Student debt and its relation to student mental health
Bibliographic record
Abstract
The present paper provides an analysis of the relationship between attitudes toward debt and mental health among university undergraduates. Data were collected from the same cohort of students across their three years of university, with responses from 2146, 1360 and 1391 first, second and third year students, respectively. Mental health was measured using the General Population version of the Clinical Outcomes in Routine Evaluation (GP-CORE). Attitudes toward debt were measured using items that tapped current financial concerns and worry about debt on leaving university. Results showed that students become more concerned about their finances as they progress through university, that there was no relationship between anticipated debt and mental health and that attitudes toward debt were related to mental health levels. Students who were identified as having high financial concerns possessed significantly worse CORE-GP scores than students with low financial concern in all three years of university. In all three years students with high financial concerns felt more ‘tense, anxious or nervous’, more ‘criticised by other people’ and found it more ‘difficult getting to sleep or staying asleep’ than students with low financial concerns. There was also evidence that students with high worry about their debt anticipated leaving university with higher amounts of debt than low debt worry students. These findings are discussed in relation to the pattern of increased student debt in UK higher education.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".