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Record 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 on OpenAlexaboutno aff
Lee Knifton, Neil Quinn, Victoria Stanhope

Bibliographic record

VenueJournal of Public Mental Health · 2025
Typeeditorial
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthFraming (construction)InequalityPsychologySociologyPublic relationsMedicinePolitical sciencePsychiatryHistory

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.021
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.131
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.128
GPT teacher head0.421
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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