Wireless Physical Activity Monitor Use Among Adults Living With HIV: A Scoping Review
Bibliographic record
Abstract
Introduction: Physical activity (PA) can help promote healthy aging while addressing health-related challenges experienced with HIV infection. To determine the benefits of PA or consequences of inactivity, it is critical to ensure that we have accurate ways of measuring PA in the context of HIV infection. Wireless physical activity monitors (WPAMs) are increasingly used for measuring PA; however, evidence of their use in the context of HIV infection is unclear. Our aim was to characterize the literature (nature and extent and gaps in evidence) pertaining to WPAM use among adults living with HIV. Methods: We conducted a scoping review using the Arskey and O'Malley framework. We answered the following question: “What is the nature and extent of evidence pertaining to WPAMs and their use among adults living with HIV?” We searched databases including MEDLINE, EMBASE, CINAHL, PubMed, Cochrane, and PsycINFO from 1980 to September 2016. Two authors independently reviewed titles and abstracts, followed by full texts for inclusion. Two authors independently piloted and then extracted data from included articles. We described characteristics of included studies using frequencies and medians and collated results from text data using content analytical techniques. Results: Our search strategy yielded 1315 citations, of which 25 articles were included. The majority of articles (76%) were published between 2011 and 2016. Among a total sample of 1212 adults living with HIV in the included studies, 56% were women. Across the 20 studies, 23 WPAMs were used including actigraphs (n = 10 WPAMs), accelerometers (n = 8), and pedometers (n = 5) to measure PA. WPAMs were used primarily as an outcome measure of PA. No included studies assessed measurement properties of WPAMs among adults living with HIV. Conclusion: WPAM use in the context of HIV infection primarily involved measuring PA. Areas to address in future research include examining the effectiveness of WPAMs for enhancing PA and assessing measurement properties of WPAMs to ensure they accurately assess PA among adults living with HIV.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.017 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".