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Record W4387008650 · doi:10.1080/19359705.2023.2257626

Risk and resilience in a time of crisis: The experiences of LGBTQ+ youth and young adults participating in a virtual AFFIRMative CBT group (AFFIRM Online) during the COVID-19 pandemic, 2020–2022

2023· article· en· W4387008650 on OpenAlexafffund
Shelley L. Craig, Ashley S. Brooks, Rachael Pascoe, Ali Pearson, Janine Xu, Valeria Khudiakova

Bibliographic record

VenueJournal of Gay & Lesbian Mental Health · 2023
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsSmiths Detection (Canada)Public Health OntarioUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaPublic Health Agency of Canada
KeywordsThematic analysisMental healthPsychological interventionCoping (psychology)PsychologyCoronavirus disease 2019 (COVID-19)General partnershipContext (archaeology)Sexual orientationPsychological resilienceSociologyQualitative researchSocial psychologyPolitical scienceClinical psychologyMedicinePsychiatrySocial science

Abstract

fetched live from OpenAlex

Introduction: LGBTQ+ youth experience significant mental health challenges, which were exacerbated by the COVID-19 pandemic. This empirically explores the experiences of LGBTQ+ youth during COVID and their participation in AFFIRM Online, a digital affirmative CBT intervention. Methods: Thematic analysis of longitudinal qualitative questionnaires explored the experiences of 184 LGBTQ+ youth during waves 1–5 of the pandemic.Result: Three themes emerged: (a) Connecting with Community During Lockdown; (b) Fostering Calm in the Chaos; and (c) Developing Hope and Coping Skills for a “Post-COVID” Future. Conclusion: Digital interventions can help LGBTQ+ youth develop coping skills that support resilience during a significant crisis.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.046
GPT teacher head0.398
Teacher spread0.352 · 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 designQualitative
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

Citations4
Published2023
Admission routes2
Has abstractyes

Explore more

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