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Record W2782922580 · doi:10.1080/19359705.2018.1427646

Evidence of changing patterns in mental health and depressive symptoms for sexual minority adolescents

2018· article· en· W2782922580 on OpenAlexafffundabout
Ryan J. Watson, Tracey Peter, Timothy McKay, Tamara Edkins, Elizabeth Saewyc

Bibliographic record

VenueJournal of Gay & Lesbian Mental Health · 2018
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of British ColumbiaUniversity of Manitoba
FundersCanadian Institutes of Health Research
KeywordsSexual minorityMental healthPsychologyClinical psychologyDepressive symptomsPsychiatryLesbianSexual orientationMinority stressSocial psychologyAnxiety

Abstract

fetched live from OpenAlex

Depression, sadness, low self-esteem, and self-harm affect a substantial number of young people in North America. However, the prevalence of these symptoms has been found to be consistently higher for sexual minority (i.e., lesbian, gay, bisexual) populations. In this study, we traced the trends and disparities in mental health, including self-harm, forgone mental health care, good feelings, feelings of sadness, and feeling good about oneself, with provincially representative data from Canada (N = 99,373; M age = 15). We reported whether the disparities have narrowed, widened, or remained the same for sexual orientation subgroups over time. We found that though sexual minorities report higher rates of all negative mental health indicators, the disparity in self-harm for gay adolescent males compared to their heterosexual counterparts has narrowed over time. However, some disparities have widened: the gap in feeling sad has widened for sexual minorities compared to their heterosexual counterparts. These findings have implications for the efficacy of interventions and the next steps in working to ameliorate mental health issues for vulnerable sexual minority adolescents in North America.

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 score0.052
Threshold uncertainty score0.936

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.072
GPT teacher head0.434
Teacher spread0.362 · 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

Citations24
Published2018
Admission routes3
Has abstractyes

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