Self-reported and measured stress related responses associated with exposure to wind turbine noise
Bibliographic record
Abstract
The current study was the first to assess stress reactions associated with wind turbine noise (WTN) exposure using self-reported and objective measures. Randomly selected participants, aged 18-79 yr (606 males; 632 females), living between 0.25 and 11.22 km from wind turbines, were exposed to outdoor calculated WTN levels up to 46 dBA (response rate 78.9%). Multiple regression modeling left the great majority (77%-89%) of the variance in perceived stress scale (PSS) scores, hair cortisol concentrations, resting blood pressure, and heart rate unaccounted for, and WTN exposure had no apparent influence on any of these endpoints. PSS scores were positively, but weakly, related to cortisol concentrations and resting heart rate (Pearson r = 0.13 and r = 0.08, respectively). Across WTN categories, modeled mean PSS scores ranged from 13.15 to 13.84 (p = 0.8614). Modeled geometric means for hair cortisol concentrations, resting mean systolic, diastolic blood pressure, and heart rate were 150.54-191.12 ng/g (p = 0.5416), 113.38-116.82 mmHg (p = 0.4990), 67.98-70.34 mmHg (p = 0.5006), and 68.24-70.71 bpm (p = 0.5223), respectively. Irrespective of WTN levels, diastolic blood pressure appeared to be slightly (2.90 mmHg 95% CI: 0.75,5.05) higher among participants highly annoyed by blinking lights on turbines (p = 0.0081). Collectively, the findings do not support an association between exposure to WTN up to 46 dBA and elevated self-reported and objectively defined measures of stress.
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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 | 0.000 | 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".