Psychometric assessment of the Post- Secondary Student Stressors Index (PSSI)
Bibliographic record
Abstract
BACKGROUND: Previous research has linked excessive stress among post-secondary students to poor academic performance and poor mental health. Despite attempts to ameliorate mental health challenges at post-secondary institutions, there exists a gap in the evaluation of the specific sources of stress for students within the post-secondary setting. METHODS: The goal of this study was to develop a new instrument to better assess the sources of post-secondary student stress. Over the course of two years, the Post-Secondary Student Stressors Index (PSSI) was created in collaboration with post-secondary students as co-developers and subject matter experts. In this study, we used a combination of individual cognitive interviews (n = 11), an online consensus survey modeled after a traditional Delphi method (n = 65), and an online pre- (n = 535) and post-test (n = 350) survey to psychometrically evaluate the PSSI using samples of students from Ontario, Canada. We collected four types of evidence for validity, including: content evidence, response processes evidence, internal structure evidence, and relations to other variables. The test-retest reliability of the instrument was also evaluated. RESULTS: The PSSI demonstrated strong psychometric properties. Content validation and response processes evidence was derived from active student involvement throughout the development and refinement of the tool. Exploratory factor analysis suggested that the structure of the PSSI reflects the internal structure of an index, rather than a scale, as expected. Test-retest reliability of the instrument was comparable to existing, established instruments. Finally, the PSSI demonstrated good relationships with like measures of stress, distress, and resilience, in the hypothesized directions. CONCLUSIONS: The PSSI is a 46-item inventory that will allow post-secondary institutions to pinpoint the most severe and frequently occurring stressors on their campus. This knowledge will facilitate appropriate targeting of priority areas, and help institutions to better align their mental health promotion and mental illness prevention programming with the needs of their campus.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".