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Record W2073591605 · doi:10.2196/jmir.1948

Internet-Based HIV and Sexually Transmitted Infection Testing in British Columbia, Canada: Opinions and Expectations of Prospective Clients

2012· article· en· W2073591605 on OpenAlexafffundabout
Travis Salway, Janine Farrell, Mark Bondyra, Devon Haag, Jean Shoveller, Mark Gilbert

Bibliographic record

VenueJournal of Medical Internet Research · 2012
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversity of British ColumbiaSimon Fraser UniversityBC Centre for Disease Control
FundersCanadian Institutes of Health ResearchUniversity of British Columbia
KeywordsGonorrheaThe InternetFocus groupMen who have sex with menMedicinePhoneInternet privacyFamily medicineSyphilisHuman immunodeficiency virus (HIV)Computer scienceWorld Wide WebBusiness

Abstract

fetched live from OpenAlex

BACKGROUND: The feasibility and acceptability of Internet-based sexually transmitted infection (STI) testing have been demonstrated; however, few programs have included testing for human immunodeficiency virus (HIV). In British Columbia, Canada, a new initiative will offer online access to chlamydia, gonorrhea, syphilis, and HIV testing, integrated with existing clinic-based services. We presented the model to gay men and other men who have sex with men (MSM) and existing clinic clients through a series of focus groups. OBJECTIVE: To identify perceived benefits, concerns, and expectations of a new model for Internet-based STI and HIV testing among potential end users. METHODS: Participants were recruited through email invitations, online classifieds, and flyers in STI clinics. A structured interview guide was used. Focus groups were audio recorded, and an observer took detailed field notes. Analysts then listened to audio recordings to validate field notes. Data were coded and analyzed using a scissor-and-sort technique. RESULTS: In total, 39 people participated in six focus groups. Most were MSM, and all were active Internet users and experienced with STI/HIV testing. Perceived benefits of Internet-based STI testing included anonymity, convenience, and client-centered control. Salient concerns were reluctance to provide personal information online, distrust of security of data provided online, and the need for comprehensive pretest information and support for those receiving positive results, particularly for HIV. Suggestions emerged for mitigation of these concerns: provide up-front and detailed information about the model, ask only the minimal information required for testing, give positive results only by phone or in person, and ensure that those testing positive are referred for counseling and support. End users expected Internet testing to offer continuous online service delivery, from booking appointments, to transmitting information to the laboratory, to getting prescriptions. Most participants said they would use the service or recommend it to others. Those who indicated they would be unlikely to use it generally either lived near an STI clinic or routinely saw a family doctor with whom they were comfortable testing. Participants expected that the service would provide the greatest benefit to individuals who do not already have access to sensitive sexual health services, are reluctant to test due to stigma, or want to take immediate action (eg, because of a recent potential STI/HIV exposure). CONCLUSIONS: Internet-based STI/HIV testing has the potential to reduce barriers to testing, as a complement to existing clinic-based services. Trust in the new online service, however, is a prerequisite to client uptake and may be engendered by transparency of information about the model, and by accounting for concerns related to confidentiality, data usage, and provision of positive (especially HIV) results. Ongoing evaluation of this new model will be essential to its success and to the confidence of its users.

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)0.003
metaresearch head score (Gemma)0.007
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 score0.232
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.388
Teacher spread0.333 · 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

Citations90
Published2012
Admission routes3
Has abstractyes

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