Background: Clinical diagnoses determine if and how therapists treat their patients. As misdiagnoses can have severe adverse effects, disseminating evidence-based diagnostic skills into clinical practice is highly important.
Objective: This study aimed to develop and evaluate a blended learning course in a multicenter cluster randomized controlled trial.
Methods: Undergraduate psychology students (N=350) enrolled in 18 university courses at 3 universities. The courses were randomly assigned to blended learning or traditional synchronous teaching. The primary outcome was the participants' performances in a clinical diagnostic interview after the courses. The secondary outcomes were diagnostic knowledge and participants' reactions to the courses. All outcomes were analyzed on the individual participant level using noninferiority testing.
Results: Compared with the synchronous course (74.6% pass rate), participation in the blended learning course (89% pass rate) increased the likelihood of successfully passing the behavioral test (odds ratio 2.77, 95% CI 1.55-5.13), indicating not only noninferiority but superiority of the blended learning course. Furthermore, superiority of the blended learning over the synchronous course could be found regarding diagnostic knowledge (β=.13, 95% CI 0.01-0.26), course clarity (β=.40, 95% CI 0.27-0.53), course structure (β=.18, 95% CI 0.04-0.32), and informativeness (β=.19, 95% CI 0.06-0.32).
Conclusions: Blended learning can help to improve the diagnostic skills and knowledge of (future) clinicians and thus make an important contribution to improving mental health care.
Trial registration: ClinicalTrials.gov NCT05294094; https://clinicaltrials.gov/study/NCT05294094.
Keywords: blended learning; clinical diagnosis; clinical interview; clinical practice; diagnosis; diagnostic test; dissemination; health personnel; mental health; mental health services; psychology students; structured clinical interviews; therapist training.
©Gabriel Bonnin, Svea Kröber, Silvia Schneider, Jürgen Margraf, Verena Pflug, Alexander L Gerlach, Timo Slotta, Hanna Christiansen, Björn Albrecht, Mira-Lynn Chavanon, Gerrit Hirschfeld, Tina In-Albon, Meinald T Thielsch, Ruth von Brachel. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 27.11.2024.