Exploring the Interrelationships Between Physical Function, Functional Exercise Capacity, and Exercise Self-Efficacy in Persons Living with HIV
Bibliographic record
Abstract
While physical activity can mitigate the metabolic effects of HIV disease and HIV medications, many HIV-infected persons report low levels of physical activity. Purpose: To determine if there were differences between the subjective and objective assessments of physical activity while controlling for sociodemographic, anthropometric, and clinical characteristics. Setting/sample: A total of 810 participants across eight sites located in three countries. Measures: Subjective instruments were the two subscales of Self-efficacy for Exercise Behaviors Scale: Making Time for Exercise and Resisting Relapse and Patient-Reported Outcomes Measurement Information System, which measured physical function. The objective measure of functional exercise capacity was the 6-minute Walk Test. Analysis: Both univariate and multivariant analyses were used. Results: Physical function was significantly associated with Making Time for Exercise (β = 1.76, p = .039) but not with Resisting Relapse (β = 1.16, p = .168). Age (β = −1.88, p = .001), being employed (β = 16.19, p < .001) and race (βs = 13.84–31.98, p < .001), hip–waist ratio (β = −2.18, p < .001), and comorbidities (β = 7.31, p < .001) were significant predictors of physical functioning. The model predicting physical function accounted for a large amount of variance (adjusted R 2 = .938). The patterns of results predicting functional exercise capacity were similar. Making Time for Exercise self-efficacy scores significantly predicted functional exercise capacity (β = 0.14, p = .029), and Resisting Relapse scores again did not (β = −0.10, p = .120). Among the covariates, age (β = −0.16, p < .001), gender (β = −0.43, p < .001), education (β = 0.08, p = .026), and hip–waist ratio (β = 0.09, p = .034) were significant. This model did not account for much of the overall variance in the data (adjusted R 2 = .081). We found a modest significant relationship between physical function and functional exercise capacity ( r = 0.27). Conclusions: Making Time for Exercise Self-efficacy was more significant than Resisting Relapse for both physical function and functional exercise capacity. Interventions to promote achievement of physical activity need to use multiple measurement strategies.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".