Published on in Vol 4, No 3 (2015): Jul-Sep

The OnTrack Diabetes Web-Based Program for Type 2 Diabetes and Dysphoria Self-Management:  A Randomized Controlled Trial Protocol

The OnTrack Diabetes Web-Based Program for Type 2 Diabetes and Dysphoria Self-Management: A Randomized Controlled Trial Protocol

The OnTrack Diabetes Web-Based Program for Type 2 Diabetes and Dysphoria Self-Management: A Randomized Controlled Trial Protocol


1The Wesley Health and Medical Research Centre, Rural and remote health centre, Brisbane, Australia

2Queensland University of Technology, Institute of Health and Biomedical Innovation, Brisbane, Australia

3Mater Mothers Hospital, Mater Medical Research Institute, Level 3 Aubigny Place, Raymond Terrace, South Brisbane, 4101, Brisbane, Australia

4Griffith Health Institute, Griffith University, Brisbane, Australia

5University of Queensland Centre for Online Health, Ground Floor, Main Building, Princess Alexandra Hospital, Woollongabba, 4102, Brisbane, Australia

6Griffith University School of Medicine & Griffith Health Institute, Griffith University Drive, Meadowbrook, 4131, Brisbane, Australia

7The Wesley Health and Medical Research Centre, Level 8 East Wing, The Wesley Hospital, Auchenflower, 4066, Brisbane, Australia

*these authors contributed equally

Corresponding Author:

Mandy Cassimatis, BA, PGDipPsych, MPsych(Clinical), PhD (Psych)

The Wesley Health and Medical Research Centre

Rural and remote health centre

Level 8 East Wing, The Wesley Hospital

451 Coronation Drive, Auchenflower

Brisbane, 4066


Phone: 61 073721 ext 1500

Fax:61 0737211555


Background: The prevalence of type 2 diabetes is rising with the majority of patients practicing inadequate disease self-management. Depression, anxiety, and diabetes-specific distress present motivational challenges to adequate self-care. Health systems globally struggle to deliver routine services that are accessible to the entire population, in particular in rural areas. Web-based diabetes self-management interventions can provide frequent, accessible support regardless of time and location

Objective: This paper describes the protocol of an Australian national randomized controlled trial (RCT) of the OnTrack Diabetes program, an automated, interactive, self-guided Web program aimed to improve glycemic control, diabetes self-care, and dysphoria symptoms in type 2 diabetes patients.

Methods: A small pilot trial is conducted that primarily tests program functionality, efficacy, and user acceptability and satisfaction. This is followed by the main RCT, which compares 3 treatments: (1) delayed program access: usual diabetes care for 3 months postbaseline followed by access to the full OnTrack Diabetes program; (2) immediate program: full access to the self-guided program from baseline onward; and (3) immediate program plus therapist support via Functional Imagery Training (FIT). Measures are administered at baseline and at 3, 6, and 12 months postbaseline. Primary outcomes are diabetes self-care behaviors (physical activity participation, diet, medication adherence, and blood glucose monitoring), glycated hemoglobin A1c (HbA1c) level, and diabetes-specific distress. Secondary outcomes are depression, anxiety, self-efficacy and adherence, and quality of life. Exposure data in terms of program uptake, use, time on each page, and program completion, as well as implementation feasibility will be conducted.

Results: This trial is currently underway with funding support from the Wesley Research Institute in Brisbane, Australia.

Conclusions: This is the first known trial of an automated, self-guided, Web-based support program that uses a holistic approach in targeting both type 2 diabetes self-management and dysphoria. Findings will inform the feasibility of implementing such a program on an ongoing basis, including in rural and regional locations.

Trial Registration: Australian and New Zealand Clinical Trials Registration number: ACTRN12612000620820; (Archived by WebCite at

JMIR Res Protoc 2015;4(3):e97



Diabetes mellitus affects an estimated 346 million people globally and type 2 diabetes accounts for 85% to 90% of all cases [1]. In Australia, type 2 diabetes affects 4% of the population [2]. Diabetes constitutes the eighth-highest burden of disease in Australia and type 2 diabetes accounts for 92% of this burden [3]. With the rapidly rising prevalence of diabetes, the effects of inadequate diabetes self-management continue to increase and resulting diabetes complications and premature mortality become more urgent to address. Diabetes is the leading cause of blindness, end-stage renal disease, and lower limb amputation in the world [1]. Moreover, the effects of diabetes on quality of life, mental health, work productivity, and other intangible losses are substantial and add further to the diabetes-related burden to society.

