Teledentistry use during the COVID-19 pandemic: Perceptions and practices of Ontario dentists
Bibliographic record
Abstract
Abstract Background: Studies have shown the potential role of teledentistry to expedite and improve consultations, diagnosis, and treatment planning while mitigating the risk of COVID-19 transmission in dental offices. However, dental professionals' utilization of teledentistry remains suboptimal. Therefore, this study aimed to determine the perceptions and practices of teledentistry among dentists during the COVID-19 pandemic in Ontario, Canada and identify associated factors. Methods: A cross-sectional study using an online survey was conducted among Ontario dentists in December 2021. The questionnaire inquired about socio-demographic attributes, perceptions about teledentistry use, its usage during the pandemic, and perspectives on its future application. Descriptive statistics including frequency distribution of categorical variables and univariate analysis of continuous variables were conducted first followed by Chi-square tests, to determine the association between professionals’ attributes such as age, gender, years of practice, and location of practice, and their views on teledentistry. SPSS Version 28.0 was used for statistical analysis. Results Overall, 456 dentists completed the survey. Majority were general dentists (91%), worked in private practices (94%), were between 55 and 64 years old (33%), and had over 16 years of professional experience (72%). The most common reason for non-utilization was a lack of interest (54%). Those who use teledentistry identified patient triage, consultation, and patient education as the three most important uses. Gender (p<0.05), type of practice (p<0.05), number of settings in which dentists practiced (p<0.05), number of resources accessed (p<0.05), and comfort levels with discussing teledentistry (p<0.05), were all found to be significantly associated with the participants’ current use of teledentistry (n=447). Type of practice (p<0.05), number of practice settings (p<0.05), number of resources accessed (p<0.05), and comfort level with discussing teledentistry (p<0.05) were significantly associated with their future willingness to use teledentistry (n=456). Conclusions Participants expressed mixed perceptions toward teledentistry. Despite the increased utilization during the COVID-19 pandemic, participants' lack of interest in teledentistry emerged as a barrier to its use. More education and knowledge dissemination about teledentistry's areas of application and technical aspects of use can increase interest in this tool, which may lead to a greater uptake by dental professionals.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".