Responsiveness to mHealth Intervention for Cannabis Use in Young Adults Predicts Improved Outcomes.
Responsiveness to mHealth Intervention for Cannabis Use in Young Adults Predicts Improved Outcomes.
复制标题
年轻人对大麻使用的移动健康干预措施的反应预示着结果的改善。
DOI：
10.1007/s11121-022-01333-z
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Berkel,Cady
中科院分区：
文献类型：
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作者：
Zaharakis,NikolaM;Mason,MichaelJ;Berkel,Cady
移动医疗（mHealth）干预措施迅速普及，部分原因是它们在减轻消费者和提供者负担方面具有优势，但人们对参与者对移动医疗计划的反应以及这可能如何影响结果的关注较少。这项研究通过检查参与者对短信提供的干预措施的反应是否可以预测超过基线结果水平的治疗结果，对文献进行了补充。我们分析了一项短信干预试验的数据，该试验用于治疗患有大麻使用障碍的年轻人（治疗组，N = 47），检查了在 3 个月的随访中测量的大麻使用戒断和使用相关问题的三项反应性指标（两项行为：治疗完成和加强信息参与；一项主观：治疗的感知帮助）。除完成情况外，各项指标均呈正相关。每个指标都可以预测高于或超出基线风险的更好治疗结果。治疗完成和加强参与（通过干预管理期间捕获的技术数据来衡量）似乎比自我报告的感知帮助更能预测结果的改善。结果表明，行为和主观反应测量似乎是对物质使用移动健康干预措施的治疗反应的有效指标。通过干预管理期间捕获的技术数据来衡量响应能力可能是监测持续参与的更强大、更有效的策略。我们讨论这些发现对于大规模部署移动医疗干预措施和监测响应能力的影响。
Mobile health (mHealth) interventions have proliferated rapidly in part because of their advantages in reducing consumer and provider burden, but less attention has been paid to participant responsiveness to mHealth programs and how this may affect outcomes. This study adds to that literature by examining whether participant responsiveness to a text messaging-delivered intervention was predictive of treatment outcomes over baseline levels of the outcome. We analyzed data from a pilot-randomized controlled trial of a text messaging-intervention to treat young adults with cannabis use disorder (treatment arm, N = 47), examining three indicators of responsiveness (two behavioral: treatment completion and booster message participation; and one subjective: perceived helpfulness of treatment) on abstinence from cannabis use and use-related problems measured at 3-month follow-up. With the exception of completion, the indicators were positively correlated with each other. Each of the indicators was predictive of better treatment outcomes above and beyond baseline risk. Treatment completion and booster participation—measured via technical data captured during intervention administration—appeared to be stronger predictors of improved outcomes than self-reported perceived helpfulness. Results suggest that behavioral and subjective responsiveness measures appear to be valid indicators of treatment response to mHealth interventions for substance use. Responsiveness measured via technical data captured during intervention administration may be a stronger and more efficient strategy for monitoring continued engagement. We discuss implications of these findings for deploying mHealth interventions at scale and monitoring responsiveness.