Depression [4,5] and anxiety [6] are significantly more prevalent in people with diabetes than in the general population. Comorbid mental health conditions are barriers to effective diabetes self-care [7] and further increase diabetes-related expenditures [8]. Dysphoria complicates the achievement of adequate glycemic control through multiple pathways. Comorbid depression and/or anxiety with diabetes predisposes individuals to diabetes-specific distress [9,10] and affects glycemic control [11] both directly (via physiological mechanisms [8-10]) and indirectly by reducing motivation for adequate self-management [12-14]. Even subclinical manifestations, such as dysphoria, are associated with clinically deleterious outcomes, including reduced self-care [7], poorer glycemic control [15,16], increased incidence and progression of diabetes complications [17,18], and greater disability [19]. Stress contributes to other common physical comorbidities in diabetes patients, including metabolic syndrome and cardiovascular disease [20]. Diabetes-specific distress (DSD)—the emotional and psychological burden posed by diabetes [21]—accounts for a high proportion of variance in depression [22] and further impedes self-management [23]. Combined effects of inadequate glycemic control and dysphoric mood in diabetes [21,22] thus call for urgent intervention.

Prior research indicates the need for behavioral diabetes self-management interventions to incorporate psychological and emotional support components for optimum efficacy [23]. Improvements in diabetes self-care are strongly associated with improved glycemic control [24,25], so behavioral interventions to support diabetes self-care might also improve clinical outcomes [26]. However, improvements in glycemic control do not generally result in significant improvements in mood [23], nor do psychological treatments for depression and anxiety in people with diabetes reliably produce improvements in glycemic control [27]. Despite the limited impact of single-focused interventions in diabetes [28], self-management interventions typically fail to address both issues. Furthermore, trials on self-management interventions often only follow-up participants for relatively short periods (eg, ≤6 months [29]) so that long-term effects remain undetermined.

There are many barriers to adequate treatment of type 2 diabetes within health systems, including a shortage of health professionals, inadequate availability of services, limited access in rural and remote regions, practitioner/patient communication problems, time pressures in medical consultations, and limitations in the skills and confidence of health professionals in the provision of psychological interventions [30]. Patients often struggle to manage the complexity of type 2 diabetes treatment regimens [31], to recognize dysphoria symptoms [32,33], acknowledge their need for support, and find the motivation to overcome barriers to a healthy lifestyle [34]. Shortcomings in health care services particularly affect patients at risk of psychological comorbidities and the number of these patients will escalate sharply as the incidence of diabetes increases [4].

Recent evidence demonstrates that Web-based diabetes self-management interventions have potential efficacy, feasibility, user acceptability, and uptake [29]. Web programs have demonstrated significant improvements in clinical, behavioral [35-37], psychological, emotional, and psychosocial outcomes [38], as well as a strong uptake and acceptability by both mature [39] and novice users [40].

Recently trialed Web-based diabetes self-management programs based on social cognitive theory (SCT) [41] have demonstrated efficacy [35,42,43]. Central tenets of SCT include self-efficacy, or one’s belief in their capabilities to execute desired courses of action, and outcome expectancies, or personal predictions of likely outcomes resulting from certain courses of action [41]. SCT encompasses the key recommendations in national practice guidelines for diabetes management [44]. These include encouraging patient empowerment (promoting self-efficacy), ongoing monitoring of target outcomes (self-evaluation), and providing diabetes education (instructions). Therefore, SCT provides a theoretical avenue by which to address both behavioral self-management and emotional issues [45]. Self-efficacy has significant positive associations with behavioral outcomes including physical activity participation [46,47], nutrition intake [48,49], weight loss [50], and diabetes self-care [51], as well as with emotional outcomes, including depressive symptoms [52], in people with diabetes.

Despite the growth in supportive evidence on Web-based diabetes programs for self-management, there are some inconsistencies in their results and further data are needed on their potential to improve glycemic control [53]. Lorig et al [54] trialed a diabetes self-management intervention that included modules to assist users in coping with emotional challenges both related and unrelated to diabetes. Although improvements were found in self-efficacy, patient activation, and glycated hemoglobin (HbA1c) at 6 months postenrollment, there were no significant improvements in health behaviors, including exercise participation. Emotional outcomes and effects on long-term glycemia were not determined. On the other hand, Glasgow and colleagues [36] reported that their Internet-based diabetes education program (D-Net) did not significantly improve mood or glycemic control, but produced significant improvements in behavioral and psychosocial outcomes. Although current trials show that Web-based diabetes programs have substantial promise, there remains a need to enrich available data on their effects on both mood and glycemia. Given the close mutual influences between dysphoria and diabetes self-management, including the challenging context of psychosocial [55] and emotional stressors [56] in which self-management is attempted, a Web intervention that utilizes a holistic approach to diabetes self-management is required. Such a program would allow users to address both the behavioral and emotional challenges of diabetes in context.

