Evaluating the inoculation effect of music on stress reactivity in healthy young and older adults: the moderating role of music absorption
Bibliographic record
Abstract
Chronic exposure to stress at any age is associated with a myriad of negative physiological and psychological consequences, and as such, development of effective low-cost and non-invasive stress reduction interventions are important. Music listening has been shown to promote faster physiological recovery from acute stress. However, there is a paucity of research examining the potential inoculation effect of music on stress reactivity, as well as potential modifier’s that may influence this effect such as music selection and music absorption. Hence, the current study examined the potential inoculation effect of music in response to acute stress, as measured by a comprehensive set of stress indices. It was hypothesized that listening to music prior to acute stress exposure would decrease stress reactivity compared to white noise (WN), and that self-selected music (SSM) would serve as a stronger inoculator than researcher-selected music (RSM). Finally, it was hypothesized that music absorption would moderate the inoculation effect of music, with a greater decrease in stress reactivity observed in high absorbers. Exploratory sub-groups analyses were also performed to examine any potential age differences in the aforementioned associations. Participants were randomly assigned to either RSM (n = 37), SSM (n = 38), or a WN group (n = 33) and listened to either music or white noise prior to undergoing the Trier Social Stress Test (TSST). Outcome indices of stress included skin conductance, heart rate, salivary cortisol and self-report affect. Mixed analyses of covariance showed that music listening did not inoculate the stress response compared with WN and SSM did not serve as a more effective inoculator than RSM. A main effect of music absorption was found, suggesting that high absorbers are more reactive than low absorbers. Although the study hypotheses were not supported, exploratory sub-group analyses in older adults suggest that music listening and absorption may modulate the stress response. This study provides new insight into the effect of music listening on stress reactivity and presents a new line of questions that require further investigation.
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".