A principal component analysis of the post-secondary student stressors index in a sample of Ontario students
Bibliographic record
Abstract
Post-secondary students report high levels of stress and mental health challenges. Identifying the key sources of stress can guide efforts to mitigate the most significant stressors and better support students' mental health. The Post-Secondary Student Stressors Index (PSSI), a 46-item inventory, was designed to comprehensively assess stressors specific to post-secondary students. However, its dimensional structure and its association with mental health indices require further validation. In the present study, a Principal Component Analysis was conducted to examine the structure of the PSSI, and the associations between the resulting stressor components and several mental health indices. Participants included 1,214 first-year students (Mage = 18.14 years, SD = 0.95), who completed the PSSI, as well as measures of perceived stress, depressive symptoms, and anxiety symptoms. Results suggested 12 components that accounted for 42 of the original 46 items, with most components demonstrating moderate to high internal consistency (α = .70 -.90). Correlational analyses revealed positive associations between the PSSI components and measures of perceived stress, depressive symptoms, and anxiety symptoms, although components with lower endorsements were associated with weaker correlations. By identifying valid and reliable components of the PSSI, this study facilitates the use of specific stressor components in future research on student stress and mental health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".