Examining Multilevel Factors Associated with the Process of Resilience among Women Living with HIV in a Large Canadian Cohort Study: A Structural Equation Modeling Approach
Bibliographic record
Abstract
OBJECTIVES: We examined how multiple, nested, and interacting systems impact the protective process of resilience for women living with HIV (WLWH). METHODS: Using data from a Cohort Study, we conducted univariate analyses, multivariable logistic regression, and a 2-step structural equation modeling for the outcome, high resilience (N = 1422). RESULTS: Participants reported high overall resilience scores with a mean of 62.2 (standard deviation = 8.1) and median of 64 (interquartile range = 59-69). The odds of having high resilience were greater for those residing in Quebec compared to Ontario (adjusted odds ratio [aOR] = 2.1 [1.6, 2.9]) and British Columbia (aOR = 1.8 [1.3, 2.5]). Transgender women had increased odds of high resilience than cisgender women (aOR = 1.9 [1.0, 3.6]). There were higher odds of resilience for those without mental health diagnoses (aOR = 2.4 [1.9, 3.0]), non-binge drinkers (aOR=1.5 [1.1, 2.1]), and not currently versus previously injecting drugs (aOR = 3.6 [2.1, 5.9]). Structural equation modeling confirmed that factors influencing resilience lie at multiple levels: micro, meso, exo, and macro systems of influence. CONCLUSION: There is a need to consider resilience as the interaction between the person and their environments, informing the development of multilevel interventions to support resilience among WLWH.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".