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.
Schizophr Bull
; 2024 Apr 29.
Article
em En
| MEDLINE
| ID: mdl-38683836
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 (nâ =â 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.
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Base de dados:
MEDLINE
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En
Ano de publicação:
2024
Tipo de documento:
Article