More Than a Deadly Virus: COVID-19 and Its Psychological Impact on American and Canadian Dental Practitioners
Bibliographic record
Abstract
Objectives: The COVID-19 pandemic has significantly affected dental professionals, thus contributing to adverse psychological outcomes. The aim of this cross-sectional study was to investigate the psychosocial state of American and Canadian dental practitioners, with special emphasis on their affective well-being (both during lockdown and after re-opening), behavioral impact and cognitive responses. Methodology: Dental practitioners in Canada and USA were invited to participate in an online survey after the initial lockdown period. The questions evaluated the pandemic’s effect on affective, behavioral, and cognitive responses. Results: A total of 587 practitioners completed the online survey. The strongest emotions experienced during the lockdown were sadness followed by fear. Female practitioners, those in the 35-44 age group, and those with less work experience reported higher scores on fear. Following lockdown, participants reported higher anticipation. Males expressed higher feelings of disgust and anger during both phases. Canadians were trustful of the situation in both phases of the pandemic, whereas the emotions of Americans were more towards disgust. About 56.7% practitioners provided teledentistry during lockdown, mainly through video calling, with Canadians being significantly more involved than the American participants. The highest scores for participants’ experiences during lockdown were for a lack of social interaction, followed by concern for contracting infection, and stress from distressing media coverage. Most practitioners were very receptive of receiving the COVID-19 vaccine. Conclusions: The emotions and behaviors of dental practitioners varied significantly during and after the initial lockdown, highlighting their psychosocial state during the pandemic. The scarcity of literature focusing on these basic emotions during similar outbreaks calls attention for pursuing more research in these areas as they significantly contribute to the overall psychological health of professionals, especially in times of crises. Given the emotions reported by dental practitioners, it would be of value to develop standardized protocols and provide remote psychological support during such periods of uncertainty.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".