Eye Care Service Use and Associated Health-Seeking Behaviors Among Malawian Adults: Secondary Analysis of the Malawi Fifth Integrated Household Survey 2019-2020
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: The use of eye care services varies among different population groups. Objective: This study aimed to assess self-reported eye care use (ECU) and associated demographic factors among Malawian adults. Methods: This study used secondary data from the Malawi Fifth Integrated Household Survey 2019-2020, a nationally representative survey. The study included 12,288 households and 27,336 individuals 15 years and older. We entered age, sex, level of education, residency (urban/rural), and chronic disease into a logistic regression model, and used a confusion matrix to predict the model's accuracy. A P value <.05 was considered statistically significant. Results: About 60.6% (95% CI 60.0%-61.2%) of those with eye problems accessed formal care 2 weeks before the survey date. A logistic regression model showed that ECU was positively associated with education compared to none (odds ratio [OR] 6.6, 95% CI 5.927-7.366; P<.001), males compared to females (OR 1.2, 95% CI 1.104-1.290; P<.001), and urban residence compared to rural (OR 1.2, 95% CI 1.118-1.375; P<.001). ECU was negatively associated with age (OR 7, 95% CI 6.782-8.476; P<.001) and having chronic diseases (OR 0.6, 95% CI 0.547-0.708; P<.001). Conclusions: Social support, women empowerment, education, and mobile clinics are key strategic areas that would increase access to eye care in Malawi. Further studies can investigate ECU among the pediatric population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it