Teledentistry use during the COVID-19 pandemic: perceptions and practices of Ontario dentists
Bibliographic record
Abstract
BACKGROUND: Teledentistry has demonstrated to expedite oral health consultations, diagnosis, and treatment planning while mitigating COVID-19 transmission risk in dental offices. However, the use of teledentistry by clinicians 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 39 item survey was conducted among Ontario dentists in December 2021. The questionnaire inquired about socio-demographic attributes, as well as perceptions of teledentistry use during the pandemic, and its future application. Descriptive statistics including frequency distribution of categorical variables and univariate analysis of continuous variables were conducted. Chi-square test was used determine the associations between professionals' attributes such as age, gender, years of practice, and location of practice, and respondents use of teledentistry. SPSS Version 28.0 was used for statistical analysis. RESULTS: Overall, 456 dentists completed the survey. The 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%). Approximately 49.3% reported using teledentistry; 13% started before the pandemic, and 36% during the pandemic. The most common reason for non-utilization was a lack of interest (54%). Respondents identified patient triage, consultation, and patient education as the three most important uses of teledentistry. Female dentists (p < 0.05), dentist working in private practice (p < 0.05), and those who worked in a single dental office (p < 0.05) adopted teledentistry more during the pandemic. Respondents who accessed more resources were more likely to report greater utilization of teledentistry, while those who reported being unconformable with teledentistry (p < 0.05) reported less utilization. Additionally, participants who reported feeling comfortable discussing teledentistry with others (p < 0.05), were more inclined to use it in the future. CONCLUSIONS: Participants expressed mixed perceptions toward teledentistry with more than half indicating it is reliable for patient triaging and patient follow-ups. 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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".