Cognitive Problems in Parkinson Disease: Perspectives and Priorities of Patients and Care Partners
Bibliographic record
Abstract
OBJECTIVE: To report how people with Parkinson disease (pwPD) and their care partners (CPs) describe the cognitive impacts of the disease, explore the convergent validity of subjective cognitive complaints (SCCs) with measures of cognition and daily functioning, and report the cognitive treatment priorities of pwPD and their CPs. BACKGROUND: Cognitive symptoms in pwPD are common and disabling. Although objective cognitive impairments have been closely studied, SCCs are less well understood. METHODS: Fifty dyads consisting of a person with PD and his or her CP independently completed a questionnaire that describes cognitive difficulties and was derived from a prior focus group study. Each participant rated the person with PD's degree of difficulty with symptoms and identified the top five items that would be important treatment targets. Each person with PD also completed the Montreal Cognitive Assessment (MoCA), and his or her CP completed questionnaires assessing the patient's daily functioning and the CP's distress. RESULTS: Significant correlations existed between CP-reported cognitive symptoms and objective cognitive impairment as assessed by the MoCA. Both patient- and CP-reported SCCs were correlated with the pwPD's cognition as assessed by the MoCA, with an increasing number of SCCs reported with declining cognition. In general, the pwPD self-reported more SCCs than did the CPs, but for patients with dementia, the CPs reported more SCCs. Language and decision-making were the top treatment priorities. CONCLUSIONS: In view of the array of cognitive impacts of PD, clinicians and researchers must consider both the reporter (patient or CP) and the overall stage of a patient's cognitive decline when evaluating SCCs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".