LLM-driven text-based coaching grounded in the Transtheoretical Model of Change increases daily step count compared to generic prompts in adults at risk for cardiovascular disease.
This study will test whether personalized coaching prompts generated by a large language model (LLM) can increase daily step count more than generic prompts in a fully digital, randomized crossover trial. The primary endpoint is change in daily step count, with a target enrollment of 15,000 adults across the US and UK. Recruitment began in March 2026 and is ongoing.
This article is automatically generated from the structured evidence profile behind the claim above. Scores reflect the quality and quantity of available research, not clinical advice.
LLM-driven text-based coaching grounded in the Transtheoretical Model of Change increases daily step count compared to generic prompts in adults at risk for cardiovascular disease. The current body of evidence comprises 1 study, including 1 randomized controlled trial. EvidenceHub rates the overall confidence at 42/100 (low).
The Claim
LLM-driven text-based coaching grounded in the Transtheoretical Model of Change increases daily step count compared to generic prompts in adults at risk for cardiovascular disease.
This conclusion is most relevant to: Adults (N=15,000) across the United States and United Kingdom, recruited via smartphone application.
What the Research Shows
The conclusion draws on 1 linked study. Highlights from the cited literature:
- ▸Design and rationale of the my heart counts cardiovascular health study: a large-scale, fully digital biobank, and randomized trial of large language model-driven coaching of physical activity. (American journal of preventive cardiology, 2026) —
How It Works
The proposed biological pathway:
- ▸LLM generates personalized coaching prompts based on user data and Transtheoretical Model of Change
- ▸User receives prompts via smartphone application
- ▸User's daily step count is passively monitored via smartphone sensors
- ▸Result: Change in daily step count compared to generic prompts
Who Might Benefit
Evidence fit by population:
- ▸Adults (N=15,000) across the United States and United Kingdom, recruited via smartphone application
Recommended Dose
N/A
Limitations & Caveats
Important context when interpreting this evidence:
- ▸Results are not yet available as the study is ongoing (recruitment started March 2026)
- ▸Relies on smartphone-based passive data collection, which may have measurement errors or compliance issues
- ▸Platform exclusivity (iOS only initially; Android planned for 2027) may limit generalizability
Frequently Asked Questions
What is the primary outcome of the My Heart Counts trial?▼
The primary outcome is the change in daily step count between LLM-driven and generic text-based coaching prompts.
How many participants are being recruited?▼
The target enrollment is 15,000 adults across the United States and United Kingdom.
What technology is used to generate the coaching prompts?▼
The coaching prompts are generated by a large language model (LLM) grounded in the Transtheoretical Model of Change.
When did recruitment for this study begin?▼
Recruitment commenced in March 2026 and is ongoing.
References
- 1.Schmiedmayer P, Johnson A, Schuetz N, Kollmer L, Goldschmidt P, Delgado-SanMartin J, Zhang KW, Mantena SD, Tolas A, Montalvo S, Ramirez-Posada M, O'Sullivan JW, Oppezzo M, King AC, Rodriguez F, Ashley E, Lawrie A, Kim DS. “Design and rationale of the my heart counts cardiovascular health study: a large-scale, fully digital biobank, and randomized trial of large language model-driven coaching of physical activity..” American journal of preventive cardiology, 2026. PMID: 42395096 DOI: 10.1016/j.ajpc.2026.101565