Developing and maintaining commitment to any significant behavior change is challenging. Over the last 30 years, motivational interviewing [57] has demonstrated an ability to enhance motivation, particularly in addictive disorders (where it began), but also in some other behavioral domains [58]. However, until now, its effects on behavior change and glycemic control in diabetes have been inconsistent with only a minority of trials having significant differential effects [59]. Recently, a new approach to eliciting motivation, which uses a motivational interviewing style but trains participants to use motivational imagery in their everyday life, has been advanced [60]. This approach, Functional Imagery Training (FIT), applies 10 years of theoretical and empirical work on the nature and modulation of desires [61]. Personalized multisensory imagery about the benefits of health maintenance behaviors, past successes, and effective strategies is elicited. This is described as television advertisements in which the participant is the actor and is reliving an event or imagining a future event. Participants are asked to practice this imagery when they undertake a routine everyday task and to set electronic reminders for times when they need to undertake a health routine or avoid a dysfunctional behavior. Imagery is cued using photos taken by the participant and is refreshed using new events that illustrate actual gains and effective strategies. Commitment and social support for the goal is elicited by sharing a brief recorded statement about the goal, why it was adopted, how it will be done, and why it will be successful; this recording is replayed if motivation is fading. Brief phone calls by the therapist remind the participant to practice their imagery and help them solve problems by using it.

The study described subsequently comprises a randomized controlled trial (RCT) involving the OnTrack Diabetes program, an automated Web-based intervention aimed to achieve and maintain improvements in type 2 diabetes self-management and dysphoria symptoms. It compares delayed and immediate access to the program, and immediate access supplemented by FIT-based coaching.

The OnTrack Diabetes Program

The development of OnTrack Diabetes is described in a companion paper [62](see Figure 1 for screenshot). The program targets physical activity participation, nutrition, adherence to health routines, and mood disturbance (depression, anxiety, and diabetes-related everyday stressors). Specifically, the program includes informational resources: goal setting, planning, and creating routines for self-care behaviors; feeling confident and problem solving via interactive tools; goal attainment scaling via self-monitoring tools, quizzes, and automated feedback graphs; relaxation and mindfulness audios; and an electronic diary. Access to health care providers is also promoted by encouraging users to establish a diabetes care team. Further, the program addresses the independent effects of depression, anxiety, and diabetes-specific distress by enabling users to provide personalized responses in the emotional support tools regarding both diabetes-specific and nonspecific emotional challenges. Although program sections appear in an ordered structure, users can choose to undertake segments in any order—a feature intended to foster user empowerment [63]. Both provided and entered text is minimized with extensive use of icons and pictures and simple sentences and vocabulary so that reading requirements do not exceed Year 7 educational levels.

Figure 1. Screenshot of the OnTrack Diabetes home page.
View this figure

Design and Setting

A pilot trial of the program is initially implemented to test for program functionality and to provide an indication of program efficacy, user acceptability, and satisfaction. Following the pilot, a RCT with the participant as the unit of randomization is implemented. The trial is conducted Australia-wide and access is ongoing. The research team is based at the Mitsubishi Centre for Rural and Remote Health at the Wesley Research Institute in Brisbane.

The RCT evaluates the efficacy of the OnTrack Diabetes program in improving the primary outcomes glycemic control (HbA1c level) and diabetes-specific distress symptoms, and the secondary outcomes of depression, anxiety, physical activity participation, diet, blood glucose self-monitoring, and medication taking. User acceptability, ease of use, utility, program satisfaction, and implementation feasibility are also assessed.

It is hypothesized that at 3 months postbaseline, the immediate access plus FIT condition will show the greatest improvements in primary and secondary outcomes compared with the immediate access and the delayed access conditions. Results of the immediate access and the delayed access conditions are expected to be similar at 6 months when both conditions will have received the full intervention. A CONSORT flow diagram for the trial is shown in Figure 2.

Figure 2. CONSORT flow diagram of the OnTrack Diabetes main randomized controlled trial.
View this figure

Recruitment and Sample

Recruitment strategies for the trial are primarily community-based: newspaper advertisements, health organization newsletters, radio broadcasts, notice board postings, bulletins, emails, and online advertisements. Targeted methods include the distribution of study flyers and posters to medical centers, letters to health institutions, pharmacies and health professionals, and featuring the OnTrack Diabetes website URL on statewide Diabetes Australia research Web pages. Attendance at diabetes-related expos and events allows in-person recruitment and further promotion of the project to health professionals.

The trial aims to enroll at least 210 participants. Selection criteria include (1) type 2 diabetes diagnosis (by a medical doctor and according to World Health Organization criteria) of at least 3 months duration, (2) age 18 years or older, (3) living in Australia without plans to leave within 12 months, (4) regular computer and Internet access, (5) contactable by phone, (6) clear command of written English (at least Year 5 education), and (7) stable diabetes pharmacotherapy (medication dose stable ≥4 weeks; medication type stable ≥3 months). Study exclusion criteria include (1) current diagnosis of mental disorder other than depression or anxiety (participant is asked if a condition has been diagnosed and if so they are informed that they will receive access to the program but not be included in the trial), (2) current suicidal risk (assessed via suicide risk assessment), (3) significant cognitive disorder (eg, from head trauma or dementia), (4) currently on steroid medication or likely to commence it in the next 12 months, and (5) pregnant or likely to become pregnant in the next 12 months.

