The effects of expressions of fear induced by background music on reading comprehension
Bibliographic record
Abstract
Background Research has suggested that background music can have a positive or negative effect that can influence the affective state of individuals. Although research has demonstrated that fear negatively influences our cognitive performance, there is a research gap in understanding the combined effects of different background music tempo and fear in influencing reading comprehension performance. Methods Data were collected from 70 participants enrolled at a public university in Canada. Participants were required to listen to background music of varying speeds with three conditions (no music, slow music and fast music). We adopted a cross‐sectional multi‐level modelling approach for the main analyses, and further analyses using t ‐test and ANOVA. Results Results indicated that expression of fear was not a significant predictor of participants' reading comprehension performance (Model 1). However, when music condition was added (Model 2) in addition to expression of fear, a significant relationship between reading comprehension performance and music condition was found, showing better reading comprehension performance in the slow music condition than in the no music condition. Furthermore, there was a significant interaction effect between music condition and expression of fear on reading comprehension performance (Model 3). Importantly, not all individuals were affected by the music to the same extent, with the possibility that baseline level of fear being the key issue in influencing comprehension performance. Conclusions Considering both expression of fear and music condition is required to understand the combined effects on cognitive performance. Expression of fear during cognitive tasks such as reading could be an essential signal that interventions should be applied. Such strategies may be especially beneficial for task performers with higher baseline levels of fear and possibly provide us with insights for best practice and research implications in the field of reading comprehension among individuals with special needs.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".