Emotion Detection Deficits and Decreased Empathy in Patients with Alzheimer’s Disease and Parkinson’s Disease Affect Caregiver Mood and Burden
Bibliographic record
Abstract
Background: Changes in social cognition occur in patients with Alzheimer’s disease and Parkinson’s disease and can be caused by several factors, including emotion recognition deficits and neuropsychiatric symptoms. The aims of this study were to investigate: 1) group differences on emotion detection between patients diagnosed with Alzheimer’s disease or Parkinson’s disease and their respective caregivers 2) the association of emotion detection with empathetic ability and neuropsychiatric symptoms in individuals with Alzheimer’s disease or Parkinson’s disease; 3) caregivers’ depression and perceived burden in relation to patients’ ability to detect emotions, empathize with others, presence of neuropsychiatric symptoms and (4) caregiver’s awareness of emotion detection deficits in patients with Alzheimer’s disease or Parkinson . Methods: In this study, patients with probable Alzheimer’s disease (N = 25) or Parkinson’s disease (N = 17), and their caregivers (N = 42), performed an emotion detection task (The Awareness of Social Inference Test – Emotion Evaluation Test). Patients underwent cognitive assessment, using the Behavioral Neurology Assessment. In addition, caregivers completed questionnaires to measure empathy (Interpersonal Reactivity Index) and neuropsychiatric symptoms (Neuropsychiatric Inventory) in patients and self-reported on depression (Geriatric Depression Scale) and burden (Zarit Burden Interview). Caregivers were also interviewed to measure dementia severity (Clinical Dementia Rating Scale) in patients. Results: The results suggest that individuals with Alzheimer’s disease and Parkinson’s disease are significantly worse at recognizing emotions than their caregivers. Moreover, caregivers failed to recognize patients’ emotion recognition deficits and this was associated with increased caregiver burden and depression. Patients’ emotion recognition deficits, decreased empathy and neuropsychiatric symptoms were also related to caregiver burden and depression. Conclusions: Changes in emotion detection and empathy in individuals with Alzheimer’s disease and Parkinson’s disease has implications for caregiver burden and depression and may be amenable to interventions with both patients and caregivers.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".