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Adverse Events Reporting in Digital Interventions Evaluations for Psychosis: A Systematic Literature Search and Individual Level Content Analysis of Adverse Event Reports
Schizophrenia Bulletin ( IF 6.6 ) Pub Date : 2024-04-06 , DOI: 10.1093/schbul/sbae031
Stephanie Allan 1 , Thomas Ward 2, 3 , Emily Eisner 4 , Imogen H Bell 5, 6 , Matteo Cella 2, 3 , Imran B Chaudhry 4, 7, 8 , John Torous 9 , Tayyeba Kiran 6 , Thomas Kabir 10 , Aansha Priyam 4 , Cara Richardson 4 , Ulrich Reininghaus 2, 11 , Anita Schick 10, 11 , Matthias Schwannauer 12 , Suzy Syrett 1 , Xiaolong Zhang 4 , Sandra Bucci 4, 13
Affiliation  

Background Digital health interventions (DHIs) have significant potential to upscale treatment access to people experiencing psychosis but raise questions around patient safety. Adverse event (AE) monitoring is used to identify, record, and manage safety issues in clinical trials, but little is known about the specific content and context contained within extant AE reports. This study aimed to assess current AE reporting in DHIs. Study Design A systematic literature search was conducted by the iCharts network (representing academic, clinical, and experts by experience) to identify trials of DHIs in psychosis. Authors were invited to share AE reports recorded in their trials. A content analysis was conducted on the shared reports. Study Results We identified 593 AE reports from 18 DHI evaluations, yielding 19 codes. Only 29 AEs (4.9% of total) were preidentified by those who shared AEs as being related to the intervention or trial procedures. While overall results support the safety of DHIs, DHIs were linked to mood problems and psychosis exacerbation in a few cases. Additionally, 27% of studies did not report information on relatedness for all or at least some AEs; 9.6% of AE reports were coded as unclear because it could not be determined what had happened to participants. Conclusions The results support the safety of DHIs, but AEs must be routinely monitored and evaluated according to best practice. Individual-level analyses of AEs have merit to understand safety in this emerging field. Recommendations for best practice reporting in future studies are provided.

中文翻译:

精神病数字干预评估中的不良事件报告:不良事件报告的系统文献检索和个体层面内容分析

背景数字健康干预措施 (DHI) 具有扩大精神病患者治疗机会的巨大潜力,但也引发了患者安全方面的问题。不良事件 (AE) 监测用于识别、记录和管理临床试验中的安全问题,但人们对现有 AE 报告中包含的具体内容和背景知之甚少。本研究旨在评估 DHI 中当前的 AE 报告。研究设计 iCharts 网络(代表学术、临床和经验专家)进行了系统的文献检索,以确定 DHI 治疗精神病的试验。作者受邀分享试验中记录的 AE 报告。对共享报告进行了内容分析。研究结果 我们从 18 项 DHI 评估中识别出 593 份 AE 报告,产生 19 个代码。只有 29 种 AE(占总数的 4.9%)被共享 AE 的人预先识别为与干预或试验程序相关。虽然总体结果支持 DHI 的安全性,但在少数情况下,DHI 与情绪问题和精神病恶化有关。此外,27% 的研究没有报告所有或至少部分 AE 的相关性信息; 9.6% 的 AE 报告被编码为不清楚,因为无法确定参与者发生了什么。结论 结果支持 DHI 的安全性,但必须根据最佳实践对 AE 进行常规监测和评估。对不良事件进行个体层面的分析有助于了解这一新兴领域的安全性。提供了未来研究中最佳实践报告的建议。
更新日期:2024-04-06
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