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Record W2903883204 · doi:10.2196/10448

Testing the Efficacy of a Social Networking Gamification App to Improve Pre-Exposure Prophylaxis Adherence (P3: Prepared, Protected, emPowered): Protocol for a Randomized Controlled Trial

2018· article· en· W2903883204 on OpenAlex
Sara LeGrand, Kelly Knudtson, David Benkeser, Kathryn E. Muessig, Andrew Mcgee, Patrick S. Sullivan, Lisa Hightow‐Weidman

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJMIR Research Protocols · 2018
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersNational Institutes of HealthEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentEmory University
KeywordsRandomized controlled trialPsychological interventionIntervention (counseling)Men who have sex with menFormative assessmentmHealthPre-exposure prophylaxisMedicineUsabilityProtocol (science)Short Message ServicePsychologyInternet privacyFamily medicineMedical educationAlternative medicineNursingComputer scienceHuman immunodeficiency virus (HIV)

Abstract

fetched live from OpenAlex

BACKGROUND: HIV prevalence is high among young men who have sex with men (YMSM) and young transgender women who have sex with men (YTWSM), particularly among minorities. Despite its proven efficacy and safety, the uptake of and adherence to pre-exposure prophylaxis (PrEP) among YMSM and YTWSM is currently limited. To date, evidence-based interventions to promote and sustain PrEP adherence have been limited and not shown to be highly efficacious. Given the widespread adoption of smartphones, mobile apps can be utilized to increase PrEP adherence for many YMSM and YTWSM. OBJECTIVE: The study consists of a formative research phase to develop an app-based intervention, P3 (Prepared, Protected, emPowered), to increase PrEP adherence, and a randomized controlled trial (RCT) to test its efficacy. P3 is a mobile app built on an established health platform, which includes social networking and game-based components to encourage PrEP adherence among YMSM and YTWSM. P3+ includes all P3 features plus adherence counseling delivered via two-way text messaging (short message service, SMS) through the app. METHODS: The formative research phase includes usability testing to assess users' comprehension of P3's educational content, understanding and use of intervention features, and overall impressions of app functionality, followed by app refinements. A subsequent field trial will identify and resolve any remaining technical challenges. A three-arm RCT (P3, P3+, and standard of care) will then be conducted at 6 iTech subject recruitment venues to assess intervention efficacy and to conduct a comparison of costs to deliver the 2 intervention arms. RESULTS: This is an ongoing research project with initial results from the formative work expected in 2020 and those from the RCT in 2021. CONCLUSIONS: P3 aims to provide an engaging, interactive experience that is highly appealing for the target population, leveraging technology already heavily integrated into the lives of young people, and thus meeting users' needs in a familiar, stimulating way. If efficacious, P3 could be a sustainable, easily disseminated, lower-cost PrEP intervention for YMSM and YTWSM. Further, the research aims to determine the processes that are essential to developing and implementing future health-related gamification interventions. TRIAL REGISTRATION: ClinicalTrials.gov NCT03320512; https://clinicaltrials.gov/ct2/show/NCT03320512 (Archived by WebCite at http://www.webcitation.org/74OVZkICl). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/10448.

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.

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)0.012
metaresearch head score (Gemma)0.025
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.095
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.147
GPT teacher head0.526
Teacher spread0.379 · 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