Effectiveness, facilitators and barriers of digital mental health services for First Nations Peoples in Australia: A systematic review (Preprint)
Notice bibliographique
Résumé
BACKGROUND First Nations peoples in Australia experience inequitable mental health outcomes and service access due to colonisation and intergenerational trauma. Geographical remoteness and limited access to culturally safe services. Digital mental health (DMH) services, which refer to offering mental health services through digital platforms, are considered potential solutions to address inequitable mental health service access faced by First Nations Australians and improve their mental health outcome. However, evidence on the effectiveness of DMH for First Nations Peoples in Australia is yet to be synthesised. This systematic review aimed to assess the effectiveness of DMH services in improving mental health outcomes for First Nations Peoples in Australia and to identify the facilitators and barriers that influence the implementation of DMH services in this context. A systematic search was conducted across six academic databases to search for studies related to DMH services for First Nations Peoples in Australia. Search terms relating to First Nations Peoples, geographic terminologies of Australia, mental health, and digital mental health services were used. Studies were included if they assessed the effectiveness of digital mental health interventions among First Nations people in Australia. Data were extracted based on study design, targeted services, and research findings, then synthesised using a thematic analysis framework. In total, 22 studies met the inclusion criteria. The included studies used a variety of study designs and researched multiple DMH services designed to provide support, treatment, and psychological assessments. A general effectiveness for non-severe mental health conditions was observed. Several determinants of facilitators and barriers of the implementation of DMH services were identified, including: 1. Organisational and administrative factors; 2. Cultural appropriateness; 3. Accessibility; 4. Integration of DMH services to the existing situation; 5. Engagement between clients and service providers; 6. Coverage of different conditions and clients; 7. Acceptability to DMH services; 8. Digital literacy, and 9. Efficiency. Given the effectiveness in providing services to most mental health conditions, DMH services have the potential to address the mental health needs of First Nations Peoples in Australia. However, the decision-making at multiple layers, as well as the design and implementation of DMH, should consider the determinants identified by this review. OBJECTIVE This systematic review aimed to assess the effectiveness of DMH services in improving mental health outcomes for First Nations Peoples in Australia and to identify the facilitators and barriers that influence the implementation of DMH services in this context. METHODS A systematic search was conducted across six academic databases to search for studies related to DMH services for First Nations Peoples in Australia. Search terms relating to First Nations Peoples, geographic terminologies of Australia, mental health, and digital mental health services were used. Studies were included if they assessed the effectiveness of digital mental health interventions among First Nations people in Australia. Data were extracted based on study design, targeted services, and research findings, then synthesised using a thematic analysis framework. RESULTS In total, 22 studies met the inclusion criteria. The included studies used a variety of study designs and researched multiple DMH services designed to provide support, treatment, and psychological assessments. A general effectiveness for non-severe mental health conditions was observed. Several determinants of facilitators and barriers of the implementation of DMH services were identified, including: 1. Organisational and administrative factors; 2. Cultural appropriateness; 3. Accessibility; 4. Integration of DMH services to the existing situation; 5. Engagement between clients and service providers; 6. Coverage of different conditions and clients; 7. Acceptability to DMH services; 8. Digital literacy, and 9. Efficiency. CONCLUSIONS Given the effectiveness in providing services to most mental health conditions, DMH services have the potential to address the mental health needs of First Nations Peoples in Australia. However, the decision-making at multiple layers, as well as the design and implementation of DMH, should consider the determinants identified by this review.
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 | 0,015 | 0,064 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,007 | 0,009 |
| Bibliométrie | 0,009 | 0,010 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 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 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 ».