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Record W3159950555 · doi:10.1097/jnc.0000000000000253

Global and Leisure-Time Physical Activity Levels Among People Living With HIV on Antiretroviral Therapy in Burundi: A Cross-sectional Study

2021· article· en· W3159950555 on OpenAlexaff
Eric Havyarimana, Alexis Sinzakaraye, Zéphyrin Ndikumasabo, Gilles Caty, Chanelle Ella Ininahazwe, Charles Sèbiyo Batcho

Bibliographic record

VenueJournal of the Association of Nurses in AIDS Care · 2021
Typearticle
Languageen
FieldMedicine
TopicHIV-related health complications and treatments
Canadian institutionsCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsCross-sectional studyMedicineHuman immunodeficiency virus (HIV)Physical activityMultivariate analysisGerontologyLeisure timeAntiretroviral therapyPhysical therapyFamily medicineViral loadInternal medicine

Abstract

fetched live from OpenAlex

ABSTRACT: The latest recommendations for HIV therapeutic management emphasize the importance of regular physical activity (PA). This cross-sectional study assessed the self-reported level of PA, amount of leisure time PA (LTPA), and the predictors of PA practiced in 257 people living with HIV (PLWH) in Burundi. The World Health Organization recommends 150 min of PA per week. In our study, 80.2% of the participants met this recommendation. Participants were more engaged in PA at work (436.8 ± 682.1 min/week) compared with leisure time (231.7 ± 383.8 min/week) and transportation (235.9 ± 496.5 min/week). Multivariate analysis revealed that men (β = -101.65; p = .01) who were white-collar workers (β = 67.21; p < .03) with higher education level (β = 274.21; p < .001) reported higher levels of LTPA than other groups. Integrating PA counseling into the routine care and implementing community-based exercise programs could enhance participation in PA in PLWH.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0000.000
Research integrity0.0010.001
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 head0.015
GPT teacher head0.344
Teacher spread0.329 · 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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Association of Nurses in AIDS CareSame topicHIV-related health complications and treatmentsFrench-language works237,207