A Mobile App to Improve Self-Management of Individuals With Type 2 Diabetes: Qualitative Realist Evaluation

Background The increasing use of Web-based solutions for health prevention and promotion presents opportunities to improve self-management and adherence to guideline-based therapy for individuals with type 2 diabetes (T2DM). Despite promising preliminary evidence, many users stop using Web-based solutions due to the burden of data entry, hidden costs, loss of interest, and a lack of comprehensive features. Evaluations tend to focus on effectiveness or impact and fail to evaluate the nuanced variables that may interact to contribute to outcome success (or failure). Objective This study aimed to evaluate a Web-based solution for improving self-management in T2DM to identify key combinations of contextual variables and mechanisms of action that explain for whom the solution worked best and in what circumstances. Methods A qualitative realist evaluation was conducted with one-on-one, semistructured telephonic interviews completed at baseline, and again toward the end of the intervention period (3 months). Topics included participants’ experiences of using the Web-based solution, barriers and facilitators of self-management, and barriers and facilitators to effective use. Transcripts were analyzed using thematic analysis strategies, after which the key themes were used to develop statements of the relationships between the key contextual factors, mechanisms of action, and impact on the primary outcome (glycated hemoglobin, HbA1c). Results Twenty-six interviews (14 baseline, 12 follow-up) were completed with 16 participants with T2DM, and the following 3 key groups emerged: the easiest fit, the best fit, and those who failed to activate. Self-efficacy and willingness to engage with the solution facilitated improvement in HbA1c, whereas competing priorities and psychosocial issues created barriers to engagement. Individuals with high baseline self-efficacy who were motivated, took ownership for their actions, and prioritized diabetes management were early and eager adopters of the app and recorded improvements in HbA1c over the intervention period. Individuals with moderate baseline self-efficacy and no competing priorities, who identified gaps in understanding of how their actions influence their health, were slow to adopt use but recorded the greatest improvements in HbA1c. The final group had low baseline self-efficacy and identified a range of psychosocial issues and competing priorities. These participants were uncertain of the benefits of using a Web-based solution to support self-management, ultimately resulting in minimal engagement and no improvement in HbA1c. Conclusions Self-efficacy, competing priorities, previous behavior change, and beliefs about Web-based solutions interact to determine engagement and impact on the clinical outcomes. Considering the balance of these patient characteristics is likely to help health care providers identify individuals who are apt to benefit from a Web-based solution to support self-management of T2DM. Web-based solutions could be modified to incorporate the existing screening measures to identify individuals who are at risk of suboptimal adherence to inform the provision of additional support(s) as needed.

[1]  Mae Keary,et al.  The Science of Evaluation: A Realist Manifesto , 2014, Online Inf. Rev..

[2]  Kazuhiko Ohe,et al.  DialBetics: A Novel Smartphone-based Self-management Support System for Type 2 Diabetes Patients. , 2014, Journal of diabetes science and technology.

[3]  Robert A. Vigersky,et al.  Mobile Phone-Based Video Messages for Diabetes Self-Care Support , 2012, Journal of diabetes science and technology.

[4]  U. Rosenqvist,et al.  Misunderstandings about illness and treatment among patients with type 2 diabetes. , 2005, Journal of advanced nursing.

[5]  I. Lee,et al.  Association between modifiable lifestyle factors and residual lifetime risk of diabetes. , 2013, Nutrition, metabolism, and cardiovascular diseases : NMCD.

[6]  S. Wild,et al.  Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. , 2004, Diabetes care.

[7]  Dennis Ross-Degnan,et al.  Mobile Phone and Smartphone Technologies for Diabetes Care and Self-Management , 2015, Current Diabetes Reports.

[8]  V. Braun,et al.  Using thematic analysis in psychology , 2006 .

[9]  L. Whitehead,et al.  Factors influencing the ability to self-manage diabetes for adults living with type 1 or 2 diabetes. , 2014, International journal of nursing studies.

