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Record W4390670736 · doi:10.1111/cdoe.12939

Investigating the perceptions and experiences of Canadian dentists on dental regulatory bodies' communications and guidelines during the <scp>COVID</scp> ‐19 pandemic

2024· article· en· W4390670736 on OpenAlexafffundabout
Kendra J. McLaughlin, Mehak Khanna, Paul Allison, Michael Glogauer, Mary McNally, Carlos Quiñonez, Leigha D. Rock, Walter L. Siqueira, Sreenath Madathil

Bibliographic record

VenueCommunity Dentistry And Oral Epidemiology · 2024
Typearticle
Languageen
FieldDentistry
TopicDental Research and COVID-19
Canadian institutionsUniversity of SaskatchewanWestern UniversityDalhousie UniversityUniversity of TorontoMcGill UniversityMcGill University Health Centre
FundersCanadian Institutes of Health Research
KeywordsPandemicMedicineQualitative researchCoronavirus disease 2019 (COVID-19)Family medicineConfusionPerceptionNursingPsychologyDiseasePathology

Abstract

fetched live from OpenAlex

OBJECTIVE: Dental regulatory bodies aim to ensure the health and safety of dentists, dental staff patients and the public. An important responsibility during a pandemic is to communicate risk and guidelines for patient care. Limited data exist on the perceptions and experiences of dentists navigating new guidelines for mitigating risk in dental care during the pandemic. The objective of this study was to use a qualitative approach to explore how dentists in Canada experienced and perceived their regulatory bodies' communication about COVID-19 risks and guidelines during the pandemic. METHODS: Participants were Canadian dentists (N = 644) recruited through the email roster of nine provincial dental associations or regulatory bodies. This qualitative analysis was nested within a prospective longitudinal cohort study in which data were collected using online questionnaires at regular intervals from August 2020 to November 2021. To address the objective reported in this paper, a conventional qualitative content analysis method was applied to responses to three open-ended questions included in the final questionnaire. RESULTS: Participants encountered challenges and frustrations amid the COVID-19 pandemic, grappling with diverse regulations and communications from dental bodies. While some bodies offered helpful guidance, many participants felt the need for improved communication on guidelines. Dentists urged for expedited, clearer and more frequent updates, expressing difficulty in navigating overwhelming information. Negative views emerged on the vague and unclear communication of COVID-19 guidelines, contributing to confusion and frustration among participants. CONCLUSION: As COVID-19 persists and in planning for future pandemics, these experiential findings will help guide regulatory bodies in providing clear, timely and practical guidelines to protect the health and safety of dentists, dental staff, patients and the public.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.513

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0290.018
Scholarly communication0.0080.003
Open science0.0030.009
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.210
GPT teacher head0.439
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes3
Has abstractyes

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