Emotional Self-Awareness and Quarter Life Crisis in Final Year of Undergraduate Nursing Students
Bibliographic record
Abstract
Background: A quarter-life crisis is when individuals experience an emotional crisis with negative feelings toward the future. Many responsibilities and demands on fourth-year students affect their psychology. A person with good self-awareness makes it easier to control emotions, read the surrounding situation, not be easily affected, and focus on himself. This study aims to analyse the relationship between self-awareness and quarter-life crisis in the final years of undergraduate nursing students. Methods: This research design is correlational with a cross-sectional approach. The sample in this study was 87 people, which was the whole population (Total Sampling). The research instrument used a self-awareness questionnaire and a quarter-life crisis questionnaire—data analysis using the Spearman Rank. Results: The study results showed that most respondents (55.2%) had sufficient emotional self-awareness, and most (52%) experienced a moderate quarter-life crisis. Analysis using the Spearman Rank test obtained a p-value of 0.018 with an error level of α = 0.05, meaning that there is a relationship between emotional self-awareness and quarter-life crisis with a strong category strength (r = -0.54) Conclusion: Some factors affect self-awareness, namely thoughts, feelings, knowledge behaviour, environment, and quarter-life crisis internal factors such as identity exploration, expectations, and religion, while external factors such as romantic relationships, work, family, and friends. Self-introspection strategies can increase self-awareness. Dealing with a crisis is not comparing yourself with others, communicating with parents, or finding professionals if the problem is getting complicated
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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 | 0.005 |
| 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 | 0.001 |
| 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".