Health Status of the Clinical Dental Students in the Jordanian Universities
Bibliographic record
Abstract
BACKGROUND: Dental students are subjected to many stresses that may affect their achievement. The purpose of this study is to assess the mental and physical health of dental students in two Jordanian Universities. METHODS: A total of 265 dental students and 228 non-dental students from two Jordanian Universities participated in the study. They completed the survey questionnaire and their responses were used in calculating the 0-100 scores for the eight health concepts by linear transformations of scores. The ANOVA test was used to determine the significant differences among the student groups, and Tukey test was used for multiple comparisons among groups. All tests were carried out at 95% confidence level. RESULTS: The results indicated that the dental students of the Jordan University of Science and Technology were of better health than their counterparts at the University of Jordan. The health scores attained by the dental students of the two universities were less than those of non-dental students of the same age. CONCLUSIONS: The physical and more significantly the mental health components of dental students should receive more attention, and further work is needed to detect the possible causes and find potent remedies for this problem. KEYWORDS: Health survey; Clinical students; Physical functioning; Mental health; Social functioning.
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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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".