Digital mental health literacy -program for the first-year medical students’ wellbeing: a one group quasi-experimental study
Notice bibliographique
Résumé
BACKGROUND: Medical students are prone to mental disorders, such as depression and anxiety, and their psychological burden is mainly related to their highly demanding studies. Interventions are needed to improve medical students' mental health literacy (MHL) and wellbeing. This study assessed the digital Transitions, a MHL program for medical students that covered blended life skills and mindfulness activities. METHODOLOGY: This was a one group, quasi-experimental pretest-posttest study. The study population was 374 first-year students who started attending the medical faculty at the University of Turku, Finland, in 2018-2019. Transitions was provided as an elective course and 220 students chose to attend and 182 agreed to participate in our research. Transitions included two 60-minute lectures, four weeks apart, with online self-learning material in between. The content focused on life and academic skills, stress management, positive mental health, mental health problems and disorders. It included mindfulness audiotapes. Mental health knowledge, stigma and help-seeking questionnaires were used to measure MHL. The Perceived Stress Scale and General Health Questionnaire measured the students' stress and health, respectively. A single group design, with repeated measurements of analysis of variance, was used to analyze the differences in the mean outcome scores for the 158 students who completed all three stages: the pre-test (before the first lecture), the post-test (after the second lecture) and the two-month follow-up evaluation. RESULTS: The students' mean scores for mental health knowledge improved (-1.6, 95% Cl -1.9 to -1.3, P<.001) and their emotional symptoms were alleviated immediately after the program (0.5, 95% Cl 0.0 to 1.1, P=.040). The changes were maintained at the two-month follow up (-1.7, 95% Cl -2.0 to -1.4, P<.001 and 1.0, 95% Cl 0.2 to 1.8, P=.019, respectively). The students' stress levels reduced (P=.022) and their attitudes towards help-seeking improved after the program (P<.001), but these changes were not maintained at the two-month follow up. The stigma of mental illness did not change during the study (P=.13). CONCLUSIONS: The digital Transitions program was easily integrated into the university curriculum and it improved the students' mental health literacy and wellbeing. The program may respond to the increasing global need for universal digital services, especially during the lockdowns due to the COVID-19 pandemic. TRIAL REGISTRATION: The trial was registered at the ISRCTN registry (26 May 2021), registration number 10.1186/ ISRCTN10565335 ).
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».