The Relationship between Traumatic Experiences, the Prevalence of Social Anxiety and Insecure Attachment among University Students
Bibliographic record
Abstract
University students face unique challenges and are considered a vulnerable population, making it crucial to understand the impact of trauma on their mental health. This study aimed to investigate the associations between traumatic experiences, the prevalence of social anxiety, and insecure attachment among MSU students. The present study adopted a quantitative research approach using the Trauma Screening Questionnaire (TSQ), the DSM-5 Severity Rating of Social Anxiety Disorder (SAD-D), moreover, for the purpose of assessing PTSD, the Vulnerable Attachment Styles Questionnaire (VASQ), Social Anxiety Disorder Severity, and Insecure Attachment, respectively. A total of 406 respondents participated in the research. Through descriptive analysis, data were collected using three different assessments, revealing that 67% of the students were identified as having a high risk of post-traumatic stress disorder (PTSD), while 6.9% experienced severe social anxiety, which was relatively low compared to the total number. Additionally, 87% of the students displayed a high level of insecure attachment. In order to test the research hypotheses, Pearson correlation analysis, linear regression analysis and path analysis were conducted in this study. The study's findings demonstrated that there was a significant correlation between traumatic experiences and insecure attachment and a non-significant correlation between traumatic experiences and social anxiety. Additionally, traumatic experiences had a significant positive effect on insecure attachment but did not significantly affect social anxiety. Lastly, traumatic experiences did not significantly affect insecure attachment through social anxiety or traumatic experiences through social anxiety.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".