Telehealth Behavioral Intervention for Diabetes Management in Adults With Physical Disabilities: Intervention Fidelity Protocol for a Randomized Controlled Trial (original) (raw)
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2021
BACKGROUND Diabetes mellitus is a major health problem among people with physical disabilities. Health coaching has been proven to be an effective approach in terms of behavioral changes, patient self-efficacy, adherence to treatment, health service use, and health outcomes. Telehealth systems combined with health coaching have the potential to improve the quality of health care by increasing access to services. Treatment fidelity is particularly important for behavior change studies; however, fidelity protocols are inadequately administered and reported in the literature. OBJECTIVE The aim of this study is to outline all the intervention fidelity strategies and procedures of a telecoaching intervention—artificial intelligence for diabetes management (AI4DM)—which is a randomized controlled trial to evaluate the feasibility, acceptability, and preliminary efficacy of a telehealth platform in adults with type 2 diabetes and permanent impaired mobility. AI4DM aims to create a web-base...
JMIR Research Protocols, 2021
Background Individuals with disabilities and type 2 diabetes require self-management programs that are accessible, sustainable, inclusive, and adaptable. Health coaching has been shown to be an effective approach for improving behavioral changes in self-management. Health coaching combined with telehealth technology has the potential to improve the overall quality of and access to health services. Objective This protocol outlines the study design for implementing the Artificial Intelligence for Diabetes Management (AI4DM) intervention. The protocol will assess the feasibility, acceptability, and preliminary efficacy of the AI4DM telehealth platform for people with disabilities. Methods The AI4DM study is a 2-arm randomized controlled trial for evaluating the delivery of a 12-month intervention, which will involve telecoaching, diabetes educational content, and technology access, to 90 individuals with diabetes and physical disabilities. The hypothesis is that this pilot project is f...
The American journal of managed care, 2006
A major problem in the dissemination of most interventions found to be efficacious is that they are of limited or unknown generalizability. To document the "robustness," or external validity, of a computer-assisted diabetes self-management program across different patient characteristics, healthcare settings (mixed payer vs health maintenance organization), intervention staff, and outcomes. A randomized controlled trial evaluating a computer-assisted behavior change program for adult patients with type 2 diabetes mellitus (n = 217) vs a computerized health risk assessment. Outcomes were identified using the RE-AIM framework and included program adoption among physicians, reach across patient groups, implementation, and behavioral (fat intake and physical activity) and biological (glycosylated hemoglobin and lipid levels) effectiveness measures. The program achieved 41% patient participation, variable adoption across healthcare settings (76% of health maintenance organizati...
Journal of Medical Internet Research, 2022
Background: "Healthy Living for People with type 2 Diabetes (HeLP-Diabetes)" was a theory-based digital self-management intervention for people with type 2 diabetes mellitus that encouraged behavior change using behavior change techniques (BCTs) and promoted self-management. HeLP-Diabetes was effective in reducing HbA1c levels in a randomized controlled trial (RCT). National Health Service (NHS) England commissioned a national rollout of HeLP-Diabetes in routine care (now called "Healthy Living"). Healthy Living presents a unique opportunity to examine the fidelity of the national rollout of an intervention originally tested in an RCT. Objective: This research aimed to describe the Healthy Living BCT and self-management content and features of intervention delivery, compare the fidelity of Healthy Living with the original HeLP-Diabetes intervention, and explain the reasons for any fidelity drift during national rollout through qualitative interviews. Methods: Content analysis of Healthy Living was conducted using 3 coding frameworks (objective 1): the BCT Taxonomy v1, a new coding framework for assessing self-management tasks, and the Template for Intervention Description and Replication. The extent to which BCTs and self-management tasks were included in Healthy Living was compared with published descriptions of HeLP-Diabetes (objective 2). Semistructured interviews were conducted with 9 stakeholders involved in the development of HeLP-Diabetes or Healthy Living to understand the reasons for any changes during national rollout (objective 3). Qualitative data were thematically analyzed using a modified framework approach. Results: The content analysis identified 43 BCTs in Healthy Living. Healthy Living included all but one of the self-regulatory BCTs ("commitment") in the original HeLP-Diabetes intervention. Healthy Living was found to address all areas of self-management (medical, emotional, and role) in line with the original HeLP-Diabetes intervention. However, 2 important changes were identified. First, facilitated