Development and Feasibility Testing of a Diabetes Mellitus Program Using Behavioral Economics to Optimize Outreach and Self-management Support With Technology.
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 66
- 试验地点
- 2
- 主要终点
- Completion of diabetes self-management training (Aim 3)
研究概览
简要总结
DM-BOOST uses clinical informatics tools to identify types of patients with gaps in diabetes care and deploy tailored, proactive outreach methods rooted in behavioral economics to nudge them towards increased engagement with diabetes self-management training and leverage patient-facing technologies to enhance longitudinal patient self-management support.
详细描述
In DM-BOOST, the Principal investigator will deploy a mixed-methods, patient-centered approach to intervention development and initiate a multiphase optimization strategy (MOST) to learn how to maximize patient engagement and support of self-management training. In this pilot, study team will complete the first phase (Preparation), and initiate feasibility piloting of the second phase (Optimization). Completion of optimization and MOST's final phase (Evaluation), will occur in a subsequent project.
In the preparation phase, Principal investigator will first analyze EHR and claims data in the UMCCTS data lake to identify sociodemographic characteristics associated with gaps in diabetes care to develop patient persona archetypes (Aim 1). Next, Principal investigator will selectively recruit patients of identified persona types as consultants, elicit stakeholder feedback during community engagement studios and conduct usability testing to iteratively design the intervention (Aim 2). Study team will then conduct a feasibility pilot (Aim 3) to assess user experience of the intervention implementation and collect exploratory outcome data to be used to inform a subsequent, complete optimization trial.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Supportive Care
- 盲法
- Double (Participant, Investigator)
盲法说明
After completing the informed consent, study staff will enter the participant's information into pre-populated REDCap identification numbers. This will assign allocation based on the randomization table. Using this technique, participants will be blinded to allocation. However, research staff will not be blinded to provide personalized training for intervention and control. The investigator will be blinded to randomization for all participants during the study.
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Adults (age 18+)
- •Cognitively able to consent (Aims 2 and 3)
- •Diagnosed with type 2 diabetes (Aims 1-3)
- •Receive primary care at UMMHC in past 12 months at time of initial analysis (Aims 1-3)
- •English speaking (Aims 2 and 3)
- •Have access to patient portal or a smart phone (Aim 3)
排除标准
- •Adults unable to consent (lacking cognitive capacity) (Aims 2 and 3)
- •Individuals who are not yet adults (infants, children, teenagers) (Aims 1-3)
- •Pregnant women (Aims 1-3)
- •Prisoners (Aims 1-3)
- •Non-English speaking (Aims 2 and 3)
结局指标
主要结局
Completion of diabetes self-management training (Aim 3)
时间窗: 9 months
Completion of diabetes self-management training.
Intervention Acceptability (Aim 2)
时间窗: 1 month
Patient-reported assessment of intervention acceptability via usability testing. Qualitative data collection informed by the Technology Acceptance Model with assessment of perceived usefulness, ease of use, behavioral intention to use and external factors. No quantitative data measured.
次要结局
- Clinical utilization (Aim 3)(9 months)
- Diabetes self-efficacy (Aim 3)(3 months)
- Diabetes treatment satisfaction (Aim 3)(3 months)
- Diabetes self-management skills (Aim 3)(3 months)
- Hemoglobin A1C (HbA1C) (Aim 3)(6 months)
- Patient engagement with Diabetes Self-Management Training (Aim 3)(9 months)
研究者
Daniel Amante
Assistant Professor
University of Massachusetts, Worcester