The Relationship between Emotional Intelligence (EQ) and Quarter Life Crisis in Final Year Students
Bibliographic record
Abstract
Quarter life crisis is a crisis that occurs in early adulthood characterized by the appearance of emotional instability. The beginning of a quarter life crisis occurs when an early adult individual becomes a final year student who does not have enough preparation to face the realities of the world. Final year students need to have the ability to overcome these emotional instability. One of them is by having emotional intelligence (EQ) which can form a positive force to maintain harmony within oneself. This study aims to determine the relationship between emotional intelligence (EQ) and quarter life crisis in final year students of the Faculty of Medicine and Health Sciences, Jambi University. This research is a quantitative study that has used correlational methods with cross-sectional design. The sampling technique has used Proportionate Stratified Random Sampling with research instruments in the form of questionnaires in the form of SEIS and a quarter life crisis scale. Data analysis using univariate analysis and bivariate analysis with gamma correlation test. There is a significant relationship between emotional intelligence (EQ) and quarter life crisis in final year students of the Faculty of Medicine and Health Sciences, University of Jambi. The emotional intelligence (EQ) variable has a negative relationship with the quarter life crisis variable in final year students of the Faculty of Medicine and Health Sciences, University of Jambi. The lower the emotional intelligence (EQ), the higher the quarter life crisis and vice versa. Final year students are expected to improve emotional intelligence (EQ) as an adaptive coping mechanism to deal with quarter life crisis.
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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 | 0.001 |
| 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) | 0.003 | 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".