Patients prefer easy adverse event reporting: Observational study within clinical trial
Background Digital intervention safety is crucial for regulatory approval and clinical adoption. However, the evaluation and reporting of adverse events (AEs) in clinical trials are often insufficient. Digital qualitative self-reporting could enhance the detection of AEs, but patient preferences for...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2025-05-01
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| Series: | Digital Health |
| Online Access: | https://doi.org/10.1177/20552076251345894 |
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| Summary: | Background Digital intervention safety is crucial for regulatory approval and clinical adoption. However, the evaluation and reporting of adverse events (AEs) in clinical trials are often insufficient. Digital qualitative self-reporting could enhance the detection of AEs, but patient preferences for using such channels remain understudied. Methods This observational study was conducted in Finland between 2022 and 2024 within a randomized controlled trial evaluating the efficacy of Meliora , a game-based digital intervention for patients living with major depressive disorder. We assessed the preferences of 1001 patients for self-reporting AEs across four channels: a prompted, within-intervention questionnaire (CORTO: Contextual, One-item, Repeated, Timely, Open-ended), a Jira questionnaire, email, and phone. Results 148 (14.8%) patients reported AEs during the study. We found a significant imbalance between the channels: 11.3% ( n = 113) of patients reported AEs using CORTO, 4.1% ( n = 41) using email, 1.1% ( n = 11) using Jira, and 0.4% ( n = 4) using phone. Conclusions These findings reveal that patients prefer low-effort methods for reporting AEs and are more likely to report AEs via a prompted, within-intervention questionnaire (CORTO) than through other methods. Integrating qualitative self-report channels into digital interventions may enhance AE detection rates, improve clinical trial safety monitoring, and support post-market surveillance. |
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| ISSN: | 2055-2076 |