A Community Mental Health Integrated Disaster Preparedness Intervention for Bushfire Recovery in Rural Australian Communities: Protocol for a Multimethods Feasibility and Acceptability Pilot Study
Notice bibliographique
Résumé
BACKGROUND: Natural hazards are increasing in frequency and intensity due to climate change. Many of these natural disasters cannot be prevented; what may be reduced is the extent of the risk and negative impact on people and property. Research indicates that the 2019-2020 bushfires in Australia (also known as the "Black Summer Bushfires") resulted in significant psychological distress among Australians both directly and indirectly exposed to the fires. Previous intervention research suggests that communities impacted by natural hazards (eg, earthquakes, hurricanes, and floods) can benefit from interventions that integrate mental health and social support components within disaster preparedness frameworks. Research suggests that disaster-affected communities often prefer the support of community leaders, local services, and preexisting relationships over external supports, highlighting that community-based interventions, where knowledge stays within the local community, are highly beneficial. The Community-Based Disaster Mental Health Intervention (CBDMHI) is an evidence-based approach that aims to increase disaster preparedness, resilience, social cohesion, and social support (disaster-related help-seeking), and decrease mental health symptoms, such as depression and anxiety. OBJECTIVE: This research aims to gain insight into rural Australian's recovery needs post natural hazards, and to enhance community resilience in advance of future fires. Specifically, this research aims to adapt the CBDMHI for the rural Australian context and for bushfires and second, to assess the acceptability and feasibility of the adapted CBDMHI in a rural Australian community. METHODS: Phase 1 consists of qualitative interviews (individual or dyads) with members of the target bushfire-affected rural community. Analysis of these data will include identifying themes related to disaster preparedness, social cohesion, and mental health, which will inform the adaptation. An initial consultation phase is a key component of the adaptation process and, therefore, phase 2 will involve additional discussion with key stakeholders and members of the community to further guide adaptation of the CBDMHI to specific community needs, building on phase 1 inputs. Phase 3 includes identifying and training local community leaders in the adapted intervention. Following this, leaders will co-deliver the intervention. The acceptability and feasibility of the adapted CBDMHI within the community will be evaluated by questionnaires and semistructured interviews. Effectiveness will be evaluated by quantifying psychological distress, resilience, community cohesion, psychological preparedness, and help-seeking intentions. RESULTS: This study has received institutional review board approval and commenced phase 1 recruitment in October 2022. CONCLUSIONS: The study will identify if the adapted CBDMHI is viable and acceptable within a village in the Northern Tablelands of New South Wales, Australia. These findings will inform future scale-up in the broader rural Australian context. If this intervention is well received, the CBDMHI may be valuable for future disaster recovery and preparedness efforts in rural Australia. These findings may inform future scale-up in the broader rural Australian context. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/53454.
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Prédiction machine sur la base complète
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,036 | 0,021 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,004 |
| Méta-épidémiologie (sens large) | 0,005 | 0,004 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,008 | 0,003 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,004 | 0,005 |
| Intégrité de la recherche | 0,005 | 0,010 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,064 | 0,009 |
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
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