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Article

Adaptation and validation the Spanish version of the

Communication Styles Inventory for nursing

María del Carmen Pérez-Fuentes 1,*, María del Mar Molero Jurado 1, María del Mar Simón

Márquez 1, África Martos Martínez 1, Ana Belén Barragán Martín 1, and José Jesús Gázquez

Linares 1,2

1 University of Almería, 04120 Almería, Spain; [email protected] (M.d.M.M.J.); [email protected] (M.d.M.S.M.); [email protected] (A.M.M.); [email protected] (A.B.B.M.); [email protected] (J.J.G.L.)

2 Universidad Autónoma de Chile, 4780000 Santiago, Chile * Correspondence: [email protected]; Tel.: +34‐950015598

Abstract: (1) Background: Healthcare attention is sometimes considered purely technical, but

communication has proven to be closely related to clinical results and patient satisfaction. Therefore,

evaluation of communication in the scope of healthcare is a priority. The purpose of this study was

to validate and adapt, if necessary, the Spanish version of the Communication Styles Inventory (CSI)

in a sample of nursing professionals. (2) Methods: The sample was made up of 2313 nursing

professionals selected at random from various medical centers in Spain, and is therefore a sample

actively employed at the time data were acquired. We started out from the Communication Style

Inventory, a questionnaire for evaluating the predominance of certain individual communication

behaviors on six scales (expressiveness, preciseness, verbal aggressiveness, questioningness,

emotionality and impression manipulativeness). (3) Results: Confirmatory Factor Analysis of the

model proposed showed god fit indices. The reliability of the model shown by the Cronbach’s alpha

of α=.81 was adequate, and so was single-level and aggregate consistency. Finally, in the analysis of

variance by type of contract, configural, metric and scalar invariance was acceptable, but not strict

invariance. (4) Conclusions: This instrument progresses in measuring non-technical attributes, such

as communication styles, in nursing personnel.

Keywords: Validation, communication, questionnaire, healthcare attention, patient satisfaction,

nursing.

1. Introduction

Communication is a basic competence of vital personal and professional importance [1,2]. In

recent decades, a great deal of research has been dedicated to communication styles in healthcare, as

one of the basic pillars of wellbeing [3]. In this job context, where transfer of personal information,

knowledge, ideas, opinions and feelings has a fundamental role [4] (p.507), communication between

healthcare professionals and patients and their families is a tool which directly influences the quality

of medical attention, the experience perceived by the patient and promotion of healthy living habits

[5-7]. Particularly significant is the basic role of nursing professionals, who remain in continuous

contact with both patients and their families, performing a wide range of tasks directed at the integral

care of their patients, and spanning from health care attention, to follow-up and quality control of

care, health promotion, and even prevention [8]. It is not surprising then that the quality of

communication between nursing professionals and their patients has important implications in

healthcare intervention, identified by the patients themselves as major elements in achieving

fundamental dignity and respect in the care relationship [9].

The literature emphasizes that there are many benefits of effective communication, for example,

adherence to treatment is stronger when the communication style of professionals promotes active

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© 2019 by the author(s). Distributed under a Creative Commons CC BY license.

participation of the patients in clinical decision-making [10]. Satisfaction of patients and their families

is greater when they feel well informed and understand the care plan presented to them [11]. Another

example is the increase in expectancies, as well as subjective improvement of the patients when they

are presented an affective, warm communication style [12]. And patient safety, satisfaction and self-

management of healthcare needs are promoted when there is effective communication between the

members of the healthcare team [13,14]. But effective communication also generates benefits for

healthcare workers. It has been found that the use of motivating language by superiors increases job

commitment of nursing professionals [15]. The incidence of violent situations toward healthcare

professionals also decreases with the use of adequate communication techniques [16,17] by

improving the confidence of professionals in fighting against aggression [18]. Furthermore, this

patient-focused communication style favors creation of a climate of understanding and empathy,

which assists in establishing healthy relationships and positively influences patient wellbeing,

satisfaction and safety [19]. With regard to empathy, even though the cognitive dimension is usually

high in the majority of these professionals [20], the importance for nursing staff to make empathetic

communication focused on the patient more cognitive than affective has been emphasized [21].

