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Record W3008541775 · doi:10.2196/16494

An Internet-Based, Peer-Delivered Messaging Intervention for HIV Testing and Condom Use Among Men Who Have Sex With Men in India (CHALO!): Pilot Randomized Comparative Trial

2020· article· en· W3008541775 on OpenAlexvenueno aff
Viraj V. Patel, Shruta Rawat, Alpana Dange, Corina Lelutiu‐Weinberger, Sarit A. Golub

Bibliographic record

VenueJMIR Public Health and Surveillance · 2020
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersNational Institute on Minority Health and Health DisparitiesNational Institute of Allergy and Infectious DiseasesNational Institute on Drug AbuseNational Institute of Mental Health
KeywordsCondomPsychological interventionRandomized controlled trialMedicineMen who have sex with menIntervention (counseling)The InternetmHealthBehavior changeFamily medicineHuman immunodeficiency virus (HIV)World Wide WebNursingComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Leveraging internet-based communication tools (eg, messaging apps, SMS text messaging, and email) may be an effective avenue for delivery of HIV prevention messages to men who have sex with men (MSM) in India, but there are limited models for such internet-based interventions. OBJECTIVE: The CHALO! pilot was an online educational and behavioral intervention aimed to determine the feasibility, acceptability, and preliminary impact of a peer-delivered, internet-based messaging intervention for HIV testing and consistent condom use for MSM in India. The messages addressed barriers to HIV testing and condom use and were theoretically based on the information-motivation-behavioral skills model. METHODS: Between February and March 2015, we recruited, enrolled, and randomized 244 participants via online advertisements on mobile dating apps and Facebook. Eligible men (18 years or older, sexually active with other men, and self-reported HIV-negative or unknown status) were randomized to receive educational and motivational messages framed as either approach (ie, a desirable outcome to be achieved) or avoidance (an undesirable outcome to be avoided) over 12 weeks via internet-based messaging platforms. Participants completed online surveys at baseline and immediately postintervention. RESULTS: Participants were similar across arms with respect to sociodemographic and behavioral characteristics. Over 82.0% (200/244) of participants were retained (ie, viewed final messages), and 52.3% (130/244) of them completed the follow-up survey. Of those completing the follow-up survey, 82.3% (107/130) liked or strongly liked participating in CHALO!. The results showed a significant increase in self-reported HIV testing in the past 6 months from baseline to follow-up (41/130, 31.5% to 57/130, 43.8%; P=.04). When including those who reported intentions to test, this percentage increased from 44.6% (58/130) at baseline to 65.4% (85/130) at follow-up (P<.01). When examining intentions to test among those without prior HIV testing, intentions increased from 32% (16/50) of the sample at baseline to 56% (28/50) of the sample at follow-up (P=.02). Condom use during anal sex did not significantly change from baseline to follow-up. HIV testing and condom use did not significantly differ between approach and avoidance conditions at follow-up. CONCLUSIONS: As one of the first studies of an online HIV prevention intervention for Indian MSM, CHALO! was feasible to implement by a community-based organization, was acceptable to participants, and demonstrated potential to improve HIV testing rates.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.083
GPT teacher head0.376
Teacher spread0.292 · 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 designRandomized trial
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

Citations37
Published2020
Admission routes1
Has abstractyes

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