The Relationship Between Women’s Health Literacy and COVID-19 Phobia: A Family Health Center Example in Turkey
Bibliographic record
Abstract
Objective: Women parents’ health literacy levels make it easier to understand the requirements and preventative measures during a pandemic. The aim of this study is to reveal the relationship and factors affecting women's fear of COVID-19 and health literacy.Methods: In this cross-sectional descriptive study, Personal Information Form, COVID-19 Phobia Scale (C19P-S), and Turkish Health Literacy Scale 32 (THLS 32) were used to gather data. The sample consisted of 161 women who applied to a family health center. Analysis of the data was done with frequency, percentage, mean, standard deviation, and minimum-maximum values. The suitability of variables to normal distribution was tested with Shapiro-wilks and Kolmogorov-Smirnov tests. For variables not conforming to normal distribution, nonparametric statistical tests were used using Q1: First quarter Q3: Third quarter and Median values. Mann-Whitney u and Kruskal-Wallis tests were used.Results: Participants’ average age was 35.79 ± 7.76. The health literacy total score is 64.93 ± 20.18 and COVID-19 Phobia Scale total score is 52.27 ± 13.13. No significant correlation was found between health literacy and COVID-19 phobia total scores.Conclusion: The COVID-19 phobia and health literacy levels were found to be moderate. A significant correlation was found between COVID-19 Phobia Scale total score and the fear caused by the news, frequent change in treatment and the negative effects of staying at home. Also, a significant correlation was found between THLS total score and participants’ education level and following health related news.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".