who can help me

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Caralise W. Hunt, PhD, RN, CMSRN, is Assistant Professor, School of Nursing, Auburn University, Auburn, AL.

Bonnie K. Sanderson, PhD, RN, is Professor, School of Nursing, Auburn University, Auburn, AL.

Kathy Jo Ellison, PhD, RN, is Associate Professor, School of Nursing, Auburn University, Auburn, AL.

Note: The corresponding author received the Academy of Medical-Surgical Nurses Cecelia Gatson Grindel Evidence-Based Practice Research Grant Award to conduct this study.

Support for Diabetes Using Technology: A Pilot Study to Improve

Self-Management

A ccording to the American Diabetes Association (ADA, 2013a), 25.8 million people

in the United States currently are living with diabetes. Approximately 90%-95% of these have type 2 dia- betes (T2DM). If not managed prop- erly, diabetes leads to multiple com- plications, including heart disease, stroke, high blood pressure, kidney disease, blindness, and limb ampu- tation. Management of diabetes requires participation in a multifac- eted program. The complex nature of diabetes treatment plans makes it difficult for people living with dia- betes to understand and maintain daily self-management (Sevick et al., 2008). Technology may assist with processing the complexities of a self-management plan by provid- ing education and visual feedback of self-management behaviors.

Review of Literature People living with diabetes are

encouraged to follow a healthy diet, monitor blood glucose, exercise, take prescribed medications, and monitor for diabetes-related com- plications by daily inspecting skin and feet and obtaining an annual eye examination (ADA, 2013b). Self-care management interven- tions improve glycemic control in people living with T2DM, leading to greater well-being and decreased complications (Minet, Moller, Vach, Wagner, & Henriksen, 2010; Renders et al., 2009). Prior to study onset, a literature review was conducted for the years 2007-2012 using PubMed,

CINAHL, and PsycINFO databases. Search terms included diabetes self- management, diabetes self-manage- ment behaviors, diabetes and self-effi- cacy, and diabetes and technology.

Research indicates self-efficacy is linked closely to diabetes self-man- agement, with higher levels of self- efficacy being related to increased participation in diabetes self-man- agement behaviors (King et al., 2010; Lanting et al., 2008; O’Hea et al., 2009). Methods to promote self- efficacy in persons with diabetes have the potential to improve dia- betes self-management, thereby improving overall disease control. Technology is being used increas- ingly to assist people living with diabetes with self-management. New technological advances can improve self-management by en - couraging patients to participate in practices and routines related to their illness and providing educa- tional and motivational support for day-to-day diabetes management.

Technological interventions offer promise for enhancing self-efficacy and support for diabetes self-man- agement. One study evaluated three different methods of diabetes educa- tion delivery, including two different web interactive methods and a tradi- tional face-to-face education (Pacaud, Kelley, Downey, & Chiasson, 2012). Improvements in diabetes knowl- edge, self-efficacy, and self-manage- ment were noted for all three meth- ods. Significant correlations were found between higher website usage and higher diabetes knowl- edge, self-efficacy scores, and meta- bolic control. Researchers conclud- ed diabetes education delivered electronically can be as effective as the traditional face-to-face delivery method and may offer options for meeting the increasing demands for diabetes self-management educa- tion.

Another study evaluated the effect of a text message-based diabetes program on diabetes management

Research for PracticeResearch for Practice

Caralise W. Hunt Bonnie K. Sanderson

Kathy Jo Ellison

Technology may assist people living with type 2 diabetes with self- management. A pilot study that used Apple® iPad® technology to support diabetes self-management is described.

July-August 2014 • Vol. 23/No. 4232

(Nundy, Dick, Solomon, & Peek, 2013). Participants received daily text messages about taking medications, weekly reminders about foot care, and appointment reminders for dia- betes-related visits. They also could request additional messages related to diabetes care, such as reminders about glucose monitoring. The intervention im proved self-efficacy for self-management by providing feedback on self-management and relating symptoms to self-manage- ment behaviors. Qualitatively, par- ticipants re ported the text messag- ing intervention increased self- awareness and control, provided reinforcement and feedback, in - creased realization of the signifi- cance of diabetes, and provided car- ing and support.

