An Assessment of the Psychometric Properties of the Perceived Stress Scale-10 (PSS10) with Business and Accounting Students
Bibliographic record
Abstract
Using a sample of 557 undergraduate business students from three U.S. comprehensive universities, this study examined: (a) the factor structure of the Perceived Stress Scale-10 (PSS10; Cohen and Williamson, 1988); (b) the invariance of its factor structure; (c) the scale's reliability; and (d) its convergent and divergent validity. Confirmatory factor analyses supported a structure with two primary factors, General Distress and Ability-to-Cope, loading on a single second-order factor, Perceived Stress. Furthermore, this model was confirmed for designated subpopulations including the 264 accounting majors who participated in the study. Notably absent in prior research, this study found two items, numbers 2 and 9, to load significantly on both the General Distress and Ability-to-Cope factors with men and the full sample, respectively. Item–total correlations, coefficient alphas, and Spearman-Brown reliability coefficients supported the reliability of the items loading on the full scale as well as on each of the two primary factors. Combined, these findings provide compelling evidence in support of the PSS10 as a stress assessment measure for business students in general, and accounting students in particular. In fact, given its practical expediency in terms of administration and scoring, the PSS10 appears to be a tool that could be used by university administrators and potentially by human resource personnel at accounting and business organizations to assess student/employee perceived stress levels before the onset of burnout tendencies, thus facilitating more timely and cost-effective intervention strategies.
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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 | 0.019 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".