Depresi Mahasiswa Ditinjau dari Keberfungsian Keluarga dan Quarter Life Crisis
Bibliographic record
Abstract
The pressure faced by college students in the digital era has become increasingly complex. Not only are they expected to be independent and succeed academically and in their careers, but they also often experience social pressure due to peers’ success shared on social media. This can trigger feelings of inferiority, anxiety, and even depression. One of the main factors contributing to depression in early adulthood is the inability to cope with life transitions, commonly referred to as a quarter-life crisis. In addition, family functioning also plays a crucial role in supporting students' mental health. This study aims to examine the simultaneous influence of family functioning and quarter-life crisis on the level of depression among university students. The research employs a quantitative approach with a causal design. The sampling technique used is purposive sampling, involving 231 student respondents from various regions in Indonesia. The measurement tools include the Family Functioning Scale adapted from the Family Assessment Device (FAD) by Epstein, Baldwin, and Bishop (1983), consisting of 52 valid items with a Cronbach’s Alpha reliability of 0.950; the Quarter-Life Crisis Scale, based on the theory of Alexandra Robbins and Abby Wilner (2001), consisting of 26 items with a reliability of 0.856; and the Depression Scale using the standardized Beck Depression Inventory-II (BDI-II) by Beck (1991).The results show that, simultaneously, family functioning and quarter-life crisis have a significant effect on students' depression levels, with a significance value of 0.000 (p < 0.05). Partially, family functioning has a negative effect on depression (p = 0.000 < 0.05), meaning that the better the family functioning, the lower the level of student depression. However, partially, the quarter-life crisis does not have a significant effect on depression, with a significance value of 0.405 (p > 0.05).
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".