ArticleJMIR mental health2022
Diagnostic Performance of an App-Based Symptom Checker in Mental Disorders: Comparative Study in Psychotherapy Outpatients.
Article in JMIR mental health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Impact of a Symptom Checker App on Patient-Physician Interaction Among Self-Referred Walk-In Patients in the Emergency Department: Multicenter, Parallel-Group, Randomized, Controlled Trial.Journal of medical Internet research · 2025Trial
- Accuracy of online symptom assessment applications, large language models, and laypeople for self-triage decisions.NPJ digital medicine · 2025Article
- The Doctors, Their Patients, and the Symptom Checker App: Qualitative Interview Study With General Practitioners in Germany.JMIR human factors · 2024Article
- Transforming Health Care Through Chatbots for Medical History-Taking and Future Directions: Comprehensive Systematic Review.JMIR medical informatics · 2024Review
- Evaluation of AI-Driven LabTest Checker for Diagnostic Accuracy and Safety: Prospective Cohort Study.JMIR medical informatics · 2024Article
- Article
- Acceptance of smart sensing, its determinants, and the efficacy of an acceptance-facilitating intervention in people with diabetes: results from a randomized controlled trial.Frontiers in digital health · 2024Article
- Diagnostic Performance, Triage Safety, and Usability of a Clinical Decision Support System Within a University Hospital Emergency Department: Algorithm Performance and Usability Study.JMIR medical informatics · 2023Article
- Telepsychiatry in an Era of Digital Mental Health Startups.Current psychiatry reports · 2023Review
- A review of the explainability and safety of conversational agents for mental health to identify avenues for improvement.Frontiers in artificial intelligence · 2023Review
- Acceptance of smart sensing: a barrier to implementation-results from a randomized controlled trial.Frontiers in digital health · 2023Article
- Online Symptom Checkers: Recommendations for a Vignette-Based Clinical Evaluation Standard.Journal of medical Internet research · 2022Article
- Evaluation of Diagnostic and Triage Accuracy and Usability of a Symptom Checker in an Emergency Department: Observational Study.JMIR mHealth and uHealth · 2022Observational
- Adapting and Implementing Apps for Mental Healthcare.Current psychiatry reports · 2022Review
- Triage Accuracy of Symptom Checker Apps: 5-Year Follow-up Evaluation.Journal of medical Internet research · 2022Article
- Article
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4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundDigital technologies have become a common starting point for health-related information-seeking. Web- or app-based symptom checkers aim to provide rapid and accurate condition suggestions and triage advice but have not yet been investigated for mental disorders in routine health care settings.
objectiveThis study aims to test the diagnostic performance of a widely available symptom checker in the context of formal diagnosis of mental disorders when compared with therapists' diagnoses based on structured clinical interviews.
methodsAdult patients from an outpatient psychotherapy clinic used the app-based symptom checker Ada-check your health (ADA; Ada Health GmbH) at intake. Accuracy was assessed as the agreement of the first and 1 of the first 5 condition suggestions of ADA with at least one of the interview-based therapist diagnoses. In addition, sensitivity, specificity, and interrater reliabilities (Gwet first-order agreement coefficient [AC1]) were calculated for the 3 most prevalent disorder categories. Self-reported usability (assessed using the System Usability Scale) and acceptance of ADA (assessed using an adapted feedback questionnaire) were evaluated.
resultsA total of 49 patients (30/49, 61% women; mean age 33.41, SD 12.79 years) were included in this study. Across all patients, the interview-based diagnoses matched ADA's first condition suggestion in 51% (25/49; 95% CI 37.5-64.4) of cases and 1 of the first 5 condition suggestions in 69% (34/49; 95% CI 55.4-80.6) of cases. Within the main disorder categories, the accuracy of ADA's first condition suggestion was 0.82 for somatoform and associated disorders, 0.65 for affective disorders, and 0.53 for anxiety disorders. Interrater reliabilities ranged from low (AC1=0.15 for anxiety disorders) to good (AC1=0.76 for somatoform and associated disorders). The usability of ADA was rated as high in the System Usability Scale (mean 81.51, SD 11.82, score range 0-100). Approximately 71% (35/49) of participants would have preferred a face-to-face over an app-based diagnostic.
conclusionsOverall, our findings suggest that a widely available symptom checker used in the formal diagnosis of mental disorders could provide clinicians with a list of condition suggestions with moderate-to-good accuracy. However, diagnostic performance was heterogeneous between disorder categories and included low interrater reliability. Although symptom checkers have some potential to complement the diagnostic process as a screening tool, the diagnostic performance should be tested in larger samples and in comparison with further diagnostic instruments.
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