Social determinants of student mental health before and after the Beirut port explosion: two cross-sectional studies
Notice bibliographique
Résumé
BACKGROUND: Students in Lebanon are facing the devastating impact of multiple national crises, including an unprecedented economic collapse and the Beirut port explosion that killed hundreds, injured thousands, and displaced hundreds of thousands of people. The aim of this study was to identify key social determinants of common mental health symptoms before and after the Beirut port explosion for students at the American University of Beirut, a university based around 4 km from the port. METHODS: Two cross-sectional studies were conducted using a representative sample of undergraduate and graduate students at the American University of Beirut. The study was conducted just before (Study 1) and repeated after the Beirut port explosion (Study 2). RESULTS: A total of 217 students participated (n = 143 in Study 1 and n = 74 in Study 2). In Study 1 before the explosion, poorer family functioning and social support were correlated with higher levels of depressive symptoms, but not with anxiety or trauma symptoms. Financial stress was correlated with depressive and trauma symptoms. In the partially adjusted regression model (adjusting for demographics), only financial stress was significantly associated with depressive symptoms. In the fully adjusted model (adjusting for adversity), financial stress was associated with depressive and anxiety symptoms. In Study 2 after the explosion, poorer family functioning and poorer social support were correlated with higher levels of depressive symptoms, while only poorer social support was correlated with higher levels of anxiety symptoms-trauma symptoms were not correlated with either. Financial stress was correlated with all symptoms. In the partially adjusted regression model, only financial stress was significantly associated with all symptom clusters. In the fully adjusted model, no variables were significant. CONCLUSION: Findings indicate a detrimental impact of financial stress on the mental health of students in Lebanon, beyond the otherwise protective effects of family and social support, in the context of an unprecedented economic crisis and extremely high levels of distress after the explosion. Findings indicate that mental health interventions for college students in Lebanon should include addressing financial stress, and that further research is needed to identify protective factors during acute emergencies.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».