Functional Health Literacy Among Chinese Populations and Associated Factors: Latent Class Analysis
Bibliographic record
Abstract
BACKGROUND: Poor functional health literacy has been found to be independently associated with poor self-assessed health, poor understanding of one's health condition and its management, and higher use of health services. Given the importance of functional health literacy, it is necessary to assess the overall status of functional health literacy in the general public. However, the literature review shows that no studies of functional health literacy have been conducted among the Chinese population in China. OBJECTIVE: This study aimed to classify Chinese populations into different functional health literacy clusters and ascertain significant factors closely associated with low functional health literacy to provide some implications for health education, medical research, and public health policy making. METHODS: We hypothesized that the participants' functional health literacy levels were associated with various demographic characteristics. Therefore, we designed a four-section questionnaire including the following information: (1) age, gender, and education; (2) self-assessed disease knowledge; (3) 3 validated health literacy assessment tools (ie, the All Aspects of Health Literacy Scale, the eHealth Literacy Scale, and the 6-item General Health Numeracy Test); and (4) health beliefs and self-confidence measured by the Multidimensional Health Locus of Control Scales Form B. Using randomized sampling, we recruited survey participants from Qilu Hospital affiliated to Shandong University, China. The questionnaire was administered via wenjuanxing. A returned questionnaire was valid only when all question items included were answered, according to our predefined validation criterion. All valid data were coded according to the predefined coding schemes of Likert scales with different point (score) ranges. Finally, we used latent class analysis to classify Chinese populations into clusters of different functional health literacy and identify significant factors closely associated with low functional health literacy. RESULTS: All data in the 800 returned questionnaires proved valid according to the predefined validation criterion. Applying latent class analysis, we classified Chinese populations into low (n=292, 36.5%), moderate-to-adequate (n=286, 35.7%), and low-to-moderate (n=222, 27.8%) functional health literacy groups and identified five factors associated with low communicative health literacy: (1) male gender (aged 40-49 years), (2) lower educational attainment (below diploma), (3) age between 38 and 68 years, (4) lower self-efficacy, and (5) belief that staying healthy was a matter of luck. CONCLUSIONS: We classified Chinese populations into 3 functional health literacy groups and identified 5 factors associated with low functional health literacy. These associated factors can provide some implications for health education, medical research, and health policy making.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".