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Record W4311573188 · doi:10.1080/00224499.2022.2153786

“A Double-Edged Sword”: Health Professionals’ Perspectives on the Health and Social Impacts of Gay Dating Apps on Young Gay, Bisexual, Trans and Queer Men

2022· article· en· W4311573188 on OpenAlexafffundabout
Maxim Gaudette, Cassandra L. Hesse, Hannah Kia, Tara Chanady, Anna Carson, Rod Knight, Olivier Ferlatte

Bibliographic record

VenueThe Journal of Sex Research · 2022
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsUniversity of British ColumbiaBritish Columbia Centre on Substance UseProvidence Health CareUniversité de MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal
FundersCanadian Institutes of Health Research
KeywordsQueerThematic analysisPsychologyQualitative researchPerceptionIntervention (counseling)NursingMedicineSociology

Abstract

fetched live from OpenAlex

Gay dating apps (GDAs) play a central role in partner-seeking for many men. The purpose of the present study was to explore health professionals' perceptions of the effects of GDAs on young gay, bisexual, trans and queer men (YGBTQM). Because health professionals have access to privileged information about YGBTQM's experiences with GDAs, they can provide unique insights about their impacts on YGBTQM health and well-being. This study drew on 28 in-depth semi-structured qualitative interviews with health professionals who provide services to YGBTQM in British Columbia, Canada. Using thematic content analysis, we identified three themes showing participants' conflicting perceptions of GDAs' impacts on YGBTQM: (1) the accessibility of sex on GDAs as either transactional or pleasurable; (2) the building of community and increased safety, which at times corresponds with increased exposure to rejection and discrimination; and (3) a perceived escalation in sexual and drug-related risk-taking in conjunction with the opportunity for education, prevention and intervention. In response to the often polarizing literature on GDAs, this study is among the first to contribute empirical evidence into the perceptions of health professionals working with YGBTQM who use GDAs, while simultaneously providing actionable insights and strategies to help identify potential harms and maximize benefits.

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)0.015
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.310
GPT teacher head0.537
Teacher spread0.227 · 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 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

Citations10
Published2022
Admission routes3
Has abstractyes

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