# Optimizing Telehealth-delivery of a Weight Loss Intervention in Older Adults with Multiple Chronic Conditions: A Sequential, Multiple Assignment, Randomized Trial

> **NIH NIH R01** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2024 · $731,886

## Abstract

PROJECT SUMMARY
Consistent with the research priorities of the National Institute on Aging, this R01 application will investigate the
optimal intervention sequence to achieve weight loss in older adults with obesity and ≥ 2 Medicare-defined
multiple chronic conditions (MCC). The growing prevalence of obesity in older adults, particularly in those with
common chronic conditions such as diabetes, hypertension, or arthritis, increases the risk of functional decline,
nursing home placement, and early mortality. Weight loss interventions can mitigate such adverse outcomes;
however, differential response to treatment is often observed due to a patient’s clinical heterogeneity. Clinicians
lack guidance on the most effective lifestyle-based intervention, and which intervention to try if the first one fails.
An innovative Sequential, Multiple Assignment, Randomized Trial (SMART) design will be conducted to identify
optimal intervention approaches for weight loss in older adults with MCC, tailoring strategies for non-responders
to weight loss. During the 52-week, two-stage trial, 180 older adults with obesity and MCC will be enrolled to
compare two weight loss interventions: a prescriptively focused, medically tailored, weight loss intervention
(prescriptive), and a behaviorally focused, health coaching intervention (behavioral). Consistent with a SMART
design, at 8-weeks, early non-responders (weight loss of <2.5%) will be randomized to: (a) more sessions of the
original assignment; (b) a combination of prescriptive and behavioral interventions; or (c) a switch to a
prescriptive, medically tailored strategy (initial, first-line behavioral arm participants) or to a behaviorally focused
health coach-delivered strategy (initial prescriptive arm participants). The SMART will enable the identification
of the treatment combinations that maximize weight loss at 52-weeks. To this end, the proposal aims to: 1) test
the superiority of an initial (first-line) prescriptive or behavioral intervention using an adaptive strategy for early
non-responders; 2) assess the patterns of initial weight loss and compare strategies for non-responders; and 3)
examine the cost-effectiveness from a societal perspective for maintaining weight loss of the proposed treatment
sequences at 78-weeks (26-weeks post-intervention completion). The primary outcome is percent weight loss at
52-weeks; secondary outcomes include global health and physical function, anthropometry, behavioral treatment
targets and risk factors, and clinical indices. Based on preliminary data, it is hypothesized that older adults with
obesity and MCC will achieve greater weight loss with a prescriptive, medically tailored intervention, and the
estimated adaptive intervention strategy tailored to a patient’s characteristics will lead to better outcomes than a
fixed intervention. If the trial is successful, the adaptive strategy will be compared to a fixed prescriptive or
behavioral strategy in a future comparative ef...

## Key facts

- **NIH application ID:** 10786098
- **Project number:** 5R01AG077163-02
- **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL
- **Principal Investigator:** John A. Batsis
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $731,886
- **Award type:** 5
- **Project period:** 2023-02-15 → 2028-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10786098

## Citation

> US National Institutes of Health, RePORTER application 10786098, Optimizing Telehealth-delivery of a Weight Loss Intervention in Older Adults with Multiple Chronic Conditions: A Sequential, Multiple Assignment, Randomized Trial (5R01AG077163-02). Retrieved via AI Analytics 2026-06-12 from https://api.ai-analytics.org/grant/nih/10786098. Licensed CC0.

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