Possible sleep bruxism, smartphone addiction and sleep quality among Brazilian university students during COVID-19 pandemic
Bibliographic record
Abstract
Objectives To evaluate the association of sleep bruxism activity with smartphone addiction and sleep quality among university students during COVID-19 pandemic. Material and Methods A cross-sectional online survey with 546 university students in social distancing was conducted (May 29th to June 2nd 2020). Participants should be undergraduate and graduate students enrolled in Brazilian public/private universities. A self-completed questionnaire collected sociodemographic characteristics, academic information, and severity of possible sleep bruxism (PSB) activities (grinding, bracing, and thrusting). Students answered the Brazilian version of Pittsburgh sleep quality index (PSQI-BR) and short form of the smartphone addiction scale (SAS-SV). Descriptive statistics and multinomial logistic regression were performed (p=0.05). Results Sample mean age was 24.9 (±5.5) years. Students with higher scores of PSQI-BR were more likely to present severe PSB-bracing (OR=1.154; 95%CI=1.057-1.260), severe PSB-grinding (OR=1.133; 95%CI=1.048-1.225) and severe PSB-thrusting (OR=1.197;95%CI=1.107-1.294). Students who had children presented 3 times more chance (OR=3.193; 95%CI=1.236-8.250) to report severe PSB-thrusting. Being female increased the chance of reporting moderate (OR=3.315; 95%CI=1.333-8.914) and severe (OR=2.940; 95%CI=1.116-7.747) PSB-thrusting. Students not enrolled in distance learning presented 2 times more chance (OR=2.638; 95%CI=1.233-5.649) of reporting moderate PSB-grinding. Students with higher scores in SAS-SV had a slight increase in the chance of presenting mild (OR=1.042; 95%CI=1.009-1.077) and moderate (OR=1.065; 95%CI=1.018-1.115) PSB-bracing, as well as mild (OR=1.044; 95%CI=1.011-1.078) and moderate (OR=1.041; 95%CI=1.005-1.077) PSB-thrusting. Conclusion Smartphone addiction, worse sleep quality, having children, female sex and not being enrolled in distance learning were associated possible sleep bruxism during COVID-19 pandemic.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 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".