Brown et al. [22] suggested that active listening is indispensable to achieve effective communication

between nursing professionals and their patients. This type of listening also helps reduce the number

of clinical malpractices claims as well as the possibility of incidents in patient treatment.

Along this line, communication between professionals in the healthcare team also has a decisive

role in service quality and patient safety. And in turn, this positively influences the wellbeing and job

satisfaction of workers, improving their self-concept of personal and professional worth [23]. Thus,

the importance of interdisciplinary communication in adequate control of the patient’s illness to

avoid medical negligence related to erroneous diagnoses and treatment problems has been

underlined [24].

Over time, different instruments have been developed to measure a person’s general

communication style, some of the most outstanding of which are the Communicator Style Measure

(CSM) [25,26], the Relational Communication Style (RCS) [27] and the Communication Style Scale (CSS)

by Gudykunst et al. [28]. Recently, De Vries, Bakker-Pieper, Konings, & Schouten [4] developed a

new tool for measuring communication styles known as the Communication Styles Inventory (CSI).

This instrument focuses exclusively on evaluating observable communicative behavior, and leaves

aside cognitive aspects and thoughts derived from interpersonal communication [29]. These authors

found that the CSI offers theoretical, empirical and practical advantages over previous measurement

instruments. One of the strengths of the CSI is its applicability in settings where communication is

the basis of interpersonal interactions, such as education, organizational or healthcare contexts [4].

With regard to the factors related to communication styles, one of the findings of De Vries et al. [4]

shows the existence of a significant association between CSI communication styles and personality

dimensions. Thus, it is understood that the communication style is determined, among other factors,

by individual personality traits. This relationship has been confirmed by several empirical studies.

For example, it has been demonstrated that high levels of “Neuroticism” in maladapted subjects with

high negative affect [30] and high levels of burnout in healthcare personnel [31] predict the use of

aggressive, hostile and authoritarian language [32-34], while the rest of personality traits are more

associated with prosocial behavior [35,36].

Another factor which influences the communication pattern of healthcare professionals is the

presence of negative emotions [37]. Falkenstein et al. [38] showed that healthcare professionals who

communicate with their patients making scant use of words with a negative emotional load are more

appreciated by their patients. In this line, Hermann, Long, & Trotta [39] point out the importance of

nursing staff using positive verbal expressions, so patients perceive they are being treated with

courtesy and respect.

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In addition to the above, with regard to sex and its relationship with communication style in

medical attention, Vogel, Meyer, & Harendza [40], showed that men have a more interrogative, less

empathetic communication style than their female coworkers. Along this line, evaluation of

communication styles of surgical trainees showed that women had a predominantly emotional

communication style, while men had higher scores in impression manipulativeness and

questioningness [41]. However, other authors have not found any differences in communication

styles used in nursing students [42].

Although healthcare attention is sometimes considered purely technical, communication has

been shown to be closely related to clinical results and patient satisfaction [43]. Evaluation of

communication in healthcare is therefore fundamental [44]. However, communication in this context,

and more specifically in nursing, has not received the necessary attention, and there are very few

instruments that evaluate it [45]. On this basis, the purpose of our study was to validate and adapt,

if necessary, the Spanish version of the Communication Styles Inventory (CSI) in a sample of nursing

professionals.

2. Experimental Section

Participants

The sample was made up of 2508 nurses selected at random from various medical centers in

Spain, and therefore, is a sample in active employment at the time data were acquired. Forty-six

subjects who did not complete the questionnaire and 149 subjects who had responded at random

(detected by control questions) were eliminated. Thus, the final study sample was made up of 2313

subjects, of whom 68.1% (n=1575) were working with temporary contracts and 31.9% (n=738) had a

permanent contract. Participants were aged 22 to 57 with a mean age of 32.7 years (SD=6.53). Of the

whole sample, 84.8% (n=1962) were women and 15.2% (n=351) men, with a mean age of 32.72

(SD=6.32) and 32.69 years (SD=6.57), respectively.

Instruments

An ad hoc questionnaire was prepared to collect the sociodemographic data (age, sex, marital

status and degree), as well as professional and job information: years of experience and employment

situation (permanent or temporary).

