Assessment of the psychometric properties of the Italian version of the New Freezing of Gait Questionnaire (NFOG-Q-IT) in people with Parkinson disease: a validity and reliability study
Bibliographic record
Abstract
INTRODUCTION: Freezing of gait (FOG) in Parkinson's disease (PD) is a challenging clinical symptom to assess, due to its episodic nature. A valid and reliable tool is the New FOG Questionnaire (NFOG-Q) used worldwide to measure FOG symptoms in PD. OBJECTIVE: The aim of this study was to translate, to culturally adapt, and to test the psychometric characteristics of the Italian version of the NFOG-Q (NFOG-Q-It). METHODS: The translation and cultural adaptation was based on ISPOR TCA guidelines to finalize the 9-item NFOG-Q-It. Internal consistency was assessed in 181 Italian PD native speakers who experienced FOG using Cronbach's alpha. Cross-cultural analysis was tested using the Spearman's correlation between the NFOG-Q-It and the Modified Hoehn-Yahr Scale (M-H&Y). To assess construct validity, correlations among NFOG-Q-It, Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS), Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), the Falls Efficacy Scale-International (FES-I), the 6-min Walking Test (6MWT), the Mini Balance Evaluation System Test (Mini-BESTest) and the Short Physical Performance Battery (SPPB) were investigated. RESULTS: The Italian N-FOGQ had high internal consistency (Cronbach's α = 0.859). Validity analysis showed significant correlations between NFOG-Q-IT total score and M-H&Y scores (r = 0.281 p < 0.001), MDS-UPDRS (r = 0.359 p < 0.001), FES-I (r = 0.230 p = 0.002), Mini BESTest (r = -0.256 p = 0.001) and 6MWT (r = -0.166 p = 0.026). No significant correlations were found with SPPB, MOCA and MMSE. CONCLUSION: The NFOG-It is a valuable and reliable tool for assessing FOG symptoms, duration and frequency in PD subjects. Results provide the validity of NFOG-Q-It by reproducing and enlarging previous psychometric data.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".