Non‐Motor Fluctuations in Parkinson's Disease: Validation of the Non‐Motor Fluctuation Assessment Questionnaire
Bibliographic record
Abstract
BACKGROUND: In patients with Parkinson's disease (PD), sleep, mood, cognitive, autonomic, and other non-motor symptoms may fluctuate in a manner similar to motor symptoms. OBJECTIVES: To validate a final version of a patient-rated questionnaire that captures the presence and severity of non-motor fluctuations in levodopa-treated PD patients (NoMoFA). METHODS: We recruited PD subjects from five movement disorders centers across the US and Canada. We assessed the internal consistency, floor and ceiling effects, test-retest reliability, and concurrent validity of NoMoFA. Classical test theory and item response theory methods informed item reduction and Delphi process yielded a final questionnaire. RESULTS: Two hundred subjects and their care-partners participated in the study (age: 66.4 ± 9.6 years; disease duration: 9 ± 5.5 years; median Hoehn and Yahr [H&Y] OFF: 3 [range 1-5]; mean Unified Parkinson's Disease Rating Scale (UPDRS) III ON score: 27.4 ± 14.9). Acceptability of the scale was adequate. There were floor effects in 8/28 items. Cronbach's alpha was 0.894. While eight items had "item-to-total" correlations below the cutoff of 0.4, removing these items did not improve Cronbach's alpha. Test-retest reliability was acceptable (intraclass correlation coefficient [ICC] 0.73; 95% confidence interval, 0.64-0.80). Concurrent validity was adequate with all Spearman's rho values comparing NoMoFA score to other measures of parkinsonian severity showing significance and in the expected direction. A final Delphi panel eliminated one item to avoid redundancy. CONCLUSIONS: The final 27-item self-administered NoMoFA is a valid and reliable questionnaire, capturing both static and fluctuating non-motor symptoms in PD. © 2021 International Parkinson and Movement Disorder Society.
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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 | 0.006 |
| 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".