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Record W4220835241 · doi:10.1177/00220221221077353

Differential Adaptation to Adversity: A Latent Profile Analysis of Youth Engagement With Resilience-Enabling Cultural Resources and Mental Health Outcomes in a Stressed Canadian and South African Community

2022· article· en· W4220835241 on OpenAlexafffundabout
Linda Theron, Sebastiaan Rothmann, Jan Höltge, Michael Ungar

Bibliographic record

VenueJournal of Cross-Cultural Psychology · 2022
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health ResearchSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsMental healthReligiosityPsychologyPsychological resilienceAllegianceSociocultural evolutionContext (archaeology)AcculturationDevelopmental psychologyClinical psychologySocial psychologyPsychiatrySociologyEthnic groupPolitical scienceGeographyPolitics

Abstract

fetched live from OpenAlex

Using person-centered latent profile analyses, this article reports two distinct sub-groups—nominal versus robust cultural allegiance—that characterize how a sample of 14- to 24-year-olds from stressed environments in South Africa ( n = 576, n females = 314, n males = 257) and Canada ( n =V481; n females = 270, n males = 211) engage with four cultural resources (spirituality, religiosity, family tradition, and community tradition). It considers how nominal versus robust cultural allegiance is associated with youths’ self-reported symptoms of depression and conduct disorder, age-group, and gender. In doing so, the article addresses pre-existing resilience studies’ general inattention to patterns of differential adaptation in how specific groups of youth adjust to adversity, and the role of cultural resources in youth mental health. The results draw attention to the importance of understanding resilience in sociocultural context and urge mental health practitioners and other resilience champions to be circumspect in their work with at-risk youth about which cultural resources they leverage for which mental health outcomes.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.065
GPT teacher head0.409
Teacher spread0.344 · 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

Citations15
Published2022
Admission routes3
Has abstractyes

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