Longitudinal associations between sense of belonging, imposter syndrome, and first-year college students’ mental health
Bibliographic record
Abstract
Objective: The first year of college is a time of major changes in social dynamics, raising questions about ways to promote students’ mental health. We examined longitudinal associations between students’ sense of belonging, imposter syndrome, depressive symptoms, and well-being. Participants: Fifty-eight first-year college students at a university in the United States participated in the study. Methods: Students completed questionnaires during the first 6 months of college (T1) and at the end of the academic year (T2). Results: Greater sense of social and academic belonging was correlated with lower imposter syndrome, depression, and greater well-being at T1. Accounting for T1 measures, lower imposter syndrome predicted greater well-being but not depression at T2. Accounting for T1 mental health, belonging was not a significant predictor of depression or well-being at T2. Conclusion: Increasing sense of belonging and addressing imposter syndrome early in the transition to college may be critical in promoting mental health.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".