All participants are asked to undertake a medical assessment by their general practitioner prior to study enrollment. Individuals with physical limitations or concurrent physical disorders are advised of the need to exercise caution in setting physical activity goals according with their doctor’s advice.


Primary outcomes include diabetes self-care behaviors, HbA1c level, and diabetes-specific distress. Secondary outcomes include depression, anxiety, (medication taking, nutrition intake, physical activity, and blood glucose self-monitoring), quality of life, and user evaluations of the program. Measures are administered at baseline and the 3-, 6-, and 12-month follow-up time points. Table 1 in Multimedia Appendix 1 lists the measures.


Participants register interest on the study website and select a time to undertake an eligibility screening appointment by phone. Eligible individuals undertake baseline measures by email and phone interview at their selected appointment time. Individuals who satisfy all criteria except inclusion criterion time since diagnosis or stable medication are asked if they wish to be recontacted for future screening; if so, they are categorized as “pending.” Individuals who are ineligible are allowed to use the program without being enrolled in the trial.

Following baseline measures, all participants who are randomly allocated to the immediate access or the immediate access plus FIT interventions receive a secure username and password with which to log on to the program. Those enrolled in the delayed access condition are informed that they will receive program access details in 3 months. Computer-generated randomization occurs automatically. One week before the due date for follow-up study measures, participants receive an email notification with a link to the online survey and a preset time for the timeline follow-back procedure phone interview. The email requests that participants email the researcher if the phone interview time does not suit them.

Delayed Access

In this condition, participants undertake their usual diabetes care with no Web-based program access. Following 3-month follow-up study measures, they receive access to the full OnTrack Diabetes program. Their access to the program is actioned by a member of the research team after which they receive an email that contains an exclusive username and password to access the program.

Immediate Access

Participants receive access to the full OnTrack Diabetes program from baseline as described in the companion paper about the development of OnTrack Diabetes [62]. This includes access to extensive information resources, a nutrition module (Eating Well and Feeling Healthy), a module focused on adherence to health regimens (Health Routines), an emotional well-being module (Thinking Well and Feeling Fine), and a maintenance module (Keeping On Track). The first section of each module includes a series of interactive tools that incorporate guided imagery, planning goal implementation, goal setting, and confidence building. The planning tools guide participants in proceeding toward their own personalized goals in incremental steps. The second section of each module is entitled “More on...” (eg, More on Health Routines) and involves setting a weekly schedule to increase participation in desired health behaviors and pleasurable activities, and tools for problem-solving challenges. A printable summary is provided on completion of each interactive tool. These summaries can be accessed on future occasions and participants can also complete tools or modules repeatedly if they wish. Self-monitoring tools allow daily monitoring of highest and lowest blood glucose levels, best and worst mood, and the degree that physical activity and nutrition goals were met. Automated feedback graphs on progress are provided for the past week, month, or 3 months. Mindfulness audios are playable on the computer or can be downloaded to an MP3 player.

Immediate Access Plus Functional Imagery Training

In addition to content received in the immediate access condition, participants in this condition receive regular therapist support phone calls wherein FIT techniques are utilized. The therapist is a provisionally registered psychologist who contacts participants twice in the first week of study enrollment and once in the second and third week of enrollment followed by biweekly calls. Calls last for an average of 30 to 40 minutes until the participant has been enrolled for 1 month, after which they last approximately 20 minutes. Participants are encouraged to practice FIT at home every day. The approach assists them to develop and maintain personalized changes to their diabetes self-care behaviors, alcohol use, smoking, or lifestyle. The therapist reinforces the imagery-based activities already included in the OnTrack Diabetes program and extends these by encouraging additional imagery rehearsal to further enhance motivation.

Statistical Analyses

Preliminary analyses assess for baseline differences and subsequent analyses control for any observed differences. The primary analyses will comprise multiple regressions, predicting posttreatment and follow-up results from baseline measures and treatment contrasts with multiple imputation being used to predict missing data. Mixed-model ANOVAs with repeated measures will also be applied to confirm whether effects are still obtained without imputations. Both methods allow an intention-to-treat approach to the data. Repeated measures ANOVAs will be used to evaluate differences in change scores between the study time points among the 3 study conditions.

User satisfaction, perceived ease of use, and usefulness are examined with ANOVAs and program reach, acceptability, implementation feasibility, and outreach are assessed using the Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) framework [64]. This will be operationalized using the OnTrack Diabetes Evaluation Questionnaire, which asks about users’ perceptions of the program’s acceptability, issues with feasibility, and outreach (ie, ability to access the program and barriers to access including poor broadband network availability). The inclusion of residents of rural and regional areas enriches this evaluation as will quantitative data about participants’ exposure to the program.

