A Population-Based Study Of Depression In Persons With Parkinson's Disease
Bibliographic record
Abstract
Parkinson’s disease (PD) is a chronic neurological condition that degenerates motor skills and degrades cognitive function over time. Depression is commonly associated with PD, and can lead to decreased quality of life and increased health care utilization in persons with PD. The goal of the current project is to estimate the prevalence of depression in PD disease patients and characterize this population in terms of demographics, differing diagnostic criteria and comorbidities. It was found that the prevalence of depression, using both the cutpoint and algorithm scoring methods are higher in PD than in the general population. In addition, a significantly greater proportion of persons with PD report suicidal ideation than the general population. Most persons with PD report poor self-rated health and almost 1 in 5 report their current health state to be worse than dead. Two-thirds of persons report their PD symptoms to be worse or much worse than when they were first diagnosed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".