An online diabetes self-manage- ment program was evaluated by Lorig and co-authors (2010). Par - ticipants accessed a website for edu- cational sessions and weekly learn- ing activities. They also formulated an action plan for each week. Participants in the intervention group had significant improve- ments in self-efficacy for diabetes self-management compared to the usual care control group.

Research has been conducted using handheld devices to promote diabetes self-management. A ran- domized controlled trial of 151 par- ticipants tested the use of personal digital assistants (PDA) for improv- ing diabetes regimen adherence (Sevick et al., 2008). Researchers found the PDA self-monitoring enhanced accuracy of estimated caloric intake and expenditure, enhanced vigilance to the dietary regimen, allowed problem-solving for glucose control issues by exam- ining dietary intake and glucose values, and allowed positive rein- forcement and goal revision as needed.

A qualitative study used a mobile phone and web-based collaborative care intervention for patients with T2DM (Lyles et al., 2011). Smart - phones and other technology to sup- port diabetes self-management were provided to study participants. Most participants appreciated email com- munications with the nurse and

found it easy to upload glucose infor- mation from meters. However, most participants found the smartphones to be frustrating. These participants had not used a smartphone previous- ly and had difficulty with basic oper- ation of the phone. Participants and re searchers recommended using the technology with devices already familiar to patients. Although partic- ipants found the smartphones frus- trating, most believed the program increased awareness of their health and helped them to be more focused and accountable for self-managing diabetes.

An experimental study was con- ducted to evaluate the effects of interactive multimedia on partici- pants’ diabetes knowledge, ability to control blood glucose, and self- care (Huang, Chen, & Yeh, 2009). Following the 3-month interven- tion, members of the experimental group had significantly higher dia- betes knowledge levels than those in the control group who received a routine education program. Re - searchers found no significant dif- ferences between groups for glyco- sylated hemoglobin (A1C) values or self-care behaviors. A1C im proved for the experimental group, but not to a level of significance. Addi - tionally, the experimental group showed improvement in all self-care behaviors except exercise for the study period; however, improve- ments again did not reach a level of statistical significance. Participants in the experimental group were sat- isfied with the diabetes interactive multimedia, indicating this may be an acceptable method for diabetes self-management education.

Diabetes self-management inter- ventions also are being delivered using the Internet. An Internet computer-assisted diabetes self- management intervention utilized goal-setting for medication adher- ence, physical activity, and food choices (Glasgow et al., 2012). Participants recorded progress toward goals and created action plans to address barriers to goal achievement. Health behaviors improved significantly for experi- mental group participants com- pared to control group participants.

Researchers noted greatest improve- ments at 4 months with small effects at 12 months.

Tang and colleagues (2013) con- ducted a multicomponent random- ized controlled trial to evaluate an online disease management system to support people living with T2DM. The intervention included wireless uploading of glucose read- ings with graphical feedback, nutri- tion and exercise logs, online mes- saging with the health care team, personalized text, and video educa- tion. At 6 months, A1C values for intervention group participants were significantly lower compared to control group participants. The difference was not significant at 12 months, however, possibly due to significant improvements in A1C among control group participants at this time. Intervention group par- ticipants also had significantly bet- ter low-density lipoprotein choles- terol values at 12 months, but no differences were seen for blood pres- sure or weight.

Self-management behavior track- ing, as well as improved access to diabetes education and health care providers, can increase knowledge, self-efficacy, and participation in self-management behaviors, and ultimately may improve diabetes outcomes (Pacaud et al., 2012). Health care professionals should develop and implement self-man- agement support technology pro- grams to meet the need to deliver individualized, cost-effective care that can reach into communities and homes (Fisher & Dickinson, 2011). While literature supports the use of technology to meet the needs of people living with diabetes, more re search is needed to determine which types of technological inter- ventions are most beneficial. Tech - nology should be evaluated for motivation for diabetes self-man- agement, user satisfaction, and dia- betes outcomes.

Purpose The purpose of this pilot study

was to determine if the use of appli- cations on Apple® iPad® technology that support diabetes self-manage-

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Support for Diabetes Using Technology: A Pilot Study to Improve Self-Management

ment will increase self-efficacy for self-management, increase participa- tion in self-management behaviors, and improve diabetes outcomes in persons with T2DM in an employer- sponsored diabetes self-management program. Specific aims for the proj- ect included the following: • Increase self-efficacy for diabetes

self-management. • Increase participation in diabetes

self-management behaviors, in - cluding monitoring blood glu - cose, taking medications, exer- cising, and following a recom- mended eating plan.

