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Record W3189754531 · doi:10.2196/30761

Limited Interaction Targeted Epidemiology of HIV in Sexual and Gender Minority American Adolescents and Adults: Feasibility of the Keeping it LITE Study

2021· article· en· W3189754531 on OpenAlexvenueno aff
Neil Gleason, Pedro Alonso Serrano, Alejandro Muñoz, Audrey L. French, Sybil Hosek

Bibliographic record

VenueJMIR Formative Research · 2021
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesNational Institute of Mental HealthNational Institutes of Health
KeywordsTransgenderLesbianMedicineSexual minorityCohortSexual orientationGerontologySocial mediaMen who have sex with menPublic healthFamily medicineHuman immunodeficiency virus (HIV)DemographyPsychologySocial psychologyNursingPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: HIV infection rates among sexual minority men and transgender individuals, particularly adolescents and young adults, remain elevated in the United States despite continued improvement in the HIV public health response. However, there remains a knowledge gap in understanding the barriers faced by this community in receiving HIV care and prevention resources. To address this, the Keeping it LITE study was conducted to assess HIV risk factors and barriers to preventive treatment in a large national cohort of young sexual minority men and transgender individuals at high risk of HIV infection. OBJECTIVE: This study aims to evaluate the feasibility of enrolling a large remote cohort, challenges encountered in recruitment, and adjustments made to address these challenges. METHODS: A large national cohort (n=3444) of young sexual minority men and transgender individuals were recruited. Participants were recruited via advertisements on social media; social apps for lesbian, gay, bisexual, transgender, and queer individuals; print advertising; and word-of-mouth. Before enrolling, participants verified their HIV status using an at-home HIV test or by providing their own testing documentation. Descriptive statistics were generated, and a series of logistic regressions were conducted to evaluate demographic differences between recruitment methods, HIV testing methods, and enrollment status. RESULTS: The Keeping it LITE study was particularly successful in recruiting participants via social media, with over half of the participants recruited from advertisements on social media platforms such as Facebook, Instagram, and Snapchat. Participants were also recruited via word-of-mouth; lesbian, gay, bisexual, transgender, and queer apps (ie, Grindr, Scruff); and print advertisements, and participants recruited from these sources tended to be older and have a higher risk profile. The study was also successful in recruiting a large sample of transgender youth, particularly transgender men and nonbinary individuals. At-home HIV testing was acceptable and more heavily used by younger participants, although several barriers were encountered and overcome in the implementation of this testing. The study had more limited success in recruiting participants aged 13-17 years because of lower enrollment rates and barriers to advertising on social media platforms. The implications of these findings for the future development of HIV research and intervention protocols among sexual minorities and trans youth are discussed. CONCLUSIONS: The methods used in the Keeping it LITE study, particularly recruitment via social media, were found to be feasible and acceptable to participants.

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)0.004
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 score0.035
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.151
GPT teacher head0.486
Teacher spread0.336 · 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

Citations17
Published2021
Admission routes1
Has abstractyes

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