RESUMEN
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.
RESUMEN
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.