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Record W4280513051 · doi:10.2196/38075

Interest in HIV Prevention Mobile Phone Apps: Focus Group Study With Sexual and Gender Minority Persons Living in the Rural Southern United States

2022· article· en· W4280513051 on OpenAlexvenueno aff
Jeb Jones, O. Winslow Edwards, Leland Merrill, Patrick S. Sullivan, Rob Stephenson

Bibliographic record

VenueJMIR Formative Research · 2022
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
FundersNational Institute of Nursing Research
KeywordsFocus groupPsychological interventionmHealthMen who have sex with menReproductive healthTransgenderTelehealthMobile phoneRural areaMedicineGerontologyPsychologyTelemedicineHuman immunodeficiency virus (HIV)Family medicinePopulationHealth careEnvironmental healthNursingPolitical scienceSociologyComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Mobile health (mHealth) interventions, including smartphone apps, have been found to be an effective means of increasing the uptake of HIV prevention tools, including HIV and sexually transmitted infection (STI) tests and pre-exposure prophylaxis. However, most HIV prevention mHealth apps tested in the United States have been tested among populations living in areas surrounding urban centers. Owing to reduced access to broadband internet and reliable cellular data services, it remains unclear how accessible and effective these interventions will be in rural areas. In addition, gay and bisexual men who have sex with men and gender minority populations in rural areas experience enhanced stigma when compared with their more urban counterparts, and these experiences might affect their willingness and interest in mHealth apps. OBJECTIVE: This study aimed to conduct online focus groups with men who have sex with men and transgender and gender diverse populations in the rural southern United States to assess their interest in mHealth HIV prevention apps and the features that they would be the most interested in using. METHODS: Focus group participants were recruited from a larger pool of sexual and gender minority respondents to a web-based research survey. The participants indicated that they would be willing to participate in an online focus group discussion. Focus groups were conducted via secure Zoom (Zoom Video Communications Inc) videoconferencing. During the focus group discussions, participants were asked to discuss their experiences with HIV and STI prevention and how these experiences were affected by living in a rural area. They were then shown screenshots of a new app to promote HIV and STI prevention among rural populations and asked to provide their opinions on the app's features. The transcripts of the discussions were reviewed and coded using a constant comparative approach. RESULTS: A total of 6 focus groups were conducted with 26 participants. Most participants were cisgender gay and bisexual men who have sex with men (19/26, 73%); the remaining participants were transgender men (2/26, 8%), were nonbinary people (2/26, 8%), or had multiple gender identities (3/26, 12%). Participants reported numerous barriers to accessing HIV and STI prevention services and accurate information about HIV and STI prevention options. Overall, the participants reported a high degree of interest in mHealth interventions for HIV and STI prevention and suggested several recommendations for the features of an app-based intervention that would be the most useful for rural residents. CONCLUSIONS: These focus group discussions indicate that rural residence is not a major barrier to mHealth HIV and STI prevention intervention implementation and that there is a high degree of interest in these approaches to HIV and STI prevention.

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)0.006
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 score0.119
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
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 head0.146
GPT teacher head0.485
Teacher spread0.339 · 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

Citations20
Published2022
Admission routes1
Has abstractyes

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