66 Association of Executive Functions and Instrumental Activities of Daily Living in Parkinson’s Disease
Bibliographic record
Abstract
Objective: Executive function (EF) abilities tend to decline with age, and disproportionately so for people with neurodegenerative disorders such as Parkinson’s Disease (PD), where EF deficits are commonly seen in the early stages of the disease. Due to their nature, EF are essential for performing tasks of daily life, particularly for the more complex instrumental activities of daily living (IADL), and deficits can impair the ability to execute IADL in PD participants. The aim of this study was to examine how EF impairments relate to IADL deficits in both healthy elderly controls and PD participants. Participants and Methods: Seventy-four participants with idiopathic PD and 66 elderly controls were recruited. All participants were non-demented. A comprehensive neuropsychological assessment was administered including the following measures of EF: Hayling Sentence Completion, Brixton Spatial Anticipation, Trail Making Test A and B, Stroop Color-Word Test, Symbol Span (Wechsler Memory Scale-III), Digit Span (Wechsler Adult Intelligence Scale-III), F-A-S test, and Semantic Fluency (Animals and Actions). Z scores were calculated from respective test manuals. Independence was measured using the 8-item Lawton IADL Scale where items are coded from 0 (dependent) to 1 (independent) and the total score ranges from 0 to 8. Motor impairments were assessed using Part III of the Movement Disorder Society Unified Parkinson’s Disease Rating Scale. Regression models were run with each cognitive measure as the dependent variable, with group (control vs. PD), age, sex, education, and motor severity as predictors, to examine the effect of group on each cognitive variable. Correlations were then run between the total IADL score, demographic variables, and cognitive variables for each participant group separately to identify the relationship between IADL and EF measures. Results: PD participants were predominantly males (n=51, 68.9%), with an average age of 70.64±6.03 and 15.22±2.78 education years. Controls were predominantly female (n=34, 51.5%) and had an average age of 71.19±7.75 and 15.85±2.82 education years. Regarding IADL function, all participants were relatively independent in their IADLs (PD: 7.72±0.69, range 4-8, Controls: 7.98±0.13, range 7-8). The most difficult IADL items for PD participants were shopping (8.2% dependent) and food preparation (12.2% dependent). When correcting for age, education, sex, and motor severity, only the Stroop Interference z-score was significant for participant group (b=0.44, t=2.14, p=0.034), where controls had slightly lower scores (-0.33±0.77) than PD participants (-0.31±0.91). Correlations in controls were significant between IADL total score and Hayling trials 1 (r=0.35, p=0.005) and 2 (r=0.33, p=0.008), and semantic fluency actions trial (r=0.34, p=0.006). In PD participants, IADL total score was only correlated with semantic fluency (animals trial, r=0.26, p=0.028). Conclusions: There were only weak associations between EF abilities and IADL in both healthy controls and PD participants, suggesting that impairments in EF do not necessarily translate into worse ability to execute IADL in PD. More correlations were found in the control group, which may be confounded by the inclusion (in both groups) of participants who already had cognitive impairment. This highlights a further need to examine whether EF impairments in people with PD influence IADL functioning above and beyond normal aging and whether specific deficits have more real-life consequences not attainable through IADL questionnaires.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".