Assessing Depression and Factors Possibly Associated with Depression during the Course of Parkinson'S Disease
Bibliographic record
Abstract
Background Although research suggests depression is common among individuals with Parkinson's disease (PD), it is unclear how to best assess depression in PD (dPD). We wanted to examine the prevalence of dPD using different definitions of depression, as well as examine factors associated with dPD. Methods One hundred fifty-eight individuals (68% male; age 66.8 ± 9.6 SD) with a primary diagnosis of PD were assessed for depression using the Harvard Department of Psychiatry/National Depression Screening Day Scale (HANDS) in an outpatient setting at the Movement Disorders Clinic at Massachusetts General Hospital. We defined depression using 4 thresholds based on the HANDS and whether or not an individual was ever on an antidepressant regimen. We also examined potential predictors of the presence of dPD. Results The prevalence of depression among study participants ranged from 11% to 57%, depending on which of the 4 definitions of depression was applied. Younger age and longer duration of PD predicted a relatively higher prevalence of depression. Having a history of depression prior to onset of PD also was predictive of dPD. Conclusions Depression appears to be relatively common among individuals with PD, and history of depression, younger age, and longer PD duration may be factors associated with dPD.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 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".