Efficacy Study of Interactive Web Application for Problem Solving in Diabetes Management
Study Details
Study Description
Brief Summary
The main hypothesis of this research is that use of an informatics intervention for problem-solving in diabetes management, Mobile Diabetes Detective (MoDD), by individuals with type 2 diabetes will lead to positive improvements on a number of primary and secondary outcomes related to their health and their management of diabetes. The primary outcomes are a reduction in individuals' glycolated hemoglobin (HbA1c), improvement in their problem-solving abilities, and self-care behaviors. Secondary outcomes include a reduction in individuals' fasting blood glucose (BG); improvement in individuals' self-efficacy, and in emotional aspect of living with diabetes. We hypothesize that primary and secondary outcome effects will be sustained at three months and twelve months. Exploratory outcomes include a decrease in individuals' Cardiovascular Risk (Body Mass Index, Blood Pressure, Total, low-density lipoprotein (LDL) and high-density lipoprotein (HDL) Cholesterol levels, and Framingham Cardiovascular Risk Score). We also hypothesize that improvements in clinical outcomes (HbA1c, fasting BG and Cardiovascular Risk) will be mediated by the improvements in problem-solving abilities and self-efficacy.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
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N/A |
Detailed Description
Well-developed problem-solving is essential to successful diabetes management results in better diabetes self-care behaviors, and leads to improvements in clinical outcomes. Problem-solving is central to many self-management and behavior change programs; the American Diabetes Association (ADA) includes problem-solving as a critical self-care behavior. Given the importance of problem solving skills, innovative diabetes education programs, such as Discovering Diabetes, have been developed and shown to be effective in fostering independent problem-solving.
At the same time, many care management programs and diabetes education centers struggle with staffing shortages, limited funding, and competitive time demands. As a result, 50 to 80% of individuals with diabetes experience significant knowledge and skill deficits. Health Information Technology (HIT) can make successful interventions available to more diverse populations. At present, however, many HIT interventions target improved patient-clinician communication and logging and monitoring, rather than focusing more specifically on fostering problem-solving skills. Moreover, few HIT interventions have been rigorously evaluated in controlled trials. The main contribution of this research is a theoretically-grounded HIT intervention, Mobile Diabetes Detective (MoDD), that incorporates best practices and current guidelines for supporting and fostering individuals' problem-solving skills in context of diabetes self-management. In our prior work we developed and evaluated a mobile application for reflection and discovery in diabetes management, MAHI (Mobile Access to Health Information). MAHI helped individuals with diabetes capture diabetes-related experiences and reflect on them under a supervision of a diabetes educator. The proposed intervention, MoDD will further extend this prior work, specifically focusing on guided problem-solving through experimentation. The intervention will utilize an open source platform for disease self-management developed by the research team.
If the results are achieved, the project will have significant impact both locally and globally. Locally, diabetes continues to be a major problem in NYC, particularly among disadvantaged populations, many of whom are served by the Health Resources and Services Administration (HRSA) funded Community Health Centers (CHCs) participating in this study. In the past 10 years, the number of people with diabetes in NYC has more than doubled. An estimated 530,000 adult New Yorkers have been diagnosed with diabetes, with another 265,000 having diabetes but are unaware. In the HRSA funded CHCs in New York State, 8% of the adult patients have a diagnosis of diabetes. At the same time, our prior studies showed that despite such barriers as low health literacy or lower socio-economic status, disadvantaged populations in NYC can greatly benefit from informatics interventions that target health and wellness. The proposed research will use HIT to partially assuage the ongoing challenge of control and management of diabetes. The expected improvement in problem-solving skills has been shown to lead to improved self-care behaviors, such as a more careful diet and appropriate level of exercise, and significant reduction in HbA1c7, which in turn has been linked to reduction in diabetes-related complications. Thinking more broadly, this research can provide new insights into facilitating problem-solving in diabetes management with HIT, as an alternative to more traditional staff-intensive interventions.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| No Intervention: Control Control Arm: Study participants attending one of the 4 control arm centers will receive usual diabetes education provided by staff at the site; be provided with free test strips for their blood glucose meters during the 4-week intervention period; given access to the MODD application at the end of the study. Instructions on how to use the MODD will be provided by site staff. |
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| Experimental: Intervention Intervention: Mobile Diabetes Detective (MoDD) Study participants attending one of the 4 Intervention sites will receive usual diabetes education provided by staff at the site and be given access to the MODD application and instructions for use for 4 weeks at the beginning of the study. After the initial 4 weeks of access to the MODD application, participants will be offered an option to continue using MODD for the duration of the study. |
Behavioral: Mobile Diabetes Detective (MoDD)
MoDD is a web-based application that is designed to help individuals with diabetes identify specific problems related to glycemic control, and engage in problem-solving process. MoDD includes a number of messages that explain its users the nature of various problems related to glycemic control, aspects of individuals' behaviors that might have contributed to these problems, and alternative behaviors that could help to improve glycemic control. In addition to these messages displayed on the MoDD website, study participants may receive SMS messages with reminders to test blood glucose, or to follow the selected new behavior.
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Outcome Measures
Primary Outcome Measures
- Change in HgA1c [Baseline, post-intervention 4 weeks, 3 months, 12 months]
Glycated hemoglobin is a form of hemoglobin that is measured primarily to identify the average plasma glucose concentration over prolonged periods of time.
