Farina, I. Masella, C. Sangiorgi, D. (2021) Positioning Social Prescribing in the scenario of community-based interventions for the transformation of mental health services for children, adolescents and young people: a review. Book of Abstract “Health Management: managing the present and shaping the future” European Health Management Association (EHMA) Annual Conference, 2021, pg. 29
Notice bibliographique
Résumé
Context \nSocial Prescribing is defined as a non-clinical and community-based service that addresses social needs \nthrough social solutions. Originated in UK for isolated and chronic-ill elderlies, the NHS has recently expanded \nSocial Prescribing as an all-age model, including children, adolescents and young people (CYP). From the first \nresults it is clear that Social Prescribing for CYP, as for adults, is a mental health and well-being service (Bertotti, \n2021). The aim of this paper is to understand how social prescribing for adolescents and young people can be \npositioned in the current scenario of transforming mental health services as a community-based intervention \nfor CYP. \nMethods \nA narrative review through systematic search has been developed. The systematic search has been conducted \nin electronic database (SCOPUS and PubMed) and integrated with grey literature capturing the material from \n2000 to 2021, through keywords as “adolescent*” or “young people” and “mental health” or “wellbeing” and \n“community-based interventions” or “community-based services” or “integrated care”. Title/abstract and full \ntext review was conducted. After screening 275 text at the title/abstract level and 119 at full-text level, including \n8 papers that were found through citations and were not part of the initial results, a total of 36 papers have \nbeen included. Papers have been analysed through a framework based on broader literature that addresses \nthe main challenges called out for youth mental health services innovation and community-based \ninterventions: access, youth-friendliness, stigma-free, youth participation, care ecosystem, sustainability. \nResults \nSeveral models and policies have been found that address the challenges and need to reform statuary services \nof CYP mental-healthcare systems. Countries as Australia, Ireland, UK and Canada have developed different \nmodels of community-based interventions, that share common principles and are mainly positioned as \nintegrated care services in the primary care tier with the aim to promote early detection of at-risk adolescents. \nSocial Prescribing shares common principles and focus on the same challenges addressed by the other \nmodels: how to make services accessible, how to design a youth-friendly and stigma-free service, how to \npromote youth participation, how to integrate the care ecosystem around CYP and make services sustainable. \nThe main difference is based on the nature of the models, where Social Prescribing focuses mainly on social \ndeterminants of health with a non-clinical approach. Another important element is the role played by the Link \nWorker as activator of the empowerment process of CYP through the recognition and activation of community \nresources. No similar role has been identified in other models. \nDiscussion \nSocial Prescribing, with its de-medicalisation and non-diagnosis centred principle, addresses an implicit gap \nin the current models and innovations of CYP mental-healthcare systems which is the potential of developing \nmental wellbeing through a non-clinical path and a relationship with the community, that for some people can \nwork as an only solution. It has the potential to shift from the effort on how to make mental health services \nmore accessible for CYP to transform how mental wellbeing is addressed and shared in the community. The \nrole of the community in community-based interventions is still unclear as well in Social Prescribing. Especially \nwhen focusing on social determinants of health in CYP mental health, further research should look at the \nimpact of services and models moving from on the individual as much as on the community and structural \nlevel.
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 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 | 0,004 | 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 ».