# The Effect of a Technology-Mediated Integrated Walking and Tai Chi Intervention on Physical Function in Veterans with COPD and Chronic Musculoskeletal Pain

> **NIH VA I01** · VA BOSTON HEALTH CARE SYSTEM · 2024 · —

## Abstract

Current physical activity (PA) interventions for persons with chronic obstructive pulmonary disease
(COPD) focus primarily on reducing the debilitating symptom of dyspnea or shortness of breath. However,
over half of patients with COPD experience chronic musculoskeletal pain which limits achievement of PA goals
and optimization of physical function. Low PA is associated with poor outcomes–increased risk of COPD acute
exacerbations, hospitalizations, and death–independent of lung function. Funded by Rehabilitation R&D, we
have developed Every Step Counts (ESC), a web-based intervention to promote PA in Veterans with COPD.
ESC couples a dynamic website with a pedometer that objectively monitors daily step counts. Based on the
Behavioral Theory of Self-Regulation, the website provides individualized step-count goals, iterative feedback,
education on disease self-management, motivation, and an online community of social support. In RCTs, we
have demonstrated ESC’s safety, feasibility, and efficacy to increase PA over 3-6 months. However, not all
participants increased daily step counts. In secondary analyses, we identified pain as a significant barrier to
PA. Participants with co-occurring pain and dyspnea walked 1,200-1,400 fewer steps per day, compared to
those with no symptoms. In its current form, ESC does not focus on pain management. Tai Chi (TC) is an
attractive nonpharmacologic treatment for chronic musculoskeletal pain. TC improves neuromuscular function,
core strength, and lower limb proprioception. Importantly, the mindfulness embedded in TC uniquely addresses
cognitive and psycho-emotional processes critical for pain management (i.e., “extinction of fear conditioning,
acceptance-based coping strategies, increased ability to self-regulate affective appraisal of nociceptive input,”
and reduced pain-related distress and catastrophizing). We have shown that persons with COPD can safely
engage with TC delivered via either in-person classes or video instruction. We propose to integrate ESC and
TC to target biopsychosocial mechanisms of pain to break the chronic pain cycle and improve physical function
in persons with COPD. We will adapt ESC with pain management content, an online TC video library, and
synchronous TC classes led by an instructor via teleconference. We will randomize participants 1:1 to ESC-TC
or usual care for 6 months. Assessments of outcomes will occur at baseline, 2, 4, and 6 months in all
participants, and at 12 months in a subset who enroll early. Aim 1: Determine the efficacy of the ESC-TC
intervention in 136 persons with COPD and chronic musculoskeletal pain to improve the primary outcome of
physical function, measured by daily step count, compared to usual care at 6 months. Aim 2: Evaluate the
effect of the ESC-TC intervention on secondary outcomes of (a) pain intensity and interference, (b) dyspnea,
(c) health-related quality of life, (d) mobility, (e) depression and anxiety, (f) exercise self-efficacy, (g)
kinesiophobi...

## Key facts

- **NIH application ID:** 10775740
- **Project number:** 5I01RX004225-02
- **Recipient organization:** VA BOSTON HEALTH CARE SYSTEM
- **Principal Investigator:** Marilyn L. Moy
- **Activity code:** I01 (R01, R21, SBIR, etc.)
- **Funding institute:** VA
- **Fiscal year:** 2024
- **Award amount:** —
- **Award type:** 5
- **Project period:** 2023-04-01 → 2028-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10775740

## Citation

> US National Institutes of Health, RePORTER application 10775740, The Effect of a Technology-Mediated Integrated Walking and Tai Chi Intervention on Physical Function in Veterans with COPD and Chronic Musculoskeletal Pain (5I01RX004225-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10775740. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*