The Communication Style Inventory (CSI) [4] is a questionnaire for evaluating the predominance

of certain behaviors in individual communication. It consists of 96 items which are grouped in six

scales (expressiveness, preciseness, verbal aggressiveness, questioningness, emotionality and

impression manipulativeness). The items are answered on a Likert-type scale where one is equivalent

to “strongly disagree” and five to “strongly agree”. However, Items 9, 10, 15, 19, 21, 26, 27, 29, 31, 37,

40, 43, 45, 47, 49, 56, 58, 60, 62, 65, 68, 69, 72, 90, 91, 93, 96 must be inverted for proper correction and

analysis. In the original version of the instrument, the authors reported reliability levels for the scales

that varied from .82 to .88 in the general population and from .83 to .87 in a sample of students.

Procedure

First, the participants were informed of the objectives of the research and guaranteed anonymity

of their answers and compliance with the ethical standards of confidentiality in data processing. For

data collection, an online Web platform enabled the questionnaires to be filled out online. A

questionnaires survey approach was conducted in 2017. In order to avoid random or incongruent

answers, control questions were inserted to enable any anomalies or biases in the answers to be

identified. Subjects who had answered at random (detected by control questions) were eliminated.

In addition to these cases, incomplete questionnaires were also discarded. The study was approved

by the Bioethics Committee of the University of Almeria (Ref: UALBIO2017/011).

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Data Analyses

First the principles of normality and distribution of the continuous variables were tested. For

this the criterion proposed by Finney and DiStefano [46], according to which ±2 and ±7 are the

maximums acceptable in skewness and kurtosis for carrying out parametric analyses, was followed.

The descriptive and confirmatory data analyses were done in two stages by validation steps

following Pérez-Fuentes, Molero, Martos, & Gázquez [47]. In the first stage, the CSI structure was

studied. For this, the sample was first divided at random into two independent homogeneous

subsamples. The first (n=1141) was used as the calibration sample, and a Confirmatory Factor

Analysis was performed for the original model taking as the measures the following fit indices: χ2/df,

Comparative Fit Index (CFI), Tucker-Lewis index (TLI), Root Mean Square Error of Approximation

(RMSEA) with a confidence interval (CI) at 90%. The χ2/df index was used considering below five

acceptable [48], CFI and IFI over or near .95, and for the RMSEA below or very near .06 [49]. As a

general norm, good model fit would be when χ2/df ratio ≤ 3; GFI, AGFI and TLI > .90; CFI > .95;

RMSEA ≤ .05. The appropriate respecifications considering theoretical and statistical criteria

(modification indices, estimation errors, standardized errors of measurement) were made to the

original model, which was subjected to the various adjustments until the model proposed, which

showed good fit indices was arrived at. The Akaike Information Criterion [50] was used to select the

models with the second subsample (n=1172) as the validation sample to validate the respecified

model. The Cronbach’s alpha and parallel forms were used for reliability analysis of the new scale.

Finally, in the second stage, the invariant character of the factorial structure proposed was

analyzed by type of contract (permanent/temporary) and gender (male/female). First, goodness of fit

of these structures was tested separately in both subsamples (Models M0a-Permanent-Male and

Model M0b-Temporary-Female). The four resulting nested models were evaluated: a) Model 1. Both

samples were considered simultaneously with free estimation of parameters. b) Model 2. Metric

invariance was shown. c) Model 3. Scalar invariance was shown. d) Model 4. Strict invariance, with

no consensus criterion for determining the criteria to employ for evaluating the difference in fit

between the different nested models [51], for evaluation of fit, this study focused on the ΔCFI

interpreting the model as completely invariant if the value found in the ΔCFI was less than .01 [52].

Analyses were performed using the SPSS statistical package version 23.0 for Windows and the

AMOS 22 program.

3. Results

3.1. Preliminary Analyses

First the data showed that the items in the CSI showed a distribution within the limits of

normality for skewness and kurtosis, respectively. Only three items (39, 63 and 87) were found with

skewness barely above 2 which were not taken into consideration in later analysis.

