数字健康干预精神分裂症研究中不良事件的测量:基于文献检索和标准操作程序框架分析的指导和建议。

Measurement of Adverse Events in Studies of Digital Health Interventions for Psychosis: Guidance and Recommendations Based on a Literature Search and Framework Analysis of Standard Operating Procedures.

机构信息

Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Sciences Centre, The University of Manchester, Manchester, UK.

Research and Innovation, Greater Manchester Mental Health NHS Foundation Trust, Manchester, UK.

出版信息

Schizophr Bull. 2024 Nov 8;50(6):1456-1470. doi: 10.1093/schbul/sbae048.

Abstract

BACKGROUND

Given the rapid expansion of research into digital health interventions (DHIs) for severe mental illness (SMI; eg, schizophrenia and other psychosis diagnoses), there is an emergent need for clear safety measures. Currently, measurement and reporting of adverse events (AEs) are inconsistent across studies. Therefore, an international network, iCharts, was assembled to systematically identify and refine a set of standard operating procedures (SOPs) for AE reporting in DHI studies for SMI.

DESIGN

The iCharts network comprised experts on DHIs for SMI from seven countries (United Kingdom, Belgium, Germany, Pakistan, Australia, United States, and China) and various professional backgrounds. Following a literature search, SOPs of AEs were obtained from authors of relevant studies, and from grey literature.

RESULTS

A thorough framework analysis of SOPs (n = 32) identified commonalities for best practice for certain domains, along with significant gaps in others; particularly around the classification of AEs during trials, and the provision of training/supervision for research staff in measuring and reporting AEs. Several areas which could lead to the observed inconsistencies in AE reporting and handling were also identified.

CONCLUSIONS

The iCharts network developed best-practice guidelines and a practical resource for AE monitoring in DHI studies for psychosis, based on a systematic process which identified common features and evidence gaps. This work contributes to international efforts to standardize AE measurement and reporting in this emerging field, ensuring that safety aspects of DHIs for SMI are well-studied across the translational pathway, with monitoring systems set-up from the outset to support safe implementation in healthcare systems.

摘要

背景

鉴于数字健康干预措施(DHIs)在严重精神疾病(SMI;例如,精神分裂症和其他精神病诊断)方面的研究迅速扩展,因此迫切需要明确的安全措施。目前,研究之间对不良事件(AEs)的测量和报告不一致。因此,成立了一个国际网络 iCharts,以系统地识别和完善一套用于 SMI 的 DHI 研究中 AE 报告的标准操作程序(SOPs)。

设计

iCharts 网络由来自七个国家(英国、比利时、德国、巴基斯坦、澳大利亚、美国和中国)和各种专业背景的 SMI 的 DHIs 专家组成。在进行文献检索后,从相关研究的作者和灰色文献中获得了 AE 的 SOPs。

结果

对 SOPs(n=32)进行彻底的框架分析,确定了某些领域的最佳实践共同点,以及其他领域的明显差距;特别是在试验期间 AE 的分类以及为研究人员提供测量和报告 AE 的培训/监督方面。还确定了可能导致 AE 报告和处理不一致的几个方面。

结论

iCharts 网络根据系统的过程制定了最佳实践指南和精神病 DHI 研究中 AE 监测的实用资源,该过程确定了共同特征和证据差距。这项工作为标准化该新兴领域的 AE 测量和报告做出了贡献,确保了 SMI 的 DHIs 的安全方面在整个转化途径中得到充分研究,并建立了监测系统,从一开始就支持在医疗保健系统中的安全实施。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/511b/11548926/f96bbd631c20/sbae048_fig1.jpg

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