retrieved from

https://www.surveymonkey.com/mp/legal/security/

144

Swenson, J.E., Smothermon, J., Rosenblad, S.R., & Chalmers, C. (2016). The future is

here: ethical practices of telemental health. Journal of Psychology and

Christianity 35(4), 310. https://doi.org/10.1037/e623842012-001

Tanrikulu, İ. (2009). Counselors-in-training students’ attitudes towards online counseling.

Procedia - Social and Behavioral Sciences, 1(1), 785–788.

https://doi:10.1016/j.srrpro.2009.01.140

Tezci, E. (2011a). Factors that influence pre-service teachers’ ICT usage in education.

European Journal of Teacher Education, 34(4), 483-499.

https://doi.org/10.1080/02619768.2011.587116

Tezci, E. (2011b). Turkish primary school teachers’ perceptions of school culture

regarding ICT integration. Technology Research and Development, 59, 429-443.

https://doi.org/10.1007/s11423-011-9205-6

Teh, L.A., Acosta, A.C, Hechanova, M.R., Garabiles, M.R., & Alianan, A.S. (2014).

Attitudes of psychology graduate students toward face-to-face and online

counseling. Phillipine Journal of Psychology, 47(2), 665-97. Retrieved from

https://www.researchgate.net/profile/Gina_Hechanova/publication/284247103_At

titudes_of_Psychology_Graduate_Students_toward_Face-to-

Face_and_Online_Counseling/links/5657bbfa08ae1ef9297bf2c5/Attitudes-of-

Psychology-Graduate-Students-toward-Face-to-Face-and-Online-Counseling.pdf

Terpstra, J. A., van der Vaart, R., Spillekom-van Koulil, S., van Dam, A., Rosmalen, J.

G. M., Knoop, H., … Evers, A. W. M. (2018). Becoming an eCoach: Training

145

therapists in online cognitive-behavioral therapy for chronic pain. Patient

Education and Counseling, 101(9). https://doi:10.1016/j.pec.2018.03.029

Toscos, T., Carpenter, M., Drouin, M., Roebuck, A., Kerrigan, C., & Mirro, M. (2018).

College students' experiences with, and willingness to use, different types of

telemental health resources: Do gender, depression/anxiety, or stress levels

matter?. Telemedicine Journal And E-Health: The Official Journal of The

American Telemedicine Association, 24(12), 998-1005.

https://doi:10.1089/tmj.2017.0243

Trepal, H., Haberstroh, S., Duffey, T., & Evans, M. (2007). Considerations and Strategies

for Teaching Online Counseling Skills: Establishing Relationships in Cyberspace.

Counselor Education and Supervision, 46(4), 266–279.

https://doi:10.1002/j.1556-6978.2007.tb00031.x

Trochim, W. M. (2006). The Research Methods Knowledge Base, 2nd Edition. Internet

WWW page, at URL: http://www.socialresearchmethods.net/kb/

Tsai, P. C. (2015). Trainee’s anxiety and counseling self-efficacy in counseling sessions.

(Doctoral dissertation). Retrieved from ProQuest. (3728750).

Venkatesh, V., & Davis, F. (2000). A Theoretical Extension of the Technology

Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2),

186-204. Retrieved from http://www.jstor.org/stable/2634758

Wangberg, S. C., Gammon, D., & Spitznogle, K. (2007). In the eyes of the beholder:

exploring psychologists' attitudes towards and use of e-therapy in

Norway. CyberPsychology & Behavior, 10(3), 418-423.

146

https://doi.org/10.1089/cpb.2006.9937

Watson, J. C. (2012). Online Learning and the Development of Counseling Self-Efficacy

Beliefs. The Professional Counselor, 2(2), 143–151.

https://doi:10.15241/jcw.2.2.143

Wells, M., Mitchell, K.J., Finkelhor, D., & Becker-Blease, K.A. (2007). Online mental

health treatment: Concerns and considerations. Cyber Psychology & Behavior,

10(3),453-459. https://doi.org/10.1089/cpb.2006.9933

Wolters, C. A., & Daugherty, S. G. (2007). Goal structures and teachers’ sense of

efficacy: Their relation and association to teaching experience and academic

level. Journal of Educational Psychology, 99, 181–193.

https://doi.org/10.1037/0022-0663.99.1.181

Yellowless, P., Shore, J., & Roberts, L. (2009) Practice guidelines for videoconferencing-

based telemental health. Telemedicine and e-Health, 16(10), 1074–1089.

https://doi:10.1089/tmj.2010.0148

Yuen, E. K., Goetter, E. M., Herbet, J. D., & Forman, E. M. (2012). Challenges and

opportunities in internet-mediated telemental health. Professional Psychology,

Research and Practice, 43, 1–8. doi:10.1037/a0025524.

Zamani, Z. A., Nasir, R., & Yusooff, F. (2010). Perceptions towards online counseling

among counselors in Malaysia. Procedia - Social and Behavioral Sciences, 5,

585–589. https://doi.org/10.1016/j.sbspro.2010.07.146

Zee, M., & Koomen, H. M. (2016). Teacher self-efficacy and its effects on classroom

processes, student academic adjustment, and teacher well-being: A synthesis of 40

147

years of research. Review of Educational research, 86(4), 981-1015.

https://doi.org/10.3102/0034654315626801

Zur, O. (2018). TeleMental health definitions. Retrieved from

https://www.zurinstitute.com/telehealth_define.html

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