Use of Internet Health Information Among Students in Jeddah, Saudi Arabia: A Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Internet is a resource used to deliver health information, and has the potential to provide nutrition education in particular for individuals with a good level of education. The purpose of this study was to investigate the use of internet as a source for health information and analyzing the related factors for internet as a source for health information among students in Jeddah, Saudi Arabia. METHODS: We recruited 164 high schools, undergraduate and postgraduate students living in Jeddah, Saudi Arabia. A self-administered structured questionnaire to collect data on searching the internet for health information was used. It included frequency and timing of search, type of information, use of information in decision making, general health condition and socio-demographic characteristics. Differences between students who perceived and those who did not perceive improvement in health care after using internet health information were assessed using the chi-squared test. RESULTS: 92.7% of the students usually searched the internet for health information and 84.8% perceived internet health information as a help towards improving their health status. Students at higher educational levels talked significantly more often with their doctors regarding the health information they got from the internet (p = 0.014). We found significantly higher rates of perceived improvement in health among females (p <0.001), participants who trusted the health information they got from the internet (p <0.001), those who searched the internet for health information for themselves and other persons (p = 0.034), who searched for information on health care, physical fitness and nutrition and specific diseases (p = 0.005) and those who did it to increase their knowledge (p = 0.024). CONCLUSION & RECOMMENDATIONS: The majority of participants perceived the health information they got from the internet as a help towards improving their health status. Interventions should be developed to enhance the use of internet health information among males and high school students.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".