Sample Size and Retention

The sample of 210 enables detection of a small effect size of f2=.046 in the multiple regressions. Although the study uses all allocated participants in the outcome analyses, efforts are made to maximize retention by maximizing rapport at the baseline assessment and collecting multiple means to contact participants, including email, landline, and mobile phone contact details, and by assertive follow-up. With these strategies, the study is aimed to have at least 70% retention at 12 months.


Ethics approval to conduct this project was granted by the Uniting Care Health Human Research Ethics Committee (#Cassimatis9111) and the Queensland University of Technology Human Research Ethics Committee (#1100000783).

This trial is currently underway with funding support from the Wesley Research Institute in Brisbane, Australia.

Results from this trial will provide information on the efficacy, practicality, and user perspectives on the effects of such a program and the success of its dissemination within the Australian context. A 12-month follow-up period will provide data on the maintenance of effects from the programs as well as patterns of usage over time and the relationship of these variables to study outcomes.

Previous trials of diabetes self-management Web-based programs have indicated that a common limitation of such programs is reduced user engagement over time [36,54,64]. It is expected that ongoing access to interactive tools and self-monitoring that users can apply to issues with self-management and dysphoria as they arise will help to maximize engagement and retention. Fortnightly email reminders may also assist users to keep on track of their program usage and prompt continued user engagement with the program [65]. Follow-up assessments during the trial will ask about usage of other treatments and website resources, but the validity of those reports cannot be guaranteed.

Results will provide information about the effectiveness of using a self-guided approach to a Web-based type 2 diabetes self-management intervention. Limitations to generalizability that commonly affect studies conducted within specific clinical or experimental settings are avoided [64] by providing nationwide access and enabling the intervention to be conducted at any location from which access to the Web via a computer is possible. As well as assessing whether the OnTrack Diabetes program will improve type 2 diabetes self-management and dysphoria, this trial is intended to serve as a source of information about the successes and shortcomings entailed in implementing such a program. Results will provide information on which future trials of Web-based cognitive behavioral therapy interventions can build in terms of processes that enhance and those that impede the practicality and rigor of research in this domain.


The authors sincerely thank Mitsubishi Development Pty Ltd for their generous support to the Mitsubishi Centre for Rural and Remote Health at the Wesley Research Institute in Brisbane, Australia.

Conflicts of Interest

MC and DK wrote the Web-based program evaluated in this study, but they do not obtain commercial gain from its use. All other authors have no competing interests to declare.

Multimedia Appendix 1

Measures used in trial.

