Using Principles of Cognitive Behavioral Therapy to Treat Anxiety in Parkinson's Disease
Bibliographic record
Abstract
Anxiety significantly affects persons with Parkinson's disease (PwP), often emerging in the prodromal phase before the onset of symptoms and persisting throughout the disease's course. It is among the most disabling, stigmatizing, and under-recognized symptoms of Parkinson's disease (PD). Consequently, it is critical to provide tools that can be universally applied and that are accessible to help all PwP live better. This article discusses the nature of anxiety in PwP, how to identify it, and how to treat it across stages of the disease. We highlight cognitive behavioral therapy (CBT), a type of psychotherapy in widespread use for anxiety and depression in general and increasingly used in PwP. The neurologist can apply the basic principles of CBT. The principles can be used by clinicians who are treating PwP globally, as they require no pharmacological intervention and minimal resources. As the disease progresses, a multidisciplinary team may be preferable to address the complex challenges that PD presents, including anxiety. The focus is on a patient-centered approach, providing compassion, hope, and resources to optimize the mental and physical well-being of PwP. Empowering PwP fosters self-agency and can significantly improve quality of life.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".