Editorial: Building resilience through healing communities
Notice bibliographique
Résumé
Medical training often fails to address the importance of culturally adapted tools and approaches that appreciate the beliefs and realities of patients influencing wellbeing, resilience patterns and intervention. The papers in this collection speak to value of integrating social and culture in both individual and community mental health engagement Transformative learning theory (TLT) (Mezirow 2003), a model resonant with Paolo Friere's theories (Friere 2020) was applied by the Ethiopian project team as a useful approach to address and transform the dissonances between biomedical and traditional healing systems.Rural populations in Ethiopia with psychosis for instance, experience challenges accessing psychiatric care with only 58 % accessing biomedical treatment. The treatment consequently falls on traditional healers of the Orthodox Christian Church who are experienced and less stigmatized than psychiatric care. The social and cultural discourse reflect in a task shifting process integrating complex locally relevant historical, relational, generational legacies, as well as spiritual traditions and diverse languages. Respectful feedback and exchange between the spiritual healers and research organizers led to productive collaborative partnerships. By exploring alternate ways of knowing and caring for seriously mentally ill patients. The Ethiopian team showed a reduction of to stigma and showed an increased referral to the psychiatric clinics.One paper identified low rates of parental mental health literacy and stigma as a fundame nta l treatment barrier in a collaborative effort of Ethiopia, Kenya and Democratic Republic of Congo enriching our understanding of tools and evaluate ways to increase use of mental health services.Research is presented on the importance of parental health literacy as a contributing factor to promote support for vulnerable youth, especially those experiencing high mental health risk. Psychedelics are increasingly used in various Euro-North American psychiatric outpatient and inpatient settings (2022, Gukasyan et al). This is one of the first papers from an LMIC cohort using psilocybin in this unique application of psychotherapy processes. Hickling's group process work culminated in a creative production of poetics and performance, while the psilocybin adaption is focussed on insight orientation with individual patients.Creative arts modalities have continued to be transportable across cultural spaces and remains an accessible treatment modality for seriously mentally ill patients (Howley 2020). These methods may use the facilitating modalities of visual arts, poetry, music, drama, dance and movement but also provide a space of protest and empowerment (Mills & Davar 2016;Hosseini 2023).The development of Zentangle as a simple mindfulness method with a cohort of treatment resistant or seriously mentally ill patients in recovery is explored in one of the papers in this series.Further evaluation on Zentangle, is however warranted to assess the impact on the quality of life and skills for recovery. The method requires only brief training and can adapt to various age groups. Art methods can similarly provide mental health support as a task shifting strategy.Likewise the Bapu Trust project in Pune, India is a group who have developed many programs integrating art based innovative task shifting for serious mental illness patients and community engagement.While Qatar is a wealthy LMIC state their medical service development focussed mainly on tertiary care clinical services while access for community mental health resources remained undeveloped until 2016.Seventy five per cent of Qatar population are migrant workers predominantly from Nepal and Bangladesh, but this population remains underserviced in view of many structural and cultura l challenges. Services remained less well developed currently for children, women and migrants.Primary care also remains is underdeveloped with a shortage of trained mental health specialists and personnel. Women similarly remain underserved in mental health services though the study confirms significant community access improvements.
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 | 0,007 | 0,028 |
| Méta-épidémiologie (sens strict) | 0,006 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,005 |
| Bibliométrie | 0,004 | 0,002 |
| Études des sciences et des technologies | 0,004 | 0,005 |
| Communication savante | 0,010 | 0,007 |
| Science ouverte | 0,006 | 0,002 |
| Intégrité de la recherche | 0,021 | 0,023 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,028 | 0,017 |
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 ».