Utilizing the Crisis Wartegg System (CWS) to Assess Emotional and Cognitive Function in Patients with Parkinson's Disease - A Proposal
Bibliographic record
Abstract
Parkinson’s disease (PD) is a progressive neurodegenerative condition that impacts not only motor functioning but also cognitive and emotional regulation. These non-motor symptoms are often underrecognized and undertreated, highlighting the need for sensitive and accessible assessment tools. This study explores the utility of the Wartegg Drawing Completion Test (WDCT), scored using the standardized Crisi Wartegg System (CWS; Crisi, 1998, 2007; Crisi & Palm, 2018), as a performance-based method for assessing emotional adaptability and coping in individuals with mild to moderate PD. The research will employ a cross-sectional, descriptive design with correlational analyses using SPSS 11.0. Participants will include 50 individuals with PD and 50 age- and gender-matched controls, recruited from the University of Kansas Parkinson’s Disease and Movement Disorder Center. Measures will include the Montreal Cognitive Assessment (MoCA), the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), the Geriatric Depression Scale (GDS-15) or Patient Health Questionnaire-9 (PHQ-9), and the CWS. We hypothesize that PD participants will show lower evocative character (EC%) scores, indicating reduced perceptual and associative engagement; lower form quality (FQ%) scores, reflecting diminished clarity and organization in visual expression; and lower affective quality (AQ%) scores, representing reduced emotional expression. Psychiatric symptoms like anxiety, depression, and cognitive slowing are discussed as contributing factors (Anderson, 2004; APDA, n.d.). The MoCA’s Clock Drawing Test and other visuospatial tasks help contextualize cognitive decline in PD (Talwar et al., 2019; Riedel et al., 2013). Limitations will include single-site recruitment, motor impairment effects, variability from medication, lack of gender or age stratification, and limited CWS norms for individuals over age 90. Findings are expected to support the value of the CWS in capturing psychological functioning in PD beyond traditional assessments.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".