Exploring stressors and coping strategies among dental students during COVID‐19 pandemic in British Columbia
Bibliographic record
Abstract
OBJECTIVE: The COVID-19 pandemic has caused stress among undergraduate dental students; coping mechanisms might be employed to deal with such stress. A cross-sectional study was conducted to explore the coping strategies employed by dental students at the University of British Columbia (UBC) in response to their self-perceived stressors during the pandemic. METHODS: An anonymous 35-item survey was distributed to all four cohorts of UBC undergraduate dental students enrolled in the 2021-2022 academic year, 229 students in total. The survey gathered sociodemographic information, self-perceived COVID-19-related stressor, and coping strategies via the Brief Cope Inventory. Adaptive and maladaptive coping were compared among the years of study, self-perceived stressors, sex, ethnicity, and living situations. RESULTS: Of the 229 eligible students, 182 (79.5%) responded to the survey. Of the 171 students that reported a major self-perceived stressor, 99 (57.9%) of them were stressed about clinical skill deficit due to the pandemic; fear of contraction was reported by 27 (15.8%). Acceptance, self-distraction, and positive reframing were the most used coping strategies among all students. The one-way ANOVA test revealed a significant difference in the adaptive coping scores among the four student cohorts (p = 0.001). Living alone was found to be a significant predictor for maladaptive coping (p < 0.001). CONCLUSION: The main cause of stress related to the COVID-19 pandemic for dental students at UBC is their clinical skills being negatively affected. Coping strategies including acceptance and self-distraction were identified. Continued mitigation efforts should be made to address students' mental health concerns and create a supportive learning environment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".