• Improve diabetes control (A1C).

Theoretical Framework The study was guided by Self-

Determination Theory, a general the- ory of human motivation which sug- gests people have three innate psy- chological needs: autonomy, comp - etence, and relatedness to others (Deci & Ryan, 2002). Au tonomy involves self-regulation of behaviors through experience and reflective self-endorsement. Com petence refers to a person’s confidence in the ability to self-manage and is similar to the self-efficacy concept. Relatedness in - volves feeling meaningfully connect- ed to others. Feeling a partnership with health care providers increases de sire to participate in self-manage- ment behaviors. Self-Determination Theory indicates support for these three needs will enhance both men- tal and physical health. People are more likely to adopt healthy behav- iors when these basic needs are sup- ported. This intervention can in - crease autonomy by allowing self- management behaviors to be tracked and reviewed. This permits re flection on self-management through visual representation of how day-to-day activities affect outcomes such as blood glucose. The use of technology to track self-management can in - crease competence when people liv- ing with diabetes see positive results based on behaviors. Relate dness can be accomplished through feedback obtained from health care providers based on documented self-manage- ment behaviors.

Methods

Design and Sample This pilot study used a two-group,

crossover, repeated-measures design. Participants were recruited from the employee health group of a diabetes and nutrition center at a local med- ical center in an urban area of the Southeast. Repre sentatives from the employee health program posted study informational flyers at the cen- ter. An informational email blast describing the study and providing researcher contact information was sent by a representative to all employees enrolled in the health program. Interested persons were referred to the primary investigator for questions about study enroll- ment if they met the inclusion crite- ria. Inclusion criteria were people liv- ing with T2DM, age 19 or older, and able to read and write English. The goal was to enroll 20 employees in the pilot study. Approximately 60 people contacted the primary inves- tigator about study participation; 17 met inclusion criteria and agreed to participate. The primary reason given by potential participants for not enrolling in the study was a lack of time.

Procedures The study proposal was reviewed

and approved by the institutional review boards from the university leading the study and the participat- ing hospital. The primary investiga- tor met with potential participants at the diabetes and nutrition center. Study details were explained and a written informed consent document was provided. Potential participants were given the opportunity to ask questions. Those who were interest- ed in participating in the study signed the consent document and were given a copy. Following in - formed consent, participants com- pleted pre-intervention demograph- ic, self-efficacy, and diabetes self- management questionnaires. Base - line A1C values were collected by diabetes and nutrition center staff and documented by researchers.

Participants were assigned ran- domly either to the intervention

(iPad) or control (journal) group. The primary investigator distributed the Apple iPad devices and provided instructions on using the diabetes self-management application to log behaviors. Participants also were instructed how to email logs to the primary investigator once per week using a single GMail account estab- lished for the study. The control group participants were given instructions on how to log diabetes self-management activities in the provided journal. Participants in both groups were asked to log dia- betes self-management behaviors in the following categories: monitoring blood glucose, following a recom- mended eating plan, exercising, and taking medications on a daily basis. Contact information for the primary investigator was provided in case participants required assistance or had questions during the study peri- od. The initial meetings, which last- ed approximately 1 hour, were con- ducted either in groups or individu- ally according to participant prefer- ence.

Researchers met with participants from both intervention and control groups 3 months following the ini- tial meeting to complete mid-inter- vention assessments. At this time, participants in the iPad group were given a paper journal to log diabetes self-management activities for the next 3 months. Participants in the paper journal group were given an iPad to document diabetes self-man- agement behaviors for the next 3 months. A final assessment was completed after this 3-month study period. A diabetes educator from the diabetes and nutrition center was available throughout the study peri- od to answer participant questions related to their medical treatment programs.

