Feasibility of Smartphone-Based Testing of Interference in Parkinson’s Disease
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Bibliographic record
Abstract
BACKGROUND: Interference refers to learned associations and established behaviors "interfering" with response to new material. It forms a core pillar of executive functions, which are commonly affected in Parkinson's disease (PD). Cognitive interference test (CIT) forms part of a smartphone application designed for ambulatory assessment in PD. OBJECTIVE: The aims of this study were to establish that CIT could effectively demonstrate interference and would perform comparably to the Stroop Color-Word Test Victoria version (VST) despite PD-related motor impairment. METHODS: Ninety-nine patients with PD were recruited. Initial evaluation included CIT, VST, Montreal cognitive assessment (MOCA), and Movement Disorders Society-sponsored revision of the -Unified Parkinson's Disease Rating Scale (MDS-UPDRS-III). A group of patients underwent repeat assessment within 2 weeks. Thirty-four healthy controls were recruited for comparison. RESULTS: Patients' mean age was 66.2 years, disease duration was 8.7 years, on-state MDS-UPDRS-III was 22, and MOCA total score was 27. CIT effectively generated interference, whereby the total time taken to complete the incongruent task was 20% longer compared to that of the baseline task. CIT key test items demonstrated convergent validity to VST (r = 0.478-0.644, p < 0.0001) and satisfactory repeatability (intraclass correlation coefficient 0.46-0.808, p ≤ 0.0002). Performance on key CIT test parameters deteriorated with increasing age (r = 0.225-0.478, p < 0.01) and MDS-UPDRS-III total score (r = 0.354-0.481, p < 0.0001). When compared to controls and patients with less motor impairment, patients MDS-UPDRS-III > 30 took longer to complete CIT and VST and had lower MOCA-attention sub-score, implying that the degree of motor impairment could not be the sole explanation for reduced CIT performance. CONCLUSIONS: We established that despite motor impairment, the novel approach of using smartphone technology to test interference in PD patients is feasible.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it