Editorial: Mental health recovery: engaging and empowering people living with mental illness and their families
Notice bibliographique
Résumé
shaped the landscape of global mental health, advocating for a shift toward recoveryoriented approaches in both practices and policies, as exemplified by the World Health Organization (WHO)'s endorsement in many of its official publications [6].The collections in this Research Topic reflect the evolving understanding of mental health recovery in the very recent years. They demonstrate how people with lived experience of mental illness can engage in meaningful living through self-reflection, peer connection, institutional innovation, and attitudinal change. Although these studies vary in research focus and methodological design, they all underscore the notion that recovery is a relational and participatory process enacted not only within the individuals but also through their multifaceted interactions with peers, professionals, and the broader communities.Zhu & Lyu (2024) present a collaborative autoethnography reflecting one author's lived experience of recovery from depression and its intersectionality with broader social contexts. Drawing from anti-stigma perspectives, the paper provides an in-depth account of how individuals make sense of their mental distress and reclaim their Two studies in this research topic focus on peer support, a growing area of interest in mental health recovery [7]. Fan, Liu & Li (2024) describe how peer interactions within a psychiatric day-care center in China foster a sense of meaning and community, despite a lack of a formal structure. In contrast, Lequin et al. (2023) examine the integration of trained Peer Mental Health Practitioners (PMHPs) at a hospital unit caring for patients with psychiatric disorders. Their qualitative study demonstrates that structured peer support benefits not only patients but also clinical teams and the institution. However, the authors also note that clearly defined roles and professional boundaries are crucial for the sustainable integration of PMHPs.Health professionals play a pivotal role in mental health service delivery and recovery processes. Their attitudes significantly influence service users' self-perception and therapeutic engagement. Evidence suggests that healthcare providers' attitudes toward mental illness are no more positive than those of the general public [8,9]. Cho & Kim (2024) attempted to address this gap by designing an empathy-enhancing program for nursing students, using patient narratives. Their quasi-experimental study shows promising effects of having service users as educators and agents of change through sharing their lived experience narratives with future care providers.Despite the valuable insights from these studies on engaging and empowering individuals with lived experience, a notable omission remains: the role of families. This omission may also reflect a broader gap in recovery research and practices literature [10]. Families often serve as primary caregivers and integral members of interpersonal networks, particularly in non-Western or low-resource settings [11]. Engaging families is essential to supporting the individual's recovery and sustaining their own well-being [12]. Future research should prioritize family integration and explore strategies to empower families as collaborative partners in recovery.In summary, the collections in this Research Topic reaffirm that recovery is neither exclusively a clinical process nor simply an intrapersonal one. Rather, it is relational, context-sensitive, and socially embedded. Meaningful engagement must extend beyond individualistic therapeutic encounters to encompass the broader domains of social relationships, institutional practices, and public narratives. Recovery takes place when people with mental illness become active participants in mental health practices and policies. To enable such recovery, mental health systems must foster recovery-oriented environments both within care settings and across broader society that value inclusion, shared decision-making, the lived experiences of individuals and families, and collective transformation [13,14].
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 | 0,004 |
| Bibliométrie | 0,004 | 0,002 |
| Études des sciences et des technologies | 0,004 | 0,005 |
| Communication savante | 0,009 | 0,007 |
| Science ouverte | 0,007 | 0,002 |
| Intégrité de la recherche | 0,024 | 0,020 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,026 | 0,013 |
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 ».