Measures Demographic information in -

cluding age, sex, race, length of time diagnosed with diabetes, and highest level of education was ob - tained prior to the study. Pre-inter- vention, mid-intervention, and post-intervention measures of self- efficacy and diabetes self-manage- ment were obtained. The Diabetes

July-August 2014 • Vol. 23/No. 4234

Management Self-Efficacy Scale (DMSES) (van der Bijl, Poelgeest- Eeltink, & Shortridge-Baggett, 1999) was used to measure self-efficacy. The 20-item instrument includes questions about self-care activities people living with T2DM must per- form to manage the disease, includ- ing eating a heart healthy diet, par- ticipating in physical activity, mon- itoring blood glucose, taking med- ications, and monitoring for com- plications. The 10-point Likert scale assessed patients’ confidence in their ability to manage their dia- betes, with higher scores indicating higher levels of self-efficacy. In - ternal consistency of the total scale measured by Cronbach’s alpha ranged from 0.81 to 0.92 in previ- ous studies (Coffman, 2008; Hunt et al., 2012; van der Bijl et al., 1999).

Participation in diabetes self- management behaviors was meas- ured using the Summary of Diabetes Self-Care Activities-Revised (SDSCA) questionnaire (Toobert, Hampson, & Glasgow, 2000). The instrument contains 11 items to evaluate the frequency with which participants engage in self-manage- ment behaviors, including diet, exercise, medication use, blood glu- cose testing, and foot care. Re - spondents indicate the frequency with which they participated in each self-management behavior in the last 7 days. Mean number of days is calculated for each category of self- management behaviors, with higher scores indicating more frequent participation in self-management behaviors. Overall internal con - sistency as measured by Cronbach’s alpha ranged from 0.65 to 0.84 in previous studies (Eigenmann, Colagiuri, Skinner, & Trevena, 2009; Hunt et al., 2012).

An iPad application (Diabetes Buddy®) was loaded on each device to track self-management behav- iors. Diabetes Buddy was chosen because it allows tracking of the rec- ommended diabetes self-manage- ment behaviors of glucose monitor- ing, eating a healthy diet, exercis- ing, and using medication. The application also allows emailing of data from within the application as well as unlimited logging of behav-

iors. Participants logged behaviors each day and emailed a report of activities each week to the primary investigator. Control group partici- pants logged the same behaviors using a paper journal.

Data Analysis Descriptive statistics were used to

analyze demographic data and A1C values. Pre-test and post-test meas- urements of self-efficacy and dia- betes self-management behaviors were analyzed using a mixed model analysis of variance with the group (monitoring method) as the be - tween-subjects factor, and self-effi- cacy and diabetes self-management behaviors as the repeated factors. A repeated measures analysis also was used to determine changes in self- management behaviors over time.

Results

Demographic Characteristics During the first phase of the

study, 3 of the 17 participants with- drew due to time constraints or family issues; the final sample was 14 participants (see Table 1 for demographic characteristics). Ten participants (59%) were female and 11 (65%) were over age 50. Thirteen (77%) of the participants had been diagnosed with T2DM less than 10 years.

Hemoglobin A1C The sample for this pilot study

had good glycemic control at base- line with an average A1C of 6.59%. No additional A1C values were available during the study period.

Self-Efficacy The mean and standard deviation

(SD) self-efficacy score for the entire sample as measured by the DMSES was high at 8.55 (+/- 0.89). This self- efficacy mean score falls within the “certain can do” for the DMSES. The group using iPads in the first arm of the study had significantly higher baseline self-efficacy scores than the second group with means (SD) at 9.1 (+/- 0.76) and 8.1 (+/- 0.43), which continued throughout the study. Self-efficacy scores for the first iPad

group (n=6) remained relatively the same from baseline to mid-interven- tion and post-intervention (9.1, 9, and 9.2). Self-efficacy scores for the second iPad group (n=8) decreased slightly from baseline to mid-inter- vention after logging using the jour- nal and increased after using the iPads, but not to a level of signifi- cance (8.1, 7.9, and 8.7). Analysis of t-tests revealed no statistically signif- icant change in either group with iPad use, indicating the intervention did not impact self-efficacy in this sample.

Diabetes Self-Management The mean diabetes self-manage-

ment score for the sample as meas- ured by the SDSCA was 5.1 (+/- 0.89) at baseline. For the group using iPads first, SDSCA scores remained the same, but decreased slightly after using the journals to log behaviors (5.4, 5.3, and 5). For the group using iPads for the sec- ond half of the study, SDSCA scores decreased after journal use, but sig- nificantly increased at post-inter- vention after using the iPads (4.8, 4.6, and 5.2). Analysis of t-tests revealed no significant differences between groups.

