Effective interventions to support recovery of people with psychosis and their families across socio-ecological levels in low-income and middle-income countries: a systematic review
Notice bibliographique
Résumé
Summary Background The aim of this systematic review was to synthesise evidence on the effectiveness and cost-effectiveness of interventions to support the recovery of people living with psychosis and their families in low-income and middle-income countries (LMICs). Methods We searched nine databases for articles published from January 2001 to January 2024 without language restrictions. Studies were eligible if they enrolled people living with psychosis or family members, and tested a psychoeducational, psychological, social, economic or service intervention or delivery or implementation strategy aimed at improving outcomes of people with psychosis. Eligible studies were required to compare outcomes with an alternative condition, using any prospective evaluation study design in a LMIC setting. We extracted summary data from published papers and appraised risk of bias using the Effective Public Health Practice Project tool. We prioritised the reporting of recovery-orientated outcomes including social inclusion, personal recovery, reduced stigma and discrimination and human rights protections. We conceptualised the person living with psychosis in their context (individual, family, organisation and community) based on the socio-ecological model of disability and highlighted studies intervening and measuring outcomes across multiple socio-ecological levels. Protocol registration: PROSPERO (CRD42022330298). Findings A total of 310 individual studies including data from 34,435 participants in 37 countries were included. Aggregate data from a further five meta-analyses, comprising data from 130 individual studies were also included. The majority of studies (77%) were conducted in upper middle-income countries. There was a dominance of studies evaluating impacts of interventions on individual-level mental health and functioning and a paucity of studies measuring the recovery-orientated outcomes prioritised by people living with psychosis. There were modest effects for comprehensive interventions involving family, psychosocial rehabilitation and care close to home provided by trained specialists however their scalability in resource-limited settings is unclear. Over half the studies were considered to have a high risk of bias. Interpretation There is a need for studies that evaluate scalable interventions supporting recovery with comprehensive and contextualised outcome measures and for greater investment in strengthening capacity to conduct rigorous psychosis research across LMICs. Funding None. Research in context Evidence before this study Recent World Health Organization (WHO) guidance on human rights-based, recovery-orientated community mental health care featured markedly few case studies of good practice for people with psychosis in low-income and middle-income countries (LMICs). Systematic reviews of interventions for psychosis in LMICs have been narrow in focus and reporting outcomes, and limited to English language publications. Added value of this study This systematic review is the most comprehensive synthesis to date of psychosis interventions in LMICs. Inclusion is not restricted by publication language. We highlight studies reporting recovery-oriented outcomes prioritised by people living with psychosis and impacts of interventions across levels of the socio-ecological model of disability. While being particularly relevant to LMICs, our findings also contribute a useful perspective for high income settings. Implications of all the available evidence Most interventions were targeted at the individual and focused on mental health and functioning outcomes, with few evaluations of impact on social inclusion and other valued outcomes. There is some evidence in support of specialist-delivered comprehensive interventions involving family, psychosocial rehabilitation and care close to home, but effect sizes were small-to-modest, and many intervention types and delivery agents have not been adequately tested, especially in LICs and rural settings. There is a clear need to develop comprehensive and contextualised measures for recovery-orientated outcomes and to invest in strengthening capacity to conduct rigorous research on interventions for psychosis in LMICs.
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 | 0,017 | 0,066 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,012 | 0,009 |
| Bibliométrie | 0,012 | 0,010 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| 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 ».