A Systematic Review of the Validity and Reliability of the Patient-Determined Disease Steps Scale
Bibliographic record
Abstract
BACKGROUND: The Patient-Determined Disease Steps (PDDS) scale is a patient-reported measure of disability used by at least 3 North American multiple sclerosis (MS) registries. We conducted a systematic review of the psychometric properties of the PDDS scale as part of a harmonization effort related to disability measures used in MS registries. METHODS: We searched the EMBASE, Ovid Medline, Scopus, Cochrane Database of Systematic Reviews, CENTRAL, CINAHL Plus, and ClinicalTrials.gov databases from database inception through July 28, 2020. Two reviewers independently screened abstracts and full-text reports for study inclusion and data extraction and assessed study quality and risk of bias. We included studies that assessed the validity or reliability of the PDDS scale. We conducted a meta-analysis to quantitatively summarize the findings. RESULTS: From the 2476 abstracts screened, 234 articles underwent full-text review, of which 5 met the inclusion criteria. These studies assessed criterion validity, construct validity, and test-retest reliability. In all studies, criterion validity was assessed by correlating the PDDS scale score with the Expanded Disability Status Scale score (pooled r = 0.73; 95% CI, 0.66-0.79). Test-retest reliability was high (pooled intraclass correlation coefficient = 0.96; 95% CI, 0.92-0.99). CONCLUSIONS: In this systematic review, the PDDS scale demonstrated criterion and construct validity for assessing disability in individuals with MS who have mild to moderate disabilities. This review also supports the test-retest reliability of the PDDS scale, although further studies with larger samples are needed.
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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 | 0.030 | 0.121 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.012 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".