- Change in Score on the Diabetes Problem-Solving Inventory (DPSI) [Baseline, post-intervention 4 weeks, 3 months, 12 months]
Diabetes Problem-Solving Inventory (DPSI) is a 9-item questionnaire that assesses individuals' problem-solving skills as applied specifically to overcoming barriers to diabetes self-management.
- Change in Score on the Summary of Diabetes Self-Care Activities Questionnaire (SDSCA) [Baseline, post-intervention 4 weeks, 3 months, 12 months]
Summary of Diabetes Self-Care Activities Questionnaire (SDSCA) contains 12 items with 5 subscales (diet, exercise, blood glucose testing, foot care, smoking status). The respondent is asked how many days in the past week he/she performed the behavior; higher scores indicate higher performance.
Secondary Outcome Measures
- Change in Score on Problem Areas in Diabetes Scale (PAID) [Baseline, post-intervention 4 weeks, 3 months, 12 months]
Problem Areas in Diabetes Scale (PAID) is a 20 item 5 point Likert scale that measures the emotional aspect of living with diabetes .
- Change in Score on the Diabetes Self-Efficacy Scale (DSES) [Baseline, post-intervention 4 weeks, 3 months, 12 months]
Diabetes Self-Efficacy Scale (DSES) is 15-item 10-point Likert scale (1-cannot do at all; 10-Certain can do) that measures the belief that one can self-manage one's own health, specifically adapted to diabetes.
- Change in Score on the Patient Health Questionnaire-2 (PHQ-2) [Baseline, post-intervention 4 weeks, 3 months, 12 months]
Patient Health Questionnaire-2 inquires about the frequency of depressed mood and anhedonia over the past 2 weeks, scoring each as 0 ("not at all") to 3 ("nearly every day").
- Change in Fasting Blood Glucose Level [Baseline, post-intervention 4 weeks, 3 months, 12 months]
Fasting blood glucose will be collected from patients' charts.
- Change in Total Cholesterol [Baseline, post-intervention 4 weeks, 3 months, 12 months]
- Change in Blood Pressure [Baseline, post-intervention 4 weeks, 3 months, 12 months]
Blood pressure will be collected using patients' charts.
- Change in High-Density Lipoprotein [Baseline, post-intervention 4 weeks, 3 months, 12 months]
- Change in Low-Density Lipoprotein [Baseline, post-intervention 4 weeks, 3 months, 12 months]
Eligibility Criteria
Criteria
Inclusion Criteria:
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Age 18-65 years
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A diagnosis of Type 2 Diabetes with HbA1c ≥ 8.0. A patient of the health center for at least 6 months
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Has participated in at least one diabetes education session at the participating site in the last 6 months
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Proficient in either English or Spanish
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Must own a basic cell phone
Exclusion Criteria:
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Pregnancy
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Presence of serious illness (e.g. cancer diagnosis with active treatment, advanced stage heart failure, multiple sclerosis)
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Presence of cognitive impairment
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Plans for leaving the community health center (CHC) in the next 12 months
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Does not have a computer and/or Internet access
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Clinical Directors Network | New York | New York | United States | 10018 |
Sponsors and Collaborators
- Columbia University
- Clinical Directors Network
- Georgia Institute of Technology
- National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Investigators
- Principal Investigator: Olena Mamykina, PhD, Columbia University
- Study Chair: Jonathan Tobin, PhD, Clinical Directors Network
Study Documents (Full-Text)
None provided.More Information
Publications
- Bonnet C, Gagnayre R, d'Ivernois JF. Learning difficulties of diabetic patients: a survey of educators. Patient Educ Couns. 1998 Oct;35(2):139-47.
- Cook S, Aikens JE, Berry CA, McNabb WL. Development of the diabetes problem-solving measure for adolescents. Diabetes Educ. 2001 Nov-Dec;27(6):865-74.
- Costa BM, Fitzgerald KJ, Jones KM, Dunning Am T. Effectiveness of IT-based diabetes management interventions: a review of the literature. BMC Fam Pract. 2009 Nov 17;10:72. doi: 10.1186/1471-2296-10-72. Review.
- Glasgow RE, Funnell MM, Bonomi AE, Davis C, Beckham V, Wagner EH. Self-management aspects of the improving chronic illness care breakthrough series: implementation with diabetes and heart failure teams. Ann Behav Med. 2002 Spring;24(2):80-7.
- Glasgow RE, Toobert DJ, Riddle M, Donnelly J, Mitchell DL, Calder D. Diabetes-specific social learning variables and self-care behaviors among persons with type II diabetes. Health Psychol. 1989;8(3):285-303.
- Hill-Briggs F. Problem solving in diabetes self-management: a model of chronic illness self-management behavior. Ann Behav Med. 2003 Summer;25(3):182-93. Review.
- Paterson B, Thorne S. Expert decision making in relation to unanticipated blood glucose levels. Res Nurs Health. 2000 Apr;23(2):147-57.
- Toobert DJ, Glasgow RE. Problem solving and diabetes self-care. J Behav Med. 1991 Feb;14(1):71-86.
- Whitlock EP, Orleans CT, Pender N, Allan J. Evaluating primary care behavioral counseling interventions: an evidence-based approach. Am J Prev Med. 2002 May;22(4):267-84. Review.
- AAAM0057
- 1R01DK090372-01A1