Navigating the shadows: the impact of mindfulness, cognitive fusion, and coping strategies on psychological distress among mental health workers in Timor Leste
Notice bibliographique
Résumé
BACKGROUND: Mental health workers in post-conflict settings such as Timor Leste face distinct stressors stemming from limited human resources, underdeveloped systems, and ongoing socio-political instability, all of which increase the risk of psychological distress among these professionals. Consequently, constructs such as mindfulness, cognitive fusion, and coping strategies are essential not only theoretically significant, but also serve as practical targets for strengthening mental resilience of these professionals in these high-burden environments. This study aims to investigate the relationships between mindfulness, cognitive fusion, coping strategies, and psychological distress (depression, anxiety, and stress) among mental health workers in Timor Leste. METHODS: A cross-sectional study design was employed, involving a convenience sample of 37 mental health workers from PRADET and the national referral hospital in Dili. Mindfulness was assessed using the Toronto Mindfulness Questionnaire (TMQ), psychological flexibility using the Acceptance and Action Questionnaire (AAQ-II), cognitive fusion was measured using the Cognitive Fusion Questionnaire (CFQ), and coping strategies were evaluated using the DBT-Ways of Coping Checklist (DBT-WCCL). Depression, anxiety, and stress were measured using the Depression Anxiety Stress Scales (DASS-21). All scales were using English validated versions. Descriptive statistics, Pearson correlation coefficients, and multiple regression analyses were used to analyze the data. RESULTS: Significant positive correlations were found between Depression and Anxiety (Spearman's rho = 0.649, p < 0.001), and between Depression and Stress (Spearman's rho = 0.753, p < 0.001). Depression was also significantly correlated with Cognitive Fusion (Spearman's rho = 0.445, p = 0.006) and Blaming Others (Spearman's rho = 0.422, p = 0.009), and negatively correlated with Coping Strategies (Skills Use) (Spearman's rho =- 0.341, p = 0.039). Anxiety and Stress were highly correlated (Spearman's rho = 0.855, p < 0.001), and both were significantly associated with Cognitive Fusion, General Dysfunctional Coping, and Blaming Others. Mindfulness (De-Centering) showed a strong positive correlation with Mindfulness (Curiosity) (Spearman's rho = 0.770, p < 0.001), and was also weakly associated with General Dysfunctional Coping (Spearman's rho = 0.343, p = 0.038). Overall, the results suggest that higher levels of depression, anxiety, and stress are linked to greater cognitive fusion and dysfunctional coping, while effective coping skills are negatively associated with depression. CONCLUSION: The findings highlight the critical roles of cognitive fusion and coping strategies in predicting psychological distress among mental health workers in Timor Leste. Cognitive fusion and dysfunctional coping strategies were associated with higher levels of depression, anxiety, and stress. Adaptive coping strategies, such as skills use, were linked to lower levels of depression. Given the high risk of vicarious trauma, compassion fatigue, and secondary traumatic stress disorder in this population, targeted interventions promoting mindfulness and adaptive coping skills are essential. Addressing these factors can enhance resilience and well-being among mental health professionals, ultimately improving the quality of care provided to their clients.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».