Emotional Burdens and Cognitive Decline: the Role of Anxiety in Mild Cognitive Impairment
Bibliographic record
Abstract
Aim: This study investigates the complex interactions between mild cognitive impairment (MCI), depression, and anxiety, focusing on how these factors affect cognitive function and progression risks.The goal is to inform early diagnostic strategies and targeted therapeutic interventions in individuals with MCI Matherial and Methods: This prospective study included 45 patients diagnosed with MCI (mean age: 66.1±7.7 years; 23 males [51%], 22 females [49%]) at a neurology outpatient clinic.Sociodemographic data, including education level and medical history, were collected.Cognitive and psychiatric assessments were conducted using the Montreal Cognitive Assessment (MoCA), Standardized Mini-Mental State Examination (SMMT), Hamilton Depression Rating Scale (HDRS), and Hamilton Anxiety Scale (HAS).Stratification was done according to anxiety severity, and comparisons were made across these groups on the cognitive performances.Results: Anxiety levels were significantly higher in females than males (p=0.001).While global MoCA and SMMT scores did not differ significantly by gender, males showed significantly better performance in verbal fluency (p=0.025) and a trend in abstract thinking (p=0.057).A significant decline in MoCA total scores was observed with increasing anxiety severity (p=0.024), with verbal fluency (p=0.011),abstract thinking (p=0.005), and attention (p=0.050)notably affected in the severe anxiety group.Conclusions: This study highlights anxiety as a key modifiable risk factor for cognitive impairment in MCI, with domain-specific deficits in executive function.Unlike depression, anxiety showed a stronger correlation with cognitive decline.These findings suggest that early identification and targeted treatment of anxiety in MCI could help delay progression to dementia and improve clinical outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".