[10]  Milada Cvancarova Småstuen,et al.  A Mobile Health Intervention for Self-Management and Lifestyle Change for Persons With Type 2 Diabetes, Part 2: One-Year Results From the Norwegian Randomized Controlled Trial RENEWING HEALTH , 2014, JMIR mHealth and uHealth.

[11]  E. L. Werner,et al.  Self-Management Skills in Chronic Disease Management: What Role Does Health Literacy Have? , 2022 .

[12]  Hye-Chung Kum,et al.  Barriers to Remote Health Interventions for Type 2 Diabetes: A Systematic Review and Proposed Classification Scheme , 2017, Journal of medical Internet research.

[13]  C. Quinn,et al.  Cluster-Randomized Trial of a Mobile Phone Personalized Behavioral Intervention for Blood Glucose Control , 2011, Diabetes Care.

[14]  C. Schmid,et al.  Self-management education for adults with type 2 diabetes: a meta-analysis of the effect on glycemic control. , 2002, Diabetes care.

[15]  Jay Shaw,et al.  A randomized wait-list control trial to evaluate the impact of a mobile application to improve self-management of individuals with type 2 diabetes: a study protocol , 2016, BMC Medical Informatics and Decision Making.

[16]  HU FRANKB.,et al.  Globalization of Diabetes , 2011, Diabetes Care.

[17]  Ray Pawson,et al.  The Science of Evaluation: A Realist Manifesto , 2013 .

[18]  Josefien van Olmen,et al.  Is realist evaluation keeping its promise? A review of published empirical studies in the field of health systems research , 2012 .

[19]  E. Eldrup,et al.  Short-form measures of diabetes-related emotional distress: the Problem Areas in Diabetes Scale (PAID)-5 and PAID-1 , 2009, Diabetologia.

[20]  Wilhelm Kirch,et al.  Mobile Applications for Diabetics: A Systematic Review and Expert-Based Usability Evaluation Considering the Special Requirements of Diabetes Patients Age 50 Years or Older , 2014, Journal of medical Internet research.

[21]  A. R. Ilersic,et al.  Research methods in social relations , 1961 .

[22]  S. Janson,et al.  Barriers to diabetes management: patient and provider factors. , 2011, Diabetes research and clinical practice.

[23]  Janet E Hux,et al.  Trends in diabetes prevalence, incidence, and mortality in Ontario, Canada 1995–2005: a population-based study , 2007, The Lancet.

[24]  J. Hewitt,et al.  Do Mobile Phone Applications Improve Glycemic Control (HbA1c) in the Self-management of Diabetes? A Systematic Review, Meta-analysis, and GRADE of 14 Randomized Trials , 2016, Diabetes Care.

[25]  M. Gallant The Influence of Social Support on Chronic Illness Self-Management: A Review and Directions for Research , 2003, Health education & behavior : the official publication of the Society for Public Health Education.

[26]  J. Treasure,et al.  Themes elicited during motivational interviewing to improve glycaemic control in adults with Type 1 diabetes mellitus , 2012, Diabetic medicine : a journal of the British Diabetic Association.

[27]  M. Peyrot,et al.  Relationships of diabetes-specific emotional distress, depression, anxiety, and overall well-being with HbA1c in adult persons with type 1 diabetes. , 2014, Journal of psychosomatic research.

[28]  D. Schunk,et al.  Self-Efficacy and Academic Motivation , 1991 .

[29]  W. Groot,et al.  The use of e-health and m-health tools in health promotion and primary prevention among older adults: a systematic literature review , 2016, BMC Health Services Research.

[30]  P. O S I T I O N S T A T E M E N T,et al.  Diagnosis and Classification of Diabetes Mellitus , 2011, Diabetes Care.

[31]  Frank B. Hu,et al.  Globalization of Diabetes , 2011, Diabetes Care.

[32]  Ralf Schwarzer,et al.  Mechanisms of health behavior change in persons with chronic illness or disability: the Health Action Process Approach (HAPA). , 2011, Rehabilitation psychology.

