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Enregistrement W4408883882 · doi:10.1108/jpmh-03-2025-167

Guest editorial: Understanding and addressing mental health inequalities in the UK and US – Part 1: framing the situation

2025· editorial· en· W4408883882 sur OpenAlexaboutno aff
Lee Knifton, Neil Quinn, Victoria Stanhope

Notice bibliographique

RevueJournal of Public Mental Health · 2025
Typeeditorial
Langueen
DomaineSocial Sciences
ThématiqueHealth disparities and outcomes
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMental healthFraming (construction)InequalityPsychologySociologyPublic relationsMedicinePolitical sciencePsychiatryHistory

Résumé

récupéré en direct d'OpenAlex

We are delighted to have developed this special edition on mental health inequalitiesthat brings together ideas from the US and the UK. It has been a collaborationbetween the University of Strathclyde in Scotland and New York University (NYU) in the US, and stems from a workshop we held in August 2023 to mark our 10-year collaboration.We had an excellent response to our call, which has resulted in a collaborative special issuethat will cover the first two editions of 2025. In this edition, we explore and frame the issues and challenges, in the next edition we will outline research that focuses upon solutions to addressthese challenges. Our papers come from a range of disciplines reflecting the broad-basednature of public mental health, based upon a social model of health and equity.Our first paper by Gregory Acevedo and colleagues is a great example of researchers from the US and England collaborating with those with lived experience to understand how the cost of living crisis is affecting the mental wellbeing of young people and the importance of community and family support. It also utilises youth participatory action research methods to generate in-depth understandings and ideas for action.Our next paper by Lijia Guo and colleagues builds upon this theme by exploring with a sample of over 45,000 the impact of family upon mental health during the pandemic. Living with children had a positive impact on hope, gratitude and loneliness, but conversely increased pressure and guilt. These were further shaped by social circumstances and highlights the importance of supporting disadvantaged families at times of stress.We were also delighted to receive a paper from Andrea Reupert at Monash exploring the inter-connection of poverty and mental health through Boots Theory. This relatable concept demonstrates how necessary short-term decisions worsen long-term mental health outcomes, helping explain the widening health gap between rich and poor.Nia Williams and James Kirkbride then synthesise the evidence for community-based interventions on the social determinants of mental health. From a very broad review, their findings again highlight that the most promising evidence is for financial and welfare support, which is particularly salient in the current cost of living crises.Migration is a major social issue in both the UK and US at present and frequently associated with destitution and trauma. Emily Clark and colleagues use community-based participatory research approaches and arts methods with asylum-seeking men to gain insights into pre- and post-migration trauma and suffering, but also highlight the value of peer groups for hope, healing and growth.Tiluka Bhanderi and colleagues explore in depth South Asian women’s mental health experiences in the US, UK and Canada. They focused upon eating disorders and highlight the social and cultural factors that can shape women’s experiences.Finally, we end this edition with a novel paper by Maya Ljubojevic looking at the Thriving City movement that has emerged in recent years in the US and Europe as a way to improve public mental health and wellbeing in urban areas. Despite some common approaches and themes, the promising Thrive model lacks consistency and clarity that is necessary to understand its value and impact.As health, social and economic inequalities widen in our troubled societies, we hope these articles help to contribute to our understanding of mental health. In the next special edition, we will focus upon solutions of these major challenges.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,021
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,131
Score d'incertitude au seuil0,998

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0210,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0030,000
Communication savante0,0010,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,128
Tête enseignante GPT0,421
Écart entre enseignants0,293 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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