3.2. Confirmatory factor analysis of the CSI and CSI-B models.

Table 1 shows the analysis of fit of the questionnaire according to the original CSI model and the

revision of that original model proposed (CSI-B). It is observed that the original model and the brief

model consist of six factors. The original model showed low fit indices, so the appropriate

respecifications were made considering theoretical and statistical criteria (modification indices,

estimation errors, standardized errors of measurement), which led to elimination of 75 items. The

brief model shows a much better fit with the calibration sample. The difference between the AIC

Default Model = 527.021 and the AIC Saturated Model = 462.000 is small compared to the original

model (AIC Default model = 9768.139; AIC Saturated model = 4420.000), showing that this model is

probably better according to the Akaike criteria for model selection.

Table 1. Fit indices for the models proposed (calibration sample; n=1141)

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Model

CFI TLI

RMSEA

χ2 (gl) χ2/df Est.

IC90%

Below Above

Original CSI model 9348.139 (2000) 4.674 .665 .652 .057 .056 .058

Proposed CSI-B Model 409.300 (174) 2.352 .956 .947 .034 .030 .038

Nota. CFI = Comparative fit index; TLI = Tucker-Lewis index; RMSEA = Root Mean Square Error

of Approximation; IC = Confidence Interval; df = Degrees of freedom; Est. = Estimation.

Figure 1. Proposed model CSI-B (validation sample n=1172)

Note: EXPRE: Expressiveness, QUES: Questioningness, EMOT: Emotionality, IM= Impression

Manipulativeness, PRE: Preciseness, VA: Verbal Aggressiveness.

Finally, fit indices for the model proposed, CSI-B, were analyzed with the validation sample

(n=1172) as shown in Figure 1. The Confirmatory Factor Analysis for the model proposed (CSI-B)

resulted in the following fit indices: χ2/df= 2.353, CFI= .956, TLI= .947, RMSEA= .034 (.030-.038).

3.3. Exploratory factor analysis of the CSI-Brief model (CSI-B)

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The principal components analysis revealed six components with eigenvalues over 1. The Scree

Test recommended making a rotation with six factors with eigenvalues of 4.84, 2.09, 1.49, 1.30, 1.17

and 0.99 respectively, as they were clearly distanced from the seventh with a score of .85 (Figure 2).

Figure 2. Scree plot for factor analysis of Model CSI-B

After the factor analysis, we selected the items with factor saturations over .40 from the Varimax

Rotation matrix. Table 2 shows how Factor 1 corresponds to the items included in the Verbal

Aggressiveness scale. This Factor 1 is comprised of three items, all with loadings of .69, and

explaining 32.06% of the variance. Factor 2 is comprised of three items and forms the Impression

Manipulativeness component, explaining 9.94% of the variance. Factor 3 is made up of four items

which form the Questioningness component and explain 7.12% of the variance. Factor 4 (four items)

is related to Expressiveness and explains 6.18% of the variance. The Emotionality component which

is clustered in Factor 5 with four items explains 5.55% of the variance. Finally, Factor 6 (Preciseness)

has three items and explains 4.69% of the variance.

Model reliability was analyzed using the Cronbach’s alpha, which with the total sample was

α=.81, for Factor 1 (Verbal Aggressiveness) α=.77, for Factor 2 (Impression Manipulativeness) α=.78,

for Factor 3 (Questioningness) α=.64, for Factor 4 (Expressiveness) α=.63, for Factor 5 (Emotionality)

α=.56, and finally for Factor 6 (Preciseness) α=.60. The data found by parallel forms also showed the

consistency of the scales on both the individual level (Spearman-Brown coefficient =.823) and

aggregate with a Guttman Split-Half Coefficient of .82

Table 2. Factor structure, communalities (h2) eigenvalues, Cronbach’s alpha and percentage of

explained variance (n=1172). Extraction method: Principal components

F1 F2 F3 F4 F5 F6 h2

Item 1 If something displeases me, I

sometimes explode with anger. .80 .69

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Item 2 I sometimes use my charm to get

something done. .76 .65

Item 3 I don't need a lot of words to get my

message across. .67 .51

Item 4

To stimulate discussion, I sometimes

express a view different from that of my

conversation partner.

.65 .50

Item 5 The comments of others have a

noticeable effect on me. .76 .63

Item 6 I sometimes flirt a little bit to win

somebody over. .83 .75

Item 7 I can be visibly tense during a

conversation. .61 .53

Item 8 Most of the time, I only need a few

words to explain something. .78 .62

Item 9 I tend to snap at people when I get

annoyed. .77 .70

Item 10 I often determine which topics are

talked about during a conversation. .64 .50

Item 11 My jokes always draw a lot of attention. .61 .45

Item 12

I try to find out what people think about

a topic by getting them to debate with

me about it.

