# Evaluating the essential components needed for a physical activity initiation and maintenance intervention to improve physical activity and arthritis pain and symptoms in Latinos with arthritis

> **NIH NIH R34** · UNIV OF NORTH CAROLINA CHAPEL HILL · 2024 · $208,939

## Abstract

More than one in five adult Latinos in the United States has arthritis and Latinos experience greater joint pain
and limitations than non-Latino Whites. Physical activity (PA) improves arthritis symptoms, yet Latinos are less
likely to engage in any PA (50%) than non-Latino Whites (65%). Camine con Gusto (CCG), the Arthritis
Foundation’s evidence-based 6-week Spanish-language version of Walk With Ease, is one of few PA
interventions tested in Latinos. CCG was shown in a pre-post study to improve outcomes in 233 Latinos with
arthritis. The Osteoarthritis Action Alliance developed an online portal for CCG with enhancements including
weekly emails/texts, tracking/goal setting, and video/audio content based on feedback from Latinos and
community-based organizations (CBOs) that offer CCG. Participants expressed a need for additional, more
resource-intensive components to CCG that have yet to be implemented or tested. The overall goal of this R34
is to plan an assessor blinded community-based randomized optimization trial to test recommended additional
components for CCG PA initiation and maintenance. To evaluate which additional components contribute
meaningfully to increasing PA, we will use the Multiphase Optimization Strategy (MOST), an approach to
developing highly efficient and scalable behavioral interventions that include only the most potent and cost-
effective components. Using MOST, we will: 1) Determine the set of components (pedometer, CCG promotora,
and maintenance promotora) when added to CCG that meaningfully increase daily steps (primary outcome)
immediately post-CCG and 6- and 12-months post-CCG; 2) Evaluate the set of components, when added to
CCG, that meaningfully improve secondary outcomes (i.e., arthritis symptoms, sleep quality) post-CCG and at
6- and 12-months; and 3) Evaluate the cost-effectiveness of the intervention components for scalability in
CBOs serving Latinos with arthritis. We have worked closely with our Community Advisory Board (CAB) on this
R34 proposal and will work with them on all aspects of the planning grant and proposed trial. Results from
each aim will inform the decision on which set of components has the greatest impact on PA initiation and
maintenance for the best cost. In this planning period, we will: 1) Use CAB input and behavioral theory to
finalize the scientific details for the study; this will include refining CCG portal enhancements and additional
intervention components (i.e., pedometer and promotoras), finalizing outcome measures, collection methods,
the research and cost-effectiveness protocols and statistical analysis plan. 2) Use CAB input to develop the
materials and application for the proposed trial; this will include recruitment, retention, and adherence
materials and approaches; manual of operating procedures; data management plan; training manuals, and
fidelity assessment plans; data safety and monitoring plan; and a detailed project timeline and budget for the
future clinical trial. T...

## Key facts

- **NIH application ID:** 10812011
- **Project number:** 1R34AR083685-01
- **Recipient organization:** UNIV OF NORTH CAROLINA CHAPEL HILL
- **Principal Investigator:** LEIGH Fleming CALLAHAN
- **Activity code:** R34 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $208,939
- **Award type:** 1
- **Project period:** 2024-01-01 → 2025-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10812011

## Citation

> US National Institutes of Health, RePORTER application 10812011, Evaluating the essential components needed for a physical activity initiation and maintenance intervention to improve physical activity and arthritis pain and symptoms in Latinos with arthritis (1R34AR083685-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10812011. Licensed CC0.

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