PDF File (Adobe PDF File), 31KB

  1. World Health Organization: Media Centre. 2015 Jan. Diabetes Fact Sheet No 312   URL: [accessed 2013-06-01] [WebCite Cache]
  2. Australian Institute of Health and Welfare. 2014. Diabetes   URL: [accessed 2014-04-10] [WebCite Cache]
  3. Australian Institute of Health and Welfare. Australia's Health 2012. Canberra: AIHW; 2013 May.   URL: [accessed 2013-06-01] [WebCite Cache]
  4. Anderson RJ, Freedland KE, Clouse RE, Lustman PJ. The prevalence of comorbid depression in adults with diabetes: a meta-analysis. Diabetes Care 2001 Jun;24(6):1069-1078. [Medline]
  5. Ali S, Stone MA, Peters JL, Davies MJ, Khunti K. The prevalence of co-morbid depression in adults with Type 2 diabetes: a systematic review and meta-analysis. Diabet Med 2006 Nov;23(11):1165-1173. [CrossRef] [Medline]
  6. Grigsby A, Anderson RJ, Freedland KE, Clouse RE, Lustman PJ. Prevalence of anxiety in adults with diabetes: A systematic review. Journal of Psychosomatic Research 2002;53(6):1053-1060 [FREE Full text] [CrossRef] [Medline]
  7. Ali S, Stone MA, Peters JL, Davies MJ, Khunti K. The prevalence of co-morbid depression in adults with Type 2 diabetes: a systematic review and meta-analysis. Diabet Med 2006 Nov;23(11):1165-1173. [CrossRef] [Medline]
  8. Egede LE, Zheng D, Simpson K. Comorbid depression is associated with increased health care use and expenditures in individuals with diabetes. Diabetes Care 2002;25(3):1069-1078. [CrossRef]
  9. Kokoszka A, Pouwer F, Jodko A, Radzio R, Mućko P, Bieńkowska J, et al. Serious diabetes-specific emotional problems in patients with type 2 diabetes who have different levels of comorbid depression: a Polish study from the European Depression in Diabetes (EDID) Research Consortium. Eur Psychiatry 2009 Oct;24(7):425-430. [CrossRef] [Medline]
  10. Fisher L, Mullan JT, Skaff MM, Glasgow RE, Arean P, Hessler D. Predicting diabetes distress in patients with Type 2 diabetes: a longitudinal study. Diabetic Medicine: A Journal Of The British Diabetic Association 2009;26(6):1464-5491. [CrossRef] [Medline]
  11. Fisher L, Mullan JT, Arean P, Glasgow RE, Hessler D, Masharani U. Diabetes distress but not clinical depression or depressive symptoms is associated with glycemic control in both cross-sectional and longitudinal analyses. Diabetes Care 2010 Jan;33(1):23-28 [FREE Full text] [CrossRef]
  12. Gonzalez JS, Peyrot M, McCarl LA, Collins EM, Serpa L, Mimiaga MJ, et al. Depression and diabetes treatment nonadherence: a meta-analysis. Diabetes Care 2008 Dec;31(12):2398-2403 [FREE Full text] [CrossRef] [Medline]
  13. Katon WJ, Russo JE, Heckbert SR, Lin EH, Ciechanowski P, Ludman E, et al. The relationship between changes in depression symptoms and changes in health risk behaviors in patients with diabetes. Int J Geriatr Psychiatry 2010 May;25(5):466-475 [FREE Full text] [CrossRef] [Medline]
  14. Scollan-Koliopoulos M, Walker EA, Bleich D. Perceived risk of amputation, emotions, and foot self-care among adults with type 2 diabetes. Diabetes Educ 2010;36(3):473-482. [CrossRef] [Medline]
  15. Anderson RJ, Grigsby AB, Freedland KE, de Groot M, McGill JB, Clouse RE, et al. Anxiety and poor glycemic control: a meta-analytic review of the literature. Int J Psychiatry Med 2002;32(3):235-247. [Medline]
  16. Pouwer F, Geelhoed-Duijvestijn PH, Tack CJ, Bazelmans E, Beekman AJ, Heine RJ, et al. Prevalence of comorbid depression is high in out-patients with Type 1 or Type 2 diabetes mellitus. Results from three out-patient clinics in the Netherlands. Diabetic Medicine 2010;27(2):1464-1224. [Medline]
  17. de Groot M, Anderson R, Freedland KE, Clouse RE, Lustman PJ. Association of depression and diabetes complications: a meta-analysis. Psychosom Med 2001;63(4):619-630. [Medline]
  18. Williams LH, Rutter CM, Katon WJ, Reiber GE, Ciechanowski P, Heckbert SR, et al. Depression and incident diabetic foot ulcers: a prospective cohort study. The American Journal of Medicine 2010;123(8):748-754. [CrossRef]
  19. Von Korff M, Katon W, Lin EH, Simon G, Ludman E, Oliver M, et al. Potentially modifiable factors associated with disability among people with diabetes. Psychosom Med 2005;67(2):233-240. [CrossRef] [Medline]
  20. Kyrou I, Tsigos C. Stress hormones: physiological stress and regulation of metabolism. Current Opinion in Pharmacology 2009;9(6):349-350.
  21. Fisher L, Mullan T, Skaff MM, Glasgow RE, Arean P, Hessler D. Predicting diabetes distress in patients with type 2 diabetes: A longitudinal study. Diabetic Medicine 2009;26(6):622-627.
  22. Gonzalez JS, Fisher L, Polonsky WH. Depression in diabetes: have we been missing something important? Diabetes Care 2011 Jan;34(1):236-239 [FREE Full text] [CrossRef] [Medline]