access by a health care professional was not implemented; interviews revealed this was because general practices had fewer resources in comparison with the RCT. Second, Healthy Living included an additional structured web-based learning curriculum that was developed by the HeLP-Diabetes team but was not included in the original RCT; interviews revealed that this was because of changes in NHS policy that encouraged referral to structured education. Interviewees described how the service provider had to reformat the content of the original HeLP-Diabetes website to make it more usable and accessible to meet the multiple digital standards required for implementation in the NHS. Conclusions: The national rollout of Healthy Living had good fidelity to the BCT and self-management content of HeLP-Diabetes. Important changes were attributable to the challenges of scaling up a digital intervention from an RCT to a nationally implemented
Diabetes, 2020
Background: Remote delivery of health care services through telehealth technology holds promise for expanding access to and engaging individuals in underserved communities. Systematic Screening and Assessment and Evaluability Assessment methods were used to identify and evaluate promising CDC-recognized National Diabetes Prevention Program Lifestyle Change and Diabetes Self-Management Education and Support (DSMES) programs utilizing telehealth technology. Objective: To describe how 8 Lifestyle Change and DSMES programs utilize telehealth technologies effectively to expand access to services in underserved communities. Methods: Eight effective programs were selected to participate in an in-depth study. Information was gathered to understand activities, adaptations, and implementation challenges through in-depth interviews with stakeholders and on-site observation. Results: In all program sites, telehealth technology seamlessly integrated into existing program models to increase patie...
Research Square (Research Square), 2022
Full list of author information is available at the end of the article Resumo Background: Behaviour change digital-assisted interventions can be a low-cost solution to enduring healthy behaviours. Understanding how to automate and tailor such interventions to patients' needs can improve health outcomes. This study aims at reviewing the evidence of the use of such interventions in a clinical setting in adult chronic patients. Methods: This study followed the PRISMA guidelines for comprehensive search, appraisal, and synthesis of research evidence. A literature search was performed to find studies published between 1 January 2017 and 26 March 2022 in peer-reviewed journals and written in English. Behaviour change interventions in adult chronic patients with automated and tailored communication systems were considered. Results: Seven quantitative studies (6 RCT and a pilot RCT) with sample sizes from 54 to 506 participants and timeframes varying from 4 to 30 weeks met the eligibility criteria. Populations comprehended patients with cardiovascular disease, chronic kidney disease, diabetes, or osteoarthritis. Communication channels included SMS, email, and voice records. Rule-based models were used to automate content in all studies and bidirectional communication was used in four of them. Content and service delivery were tailored given the patient's goals, needs, functional ability, activity, personal characteristics, and communication channel preferred. Most data management platforms used were developed in prior studies. Interventions were designed based on 9 different behaviour change models. There was no evidence of improvements in clinical outcomes after the intervention. Some studies showed improvements in self-efficacy (n=1), the use of dietary data info (n=1), physical activity (n=2), social support (n=1), and quality of life (n=1). The risk of bias analysis revealed that one study had moderate risk and the remaining had low risk. Conclusion: This study supports researchers that are designing digital behaviour change interventions by putting in evidence the intervention's features needed to be considered during this step. It revealed that the most efficient solutions were tailored to patients' needs and disease stages and that further research on the mechanisms of change and content automation needs to be done.
Journal of Telemedicine and Telecare
Introduction Evidence supporting home telehealth effects on clinical outcomes in diabetes is available, yet mechanisms of action for these improvements remain poorly understood. Behavioural change is one plausible explanation. This study investigated the behavioural effects of a mobile-phone based home telehealth (MTH) intervention in people with diabetes. It was hypothesized that MTH would improve self-efficacy, illness beliefs, and diabetes self-care. Methods A randomized controlled trial compared standard care to standard care supplemented with MTH (self-monitoring, data transmission, graphical and nurse-initiated feedback, educational calls). Self-report measures of self-efficacy, illness beliefs, and self-care were repeated at baseline, three months, and nine months. MTH effects were based on the group by time interactions in hierarchical linear models and effect sizes with 95% confidence intervals (CIs). Interviews with MTH participants explored the perceived effects of MTH on...