Activity Logs A comparison of self-manage-

ment behavior activity logs between iPad use and journal use revealed mixed results. Some participants logged more self-management be - haviors when they used the iPad and others logged more activities using the journal. This may indicate the process of tracking self-manage- ment behaviors may be more important than the method used to track behaviors. Personal prefer- ences must be considered.

Discussion Results revealed no difference in

self-efficacy scores between the iPad and journal study groups; however, self-efficacy scores were very high at baseline, making it difficult to iden- tify improvement. A larger, more varied sample is needed for addi- tional evaluation. Additionally, the average A1C of 6.5% for the sample

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indicated good glycemic control. These findings support previous research indicating higher levels of self-efficacy are linked with im - proved glycemic control. Self-effica- cy areas that were scored lowest by participants involved following a healthy eating plan. This also supported previous research indi- cating people living with diabetes struggle with dietary self-manage- ment (Booth, Lowis, Dean, Hunter, & McKinley, 2013; Franks et al., 2012; Song & Kim, 2009).

Participant scores on the SDSCA remained the same in the first iPad group and significantly increased in the second group after iPad use. The significant increase in the second group may indicate tracking of behaviors using the iPad applica- tion increases awareness of and need to participate in self-manage- ment. Both groups had decreases in SDSCA scores at midpoint. Perhaps documenting behaviors led to par- ticipants’ realization they were not performing self-management as often as they thought. Of the SDSCA categories, taking medica-

tions had the highest score while exercise had the lowest. Similar results were found in previous stud- ies (Al-Khawaldeh, Al-Hassan, & Froelicher, 2012; Hunt et al., 2012; Song & Kim, 2009).

A1C values were collected by dia- betes and nutrition center staff and reported to the primary re searcher. Because the majority of participants were below 7%, staff did not recom- mend obtaining another A1C for 6 months. At the 6-month point, most participants did not have another A1C drawn primarily be - cause the diabetes and nutrition center was in the process of relocat- ing and the primary researcher had to meet participants at other loca- tions for the post-intervention data collection.

Qualitatively, participants off ered mostly positive comments about using the iPad application to track self-management behaviors. Parti - cipants discussed how the applica- tion had helped them keep track of blood glucose levels, food intake, and exercise. One participant liked

the carbohydrate counter and indi- cated she had not known how to track carbohydrates prior to using the application. Participants found the summary of activities helpful and liked having all the self-manage- ment information available at a glance. For some participants, seeing all the information in one place enabled them to link self-manage- ment activities with glucose control. For example, a participant stated he did not realize until he began track- ing his exercise that if he exercised more, his glucose was lower and he did not have to use as much insulin. One participant said tracking made him realize he was not doing enough to manage his diabetes even though he thought he was.

Nursing Implications The complexity of diabetes man-

agement makes the use of technolo- gy important to improving out- comes for patients with diabetes. Technological advances offer prom- ise for promoting diabetes self-man- agement (Liang et al., 2011; Lyles et al., 2011; Pal et al., 2013). Providing technology to promote tracking of diabetes self-management encour- ages patient autonomy. Patients can visualize progress toward goals using diabetes applications, which will promote competence. Sup - porting patients in self-management through technology may improve diabetes outcomes. Effec tive self- management contributes to blood glucose control, lowered blood pres- sure and cholesterol, avoidance of complications, and improved quali- ty of life (Funnell et al., 2007; Jones et al., 2003; Sousa, Zauszniewski, Musil, Lea, & Davis, 2005). In con- trast, patients who do not participate in daily self-management activities have an increased risk for developing diabetes-related complications, in - cluding stroke, heart disease, kidney disease, limb amputation, and blind- ness (American Association Diabetes Educators, 2006).

As identified in this study as well as previous research, diet and exer- cise are two areas with which peo- ple living with diabetes struggle and could benefit from support. An Internet-based intervention pro-

Support for Diabetes Using Technology: A Pilot Study to Improve Self-Management

TABLE 1. Sample Demographics

Characteristic n %

Sex

Male 7 41.2

Female 10 58.8

Age

19-50 6 35.3

51 and older 11 64.7

Race

African American 3 17.7

Caucasian 13 76.5

Other 1 6

Educational Level

Less than high school graduate 1 6

High school graduate and some college 11 64.7

College graduate or professional degree 5 29.3

Number of Years Diagnosed with Diabetes

10 years or less 13 76.5

11 years of more 4 23.5

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duced significant improvements in healthy eating and physical activity for a group of people living with T2DM (Glasgow et al., 2012). Nurses can provide education in these areas and use available tech- nological resources to help patients access ongoing education and sup- port in these areas.

