2025-11-04 ニューヨーク大学(NYU)
<関連情報>
- https://www.nyu.edu/about/news-publications/news/2025/november/-can-a-fitbit-help-detect-and-treat-ptsd-in-veterans-.html
- https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0332239
退役軍人のPTSDと大麻使用に関する遠隔測定研究:募集、維持、データの入手可能性 A remote measurement study of PTSD and cannabis use among veterans: Recruitment, retention, and data availability
Daniel Leightley,Bistra Dilkina,Eric R. Pedersen,Emily Dworkin,Shaddy Saba,Esther Howe,Praneeth Thota,Sriram Nuthi,Angeles Sedano,Jordan P. Davis
PLOS One Published: September 29, 2025
DOI:https://doi.org/10.1371/journal.pone.0332239
Abstract
With the growing availability of cannabis and increasing public support for legalization, cannabis use disorder (CUD) rates have risen, particularly among veterans, who face disproportionately high rates of co-occurring posttraumatic stress disorder (PTSD) and CUD. Veterans often use cannabis to manage PTSD symptoms, yet research suggests cannabis may exacerbate and maintain these symptoms. Predicting symptom escalation remains challenging due to the complexity of PTSD-CUD interactions and a lack of predictive tools. Advances in mobile and wearable technology provide new opportunities for real-time monitoring, integrating active (self-reported) and passive (sensor-based) data to improve symptom prediction and intervention timing. This longitudinal study examined the feasibility of collecting data among recently discharged veterans with PTSD and cannabis use. The study employed the MAVERICK mobile app, integrating passive data (e.g., heart rate, sleep, activity) and active data (e.g., self-report surveys) over three months. Phase 1 involved beta testing with 20 veterans, assessing feasibility and acceptability, while Phase 2 recruited 75 veterans to evaluate recruitment, retention, and data completeness. Findings indicate high feasibility, with 91.9% of participants providing passive data and a 68% response rate for daily self-report measures. However, data availability varied across measures. These results highlight the potential for integrating passive and active data to improve symptom prediction and early intervention efforts for PTSD and CUD in veterans. Future research should explore long-term engagement strategies and clinical applications of these digital tools to enhance veteran mental health care.
