Psychosocial impact of Parkinson's disease‐associated dysarthria: Cross‐cultural adaptation and validation of the Dysarthria Impact Profile into European Portuguese
Bibliographic record
Abstract
AIM: The present study sought to make a cross-cultural adaptation of the Dysarthria Impact Profile (DIP) for European Portuguese (EP) and validate it for use in Parkinson's disease (PD) patients. METHODS: The cross-cultural adaptation was carried out in accordance with the guidelines. The EP version of the DIP was administered to 80 people with PD, and 30 sex- and age-matched control participants. Psychometric properties, acceptability, feasibility reliability (internal consistency and intrarater agreement) and validity (construct, convergent and known-groups validity) were assessed using other assessment tools (motor disability and impairment, and voice impact). RESULTS: Overall, the EP-DIP final version has the same conceptual meaning, semantics, idiomatic and score equivalences as the original version. Statistical analyses showed adequate feasibility (missing data <5%), good acceptability (ceiling or floor effects <15%; high requests of assistance to complete the questionnaire), satisfactory internal consistency (Cronbach's α = 0.9), weak-to-moderate intrarater reliability, good construct validity, strong convergent validity (with the Voice Handicap Index; Spearman's P = -0.8) and good known-groups validity (between those with PD and control participants). CONCLUSIONS: The EP-DIP version displays the salient features of a valid patient-based assessment tool used to measure the psychosocial impact of slight-to-mild dysarthria in people with PD. Geriatr Gerontol Int 2018; 18: 767-774.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 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".