Affiliate stigma and associated factors among informal caregivers of people with mental illness in southwestern Uganda: A multi-center cross-sectional study
Bibliographic record
Abstract
The stigma surrounding mental illnesses is widespread and informal caregivers of patients with mental illness face stigma because of their relationship with the patients they care for. Despite the key role played by these informal caregivers in the management of people with mental illness, few studies have assessed affiliate stigma and its factors associated among this population. This study aimed to investigate the prevalence of affiliate stigma and associated factors among caregivers of patients with mental illness in southwestern Uganda. We used a cross-sectional study design and enrolled 385 caregivers. We assessed affiliate stigma, depression, and social support using the affiliate stigma scale, patient health questionnaire-9 and social support using the social provision scale respectively. We ran multivariable logistic regression models to assess for the factors associated with affiliate stigma among caregivers. The prevalences of affiliate stigma and depression were 65.97% and 25.2% respectively. Factors associated with affiliate stigma included caregiving for one year or longer (AOR: 1.89; 95% CI: 01.07-03.35; p = 0.03), having more than one patient to care for (AOR: 3.40; 95% CI: 01.39-08.36; p = 0.01), being the only caregiver to the patient (AOR: 2.60; 95% CI: 1.27-5.33; p = 0.01), being depressed (AOR: 75.76; 95% CI: 10.03-572.26; p < 0.001), and social support (AOR: 0.14; 95% CI: 0.06-0.29; p = 0.04). This prevalence of affiliate stigma among caregivers of patients with mental illness is high in southwestern Uganda and depression is a key predictor. Considering the important role played by informal caregivers, more studies are necessary to inform interventions to address affiliate stigma, depression, and overall mental health of caregivers.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".