Web-Based Health Information Seeking Among Students at Kuwait University: Cross-Sectional Survey Study
Bibliographic record
Abstract
BACKGROUND: Owing to the revolution in technology, the internet has become an important aspect of people's lives. Modern technology is enabling people from diverse educational backgrounds to use the internet for several purposes, one of which is health information seeking. Recently, Web-based health information has become more popular among patients all over the world and among the general public. OBJECTIVE: This study aimed to investigate the use of Web-based health resources among undergraduate students from different faculties at Kuwait University. METHODS: The study employed a cross-sectional design with students selected from 8 faculties of Kuwait University, 4 faculties of Literature and 4 faculties of Science. Data were collected using structured questionnaires, and analysis was done using a chi-square test and binary logistic regression to determine the factors associated with seeking health information on the Web. RESULTS: The sample size obtained was 1132 with a response rate of 90.27% (1132/1254). Overall, the prevalence of students seeking Web-based health information was 92.66%. (1049/1132) The most significant factors associated with seeking health information on the Web were age, gender, faculty, year of study, primary source of internet, and level of experience with internet use. In total, 90.0% (325/361) of students who were aged older than 21 years used Web-based health information compared with 82.8% (275/332) of those who were aged 18 years. In addition, female students showed a higher prevalence (829/934, 88.8%) of Web-based health information seeking than males (210/270, 77.8%). Students who majored in faculties of Science were more likely to seek health information than those who majored in faculties of Literature. All the differences found in the study were statistically significant (P<.05). CONCLUSIONS: The study concluded that many people use the internet for seeking health information. Sociodemographic factors have a significant association with Web-based health information seeking. Therefore, doctors must educate the public about the health information websites that can be trusted.
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How this classification was reachedexpand
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 | 0.027 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.007 |
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; both teacher heads agree on what is shown here.
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".