E-Health Literacy and Health Information Seeking Behavior Among University Students in Bangladesh
Bibliographic record
Abstract
Web 2.0 has become a leading health communication platform and will continue to attract young users; therefore, the objective of this study was to understand the impact of Web 2.0 on health information seeking behavior among university students in Bangladesh. A random sample of adults (n = 199, mean 23.75 years, SD 2.87) participated in a cross-sectional, a survey that included the eHealth literacy scale (eHEALS) assessed use of Web 2.0 for health information. Collected data were analyzed using a descriptive statistical method and t-tests. Finally logistic regression analyses were conducted to determine associations between sociodemographic, social determinants, and use of Web 2.0 for seeking and sharing health information. Almost 74% of older Web 2.0 users (147/199, 73.9%) reported using popular Web 2.0 websites, such as Facebook and Twitter, to find and share health information. Current study support that current Web-based health information seeking and sharing behaviors influence health-related decision 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 | 0.000 | 0.002 |
| 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 | 0.001 | 0.000 |
| 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".