Measurement properties of the Michigan hand outcomes questionnaire: Rasch analysis of responses from a traumatic hand injury population
Bibliographic record
Abstract
This study aimed to use Rasch analysis to test the content, scoring, and measurement properties of the Michigan Hand Outcomes Questionnaire (MHQ). MHQ scores from 196 patients with hand and wrist conditions were collected in an outpatient hand rehabilitation facility. Rasch analysis was conducted to assess the fit statistics of MHQ to confirm the scaling structure of disability subscales, and to identify differential item functioning. The MHQ did not fit with the Rasch model (χ2 = 2376.78, df = 74, p < 0.001), and most thresholds of item responses were disordered. The original scoring algorithm derived from 5-point Likert response options was adjusted to 3-point Likert (10 items) and 4-point Likert (11 items) based on the visual inspection of the thresholds map. Differential item functioning was present in the revised scale based on the age, sex, and dominant hand. Only 3 revised subscales of the MHQ including activities daily living (one hand), aesthetics, and satisfaction showed acceptable fit to the Rasch model. Unidimensionality was achieved in all revised subscales. The overall MHQ had a substantial misfit from the Rasch model. Despite efforts of item reduction and rescoring, we did not reach a satisfactory solution. This calls into question the validity of the statistical evaluations performed on this scale using the traditional scoring.Implications for rehabilitationThe MHQ was designed to measure different dimensions of pain and disability but demonstrates multiple measurement problems that undermine it use in present form.It is not appropriate to sum all 37 items of the MHQ into a single score.Three subscales of activities daily living (one hand), aesthetics, and satisfaction can provide unidimensional subscales scores with interval level scaling if scored with our proposed Rasch-based revised scoring.The 27-item version of the MHQ is shown to have strong psychometric properties for administration with patients with hand injuries; however, it requires further validation. The MHQ was designed to measure different dimensions of pain and disability but demonstrates multiple measurement problems that undermine it use in present form. It is not appropriate to sum all 37 items of the MHQ into a single score. Three subscales of activities daily living (one hand), aesthetics, and satisfaction can provide unidimensional subscales scores with interval level scaling if scored with our proposed Rasch-based revised scoring. The 27-item version of the MHQ is shown to have strong psychometric properties for administration with patients with hand injuries; however, it requires further validation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.030 | 0.081 |
| 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 | 0.000 | 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".