Associations of cognitive functionng and mental well-being of individuals with atrial fibrillation with perceived environmental stressors and contact with nature
Bibliographic record
Abstract
There is growing evidence of the link between environmental factors and neurocognitive health, but relatively little is still known about them.Aim: The present study aimed to investigate the associations of air pollution and noise annoyances in the residential environment, and time spent in nature with cognitive functioning and symptoms ofanxiety and depression among individuals with atrial fibrillation aged 45 to 65 years.Materials and methods: A longitudinal study was conducted among 56 outpatients with atrial fibrillation, between 2023 and 2025, examined at the St. George University Hospital in Plovdiv. They completed a questionnaire collecting information about their socio-demographic characteristics, perceptions of their living environment, lifestyle, and symptoms of anxiety and depression. The Montreal Cognitive Assessment, Isaac’s Set Test, and Patient Health Questionnaire 4-item form were administered.Results: Our results support the study hypothesis, suggesting that spending more time in nature is protectively associated with symptoms of anxiety and depression and overall cognitive functioning. The noise and air pollution annoyances in the living environment appear to be associated with poorer neuropsychological test scores.Conclusion: Perceptions of the living environment are associated with indicators of neuropsychological health. These results provide grounds for taking environmental factors into account in the social history of individuals in that group. Further research is needed in larger and more representative samples.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".