.69 .53

Item 13 I like to talk a lot. .73 .57

Item 14 I can sometimes react somewhat

irritably to people. .69 .64

Item 15 People can tell that I am emotionally

touched by some topics of conversation. .61 .49

Item 16 I often determine the direction of a

conversation. .67 .52

Item 17 I regularly have discussions with

people about the meaning of life. .60 .44

Item 18 I sometimes put on a very seductive

voice when I want something. .75 .69

Item 19

I find it hard to talk in a relaxed manner

when what I have to say is valued

highly.

.56 .39

Item 20 With a few words I can usually clarify

my point to everybody. .76 .62

Item 21

By making controversial statements, I

often force people to express a clear

opinion.

.65 .47

Eigenvalue 4.84 2.09 1.50 1.30 1.17 .99

Percentage of explained variance 23.06 9.94 7.12 6.18 5.55 4.69 56.54

Kaiser-Meyer-Olkin .86

Barlett’s sphericity 2(210)=5566.24, p<.000

Cronbach’s Alpha .77 .78 .64 .63 .56 .60 .81

Note. The items are listed in decreasing order according to the original scale. Display coefficient >.40.

F1: Verbal Aggressiveness; F2: Impression Manipulativeness; F3: Questioningness; F4:

Expressiveness; F5: Emotionality; F6: Preciseness.

3.4. Analysis of Invariance of Model CSI-B

Table 3. Multigroup analysis of invariance by type of contract (permanent/temporary) and by

gender (male/female)

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Model χ2 df χ2 / df Δχ2 CFI ΔCFI IFI RMSEA (IC 90%)

M0a (permanent) 734.165

(p=.000) 405 1.812 .946 .946 .027 (.024-.030)

M0b (temporary) 734.165

(p=.000) 405 1.812 .946 .946 .027 (.024-.030)

M1 (overall base

model)

645.863

(p=.000) 348 1.856 88.302 .946 .946 .027 (.024-.030)

M2 (FS) 654.472

(p=.000) 363 1.802 79.693 .947 .001 .947 .026 (.023-.029)

M3 (FS + Int) 676.613

(p=.000) 384 1.762 57.552 .947 .001 .947 .026 (.022-.029)

M4 (FS + Int + Err) 772.819

(p=.000) 426 1.814 38.654 .937 .011 .937 .026 (.023-.029)

M0a (male) 672.460

(p=.000) 348 1.932 .941 .942 .028 (.025-.031)

M0b (female) 672.460

(p=.000) 348 1.932 .941 .942 .028 (.025-.031)

M1 (overall base

model)

672.460

(p=.000) 348 1.932 .940 .940 .028 (.025-.031)

M2 (FS) 694.729

(p=.000) 363 1.913 22.269 .918 .022 .919 .032 (.029-.035)

M3 (FS + Int) 833.458

(p=.000) 384 2.170 160.998 .916 .024 .916 .031 (.028-.034)

M4 (FS + Int + Err) 900.886

(p=.000) 426 2.115 228.426 .914 .026 .914 .031 (.028-.034)

Note: FS= Factor Saturations, Int=Intercepts, Err=Errors.

Table 3 shows the values for the six different models. In the analysis of variance based on type

of contract, in all cases, ΔCFI was less than .01, so configural, metric and scalar invariance were

accepted, except for Model 4, where it was .011, so strict invariance could not be accepted. With

regard to gender, the ΔCFI was over .01 in Models 2, 3 and 4, and only configural invariance was

accepted. Specifically, the ΔCFI between Model 1 (overall base model) and the rest of the models 3

and 4 was .022-.026, so metric, scalar and strict invariance could not be accepted.

