Family quality of life in families affected by HIV: the perspective of HIV-positive mothers
Bibliographic record
Abstract
The HIV infection of a family member can impact family quality of life (FQoL). The objectives of this study are to (1) describe patterns of FQoL among mothers living with HIV (MLHIV) and (2) identify key factors associated with FQoL in families affected by HIV. Recruitment took place in HIV-specialized clinics and community organizations. A 100 MLHIV and 67 of their children participated in this study. Mothers were on average 40.8 years old and reported having an average of two dependent children at home (M = 2.1, SD = 1.0). Participating children were 16.2 years old, on average. Half of the children were boys (50.8%). More than half were aware of their mother's positive HIV status (68.2%) and 19.7% were diagnosed with HIV. All HIV-positive children were aware of their status. A latent profile analysis was performed on the five continuous indicators of FQoL, and three main profiles of self-reported FQoL among MLHIV were established: high FQoL (33%), moderate FQoL (58%), and low FQoL (9%). Among the mothers' characteristics, education, physical functioning, social support, and resilience increased FQoL, while anxiety and irritability decreased FQoL. Among the children's characteristics, resilience followed the FQoL profile. A trend was observed toward children's greater awareness of the mother's HIV status in high and low FQoL profiles. Additionally, irritability tended to be higher within the lower FQoL profile. FQoL profiles can be used to identify families needing special care, particularly for family interventions with both parents and children. Other relevant indicators must be studied (e.g., closeness and support between family members, availability and accessibility of care, family structure, father-child relationships, and medical condition of the mother) and longitudinal research conducted to estimate the direction of causality between FQoL profile and individual family member characteristics.
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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 | 0.000 | 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 | 0.000 | 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".