Determınıng The Relatıonshıp Between Nursıng Students’ Alexıthymıa Levels and Submıssıve Behavıor and Self-Esteem
Bibliographic record
Abstract
Aim: This study was conducted to examine the relationship between that nursing students’ alexithymia levels with submissive behavior and self-esteem. Material and Method: The population of the study consists of nursing students studying at Kilis 7 Aralık University. Its sample consists of 226 nursing students. The study was conducted between January February 2021. Toronto Alexithymia Scale, Submissive Behaviors Scale and Rosenberg Self-Esteem Scale were used for data. The data were evaluated in the SPSS 24.0 statistics program. In addition to descriptive statistics, Kruskal-Wallis, Mann-Whitney U and correlation tests were used to evaluate the data obtained in the study. Ethics committee and institution permission was obtained in order to conduct the study. Findings: Nursing students Toronto Alexithymia Scale total score average is 51.94 ± 9.97, Submissive Behaviors Scale total score average is 40.57 ± 9.90, Rosenberg Self-Esteem Scale total score average is found as 29.63 ± 4.18. Nursing students alexithymia levels with between submissive behavior was determined positive way a weak relationship (r = 0.369, p = 0.000). Students’ alexithymia levels with between Self-Esteem was found negative way a middle-level relationship (r = -0.461, p = 0.000). It was determined that 51.3 % of the Toronto Alexithymia Scale received > 52 points. Result: Nursing students’ alexithymia level were determined that submissive behavior and self-esteem are middle. As alexithymia level increased, also is increased show submissive behavior and as alexithymia level decreased, was determined self-esteem increased.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".