Heart rate variability under acute stress and noise in healthy subjects: A tool to study autonomic activity in tinnitus?
Bibliographic record
Abstract
Introduction: Individuals with hearing disorders such as tinnitus often experience high levels of stress, anxiety, depression, and decreased sound tolerance. These factors may be related to maladaptive autonomic regulation, affecting their response to acute stress. Heart rate variability (HRV) is a reliable measure of autonomic activity, but its interaction with psychological factors is not well understood. Objectives: The aim was to develop a multimodal stress induction protocol in a non-clinical population and to determine how psychological factors influence physiological responses. Methods: Electrocardiograms were recorded from 30 healthy young adults during three stress tasks: mental arithmetic, noise exposure, and a cold pressor test. Heart rate (HR) and root mean square of successive differences (RMSSD) were used to index autonomic activity. Participants also completed questionnaires on perceived stress, noise sensitivity, anxiety, and depression to examine relationships with HRV. Results: All tasks produced significant time-dependent effects on HRV features, but to different extents. Mental arithmetic produced the largest increase in HR and decrease in RMSSD. In contrast, the noise task showed a significant decrease in HR without a change in RMSSD, suggesting that the task induced relaxation. In the CPT, females showed increased HR but a decrease in RMSSD, whereas males showed the reverse pattern. Psychological factors significantly interacted with HRV dynamic changes during mental and noise tasks, but not during CPT. Conclusions: HRV responses to acute stress are non-stationary and influenced by psychological factors. Thus, this protocol presents an original approach to study autonomic activity in stress-related conditions such as tinnitus.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".