Self-Report of the Perception of Stress and Signs of Bruxism Generated during the Pandemic in Student of the Health Area
Bibliographic record
Abstract
Bruxism is the repetitive muscle-mandibular behavior characterized by clenching and/or grinding of the teeth, which reflects the presence of one or more underlying conditions or factors. The objective of this descriptive study was to determine the association between bruxism and stress self-perceived during the pandemic, as well as their frequency by gender and academic area. An interrogation and self-perceived stress scale PSS-14 were applied to students from the different areas of the Institute of Health Sciences (ICSa) to determine the presence or absence of stress and bruxism symptom, a Chi-square was used for the comparison between variables, considering a value of p<0.005 as significant, a two-way ANOVA was performed to evaluate the difference between the symptoms before and during the isolation of the pandemic. The total number of participants was 825, a final sample of 420 students was obtained, made up of 297 (70.72%) women and 123 (29.28%) men, with an average age of 20±1.75 years. We found an association between the frequency of bruxism and severe stress generated during the social isolation of the COVID-19 pandemic, with a high perception of stress in the medicine area and a high frequency of bruxism in the area of nutrition p>0.005. ICSa students between 18 and 24 age perceive symptoms of bruxism and high levels of stress caused during the pandemic.
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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 | 0.003 |
| 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 | 0.001 |
| 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".