Mediators of antiretroviral adherence: A multisite international study
Bibliographic record
Abstract
The purpose of this study was to investigate the effects of stressful life events (SLE) on medication adherence (3 days, 30 days) as mediated by sense of coherence (SOC), self-compassion (SCS), and engagement with the healthcare provider (eHCP) and whether this differed by international site. Data were obtained from a cross-sectional sample of 2082 HIV positive adults between September 2009 and January 2011 from sites in Canada, China, Namibia, Puerto Rico, Thailand, and US. Statistical tests to explore the effects of stressful life events on antiretroviral medication adherence included descriptive statistics, multivariate analysis of variance, analysis of variance with Bonferroni post-hoc analysis, and path analysis. An examination by international site of the relationships between SLE, SCS, SOC, and eHCP with adherence (3 days and 30 days) indicated these combined variables were related to adherence whether 3 days or 30 days to different degrees at the various sites. SLE, SCS, SOC, and eHCP were significant predictors of adherence past 3 days for the United States (p = < 0.001), Canada (p = 0.006), and Namibia (p = 0.019). The combined independent variables were significant predictors of adherence past 30 days only in the United States and Canada. Engagement with the provider was a significant correlate for antiretroviral adherence in most, but not all, of these countries. Thus, the importance of eHCP cannot be overstated. Nonetheless, our findings need to be accompanied by the caveat that research on variables of interest, while enriched by a sample obtained from international sites, may not have the same relationships in each country.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".