THE RELATIONSHIP BETWEEN SOCIAL SUPPORT FROM PEERS AND FAMILY AND THE QUARTER LIFE CRISIS IN K-POP FANDOM
Bibliographic record
Abstract
Objective: This study aims to examine the relationship between peer and family social support and the quarter life crisis experienced by individuals within the K-pop fandom, specifically members of the Seventeen (Carat) fan community. Method: Using a quantitative correlational design, data were collected from 146 purposively selected participants out of a population of 250 fandom members. The analysis employed a multiple regression correlation test to assess the influence of social support on the quarter life crisis. Results: The findings indicate a significant negative relationship between peer social support and quarter life crisis (r = -0.385; p < .001), and between family social support and quarter life crisis (r = -0.445; p < .001). The combined contribution of peer and family social support to the reduction of quarter life crisis was 56.5%, suggesting that greater perceived support is associated with lower levels of psychological distress during emerging adulthood. Novelty: This research introduces a unique perspective by focusing on the psychosocial dynamics of the K-pop fandom—particularly the Seventeen fandom—which remains an underexplored population in psychological studies. The findings contribute to the growing discourse on youth mental health in digital fan communities, emphasizing the protective role of social support.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".