Stress levels, alexithymia, type A and type C personality patterns in undergraduate students.
Bibliographic record
Abstract
INTRODUCTION: Since there have been a number of empirical observations that may lead to the conclusion of an increasing rate of risk behaviors in Romanian students, such as aggression, over-competitive conduct and lack of collaboration, immorality, peer pressure and even an increasing rate of suicide, and suicide attempts, we have undergone a study to indentify if there is a high rate of risk type personality patterns that may lead to these deportments. MATERIAL AND METHODS: We have selected a total number of 500 students from the three largest universities in Bucharest, Romania--"Carol Davila" University of Medicine and Pharmacy (UMF), Bucharest Polytechnics University (UPB), and the Bucharest Academy of Economical Studies (ASE). All subjects received a questionnaire containing four diagnostic tools and several demographics questions. We have chosen the Twenty Item Toronto Alexithymia Scale (TAS20), the Jenkins Activity Survey (JAS-13) and the Anger-In Questionnaire for type C personality pattern. We have also added the Columbia stress analysis questionnaire for the evaluation of stress levels and coping capacity at the moment the subjects were interviewed. RESULTS: Columbia stress survey results confirm that there is a high stress level among students of all universities, but a more detailed stratification by university, gender and analyzed factor shows a very high F factor and T factor positive responses. Alexithymia, Type A and Type C personality patterns show a much higher prevalence than the general population, especially in medical students. We have found higher frequencies in men for all of the three studied parameters CONCLUSIONS: Approaching alexithymia and type A behavior both by cognitive methods and by assessing and addressing consequential risk factors should become an issue among universities.
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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 | 0.000 | 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 | 0.000 | 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) | 0.002 | 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".