  23. Fisher L, Glasgow RE, Strycker LA. The relationship between diabetes distress and clinical depression with glycemic control among patients with type 2 diabetes. Diabetes Care 2010 May;33(5):1034-1036 [FREE Full text] [CrossRef] [Medline]
  24. Zhang X, Norris SL, Gregg EW, Cheng YJ, Beckles G, Kahn HS. Depressive symptoms and mortality among persons with and without diabetes. Am J Epidemiol 2005 Apr 1;161(7):652-660 [FREE Full text] [CrossRef] [Medline]
  25. Egede L, Nietert PJ, Zheng D. Depression and all-cause and coronary heart disease mortality among adults with and without diabetes. Diabetes Care 2005 May 26;28(6):1339-1345. [CrossRef] [Medline]
  26. Fisher EB, Thorpe CT, DeVellis BM, DeVellis RF. Healthy coping, negative emotions, and diabetes management: A systematic review and appraisal. Diabetes Educ 2007;33(6):1080-1103. [CrossRef] [Medline]
  27. Asche C, LaFleur J, Conner C. A review of diabetes treatment adherence and the association with clinical and economic outcomes. Clinical Therapeutics 2011;33(1):425-430. [CrossRef] [Medline]
  28. Holman RR, Paul SK, Bethel MA, Matthews DR, Neil HA. 10-year follow-up of intensive glucose control in type 2 diabetes. N Engl J Med 2008 Oct 9;359(15):1577-1589. [CrossRef] [Medline]
  29. Heinrich E, Schaper NC, de Vries NK. Self-management interventions for type 2 diabetes: a systematic review. European Diabetes Nursing 2010 Aug;7(2):71-76. [CrossRef]
  30. Ismail K, Winkley K, Rabe-Hesketh S. Systematic review and meta-analysis of randomised controlled trials of psychological interventions to improve glycaemic control in patients with type 2 diabetes. Lancet 2004 May 15;363(9421):1589-1597. [CrossRef] [Medline]
  31. Wang M, Tsai P, Chou K, Chen C. A systematic review of the efficacy of non-pharmacological treatments for depression on glycaemic control in type 2 diabetics. J Clin Nurs 2008 Oct;17(19):2524-2530. [CrossRef] [Medline]
  32. Ramadas A, Quek KF, Chan CK, Oldenburg B. Web-based interventions for the management of type 2 diabetes mellitus: a systematic review of recent evidence. Int J Med Inform 2011 Jun;80(6):389-405. [CrossRef] [Medline]
  33. Peyrot M, Rubin RR, Lauritzen T, Snoek FJ, Matthews DR, Skovlund SE. Psychosocial problems and barriers to improved diabetes management: results of the Cross-National Diabetes Attitudes, Wishes and Needs (DAWN) Study. Diabet Med 2005 Oct;22(10):1379-1385. [CrossRef] [Medline]
  34. Odegard PS, Capoccia K. Medication taking and diabetes: a systematic review of the literature. Diabetes Educ 2007;33(6):1014-29; discussion 1030. [CrossRef] [Medline]
  35. Pouwer F. Should we screen for emotional distress in type 2 diabetes mellitus? Nat Rev Endocrinol 2009 Dec;5(12):665-671. [CrossRef] [Medline]
  36. Hayes E, McCahon C, Panahi MR, Hamre T, Pohlman K. Alliance not compliance: coaching strategies to improve type 2 diabetes outcomes. J Am Acad Nurse Pract 2008 Mar;20(3):155-162. [CrossRef] [Medline]
  37. Griffiths F, Lindenmeyer A, Powell J, Lowe P, Thorogood M. Why are health care interventions delivered over the internet? A systematic review of the published literature. J Med Internet Res 2006;8(2):e10 [FREE Full text] [CrossRef] [Medline]
  38. Liebreich T, Plotnikoff RC, Courneya KS, Boulé N. Diabetes NetPLAY: A physical activity website and linked email counselling randomized intervention for individuals with type 2 diabetes. Int J Behav Nutr Phys Act 2009;6:18 [FREE Full text] [CrossRef] [Medline]
  39. Glasgow RE, Boles SM, McKay HG, Feil EG, Barrera M. The D-Net diabetes self-management program: long-term implementation, outcomes, and generalization results. Prev Med 2003 Apr;36(4):410-419. [Medline]
  40. Glasgow RE, Nutting PA, Toobert DJ, King DK, Strycker LA, Jex M, et al. Effects of a brief computer-assisted diabetes self-management intervention on dietary, biological and quality-of-life outcomes. Chronic Illn 2006 Mar;2(1):27-38. [Medline]
  41. Bond GE, Burr RL, Wolf FM, Feldt K. The effects of a web-based intervention on psychosocial well-being among adults aged 60 and older with diabetes: a randomized trial. Diabetes Educ 2010;36(3):446-456. [CrossRef] [Medline]
  42. Bond G, Burr R, Wolf FM, Price M, McCurry SM, Teri L. The effects of a web-based intervention on the physical outcomes associated with diabetes among adults age 60 and older: a randomized trial. Diabetes Technology & Therapeutics 2007;9(1):52-59. [CrossRef] [Medline]
  43. McKay HG, King D, Eakin EG, Seeley JR, Glasgow RE. The diabetes network internet-based physical activity intervention: a randomized pilot study. Diabetes Care 2001 Aug;24(8):1328-1334. [Medline]
  44. Bandura A. Social Foundations of Thought and Action: A Social Cognitive Theory. Englewood Cliffs, NJ: Prentice-Hall Inc; 1986.
