Preliminary evidence for the validity of the Brief Post-Secondary Student Stressors Index (Brief-PSSI): A cross-sectional psychometric assessment
Bibliographic record
Abstract
The brief version of the Post-Secondary Student Stressors Index (Brief-PSSI) was developed in order to improve the usability of the instrument as a method for evaluating the severity and frequency of stressors faced by post-secondary students. While the original 46-item instrument has been thoroughly psychometrically validated and successfully used among student populations, the length of the instrument limits its utility. Providing a valid, shortened version of the PSSI will enable institutions to include the tool on existing online surveys currently being deployed to surveil the mental health and wellbeing of their students. This study reports preliminary evidence in support of the validity and reliability of the Brief-PSSI using a cross-sectional pilot sample of students attending an Ontario university in 2022. A total of 349 participants (average age 25 (SD = 7.7), range 19-60) completed the first survey, while 149 completed the follow-up survey (average age of 26 (SD = 7.7), range 17-60). Evidence of internal structure, relations to other variables, and of test-retest reliability was assessed according to established index validation guidelines, including the specification of multiple-indicator, multiple-cause models, and Spearman's rho correlation coefficients. Results provide preliminary support for the validity and reliability of the tool, which demonstrated acceptable goodness-of-fit statistics, statistically significant relationships with like constructs in the hypothesized directions, and good test-retest reliability correlation coefficients. The Brief-PSSI is a useful tool for evaluating the sources of stress among post-secondary students, assessing both the severity of stress experienced and frequency with which each stressor occurred. Future research should explore the practical utility of adding the Brief-PSSI to existing survey assessments as well as pursue the continued collection of validation evidence for the tool among varied student populations.
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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 | 0.015 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".