Effects of Psychotherapy on Depression and Cognitive Impairment in Patients with Parkinson's Disease
Bibliographic record
Abstract
Objective: To explore the effects of psychotherapy on depression and cognitive impairment in patients with Parkinson's disease(PD).Methods: Seventy PD patients were randomly divided into psychotherapy group(n=35) and medication group(n=35).The depressive symptoms and cognitive impairment were assessed at days 0,7 and 60,using the MMSE,MoCA,SDS,and HAMD scales.Results: Depressive symptoms and cognitive impairment were found in patients with PD.No significant difference of scores was observed at day 7 after psychotherapy.At day 60,HAMD and SDS scores were significantly lower than those at days 0 and 7 in psychotherapy group(P0.05).According to MMSE test,the total score,factor orientation score,calculation,and speech were significantly higher at day 60 than those in psychotherapy group at days 0 and 7(P0.05).MoCA test also revealed higher total score,factor executive function score,naming and orientation at day 60 than those measured at days 0 and 7 in psychotherapy group(P0.05).However,in medication group,only factor orientation score in MMSE and factor executive function and orientation score were significantly higher at day 60 than those at days 0 and 7(P0.05).The psychotherapy group showed significantly decreased HAMD and SDS score as well as enhanced total score of MMSE and MoCA compared with that of medication group(P0.05).Conclusion: Psychotherapy helps to attenuate depression and cognitive impairment in patients with PD.
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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 | 0.000 | 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) | 0.001 | 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".