# Comparative Effectiveness of Adding Family Supporter Training and Engagement to a CHW-Led Intervention to Improve Behavioral Management of Multiple Risk Factors for Diabetes Complications

> **NIH NIH R01** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2021 · $497,103

## Abstract

Challenges to controlling blood glucose, blood pressure, and cholesterol levels put 16 million U.S. adults
at high risk of disabling diabetes complications. Diabetes self-management (DSM) interventions have
struggled to deliver relevant, effective, and sustainable support for at-risk adults with diabetes to improve
multiple key DSM behaviors, become more activated participants in healthcare, and reduce diabetes
complications. One largely untapped resource for this support is patients' family and friends. 75% of
adults with diabetes reach out to an unpaid family member or friend (a family supporter) for ongoing help
with diabetes management. However, diabetes management interventions to date lack structured and
tested approaches to directly engage patients' supportive family members in promoting and sustaining
patient activation and improved diabetes management. The objective of this study is to compare the
effectiveness of a novel strategy – Family Partners for Health Action (FAM-ACT) – to individual patient-
focused diabetes self-management education (DSME) and care management. FAM-ACT directly engages
family supporters of at-risk adults with diabetes by providing them the core skills to allow them to
effectively support health behavior change, medication adherence, and active engagement with patient's
healthcare providers. A fundamental focus of FAM-ACT is providing family with the ability to give
autonomy supportive and need-responsive help to patients. Community Health Workers (CHWs) will
deliver FAM-ACT to low-income patients and their family supporters, plus take the novel step of helping
family supporters integrate their efforts with those of patients' primary care teams. The specific aims of
this study are to 1) Compare the effect of FAM-ACT on patients' diabetes health outcomes to standard,
individually-focused, CHW-led DSME and Care Management (DSME+CM), 2) Compare the effect of
FAM-ACT on patient health behaviors and perceived support to standard, individually-focused
DSME+CM, and 3) Examine whether health and health behavior gains made in FAM-ACT are better
sustained after the intervention period than those made in DSME+CM. 240 patient + family member
pairs will be randomized to FAM-ACT or DSME+CM for 12 months. Main diabetes health outcomes
will include change from baseline to 12 months in UKPDS 5-Year cardiac risk score, HbA1c, and systolic
blood pressure. Main patient behavioral outcomes will include diabetes self-management behaviors, and
perceived social support and autonomy supportiveness from family. Sustainability will be assessed at 18
months, after a period of 6 months without CHW intervention. We expect this study to produce an
innovative, evidence-based protocol and tool set that leverages family support to help patients optimize
and sustain management of multiple diabetes complication risk factors over time. This project is
innovative because it provides family supporters with underlying support, communication, and health...

## Key facts

- **NIH application ID:** 10134332
- **Project number:** 5R01DK116733-04
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Ann-Marie Rosland
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $497,103
- **Award type:** 5
- **Project period:** 2018-07-25 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10134332

## Citation

> US National Institutes of Health, RePORTER application 10134332, Comparative Effectiveness of Adding Family Supporter Training and Engagement to a CHW-Led Intervention to Improve Behavioral Management of Multiple Risk Factors for Diabetes Complications (5R01DK116733-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10134332. Licensed CC0.

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