[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100583745":3},{"organization":4,"armGroups":7,"interventions":18,"overallOfficials":11,"centralContacts":11,"locations":11,"responsibleParty":24,"collaborators":11,"id":28,"slug":29,"hasResults":30,"nctId":31,"briefTitle":32,"officialTitle":33,"acronym":11,"eligibilityCriteria":34,"healthyVolunteers":35,"sex":36,"minAge":37,"maxAge":11,"enrollmentInfo":38,"targetDuration":11,"studyType":41,"phases":42,"briefSummary":44,"conditions":45,"keywords":11,"overallStatus":47,"whyStopped":11,"lastUpdateSubmitDate":48,"lastUpdatePostDateStruct":49,"startDateStruct":52,"completionDateStruct":54,"leadSponsor":56,"locationsCount":11},{"fullName":5,"class":6},"Stanford University","OTHER",[8,14],{"label":9,"type":10,"description":11,"interventionNames":12},"Personalized LLM-Generated Coaching Prompts","EXPERIMENTAL",null,[13],"Behavioral: Pre-Generated Personalized LLM Coaching Impact",{"label":15,"type":16,"description":11,"interventionNames":17},"Generic Activity Prompts","ACTIVE_COMPARATOR",[13],[19],{"type":20,"name":21,"description":22,"armGroupLabels":23,"otherNames":11},"BEHAVIORAL","Pre-Generated Personalized LLM Coaching Impact","After the initial 7 days, participants will switch to the other type of prompting for another 7 days. This means that participants who initially received personalized LLM-generated prompts will then receive generic activity prompts, and vice versa. This crossover design allows for each participant to experience both types of interventions, providing a within-subject comparison of the effectiveness of personalized versus generic prompts in increasing physical activity levels.",[15,9],{"type":25,"investigatorFullName":26,"investigatorTitle":27,"investigatorAffiliation":5,"oldNameTitle":11,"oldOrganization":11},"PRINCIPAL_INVESTIGATOR","Euan Ashley","Fellow, Cardiovascular Medicine","100583745","llm-generated-coaching-prompts-100583745",false,"NCT06880315","LLM-Generated Coaching Prompts","Enhancing Physical Activity With LLM-Generated Coaching Prompts: A My Heart Counts Study","Inclusion Criteria:\n\n* Age: Participants must be 18 years or older.\n* Health Status: Participants must be healthy enough to engage in physical activity.\n* Language Proficiency: Participants must be able to read, understand, and consent in English or Spanish (dependent on which is being studied).\n* Device Ownership: Participants must possess an iPhone and an Apple Watch.\n* Data Sharing: Participants must be willing to share their HealthKit data via secure upload.\n\nExclusion Criteria:\n\n* Age: Participants under the age of 18.\n* Health Status: Participants who are not healthy enough to engage in physical activity.\n* Language Proficiency: Participants who cannot read, understand, or consent in English or Spanish.\n* Device Ownership: Participants who do not have both an iPhone and an Apple Watch.\n* Data Sharing: Participants unwilling to share their HealthKit data via secure upload.",true,"ALL","18 Years",{"count":39,"type":40},50,"ESTIMATED","INTERVENTIONAL",[43],"NA","This pilot study aims to evaluate whether personalized coaching prompts generated by a large language model (LLM) can effectively increase physical activity levels among participants. The study will involve 50 participants who will receive daily text messages, either personalized by the LLM or generic, over a 14-day period. Participants will share their HealthKit data for analysis. The findings will inform the development of future versions of the My Heart Counts application, enhancing user engagement and health outcomes.",[46],"Exercise","NOT_YET_RECRUITING","2026-07-21",{"date":50,"type":51},"2026-07-23","ACTUAL",{"date":53,"type":40},"2027-01-20",{"date":55,"type":40},"2027-12-01",{"name":5,"class":6}]