MétaCan
Menu
← Back to cohort
Record W2598064100 · doi:10.2196/resprot.6391

Get+Connected: Development and Pilot Testing of an Intervention to Improve Computer and Internet Attitudes and Internet Use Among Women Living With HIV

2017· article· en· W2598064100 on OpenAlexvenueno aff
Gabriela Seplovich, Keith J. Horvath, Lorlette J. Haughton, Oni J. Blackstock

Bibliographic record

VenueJMIR Research Protocols · 2017
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersNational Institute of Mental Health
KeywordsThe InternetIntervention (counseling)Human immunodeficiency virus (HIV)Internet privacyPsychologyMedicineGerontologyMedical educationFamily medicineWorld Wide WebComputer scienceNursing

Abstract

fetched live from OpenAlex

BACKGROUND: For persons living with chronic medical conditions, the Internet can be a powerful tool for health promotion, and allow for immediate access to medical information and social support. However, women living with human immunodeficiency virus (HIV) in the United States face numerous barriers to computer and Internet use. Health behavior change models suggest that the first step towards adopting a new health behavior is to improve attitudes towards that behavior. OBJECTIVE: To develop and pilot test Get+Connected, an intervention to improve computer and Internet attitudes and Internet use among women living with HIV. METHODS: To develop Get+Connected, we reviewed the extant literature, adapted an existing curriculum, and conducted a focus group with HIV-positive women (n=20) at a community-based organization in the Bronx, New York. Get+Connected was comprised of five weekly sessions covering the following topics: basic computer knowledge and skills, identifying reliable health-related websites, setting up and using email and Facebook accounts, and a final review session. We recruited 12 women to participate in pilot testing. At baseline, we collected data about participants' sociodemographic information, clinical characteristics, and technology device ownership and use. At baseline, intervention completion, and three months postintervention, we collected data regarding attitudes towards computers and the Internet (Attitudes Towards Computers and the Internet Questionnaire [ATCIQ]; possible scores range from 5-50) as well as frequency of Internet use (composite measure). To examine changes in ATCIQ scores and Internet use over time, we used generalized estimating equations. We also collected qualitative data during intervention delivery. RESULTS: Among women in our sample, the median age was 56 years (interquartile range=52-63). All participants were black/African American and/or Latina. Seven participants (7/12, 58%) had a high school diploma (or equivalent) or higher degree. Ten participants (10/12, 83%) reported owning a mobile phone, while only one (1/12, 8%) reported owning a computer or tablet. Only one participant (1/12, 8%) reported having ever used the Internet or email. Internet nonusers cited lack of computer/Internet knowledge (6/11, 54%) and lack of access to a computer or similar device (4/11, 36%) as the main barriers to use. Over time, we observed an improvement in attitudes towards computers and the Internet (ATCIQ scores: 33.5 at baseline, 35 at intervention completion, and 36 at three months postintervention; P=.008). No significant increase in Internet use was observed (P=.61). Qualitative findings indicated excitement and enthusiasm for the intervention. CONCLUSIONS: In our sample of urban, technology-inexperienced HIV-positive women, participation in Get+Connected was associated with an improvement in attitudes towards computers and the Internet, but not Internet use. Changing attitudes is the first step in many health behavior change models, indicating that with improved access to computer and Internet resources, frequency of Internet use may also have increased. Future studies should consider addressing issues of access to technology in conjunction with Get+Connected.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.174
GPT teacher head0.481
Teacher spread0.307 · 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 designNon-randomized trial
Domainnot available
GenreProtocol

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

Citations5
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJMIR Research Protocols→Same topicHIV/AIDS Research and Interventions→French-language works237,207→