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Record W2762641325 · doi:10.1080/19359705.2017.1385559

Being humorous and seeking diversion: Promoting healthy coping skills among LGBTQ+ youth

2017· article· en· W2762641325 on OpenAlexafffund
Shelley L. Craig, Ashley Austin, Yu‐Te Huang

Bibliographic record

VenueJournal of Gay & Lesbian Mental Health · 2017
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of Toronto
FundersInstitute of Infection and ImmunityCommercializations Promotion Agency for R and D Outcomes
KeywordsDisengagement theoryCoping (psychology)PsychologyFeelingClinical psychologyPopulationPsychological interventionDevelopmental psychologySocial psychologyMedicinePsychiatryGerontology

Abstract

fetched live from OpenAlex

LGBTQ+ youth encounter pervasive stigma-related stress that requires effective coping skills. This study explored the coping patterns of LGBTQ+ youth participants (N = 30) in a cognitive-behavioral therapy-based coping skills training. Participants, 15–18 years old with a range of gender, sexual, racial and ethnic identities, completed a coping skills inventory (A-COPE) with 12 subscales at two time points. Based on the stigma-coping framework, coping skills were broadly classified as disengagement or engagement strategies. LGBTQ+ youth were most likely to utilize avoiding problems as a strategy to cope with stress, followed closely by being humorous, relaxing, and ventilating feelings. Notably, seeking professional and spiritual support were the least adopted coping strategies. Post-intervention, participants reported significant increases in the areas of primary control (solving family problems) and secondary control (seeking spiritual support, seeking diversion, engaging in demanding activities, and being humorous). The findings demonstrate the versatility of LGBTQ+ youth's coping strategies and show the potential of the AFFIRM intervention to promote engagement coping patterns among this population.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.040
GPT teacher head0.386
Teacher spread0.347 · 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 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

Citations27
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Gay & Lesbian Mental HealthSame topicLGBTQ Health, Identity, and PolicyFrench-language works237,207