Reliability of the Second and Third Iterations of the Sensory–Motor Dysfunction Questionnaire in a Subclinical Neck Pain Population
Bibliographic record
Abstract
Background/Objectives: This study aimed to address limitations of the pilot reliability study on the Sensory–Motor Dysfunction Questionnaire (SMD-Q) in two parts. Part 1 evaluated the intra-rater reliability of SMD-Q version 2 (V2). Part 2 addressed V2’s limitations before assessing the intra-rater reliability of version 3 (V3). V2 framed questions as “over the past week”, whereas V3 also framed questions as “in a typical/usual week”. Methods: The SMD-Q was administered via QualtricsTM at baseline and 4 to 7 days later to subclinical neck pain participants, 51 in part 1 (32 F; mean age ± SD: 21.17 ± 2.66 y) and 27 in part 2 (20 F; mean age ± SD: 21.89 ± 2.81 y). Reliability statistics (quadratic weighted kappa (Kw) and Cronbach’s alpha (α)) were calculated for all items (V2) and total scores (V2 and V3). Results: There was excellent agreement for V2 total scores (Kw ≥ 0.75), and V3 total scores for “in a typical/usual week” (Kw ≥ 0.75), but fair to good agreement for V3 total scores of “over the past week” (0.40 < Kw < 0.75). V2 had acceptable (0.7 ≤ α < 0.8) to good internal consistency (0.8 ≤ α < 0.9), while V3 had good internal consistency for both administrations. Conclusions: Versions 2 and 3 of the SMD-Q appear to reliably capture disordered sensorimotor integration in people with subclinical neck pain, with improved reliability in V3 when questions are framed as “in a typical/usual week”. However, further research is needed to confirm this finding.
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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 | 0.014 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".