A growing number of people have access to smartphone and Internet technology (Brenner, 2013; Duggan & Smith, 2013). As technol- ogy and devices become more accessible, options for use in chron- ic disease management will increase. Technology can be used to supple- ment health care provider education and support when resources, includ- ing time, are limited. Technology that is accessible at the time a patient needs it offers continuous support and tools for managing multiple self- care behaviors (Glasgow et al., 2012). Nurses should be knowledgeable about various technological ad - vances and assist patients to identi- fy technology that can be used to facilitate diabetes self-management.

Limitations This pilot study included a small

convenience sample. Participants had good glycemic control and high self-efficacy scores at baseline, which may have limited the effec- tiveness of the intervention. An additional limitation was the use of self-report measures. The study required participants to log self- management activities each day. Due to time constraints or other issues, participants may have per- formed self-management activities but did not log them using the iPad application or journal. The logs may not represent accurately the number of self-management activi- ties participants completed each day. Finally, the food entry section of the iPad application was reported to be tedious to use. Participants had to follow multiple steps to enter a consumed food and locating foods was difficult. Every partici- pant qualitatively listed the food entry as problematic on the iPad application evaluation.

Recommendations for Future Research

Findings from this pilot study will be used as preliminary data to guide a larger study to evaluate the effect of technology to support diabetes self- management for people living with T2DM. Expanded re cruitment sites will be used to obtain a heteroge- neous sample. Future directions in - clude exploration of providing dia- betes self-management education and social support using smartphone applications. Provision of both gener- al and personalized health education through technological devices is lack- ing (Chomutare, Fernandez-Luque, Arsand, & Hartvigsen, 2011). Re - search should focus on integration of diabetes management education and health care provider/peer support for people with diabetes using technolo- gy. Current studies indicate technol- ogy can have a positive impact on diabetes self-management. The po - tential for technological advances as adjuncts to clinical care should be explored. Future studies should iden- tify which technologies are most effective for improving self-manage- ment and diabetes outcomes. Addi - tionally, other potential uses of tech- nology for self-management should be explored.

Conclusion Self-management requires peo-

ple living with diabetes to under- stand the multifaceted treatment plan, and modify and maintain daily behaviors. Maintaining daily self-management is necessary, but challenging. As technology ad - vances, health care providers need to reinvent approaches to educating and assisting patients to self-man- age T2DM. Research is needed to evaluate the most effective forms of technology for promoting diabetes self-management.

REFERENCES Al-Khawaldeh, O.A., Al-Hassan, M.A., &

Froelicher, E.S. (2012). Self-efficacy, self-management, and glycemic control in adults with type 2 diabetes mellitus. Journal of Diabetes and Its Compli - cations, 26, 10-16. doi:10.1016/j.jdia comp.2011.11.002

American Association of Diabetes Educators. (2006). Regulatory restrictions limit peo- ple with diabetes from receiving the self- management skills they need. Retrieved from http://www.diabeteseducator.org/ export/sites/aade/_resources/pdf/cde_ medicare_provider.pdf

American Diabetes Association (ADA). (2013a). Statistics about diabetes. Retrieved from http://www.diabetes.org/ diabetes-basics/diabetes-statistics/

American Diabetes Association (ADA). (2013b). Standards of medical care in diabetes-2013. Diabetes Care, 36(Suppl. 1), s11-s66. doi:10.2337/dc13- s011

Booth, A.O., Lowis, C., Dean, M., Hunter, S.J., & McKinley, M.C. (2013). Diet and phys- ical activity in the self-management of type 2 diabetes: Barriers and facilitators identified by patients and health profes- sionals. Primary Health Care Research & Development, 14(3), 293-306. doi:10.1017/S1463423612000412

Brenner, J. (2013). Pew research Internet proj- ect: Mobile technology fact sheet. Retrieved from http://pewinternet.org/ Commentary/2012/February/Pew- Internet-Mobile.aspx

Chomutare, T., Fernandez-Luque, L., Arsand, E., & Hartvigsen, G. (2011). Features of mobile diabetes applications: Review of the literature and analysis of current applications compared against evi- dence-based guidelines. Journal of Medical Internet Research, 13(3), e65. doi:10.2196/jmir.1874

Coffman, M.J. (2008). Effects of tangible social support and depression on dia- betes self-efficacy. Journal of Geron - tological Nursing, 34, 32-39.

