Development of a Remote Version of the Graded Redefined Assessment of Strength, Sensation, and Prehension (GRASSP): Validity and Reliability
Bibliographic record
Abstract
BACKGROUND: The Graded Redefined Assessment of Strength, Sensation, and Prehension (GRASSP V1.0) was developed in 2010 as a 3-domain assessment for upper extremity function after tetraplegia (domains: Strength, Sensibility, and Prehension). A remote version (rGRASSP) was created in response to the growing needs of the field of Telemedicine. OBJECTIVE: The purpose of this study was to assess the psychometric properties of rGRASSP, establishing concurrent validity and inter-rater reliability. METHODS: Individuals with tetraplegia (n = 61) completed 2 visits: 1 in-person and 1 remote. The first visit was completed in-person to administer the GRASSP, and the second visit was conducted remotely to administer the rGRASSP. The rGRASSP was scored both by the administrator of the rGRASSP (Examiner 1), and a second assessor (Examiner 2) to establish inter-rater reliability. Agreement between the in-person and remote GRASSP evaluations was assessed using the intraclass correlation coefficient (ICC) and Bland-Altman agreement plots. RESULTS: The remote GRASSP demonstrated excellent concurrent validity with the GRASSP (left hand intraclass correlation coefficient (ICC) = .96, right ICC = .96). Concurrent validity for the domains was excellent for strength (left ICC = .96, right ICC = .95), prehension ability (left ICC = .94, right ICC = .95), and prehension performance (left ICC = .92, right ICC = .93), and moderate for sensibility (left ICC = .59, right ICC = .68). Inter-rater reliability for rGRASSP total score was high (ICC = .99), and remained high for all 4 domains. Bland-Altman plots and limits of agreements support these findings. CONCLUSIONS: The rGRASSP shows strong concurrent validity and inter-rater reliability, providing a psychometrically sound remote assessment for the upper extremity in individuals with tetraplegia.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".