Precollege and In-College Bullying Experiences and Health-Related Quality of Life Among College Students
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Bullying is a commonly occurring problem behavior in youths that could lead to long-term health effects. However, the impact of school bullying experiences on health-related quality of life (HRQOL) among college students has been relatively underexplored. This study aimed to describe school bullying experiences and to empirically examine their associations with HRQOL among college students in Taiwan. METHODS: Self-administered survey data (response rate 84.2%) were collected from 1452 college students in 2013 by using proportional stratified cluster sampling. Different types of bullying experiences (ie, physical, verbal, relational, and cyber) before and in college, for bullies and victims, were measured. HRQOL was assessed by the World Health Organization Quality of Life (WHOQOL-BREF) Taiwan version. RESULTS: College students with cyber bullying-victimization experiences before college (β 0.060) reported significantly higher HRQOL in physical health. Regarding social relationships, those with verbal (β -0.086) and relational (β -0.056) bullying-victimization experiences, both before and in college, reported significantly lower HRQOL, whereas those with verbal (β 0.130) and relational (β 0.072) bullying-perpetration experiences in both periods reported significantly higher HRQOL. Students with cyber bullying-victimization experiences in college (β 0.068) reported significantly higher HRQOL in the environment domain. Last, the effects of verbal and relational bullying-victimization experiences on psychological HRQOL could be mediated and manifested through depression. CONCLUSIONS: Various types of bullying experiences occurring before and in college were differentially associated with HRQOL in different domains. These findings underscore the importance of developing school policies and health education initiatives to prevent school bullying and ameliorate its short-term and long-term effects on HRQOL.
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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 | 0.002 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".