Deci, E.L., & Ryan, RM. (Eds.). (2002). Handbook of self-determination re - search. Rochester, NY: University of Rochester Press.

Duggan, M., & Smith, A. (2013). Pew research Internet project: Cell Internet use 2013. Retrieved from http://pewinternet.org/ Reports/2013/Cell-Internet.aspx

Eigenmann, C.A., Colagiuri, R., Skinner, T.C., & Trevena, L. (2009). Are current psy- chometric tools suitable for measuring outcomes of diabetes education? Diabetic Medicine, 26, 425-436.

Fisher, L., & Dickinson, W. P. (2011). New technologies to advance self-manage- ment support in diabetes: Not just a bunch of cool apps! Diabetes Care, 34(1), 240-243. doi: 10.2337/dc10-1830

Franks, M.M., Hemphill, R.C., Seidel, A.J., Stephens, M.A., Rook, K.S., & Salem, J.K. (2012). Setbacks in diet adherence and emotional distress: A study of older patients with type 2 diabetes and their spouses. Aging & Mental Health, 16(7), 902-910. doi: 10.1080/13607863.2012. 67448

Funnell, M.M., Brown, T.L., Childs, B.P., Haas, L.B., Hosey, G.M., Jensen, B., … Weiss, M.A. (2007). National standards for dia- betes self-management education. The Diabetes Educator, 33, 599-614. doi:10.2337/dc07-9923

Research for Practice

July-August 2014 • Vol. 23/No. 4 237

Glasgow, R.E., Kurz, D., King, D., Dickman, J.M., Faber, A.J., Halterman, E., … Ritzwoller, D. (2012). Twelve-month out- comes of an Internet-based diabetes self-management support program. Patient Education and Counseling, 87, 81-92. doi:10.1016/j.pec.2011.07.024

Huang, J.P., Chen, H.H., & Yeh, M.L. (2009). A comparison of diabetes learning with and without interactive multimedia to improve knowledge, control, and self-care among people with diabetes in Taiwan. Public Health Nursing, 26(4), 317-328. doi: 10.1111/j.1525-1446.2009.007786.x

Hunt, C.W., Grant, J.S., Pryor, E.R., Moneyham, L., Wilder, B., & Steele, M.M. (2012). Relationships among self- efficacy, social support, social problem- solving, and self-management in a rural sample living with type 2 diabetes melli- tus. Research and Theory for Nursing Practice, 26, 126-141.

Jones, H., Edwards, L., Vallis, T.M., Ruggiero, L., Rossi, S.R., Rossi, J.S., & Zinman, B. (2003). Changes in diabetes self-care behaviors make a difference in glycemic control: The Diabetes Stages of Change (DiSC) study. Diabetes Care, 26(3), 732- 737.

King, D.K., Glasgow, R.E., Toobert, D.J., Strycker, L.A., Estabrooks, P.A., Osuna, D., & Faber, A.J. (2010). Self-efficacy, problem solving, and social-environmen- tal support are associated with diabetes self-management behaviors. Diabetes Care, 33, 751-753. doi:10.2337/dc09- 1746

Lanting, L.C., Joung, I.M.A., Vogel, I., Bootsma, A.H., Lamberts, S.W.J., & Mackenbach, J.P. (2008). Ethnic differ- ences in outcomes of diabetes care and the role of self-management behavior. Patient Education and Counseling, 72, 146-154.

