Personal characteristics and styles of coping with stress of nursing students of a university in Turkey
Bibliographic record
Abstract
Objective: University studentship and the university life itself have the potential to create worry and stress. Nursing education is a hard and stressful process. The purpose of this study is to identify nursing students’ ways of coping with stress. Methods: The study was designed as a descriptive and cross-sectional. Target population of this study was all the students who were enrolled in a nursing school of a university located in Turkey. The data were collected “Personal Information Form”, developed by the researchers in light of the related literature, with a view to identifying socio-demographic features of the participants and “Ways of Coping Questionnaire” with a view to finding out the ways of coping with stress. Results: The participants of the study were 467 students. An evaluation of the WoCQ sub-scale mean scores of the nursing students in the present study showed that they got 21.15 ± 3.92 from the self-confident style, 14.03 ± 2.87 from the optimistic style, and 12.04 ± 2.97 from the seeking social support. An evaluation of the WoCQ sub-scale mean scores of the nursing students according to grade level shows that first graders got 12.13 ± 2.19 from the submissive style ( p = .037), who were pleased with the school tended to be more self-confident and who could not communicate with the opposite sex tended to have a more helpless style ( p = .004) in coping with stress. Conclusions: Results of the present study indicate that various factors play a role in nursing students’ ways of coping with stress and they seem to cope with stress effectively.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".