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Record W4405259587 · doi:10.1017/s2045796024000830

War exposure, daily stressors, and mental health 15 years on: implications of an ecological framework for addressing the mental health of conflict-affected populations

2024· article· en· W4405259587 on OpenAlexaff
Kenneth E. Miller, Andrew Rasmussen

Bibliographic record

VenueEpidemiology and Psychiatric Sciences · 2024
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMental healthStressorPsychologyPsychiatryEcologyBiology

Abstract

fetched live from OpenAlex

AIMS: , reflect deeply held beliefs about the causes and nature of distress in war-affected communities. Drawing on the burgeoning literature on armed conflict and mental health, the reports of mental health and psychosocial support (MHPSS) staff in the field, and on research on the psychology and psychophysiology of stress, we proposed an integrative model that drew on the strengths of both frameworks and underscored their essential complementarity. Our model includes two primary pathways by which armed conflict impacts mental health: directly, through exposure to war-related violence and loss, and indirectly, through the harsh conditions of everyday life caused or exacerbated by armed conflict. The mediated model we proposed draws attention to the effects of stressors both past (prior exposure to war-related violence and loss) and present (ongoing conflict, daily stressors), at all levels of the social ecology; for that reason, we have termed it an ecological model for understanding the mental health needs of conflict-affected populations. METHODS: In the ensuing 15 years, the model has been rigorously tested in diverse populations and has found robust support. In this paper, we first summarize the development and key tenets of the model and briefly review recent empirical support for it. We then discuss the implications of an ecological framework for interventions aimed at strengthening mental health in conflict-affected populations. RESULTS: We present preliminary evidence suggesting there has been a gradual shift towards more ecological (i.e., multilevel, multimodal) programming in MHPSS interventions, along the lines suggested by our model as well as other conceptually related frameworks, particularly public health. CONCLUSIONS: We reflect on several gaps in the model, most notably the absence of adverse childhood experiences. We suggest the importance of examining early adversity as both a direct influence on mental health and as a potential moderator of the impact of potentially traumatic war-related experiences of violence and loss.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.759
Threshold uncertainty score0.668

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.174
GPT teacher head0.478
Teacher spread0.304 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations30
Published2024
Admission routes1
Has abstractyes

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