Health Literacy Cross-Sectional National Survey in Cameroon General Population
Bibliographic record
Abstract
Background: Health literacy (HL) is the ability of an individual to obtain and translate knowledge and information in order to maintain and improve health in a way which is appropriate to that individual and system contexts. It has become a priority for health in the 21st century, and many countries have included HL as a key priority in their policies and practices. However, in many African countries, such as Cameroon, information about the status of HL among population remains scarce. Objective: This study sought to describe the HL level of the Cameroonian population and its determinants. Methods: A cross-sectional national survey using the European Health Literacy Survey Questionnaire short forms (HLS-EU-Q16) was conducted. Both English and French version of HLSEU16 were used due to the fact that the country is bilingual. 1,226 persons (50.5% females, ages 15-96 years, mean age 27.99 years, standard deviation 9.73) completed an online (47%) and paper (53%) questionnaire. Results: At least one quarter (1/4) of respondents (24.6%) showed insufficient HL and 74.3%, almost three quarter (3/4) had limited (insufficient and problematic) HL. Sufficient HL was predominant in all subcategories of the population. Subgroups within the population with low HL were those with more than two chronic diseases (F(3; 1,222) = 4.673, p = .003) and those living in rural areas (F(2; 1,223) = 21.870, p < .001). Participants with high HL evaluated their health as very good (F(3; 1,222) = 24.586, p< .001) and were satisfied with their life (F(3; 1,222) = 15.317, p< .001). Discussion and conclusion: Limited HL represents an important challenge for health policies and practices across Cameroon like in many European countries. The influence of socio-cultural aspect in HL must be taken into account when developing HL tools to ensure quality measurement and to improve health equity around the world.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".