Psychological Impact of Caregiving for Children With Eye Diseases: A Systematic Review and Meta-analysis
Why this work is in the frame
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Bibliographic record
Abstract
Purpose: To identify and characterize the psychological impact of caregiving for children with eye disease. Awareness of the caregiving experience and insight into the factors related to caregiver burden is necessary to support high-quality ophthalmic care and develop supportive interventions. Methods: The databases MEDLINE (Ovid), CINAHL, EMBASE, Cochrane Library, PsychINFO, PubMed, and Google Scholar were queried up to June 25, 2021. Studies included assessed the psychological impact of providing care to children with eye diseases. A risk of bias assessment was performed according to the Modified Downs and Black Checklist. Demographic data and measures of burden were extracted and tabulated. Results: A total of 2,823 articles were screened, 28 underwent data extraction, and 7 were included in the meta-analysis. The meta-analysis indicated significant levels of burden (40% mild, 95% CI: [0.28 to 0.53]; 59% moderate, 95% CI: [0.36 to 0.82]; 7% severe, 95% CI: [0.02 to 0.11]) and depression (26% mild, 95% CI: [0.17 to 0.35]; 8% moderate, 95% CI: [0.03 to 0.14]); 11% severe, 95% CI:[0.03 to 0.10]). Interventions such as educational programs, life skills training programs, and other home-based early intervention programs were shown to improve psychological well-being of families. Conclusions: Caregivers experience significant levels of burden and depression, which may, in turn, affect the level of ophthalmic care they can provide for their children. Further studies investigating educational or psychological interventions for parents are needed, because the small number of studies that investigated these types of interventions have reported reduced parental stress and improved well-being. [ J Pediatr Ophthalmol Strabismus . 2023;60(4):238–247.]
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.014 | 0.010 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 it