# 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 · 2022 · $88,290

## Abstract

Project Summary (Abstract)
Diabetes self-management (DSM) interventions have struggled to deliver relevant, effective, and sustainable
support for at-risk adults with diabetes to improve 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. Three out of four 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 effective approaches to directly engage patients’ family members in supporting
successful diabetes management. The long-term goal of this research is to produce structured and evidence-
based approaches that engage family supporters in helping at-risk adults initiate and sustain effective diabetes
management behaviors. The objective of this study is to compare the effectiveness of a novel program—
Family Partners for Health Action (FAM-ACT)—to more traditional, individual patient-focused diabetes self-
management education and care management (I-DSME/CM). FAM-ACT uses three innovative approaches to
enhance the impact of family support on diabetes management: 1) provide family members core behavioral
strategies directed at specific roles in supporting diabetes medical and lifestyle management, 2) teach family
members how to deliver support in patient-autonomy supportive ways, and 3) teach family supporters ways to
boost patients’ activated participation in healthcare. Community Health Workers (CHWs) will deliver FAM-ACT
to patient-family supporter dyads at an urban federally qualified health center. 268 patients with type 2 diabetes
and either poor glycemic or blood pressure control, together with a family supporter, will be randomized to
receive either FAM-ACT or CHW-led I-DSME/CM over 6 months. The specific aims of this study are to 1)
Determine the effect of FAM-ACT on patients’ diabetes health outcomes compared to I-DSME/CM, 2)
Determine the effect of FAM-ACT on patient health behaviors and perceived support compared to I-DSME/CM,
and 3) Determine the sustainability of health outcomes and health behavior gains made in FAM-ACT compared
to I-DSME/CM. The main diabetes health outcome is change from baseline to 6 months in Hemoglobin A1c.
Patient behavioral outcomes will include diabetes self-management behaviors, and perceived social support
and autonomy supportiveness from family. Sustainability will be assessed at 12 months, after a period of 6
months without CHW intervention. This project is significant because it builds on prior CHW and peer support
models to help at-risk diabetes patients with few resources achieve and sustain core health behaviors that
underlie successful management of multiple risk factors for diabetes complications. Ultimately, this study will
have a positive impact by producing a novel, scalable, evidence-based protocol and tools that lev...

## Key facts

- **NIH application ID:** 10528905
- **Project number:** 3R01DK116733-04S1
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Ann-Marie Rosland
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $88,290
- **Award type:** 3
- **Project period:** 2021-12-01 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10528905

## Citation

> US National Institutes of Health, RePORTER application 10528905, 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 (3R01DK116733-04S1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10528905. Licensed CC0.

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