Reliability of the seated postural control measure for adult wheelchair users
Bibliographic record
Abstract
PURPOSE: To evaluate the test-retest and interrater reliability of the Seated Postural Control Measure for Adults 1.0 (SPCMA 1.0). METHOD: The participants were evaluated first by two raters and then, 3 weeks later, by one rater. Section 1 (one item, seven-point scale) evaluates the adult's overall ability to control its posture in a sitting position. Sections 2 and 3 (22 items each, scored on a seven-point scale), evaluate the adult's postural alignment in a static position and the changes in postural alignment induced by a dynamic activity. RESULTS: For the test-retest reliability, the intraclass correlation coefficient (ICC) of section 1 was excellent (0.95) and moderate to good for sections 2 and 3 (0.60 - 0.62) and their subsections (0.47 - 0.78). For interrater reliability, the three sections had good to excellent ICCs (0.68 - 0.93) and their subsections had moderate to good ICCs (0.41 - 0.69). A large range was observed in Kappa coefficients (test-retest and interrater reliability) for the item analysis of the sections 2 and 3, due to a lack of variability in some items. CONCLUSIONS: The results confirm that the SPCMA is reliable as a whole. Suitable information has been obtained for the development of the SPCMA 2.0 and, although further psychometric testing is needed, the latter should improve clinical evaluation of seated postural control in adult wheelchair users.
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 | 0.008 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".