The Relationship of Spiritual Well-Being and Involvement with Depression and Perceived Stress in Korean Nursing Students
Bibliographic record
Abstract
UNLABELLED: This study was conducted to identify the relationship among spiritual well-being, depression and perceived stress. Participants were 518 nursing students located in K province, Korea. DESIGN: Exploratory design was used for this study. Data were collected and analyzed by t-test, ANOVA, Pearson correlation coefficients. The results were as follows; 1) Participants' mean scores were Spiritual Well-Being 76.03 (15.74), Religious Well-Being 32.8 (15.74), Existential Well-Being 43.23 (8.12), depression 9.10 (7.06), and level of stress 15.47 (5.49). 2) Spiritual Well-Being, Existential Well-Being, and Religious Well-Being were significantly different with the number of attendance to religious ceremony, the degree of subjective satisfaction regard to major and idea for future employment. 3) Negative correlations existed between Spiritual Well-Being and participants' perceived stress, and depression. 4) Particularly, Existential Well-Being has more inverse correlation with depression and stress than Religious Well-Being. This investigation highlighted Existential Well-Being as an important factor with lower levels of depression and perceived stress. According to these result, Spiritual Well-Being promotion program is needed to develop as a positive concept to adjust college life and spiritual well-being is required to take care of patients as potential power for nursing students in their future.
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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 | 0.000 | 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) | 0.002 | 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".