Comparison of an Online-Only Parkinson’s Disease Research Cohort to Cohorts Assessed In Person
Bibliographic record
Abstract
BACKGROUND: Online tools for data collection could be of value in patient-oriented research. The Fox Insight (FI) study collects data online from individuals with self-reported Parkinson's disease (PD). Comparing the FI cohort to other cohorts assessed through more traditional (in-person) observational research studies would inform the representativeness and utility of FI data. OBJECTIVE: To compare self-reported demographic characteristics, symptoms, medical history, and PD medication use of the FI PD cohort to other recent observational research study cohorts assessed with in-person visits. METHODS: The FI PD cohort (n = 12,654) was compared to 3 other cohorts, selected based on data accessibility and breadth of assessments: Parkinson's Progression Markers Initiative (PPMI; PD n = 422), Parkinson's Disease Biomarker Program (PDBP; n = 700), and PD participants in the LRRK2 consortium without LRRK2 mutations (n = 508). Demographics, motor and non-motor assessments, and medications were compared across cohorts. Where available, identical items on surveys and assessments were compared; otherwise, expert opinion was used to determine comparable definitions for a given variable. RESULTS: The proportion of females was significantly higher in FI (45.56%) compared to PPMI (34.36%) and PDBP (35.71%). The FI cohort had greater educational attainment as compared to all other cohorts. Overall, prevalence of difficulties with motor experiences of daily living and non-motor symptoms in the FI cohort was similar to other cohorts, with only a few significant differences that were generally small in magnitude. Missing data were rare for the FI cohort, except on a few variables. DISCUSSION: Patterns of responses to patient-reported assessments obtained online on the PD cohort of the FI study were similar to PD cohorts assessed in-person.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".