Goal management training and psychoeducation / mindfulness for treatment of executive dysfunction in Parkinson’s disease: A feasibility pilot trial
Bibliographic record
Abstract
INTRODUCTION: As there is currently no pharmacological treatment for Parkinson's Disease Mild Cognitive Impairment (PD-MCI) with executive dysfunctions, specific cognitive interventions must be investigated. Most previous studies have tested bottom-up cognitive training programs but have not shown very good results. OBJECTIVES: The aim of this study was to test ease of implementation, differential safety and preliminary efficacy of two top-down (strategy-learning) home-based, individualized, cognitive interventions: Goal Management Training (GMT), adapted for PD-MCI (Adapted-GMT), and a psychoeducation program combined with mindfulness exercises (PSYCH-Mind). METHODS: This was a single-blind block-randomized between-group comparative study. Twelve PD-MCI with mild executive dysfunctions were divided in four blocks and randomly assigned to any of the two interventions. The participants were included if they had PD-MCI diagnosis (no dementia), with stabilized medication. Both groups (Adapted-GMT and PSYCH-mind) received five intervention sessions each lasting 60-90 minutes for five weeks. Measures were collected at baseline, mid-point, one-week, four-week and 12-week follow-ups. Executive functions were assessed with the Dysexecutive questionnaire (DEX) and the Zoo Map Test (ZMT). Quality of life (QoL) and psychiatric symptoms were also evaluated. Repeated measures ANCOVAs (mixed linear analysis) were applied to all outcomes. RESULTS: There was one drop out, and both interventions were feasible and acceptable. Despite the small sample size limiting statistical power, patients of both groups significantly improved executive functions per the DEX-patient (Time: F(4,36) = 2.96, p = 0.033, CI95%: 10.75-15.23) and DEX-caregiver scores (Time: F(4,36) = 6.02, p = 0.017, CI95%: 9.63-17.23). Both groups significantly made fewer errors between measurement times on the ZMT (Time: F(3,36) = 16.66, p = 0.001, CI95%: 1.07-2.93). However, QoL significantly increased only in PSYCH-Mind patients at four-week follow-up (interaction Time*Group: F(4,36) = 5.31, p = 0.002, CI95%: 15.33-25.61). CONCLUSION: Both interventions were easily implemented and proved to be safe. Because both interventions are arguably cost-effective, these pilot findings, although promising, need to be replicated in large samples. CLINICALTRIALS.GOV IDENTIFIER: NCT04636541.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".