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Record W7029587749

Knowledge translation for treatment planning in restorative and prosthetic dentistry

2016· dissertation· en· W7029587749 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2016
Typedissertation
Languageen
FieldArts and Humanities
TopicHistorical, Literary, and Cultural Studies
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsRestorative dentistryAmalgam (chemistry)Evidence-based dentistryRadiation treatment planningClinical PracticeCurriculumBest evidenceEvidence-based practice
DOInot available

Abstract

fetched live from OpenAlex

Dentists should make their clinical decisions based on the best evidence available. In recent years, training in evidence-based dentistry (EBD) has been incorporated into undergraduate dental curricula to aid students in their clinical practice. However, implementation of an evidence-based practice (EBP) by dentists is very limited, especially in the field of restorative and prosthetic dentistry. Therefore, the aim of this research project was to identify and find a solution for barriers preventing EBP implementation. To identify the EBP implementation barriers, we designed and applied a paper format self-administered questionnaire on dental undergraduate and graduate students. In order to find a solution for the lack of EBP implementation, we conducted a systematic review oriented to clinical practice which extracted the data of the available literature on the survival of single-unit crowns and dental fillings performed on posterior permanent teeth. Our results demonstrated that less than two in ten students base their restorative treatment-planning on the best available evidence and this may be due to students taking too long to find an answer to the clinical question and the difficulties in indentifying the best available evidence for each specific scenario. Therefore, we conducted a systematic review to facilitate EBD in restorative treatment-planning. Our systematic review showed that the more the remaining tooth structure is available, the lower the failure rate among restorative treatments. It also suggested that vital teeth with two or fewer walls left should be restored with crowns, whereas teeth with more tooth structure should be restored with dental fillings, preferably amalgam restorations. Non-vital teeth with two or fewer walls left should be treated with crowns with post and core, whereas those with more tooth structure should be treated only with crowns. The restoration of non-vital teeth with less than a wall remaining has to be reconsidered since they have very high risk of failure. In conclusion, findings from this project indicate that dental students rarely apply EBD principles into practice and the main barrier preventing EBP implementation was lack of time. Therefore, the strategy proposed in this project was to provide easily accessible evidence-based knowledge in order to facilitate restorative treatment-planning based on the best evidence. Our knowledge synthesis results showed the areas of weakness in the restorative and prosthetic dentistry literature, either by high-risk of bias or lack of information, to address many of the restorative clinical scenarios that dental students and clinicians encounter for decision-making. This work could also serve as a foundation for future development of clinical guidelines in restorative and prosthetic dentistry.Keywords: evidence-based dentistry; quality of evidence; recommendation; dental education; treatment planning; decision-making; clinical practice; restorative dentistry; dental fillings; composite resins; dental amalgam; crowns; indirect restorations; direct restorations.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.978
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.083
GPT teacher head0.293
Teacher spread0.210 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations0
Published2016
Admission routes1
Has abstractyes

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