PREDHICT: Precision Recruitment and Engagement of Diabetics and Hypertensives in Clinical Studies

Not Applicable

Completed

Brief Summary: For the sub-study, this digital navigation tool will both inform/educate, engage, support, and navigate participants and providers through the process of clinical trial participation via personalization (data profiling, adaptive and customized messaging, and tailored digital navigation) in a sample of 100 participants with diabetes and hypertension.

Detailed Description: To identify provider- and system-level facilitators (solutions) of clinical trial participation that can be in corporated in the digital navigation tool. We will pay special emphasis on the behavior research volunteerism and altruism and individuals who are at risk for cardio metabolic conditions. To develop solutions that will address patient-, provider and system-level barriers preventing clinical trial participation Objective 2: To test the adherence, feasibility, and efficacy of a research volunteerism and altruism component of a health and wellness web app. that provides personalized newsfeeds and curriculum about research and health-related volunteer and altruistic activities versus traditional patient navigation procedures and resources in clinical trial awareness.'awareness/knowledge, attitudes, willingness to participate in clinical trial, self-efficacy, and share knowledge about clinical trial opportunities to social network. To determine which elements of the digital tool and mobil app are associated with increased awareness/knowledge, intent to participate, and contagion

Recruitment & Eligibility

Inclusion Criteria

NYU and/or Bellevue patient
Diagnosed with HTN and pre-diabetes/diabetes
Must be English speakers
Ownership of a smart phone and are willing to use it to download app built in TrialX which will be free for participants
Must be ambulatory

Exclusion Criteria

are unable or unwilling to provide informed consent;
are unable to participate meaningfully in an intervention that involves self-- monitoring using software available in English (e.g., due to uncorrected sight impairment, illiterate, non-English-speaking, dementia);
are institutionalized (e.g., in a nursing home or personal care facility, or those who - are incarcerated and have limited control over self-management)
have a history of heart disease, kidney disease, or retinopathy (to rule-out those with long-standing, undiagnosed T2D)

Arm && Interventions

Group	Intervention	Description
Control group	control group	Participants will receive non-personalized information (one-size-fits-all) diet, sleep and physical activity recommendations via messaging delivered by app.
Intervention Group	Lifestyle management	Participants will receive personalized messages about achieving healthy diet, physical activity and sleep as well as summary of their performance for the week and month. They will also receive personalized content about research volunteerism and altruistic activities.

Primary Outcome Measures

Name	Time	Method
Change in clinical trials participation Change in User Adherence	Baseline Visit, 4 week follow up visit, 6 month follow up visit	Will show that one-size-fits-all versus personalization leads to greater adherence. Adherence will be based on whether the subject met the daily and weekly behavior recommendations.
Change in glucose level Change in blood pressure	Baseline Visit, 4 week follow up visit, 6 month follow up visit	The amount of sugar levels will be determined the Harris-Benedict Calculator, which consists of height, weight, weight age and activity levels
Change in physical activity	Baseline Visit, 4 week follow up visit, 6 month follow up visit	FitBit tracking will measure increase in physical activity adherence.
Change in physical activity by self-report	Baseline Visit, 4 week follow up visit, 6 month follow up visit	Increase in physical activity will be measured by self-report diaries collected by study staff through health and wellness app platforms.
Change in body mass index Change in blood pressure	Baseline Visit, 4 week follow up visit, 6 month follow up visit	Change in body mass index will be determined by the self reported information the vb=vodt

Secondary Outcome Measures

Name	Time	Method