A Study of the Relationship between Internet Dependence and Social Skills of Students of Medical Sciences
Bibliographic record
Abstract
Introduction: Internet dependence is a topic of interest that has been discussed as a behavior-based addiction in recent years and has become a growing issue in the information technology era. This addiction has caused many problems for college students. In this regard, the current study aimed to investigate the relationship between Internet addiction and social skills of students of Medical Sciences. Methods: This is a descriptive-correlational study. The sample included 354 medical students who were selected through applying stratified random sampling method and were tested using two questionnaires of Internet Addiction and Social Skills. Data were analyzed applying the Pearson correlation coefficient and stepwise regression analysis. Results: The findings indicated that there were significant positive relationships between Internet dependence and social skills. Internet dependence has a reversed relation with initiation and termination, assertiveness, social reinforcement, empathy, and cooperation. Increasing Internet dependence, these skills weakened. However, no significant correlation was found between Internet dependence and orientation skills. Moreover, the results of the regression analysis showed that these five variables predicted about 66% of the criterion variable (internet dependence). Conclusion: Since Internet addiction can falter students’ social skills and has strong negative effects on interpersonal communication and social interaction, it is essential to make efforts to give students’ use of the Internet a specific direction to avoid its probable adverse effects.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.008 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".