Keep it brief: Can a 4-item stress screener predict university adjustment over 18 months?
Bibliographic record
Abstract
The transition to university is an exciting yet challenging period for many students. While previous research has documented the association between stress and adjustment, little is known about the long-term effect of students’ early stress on their subsequent university adjustment. The present study sought to examine the effectiveness of a short, 4-item stress measure in predicting student adjustment to university following a 6- and 18-month delay. Participants were 122 first-year, undergraduate students (Mage = 18.36, SD = .89; 73.9% women) who reported their stress during their first semester (baseline), and university adjustment six months (T1) and 18 months later (T2). Baseline stress significantly predicted future adjustment to university at both timepoints, explaining 21% (T1) and 14% (T2) of the variance in adjustment. Results reinforce the importance of identifying early signs of stress during the transition to university given its enduring effect on students’ adjustment. Findings are discussed within the context of approaches to student 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".