A Blended Learning Course on the Diagnostics of Mental Disorders: Multicenter Cluster Randomized Noninferiority Trial.

IF 5.8 2区医学 Q1 HEALTH CARE SCIENCES & SERVICES Journal of Medical Internet Research Pub Date : 2024-11-27 DOI:10.2196/54176

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

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Abstract

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.

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精神障碍诊断混合学习课程：多中心群组随机非劣效性试验》。

背景：临床诊断决定了治疗师是否以及如何治疗患者。由于误诊可能造成严重的不良影响，因此在临床实践中推广循证诊断技能非常重要：本研究旨在通过多中心群组随机对照试验开发和评估混合式学习课程：方法：心理学本科生（N=350）选修了 3 所大学的 18 门大学课程。这些课程被随机分配到混合式学习或传统同步教学中。主要结果是学员在课程结束后的临床诊断访谈中的表现。次要结果是诊断知识和学员对课程的反应。所有结果均采用非劣效性检验对学员个人进行分析：结果：与同步课程（通过率为 74.6%）相比，参加混合式学习课程（通过率为 89%）增加了成功通过行为测试的可能性（几率比 2.77，95% CI 1.55-5.13），这表明混合式学习课程不仅不具劣势，而且更具优势。此外，混合式学习在诊断知识（β=.13，95% CI 0.01-0.26）、课程清晰度（β=.40，95% CI 0.27-0.53）、课程结构（β=.18，95% CI 0.04-0.32）和信息量（β=.19，95% CI 0.06-0.32）方面均优于同步课程：混合式学习有助于提高（未来）临床医生的诊断技能和知识，从而为改善精神卫生保健做出重要贡献：试验注册：ClinicalTrials.gov NCT05294094；https://clinicaltrials.gov/study/NCT05294094。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Medical Internet Research 医学-卫生保健

CiteScore

14.40

自引率

5.40%

发文量

654

审稿时长

1 months

期刊介绍： The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades. As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor. Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.