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Record W7147200693 · doi:10.2196/80705

Acceptability, feasibility, and user experiences of NOLA Gem: a geospatially customizable culturally tailored JITAI for violence-affected people living with HIV (Preprint)

2025· article· en· W7147200693 on OpenAlexvenueno aff
Simone J. Skeen, Stephanie Tokarz, Rayna E. Gasik, Ethan A. Smith, Katherine P. Theall, Gretchen Clum

Bibliographic record

VenueJMIR Human Factors · 2025
Typearticle
Languageen
FieldComputer Science
TopicInnovative Human-Technology Interaction
Canadian institutionsnot available
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)Qualitative researchFocus groupNarrativeWork (physics)Perspective (graphical)Context (archaeology)

Abstract

fetched live from OpenAlex

Background: Posttraumatic stress, along with comorbid mental health challenges and hazardous alcohol use, disproportionately affects people living with HIV. The drivers of these stressors are both intraindividual, rooted in early life adversity and firsthand violence exposures, and contextual, often place-based. Imparting effective coping skills and distinguishing between changeable and unchangeable stressors can improve stress management in the short term, with cascading effects on key HIV continuum of care end points, such as antiretroviral therapy adherence. However, problem- and emotion-based coping skills, delivered via traditional linear in-person group modalities, may falter in the moment. To address this, we adapted the evidence-based Living in the Face of Trauma intervention into an iOS- and Android-native app, featuring daily diary-triggered coping skills recommendations, self-guided Living in the Face of Trauma psychoeducational sessions, and a customizable geofencing function. Objective: This mixed methods study aimed to examine the acceptability, feasibility, and user experiences of NOLA (New Orleans, Louisiana) Gem, focusing on user interaction costs relative to geographic ecological momentary assessment (GEMA) alone and refining future optimization options. Methods: People living with HIV (N=32) were recruited across New Orleans and initially randomized 1:1 to treatment (NOLA Gem + GEMA) versus control (GEMA) for 21 days. Feasibility was assessed via enrollment and attrition rates. At the immediate postassessment, participants completed acceptability and usability measures and a brief structured usability interview. Analyses included descriptive statistics, bivariate logit modeling, and synergistic human-large language model deductive coding. Results: In total, 30 participants (n=22 in the GEMA + NOLA Gem treatment arm) completed the pilot, representing 94% (n=29) of baseline enrollees. Acceptability was very high across the board: 100% (n=30) of users considered NOLA Gem "very" or "somewhat" successful in addressing their daily lives, with 91% (n=28) endorsing increased calm and emotional well-being. In addition, 50% (n=11) of NOLA Gem users were "extremely likely" (Net Promoter Score=10/10) to recommend the app to friends. Eight (27%) GEMA and GEMA + NOLA Gem users reported privacy concerns. Eleven (50%) NOLA Gem users received geofencing alerts; perceptions of this feature's helpfulness were mixed. No statistically significant sociodemographic or clinical predictors of disparate acceptability or increased privacy concerns were found. No additional frictions were evidenced by GEMA + NOLA Gem versus GEMA users. Qualitatively, NOLA Gem users praised the just-in-time mindfulness, breathing, problem-solving skills delivery, and broader stress control and self-insight benefits. A subset of users pointed out the burdensome length and sometimes inconvenient timing of the daily diaries. Recommendations for next-generation personalization included user-specific dynamic daily diary and geofencing prompt tailoring. Conclusions: Our small pilot study demonstrated high NOLA Gem acceptability and feasibility, as well as a rich and beneficial user experience among people living with HIV, with clear and actionable opportunities for improvement.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.052
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.016
GPT teacher head0.295
Teacher spread0.279 · 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".

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Citations0
Published2025
Admission routes1
Has abstractno

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