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Record W4297268511 · doi:10.1101/2022.09.25.22280346

Wireless physical activity monitor use among adults living with HIV in a community-based exercise intervention study: a quantitative longitudinal observational study

2022· preprint· en· W4297268511 on OpenAlexafffundabout
Joshua R. Turner, Justin Cheng, Judy Chow, Farhanna Hassanali, Hayley Sevigny, Michael Sperduti, Soo Chan Carusone, Matthieu Dagenais, Kelly K. O’Brien

Bibliographic record

VenuemedRxiv · 2022
Typepreprint
Languageen
FieldMedicine
TopicHIV-related health complications and treatments
Canadian institutionsInstitute for Work & HealthBrock UniversityToronto Rehabilitation InstituteMcMaster UniversityUniversity of Toronto
FundersCanadian Institutes of Health ResearchUniversity of TorontoCanada Research Chairs
KeywordsObservational studyPsychological interventionMedicineMental healthIntervention (counseling)Social supportPhysical therapyPercentileLongitudinal studyGerontologyPsychologyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

ABSTRACT Objectives Our aim was to examine Wireless Physical Activity Monitor (WPAM) use and its associations with contextual factors (age, highest education level, social support, mental health) among adults living with HIV engaged in a community-based exercise (CBE) intervention. Design Quantitative longitudinal observational study. Setting Toronto YMCA, Ontario, Canada. Participants Eighty adults living with HIV who initiated the CBE intervention. Interventions Participants received a WPAM to track physical activity during a 25-week CBE intervention involving thrice-weekly exercise, supervised weekly (Phase 1) and a 32-week follow-up involving independent thrice-weekly exercise (Phase 2). Outcome measures Uptake was measured as participants who consented to WPAM use at intervention initiation. Usage was defined as the median proportion of days participants had great than 0 steps out of the total number of days in the study. We measured contextual factors using a baseline demographic questionnaire (age, highest education level), and median scores from the Medical Outcomes Study-Social Support Scale and Patient Health Questionnaire (mental health), where higher scores indicated greater social support and mental health concerns, respectively. We calculated Spearman correlations between WPAM usage and contextual factors defined as weak (ρ≥0.2, moderate (ρ≥0.4), strong (ρ≥0.6), or very strong (ρ≥0.8). Results Seventy-six of 80 participants (95%) consented to WPAM use. In Phase 1, 66% of participants (n=76) used the WPAM at least one day. Median WPAM usage was 50% (25 th , 75 th percentile: 0%, 87%; n=76) of days enrolled in Phase 1 and 23% (0%, 76%; n=64) of days during Phase 2. Correlation coefficients ranged from weak for age (ρ=0.26) and mental health scores (ρ=-0.25) to no correlation (highest education level, social support). Conclusions Most adults living with HIV consented to WPAM use, however, usage declined over time. Future implementation of WPAMs should consider factors to promote sustained usage by adults living with HIV. Trial Registration NCT02794415 STRENGTHS & LIMITATIONS OF THIS STUDY To our knowledge, this is the first quantitative study to measure wireless physical activity monitor (WPAM) use among adults living with HIV engaged in a community-based exercise intervention. The longitudinal study design enabled us to examine changes in WPAM use over time. Utilizing objective measures of physical activity (WPAM) and self-reported (questionnaire) measures of physical activity enabled us to investigate associations of different measurement approaches of physical activity levels among adults living with HIV. Limitations included variable and incomplete participant data across multiple data sources such as, WPAM synchronization, self-reported step count, and completion of weekly exercise questionnaires.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.176
Threshold uncertainty score0.350

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.127
GPT teacher head0.396
Teacher spread0.268 · 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 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

Citations0
Published2022
Admission routes3
Has abstractyes

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