4. Discussion

The objective of this study was to examine the psychometric properties of the CSI [4] in the

healthcare context and more specifically in nursing. The results showed that the CSI brief version for

nursing personnel had adequate item discrimination, and may be considered a valid and reliable

instrument for evaluating communication styles in this population. Therefore, confirmatory factor

analysis of the model supported the six-factor structure of the original model (expressiveness,

preciseness, verbal aggressiveness, questioningness, emotionality and impression manipulativeness)

[4]. Nevertheless, this brief version does not have the 96 items on the original scale. The brief CSI

version consists of 21 items resulting from the eliminating three items from the start because they did

not have adequate skewness indices, and then 72 more after respecification following theoretical and

statistical criteria. Thus, the CSI-B model found has four items each for the expressiveness,

questioningness and emotionality factors and three items each for the verbal aggressiveness,

preciseness and impression manipulativeness factors.

The fit results for this abbreviated model were better than in the original model, both for the

calibration sample and for the validation sample. Similarly, internal consistency of the scale was

adequate with .81, with somewhat lower alphas for the various subscales (.77 the verbal

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aggressiveness factor, .78 for impression manipulativeness, .64 questioningness, .63 on the

emotionality factor, .56 for expressiveness and .60 for preciseness).

As communication in healthcare is a variable acquiring more and more importance due to its

significant implications for patient care quality [5-7], its evaluation in this context is necessary [44].

To date, the instruments for evaluating communication styles in healthcare professionals, and

especially in nurses, have been rare, and furthermore, some of them are based on the analysis of the

role of professional communication with the patient [45], and do not analyze all the contexts in which

the professional needs communication skills. Therefore, this instrument is an advance in

measurement of non-technical attributes, such as communication styles, in nursing personnel, both

with their superiors and their coworkers, in addition to persons with whom the most direct attention

is given, such as patients and their families [8].

As limitations of this study, we must mention the nonacceptance of some invariance, for

example, with respect to the type of contract, for which configural, metric and scalar invariance was

accepted, while only configural invariance could be accepted across gender. In view of this result,

although there is substantial equivalence of the construct across gender, we cannot affirm that there

is equality between scale factors in the subsamples analyzed. Therefore, future research should

evaluate each of the items that configure these factors to study the cause of the poor fit. Nevertheless,

although this may seem to be influenced by the small sample of men, which is a limitation of this

study, this actually corresponds to the reality of the population of nursing professionals, where the

ratio of men is very small. Thus, in the future we could work on applying the model proposed of the

questionnaire to an equivalent sample of men and women, although it would be very hard and would

involve discarding many female participants.

Another limitation of the study is the low alpha scores, especially on the expressiveness and

preciseness factors. This may be due to the brevity of the questionnaire, which could have generated

losses when evaluating communication styles. Therefore, we emphasize the need to evaluate the

adequacy of the items which comprise the factors in the scale and whether to eliminate some of the

factors which originally were maintained from the original model, and which when the items were

drastically decreased, influenced the alpha.

5. Conclusions

Communication in healthcare is a very relevant activity involved in a multitude of areas.

Therefore, the styles professionals in this sector use in communicating must be adequately evaluated,

to find out related factors as well as their scope. The brief version of the CSI for nursing professionals

is a valid instrument for evaluation of this construct.

We can state that the Communication Style Inventory Brief version for nursing personnel has

favorable psychometric properties for evaluating these professionals. However, given the limitations

commented on above, we recommend that this model continue to be analyzed to make sure of the

technical attributes and psychometric characteristics of the instrument and be able to validate its use

in other healthcare sectors. Future lines of research evaluating the variance of the model could also

consider other variables, such as years of professional experience, since communication style is an

attribute developed over time.

Author Contributions: M.d.C.P.F., M.d.M.M.J., A.B.B.M., M.d.M.S.M., J.J.G.L. and A.M.M. contributed to the

conception and design of the review. M.d.C.P.F. applied the search strategy. All authors applied the selection

criteria. All authors completed the assessment of risk of bias. All authors analysed and interpreted data. All

authors wrote this manuscript. M.d.M.M.J., M.C.P.F. and J.J.G.L. edited this manuscript. M.d.C.P.F. is

responsible for the overall project.

Funding: This research received no external funding.

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Acknowledgments: The present study was undertaken in collaboration with the Excma. Diputación Provincial

de Almería. Part of this work has been developed thanks to the financing of University Teaching Training in

Deficit Areas, Gerty Cori Aid, for the help in hiring research staff in predoctoral training, granted by María del

Mar Simón Márquez.

Conflicts of Interest: The authors declare no conflict of interest.

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