’Less is more’: validation with Rasch analysis of five short-forms for the Brain Injury Rehabilitation Trust Personality Questionnaires (BIRT-PQs)
Bibliographic record
Abstract
Background Previous analyses demonstrated a lack of unidimensionality, item redundancy, and substantial administrative burden for the Brain Injury Rehabilitation Trust Personality Questionnaires (BIRT-PQs).Objective To use Rasch Analysis to calibrate five short-forms of the BIRT-PQs, satisfying the Rasch model requirements.Methods BIRT-PQs data from 154 patients with severe Acquired Brain Injury (s-ABI) and their caregivers (total sample = 308) underwent Rasch analysis to examine their internal construct validity and reliability according to the Rasch model.Results The base Rasch analyses did not show sufficient internal construct validity according to the Rasch model for all five BIRT-PQs. After rescoring 18 items, and deleting 75 of 150 items, adequate internal construct validity was achieved for all five BIRT-PQs short forms (model chi-square p-values ranging from 0.0053 to 0.6675), with reliability values compatible with individual measurements.Conclusions After extensive modifications, including a 48% reduction of the item load, we obtained five short forms of the BIRT-PQs satisfying the strict measurement requirements of the Rasch model. The ordinal-to-interval measurement conversion tables allow measuring on the same metric the perception of the neurobehavioral disability for both patients with s-ABI and their caregivers.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".