JMIR research protocols, 2015
The role of technology in health care delivery has grown rapidly in the last decade. The potential of mobile telehealth (MTH) to support patient self-management is a key area of research. Providing patients with technological tools that allow for the recording and transmission of health parameters to health care professionals (HCPs) may promote behavior changes that result in improved health outcomes. Although for some conditions the evidence of the effectiveness of MTH is clear, to date the findings on the effects of MTH on diabetes management remain inconsistent. This study aims to evaluate an MTH intervention among insulin-requiring adults with diabetes to establish whether supplementing standard care with MTH results in improved health outcomes-glycated hemoglobin (HbA1c), blood pressure (BP), health-related quality of life (HRQoL), diabetes self-management behaviors, diabetes health care utilization, and diabetes self-efficacy and illness beliefs. An additional objective was to...
Journal of the American Medical Informatics Association, 2017
Objective: The purpose of this systematic review and meta-analysis was to examine the effect of health information technology (HIT) diabetes self-management education (DSME) interventions on glycemic control in medically underserved patients. Materials and Methods: Following an a priori protocol, 5 databases were searched. Studies were appraised for quality using the Cochrane Risk of Bias assessment. Studies reporting either hemoglobin A1c pre-and post-intervention or its change at 6 or 12 months were eligible for inclusion in the meta-analysis using random effects models. Results: Thirteen studies met the criteria for the systematic review and 10 for the meta-analysis and represent data from 3257 adults with diabetes (mean age 55 years; 66% female; 74% racial/ethnic minorities). Most studies (n ¼ 10) reflected an unclear risk of bias. Interventions varied by HIT type: computer software without Internet (n ¼ 2), cellular/automated telephone (n ¼ 4), Internet-based (n ¼ 4), and telemedicine/telehealth (n ¼ 3). Pooled A1c decreases were found at 6 months (À0.36 (95% CI, À0.53 and À0.19]; I 2 ¼ 35.1%, Q ¼ 5.0), with diminishing effect at 12 months (À0.27 [95% CI, À0.49 and À0.04]; I 2 ¼ 42.4%, Q ¼ 10.4). Discussion: Findings suggest that medically underserved patients with diabetes achieve glycemic benefit following HIT DSME interventions, with dissipating but significant effects at 12 months. Telemedicine/telehealth interventions were the most successful HIT type because they incorporated interaction with educators similar to in-person DSME. Conclusion: These results are similar to in-person DSME in medically underserved patients, showing that welldesigned HIT DSME has the potential to increase access and improve outcomes for this vulnerable group.
JBI evidence implementation, 2022
Assess effect of diabetes self-management education and support methods, providers, duration, and contact time on glycemic control in adults with type 2 diabetes. Method: We searched MEDLINE, CINAHL, EMBASE, ERIC, and PsycINFO to December 2013 for interventions which included elements to improve participants' knowledge, skills, and ability to perform self-management activities as well as informed decision-making around goal setting. Results: This review included 118 unique interventions, with 61.9% reporting significant changes in A1C. Overall mean reduction in A1C was 0.74 and 0.17 for intervention and control groups; an average absolute reduction in A1C of 0.57. A combination of group and individual engagement results in the largest decreases in A1C (0.88). Contact hours !10 were associated with a greater proportion of interventions with significant reduction in A1C (70.3%). In patients with persistently elevated glycemic values (A1C > 9), a greater proportion of studies reported statistically significant reduction in A1C (83.9%). Conclusions: This systematic review found robust data demonstrating that engagement in diabetes selfmanagement education results in a statistically significant decrease in A1C levels. Practice implications: The data suggest mode of delivery, hours of engagement, and baseline A1C can affect the likelihood of achieving statistically significant and clinically meaningful improvement in A1C.