  45. Lorig K. What do you think of when you think of patient education? Kate Lorig interviewed by Melissa Gilkey and Cezanne Garcia. Health Promot Pract 2010 Mar;11(2):169-172. [CrossRef] [Medline]
  46. Anderson-Bill E, Winett RA, Wojcik JR. Social cognitive determinants of nutrition and physical activity among web-health users enrolling in an online intervention: the influence of social support, self-efficacy, outcome expectations, and self-regulation. JMIR 2011;13(1):e28-e28. [CrossRef]
  47. Australian Government National Health and Medical Research Council. 2010. National Evidence Based Guidelines for the Management of Type 2 Diabetes Mellitus   URL: [accessed 2013-06-01] [WebCite Cache]
  48. Bandura A. Health promotion by social cognitive means. Health Educ Behav 2004 Apr;31(2):143-164. [CrossRef] [Medline]
  49. Plotnikoff RC, Lippke S, Courneya KS, Birkett N, Sigal RJ. Physical activity and social cognitive theory: A test in a population sample of adults with type 1 or type 2 diabetes. Applied Psychology: An International Review 2008;57(4):628-643. [CrossRef]
  50. Plotnikoff RC, Trinh L, Courneya KS, Karunamuni N, Sigal RJ. Predictors of physical activity in adults with type 2 diabetes. Am J Health Behav 2011 May;35(3):359-370 [FREE Full text] [Medline]
  51. Nouwen A, Ford T, Balan AT, Twisk J, Ruggiero L, White D. Longitudinal motivational predictors of dietary self-care and diabetes control in adults with newly diagnosed type 2 diabetes mellitus. Health Psychology 2011;30(6):771-779 [FREE Full text] [CrossRef]
  52. Savoca M, Miller C. Food selection and eating patterns: themes found among people with type 2 diabetes mellitus. Journal of Nutrition Education 2001 Jul;33(4):224-233 [FREE Full text] [CrossRef]
  53. Winett RA, Tate DF, Anderson ES, Wojcik JR, Winett SG. Long-term weight gain prevention: a theoretically based Internet approach. Prev Med 2005;41(2):629-641 [FREE Full text] [CrossRef]
  54. Weinger K, Butler HA, Welch GW, La Greca AM. Measuring diabetes self-care: a psychometric analysis of the Self-Care Inventory-Revised with adults. Diabetes Care 2005 Jun;28(6):1346-1352 [FREE Full text] [Medline]
  55. Markowitz SM, Gonzalez JS, Wilkinson JL, Safren SA. A review of treating depression in diabetes: emerging findings. Psychosomatics 2011;52(1):1-18 [FREE Full text] [CrossRef] [Medline]
  56. Lorig K, Ritter PL, Laurent DD, Plant K, Green M, Jernigan VB, et al. Online diabetes self-management program: a randomized study. Diabetes Care 2010 Jun;33(6):1275-1281 [FREE Full text] [CrossRef] [Medline]
  57. Miller W, Rollnick S, Conforti K. Motivational Interviewing: Preparing People for Change, Second Edition. New York: Guilford Publication Inc; 2002.
  58. Dunn C, Deroo L, Rivara FP. The use of brief interventions adapted from motivational interviewing across behavioral domains: a systematic review. Addiction 2001 Dec;96(12):1725-1742. [CrossRef] [Medline]
  59. Mulimba AC, Byron-Daniel J. Motivational interviewing-based interventions and diabetes mellitus. British Journal of Nursing 2014;23(1):8. [CrossRef]
  60. Kavanagh DJ, Andrade J, May J, Connor JP. Imagery-based skills training for wellbeing—An alternative to motivational interviewing for alcohol misuse. A response to McCambridge and Rollnick (2013). Addiction 2014;109(7):1062-1063. [CrossRef]
  61. Kavanagh DJ, Andrade J, May J. Imaginary relish and exquisite torture: The elaborated intrusion theory of desire. Psychological Review 2005;112:446-467. [CrossRef]
  62. Cassimatis M, Kavanagh DJ, Hills AP, Smith AC, Scuffham PA, Edge S, et al. Development of the OnTrack Diabetes Program. JMIR Res Protoc 2015 May 26;4(2):e24. [CrossRef]
  63. van Bastelaar BK, Cuijpers P, Pouwer F, Riper H, Snoek FJ. Development and reach of a web-based cognitive behavioural therapy programme to reduce symptoms of depression and diabetes-specific distress. Patient Educ Couns 2011 Jul;84(1):49-55. [CrossRef] [Medline]
  64. Glasgow RE, McKay HG, Piette JD, Reynolds KD. The RE-AIM framework for evaluating interventions: what can it tell us about approaches to chronic illness management? Patient Educ Couns 2001 Aug;44(2):119-127. [Medline]
  65. Fisher KL. Assessing psychosocial variables: a tool for diabetes educators. Diabetes Educ 2006;32(1):51-58. [CrossRef] [Medline]

FIT: Functional Imagery Training
RCT: randomized controlled trial
SCT: social cognitive theory

Edited by G Eysenbach; submitted 02.07.13; peer-reviewed by J Speight, H Bridgman; comments to author 25.08.13; revised version received 02.09.14; accepted 06.09.14; published 04.08.15


©Mandy Cassimatis, David John Kavanagh, Andrew Paul Hills, Anthony Carl Smith, Paul A Scuffham, Christian Gericke, Sophie Parham. Originally published in JMIR Research Protocols (, 04.08.2015.

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