[33]  Steven Blair,et al.  Low Cardiorespiratory Fitness and Physical Inactivity as Predictors of Mortality in Men with Type 2 Diabetes , 2000, Annals of Internal Medicine.

[34]  P. Krebs,et al.  Health App Use Among US Mobile Phone Owners: A National Survey , 2015, JMIR mHealth and uHealth.

[35]  H. King,et al.  Global Burden of Diabetes, 1995–2025: Prevalence, numerical estimates, and projections , 1998, Diabetes Care.

[36]  B. Stetson,et al.  Assessing the Value of the Diabetes Educator , 2011, The Diabetes educator.

[37]  C. Quinn,et al.  WellDoc mobile diabetes management randomized controlled trial: change in clinical and behavioral outcomes and patient and physician satisfaction. , 2008, Diabetes technology & therapeutics.

[38]  Catherine Pope,et al.  Assessing the implementability of telehealth interventions for self-management support: a realist review , 2015, Implementation Science.

[39]  M. Gafencu,et al.  Association between coping mechanisms and adherence to diabetes-related self-care activities: a cross-sectional study , 2017, Patient preference and adherence.

[40]  J. Piette,et al.  I Help You, and You Help Me , 2005, The Diabetes educator.

[41]  Bjørg Karlsen,et al.  Dropout From an eHealth Intervention for Adults With Type 2 Diabetes: A Qualitative Study , 2017, Journal of medical Internet research.

[42]  Robert M. Anderson,et al.  Social Support, Quality of Life, and Self-Care Behaviors Among African Americans With Type 2 Diabetes , 2008, The Diabetes educator.

[43]  G. Reiber,et al.  Factors Influencing Disease Self-Management Among Veterans with Diabetes and Poor Glycemic Control , 2007, Journal of General Internal Medicine.

[44]  J. Protheroe,et al.  Social networks, social capital and chronic illness self-management: a realist review , 2011, Chronic illness.

[45]  Lucy Yardley,et al.  Opportunities and Challenges for Smartphone Applications in Supporting Health Behavior Change: Qualitative Study , 2013, Journal of medical Internet research.

[46]  A. Kennedy,et al.  The Contribution of Social Networks to the Health and Self-Management of Patients with Long-Term Conditions: A Longitudinal Study , 2014, PloS one.

[47]  O. Pedersen,et al.  Effect of a multifactorial intervention on mortality in type 2 diabetes. , 2008, The New England journal of medicine.

[48]  S. Hampson,et al.  Implementing a psychological intervention to improve lifestyle self-management in patients with type 2 diabetes. , 2001, Patient education and counseling.

[49]  Marius Veseth,et al.  Negotiating the coresearcher mandate – service users’ experiences of doing collaborative research on mental health , 2012, Disability and rehabilitation.

[50]  Peter T Katzmarzyk,et al.  Prevalence of class I, II and III obesity in Canada , 2006, Canadian Medical Association Journal.

[51]  P. Zimmet The burden of type 2 diabetes: are we doing enough? , 2003, Diabetes & Metabolism.

[52]  Silvio E. Inzucchi,et al.  Personalized Management of Hyperglycemia in Type 2 Diabetes , 2013, Diabetes Care.

[53]  Matthew J. Crowley,et al.  Patient perceptions of a comprehensive telemedicine intervention to address persistent poorly controlled diabetes , 2017, Patient preference and adherence.

[54]  L. J. Gray,et al.  Real‐world factors affecting adherence to insulin therapy in patients with Type 1 or Type 2 diabetes mellitus: a systematic review , 2013, Diabetic medicine : a journal of the British Diabetic Association.

[55]  M. Cvancarova Småstuen,et al.  Tailored Communication Within Mobile Apps for Diabetes Self-Management: A Systematic Review , 2017, Journal of medical Internet research.

[56]  Syed Ali Hussain,et al.  A qualitative study of user perceptions of mobile health apps , 2016, BMC Public Health.