Preliminary evaluation of the reliability and validity of the 3D printed Toronto Rehabilitation Institute-Hand Function Test in individuals with spinal cord injury
Bibliographic record
Abstract
The study objectives were to evaluate the inter-rater and intra-rater reliability; and criterion and construct validity of the 3D printed Toronto Rehabilitation Institute -Hand Function Test (3D TRI-HFT) in individuals with spinal cord injury (SCI). Observational study. Inpatient Rehabilitation Hospital. Four individuals with subacute and three individuals with chronic SCI. Reliability and validity of the 3D TRI-HFT was assessed within two interventional studies. Participants performed the 3D TRI-HFT, Graded Redefined Assessment of Strength, Sensibility and Prehension (GRASSP), Functional Independence Measure (FIM) and the Spinal Cord Independence Measure (SCIM) at baseline, after 20 and 40 sessions of therapy and at six month follow-up from baseline. 3D TRI-HFT assessments were graded at the time of performance and re-graded from the video recordings for purpose of reliability testing. Validity testing was done by comparing the scores on 3D TRI-HFT with the scores on the GRASSP, and the FIM and SCIM self care sub-scores. The 3D TRI-HFT had high intra-rater and inter-rater reliability in sub-acute and chronic SCI with ICC values exceeding 0.99. Moderate to strong correlations were found between 3D TRI-HFT object manipulation scores and the FIM and SCIM self care sub-scores, with r values in the range of 0.7–0.8. Strong correlations were found between the various components of GRASSP and the 3D TRI-HFT, with r values exceeding 0.9. The 3D TRI-HFT is a reliable and valid measure to assess unilateral hand gross motor function in individuals with SCI.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".