Exploring the role of motherhood in healthcare engagement for women living with HIV in the USA
Bibliographic record
Abstract
Mothers living with HIV are faced with managing their own complex healthcare and wellness needs while caring for their children. Understanding the lived experiences of mothers living with HIV, including grandmothers and mothers with older children - who are less explicitly represented in existing literature, may guide the development of interventions that best support them and their families. This study sought to explore the role of motherhood and related social/structural factors on engagement with HIV care, treatment-seeking behaviour, and overall HIV management among mothers living with HIV in the USA to inform such efforts. Semi-structured interviews were conducted between June and December 2015 with 52 mothers living with HIV, recruited from the Women's Interagency HIV Study (WIHS) sites in four US cities. Five broad themes were identified from the interviews: children as a motivation for optimal HIV management; children as providing logistical support for HIV care and treatment; the importance of social support for mothers; stressors tied to responsibilities of motherhood; and stigma about being a mother living with HIV. Findings underscore the importance of considering the demands of motherhood when developing more effective strategies to support mothers in managing HIV and promoting the overall health and well-being of their families.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".