Rasch analysis of the firefighters’ critical incident inventory questionnaire
Bibliographic record
Abstract
BACKGROUND: The Critical Incident Inventory (CII) was developed to assess stressful exposures in firefighters and emergency service workers. The CII includes six subscales: trauma to self, victims known to fire-emergency worker, multiple casualties, incidents involving children, unusual or problematic tactical operations, and exposure to severe medical trauma. OBJECTIVES: To examine the construct validity of all subscales of the Critical Incident Inventory (CII) by assessing the unidimensionality of the scales, and the interval properties of CII subscales by examining fit to the Rasch model and ordering of item thresholds. METHODS: This was a secondary data analysis based on survey data collected from a sample of 390 firefighters. RESULTS: Item 4 and Item 20 were removed with the confirmation of unacceptable fit residual. This revised version of the CII showed satisfactory fit to the Rasch model by non-significant Chi-square test and acceptable level of item fit. We rescored the CII original version and considered all items as only dichotomous response options where 0 represented the original no experience, and 1 presents the combination of experiencing 1, 2, 3 cases. CONCLUSION: The re-appraisal of the revised version CII indicated a satisfactory level of Rasch model fit.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".