Liang, X., Wang, Q., Yang, X., Cao, J., Chen, J., Mo, X., … Gu, D. (2011). Effect of mobile phone intervention for diabetes on glycaemic control: A meta-analysis. Diabetic Medicine, 28(4), 455-463. doi:10.1111/j.1464-5491.2010.03180.x

Lorig, K., Ritter, P.L., Laurent, D.D., Plant, K., Green, M. Jernigan, V.B.B., & Case, S. (2010). Online diabetes self-manage- ment program. Diabetes Care, 33(6), 1275-1281. doi:10.2337/dc09-2153

Lyles, C.R., Harris, L.T., Le, T., Flowers, J., Tufano, J., Britt, D., … Ralston, J.D. (2011). Qualitative evaluation of a mobile phone and web-based collaborative care intervention for patients with type 2 dia- betes. Diabetes Technology & Thera - peutics, 13(5), 563-569. doi:10.1089/ dia.2010.0200

Minet, L., Moller, S., Vach, W., Wagner, L., & Henriksen, J.E. (2010). Mediating the effect of self-care management interven- tion in type 2 diabetes: A meta-analysis of 47 randomised controlled trials. Patient Education and Counseling, 80, 29-41. doi:10.1016/j.pec.2009.09.033

Nundy, S., Dick, J.J., Solomon, M.C., & Peek, M.E. (2013). Developing a behavioral model for mobile phone-based diabetes

interventions. Patient Education and Counseling, 90, 125-132. doi:10.1016/ j.pec.2012.09.008

O’Hea, E.L., Moon, S., Grothe, K.B., Boudreaux, E., Bodenlos, J.S., Wallston, K., & Brantley, P.J. (2009). The interac- tion of locus of control, self-efficacy, and outcome expectancy in relation to HbA1c in medically underserved individuals with type 2 diabetes. Journal of Behavioral Medicine, 32, 106-117. doi:10.1007/ s10865-008-9188-x

Pacaud, D., Kelley, H., Downey, A.M., & Chiasson, M. (2012). Successful delivery of diabetes self-care education and fol- low-up through ehealth media. Canadian Journal of Diabetes, 36, 257-262. doi:10.1016/j..jcjd.2012.08.006

Pal, K., Eastwood, S.V., Michie, S., Farmer, A.J., Barnard, M.L., Peacock, R., … Murray, E. (2013). Computer-based dia- betes self-management interventions for adults with type 2 diabetes mellitus. Cochrane Reviews, 3. doi:10.1002/ 14651858.CD008776.pub2

Renders, C.M., Valk, G.D., Griffin, S.J., Wagner, E., van Eijk, J.T., & Assendelft, W.J.J. (2009). Interventions to improve the management of diabetes mellitus in primary care, outpatient and community settings. Cochrane Database of Systematic Reviews 2000, 4, CD001481. doi:10.1002/14651858.CD 001481

Sevick, M.A., Zickmund, S., Korytkowski, M., Piraino, B., Sereika, S., Mihalko, S., … Burke, L.E. (2008). Design, feasibility, and acceptability of an intervention using

personal digital assistant-based self- monitoring in managing type 2 diabetes. Contemporary Clinical Trials, 29(3), 396- 409. doi:10.1016/j.cct.2007.09.004

Song, M.S., & Kim, H.S. (2009). Intensive management program to improve glyco- sylated hemoglobin levels and adher- ence to diet in patients with type 2 dia- betes. Applied Nursing Research, 22, 42-47. doi:10.1016/j.apnr.2007.05.004

Sousa, V.D., Zauszniewski, J.A., Musil, C.M., Lea, P.J.P., & Davis, S.A. (2005). Relationships among self-care agency, self-efficacy, self-care, and glycemic con- trol. Research and Theory for Nursing Practice, 19, 217-230. doi: 10.1891/ rtnp.2005.19.3.217

Tang, P.C., Overhage, J.M., Chan, A.S., Brown, N.L., Aghighi, B., Entwistle, M.P., ... Young, C.Y. (2013). Online disease management of diabetes: Engaging and motivating patients online with enhanced resources-diabetes (EMPOWER-D), a randomized controlled trial. Journal of the American Medical Informatics Association, 20, 526-534. doi:10.1136/ amiajnl-2012-001263

Toobert, D.J., Hampson, S.E., & Glasgow, R.E. (2000). The summary of diabetes self-care activities measure. Diabetes Care, 23, 943-950.

van der Bijl, J., Poelgeest-Eeltink, A.V., & Shortridge-Baggett, L. (1999). The psy- chometric properties of the diabetes management self-efficacy scale for patients with type 2 diabetes mellitus. Journal of Advanced Nursing, 30, 352- 359.

Support for Diabetes Using Technology: A Pilot Study to Improve Self-Management

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