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Record W2944716603 · doi:10.1080/13811118.2019.1610677

Experiences of Suicide in Transgender Youth: A Qualitative, Community-Based Study

2019· article· en· W2944716603 on OpenAlexaboutno aff
Quintin A. Hunt, Quinlyn J. Morrow, Jenifer K. McGuire

Bibliographic record

VenueArchives of Suicide Research · 2019
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsTransgenderCognitive reframingMental healthPsychologyQualitative researchSuicide preventionDysphoriaPoison controlClinical psychologyPsychological resiliencePsychiatryMedicineAnxietySocial psychologyMedical emergency

Abstract

fetched live from OpenAlex

Objective: The aim was to develop understanding around the experience of suicide in transgender youth. Method: Qualitative analysis with 85 interviews with transgender youth about their histories with suicidality was performed. Participants were recruited from community clinics in three counties (United States, Canada, and Ireland) between 2010 and 2014. Results: Factors that precipitated participants’ suicide attempts included rejection based on gender identity and gender dysphoria. Participants demonstrated resilience by attempting to connect with loved ones for support and through self-awareness of mental states, including by regulating behaviors they perceived to adversely affect their mental health. Conclusions: Transgender youth may fear seeking health care due to health professionals’ lack of understanding of transgender issues and fear of further victimization. Reframing suicidality as a rational decision-making process in response to stress may further understanding of why people attempt suicide and provide new avenues for intervention.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0070.004
Scholarly communication0.0020.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.371
GPT teacher head0.555
Teacher spread0.184 · 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 source (direct Gemma or distilled Codex), 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

Citations46
Published2019
Admission routes1
Has abstractyes

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