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Implementing Evidence‐Based Practice in Undergraduate Teaching Clinics: A Systematic Review and Recommendations

2004· review· en· W2125820775 on OpenAlexaff
Sara B. Werb, David Matear

Bibliographic record

VenueJournal of Dental Education · 2004
Typereview
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEvidence-based dentistryMedical educationCurriculumSystematic reviewEvidence-based practicePsychological interventionEvidence-based medicineMEDLINEQuality (philosophy)PsychologyHealth careMedicineAlternative medicineNursingPedagogy

Abstract

fetched live from OpenAlex

The objective of this project was to identify an effective methodology of approaching and implementing evidence-based principles in undergraduate teaching clinics to promote evidence-based dentistry in future clinical practice. A systematic review was undertaken to examine evidence-based clinical teaching and faculty continuing education. Research published from 1996 to 2002 was retrieved by searching several databases and the Internet, along with conducting hand searches and reviewing bibliographies maintained by faculty experts. Qualitative checklists for different types of studies were created to evaluate the literature. Relevant studies were selected if they met all four predetermined essential criteria and a minimum of two out of three desirable criteria. Systematic reviews were chosen if they met all five essential criteria. Data from selected articles were extracted, and study quality was assessed. We found that three systematic reviews and nine original research articles were deemed methodologically acceptable. Problem-based learning and evidence-based health care interventions increased student knowledge of medical topics and their ability to search, evaluate, and appraise medical literature. Dental students in a problem-based learning curriculum, emphasizing evidence-based practices, scored higher on the NDB I (National Dentistry Boards, Part I) than students in traditional curricula. While effective modules in implementing theoretical evidence-based principles exist, very few high-quality studies are available that examine these principles in dental undergraduate teaching clinics. No methodologically appropriate studies on the education of faculty in the implementation of evidence-based principles are available. Some studies promote promising theories and methodologies of teaching evidence-based care; based on these theories, a comprehensive model is proposed in this article. Considering the strength of evidence in the reviewed literature, we concluded that an evidence-based approach to clinical care is effective.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gptMeta-epidemiology (broad)
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
grokMeta-epidemiology (broad)
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
opusno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.106
metaresearch head score (Gemma)0.216
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.894
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1060.216
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0080.006
Bibliometrics0.0160.012
Science and technology studies0.0020.002
Scholarly communication0.0070.011
Open science0.0060.004
Research integrity0.0080.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.259
GPT teacher head0.646
Teacher spread0.387 · 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

Labeled directly by 3 models reading the full record.

Meta-epidemiology (broad)

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designSystematic review
Domainnot available
GenreReview

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

Citations55
Published2004
Admission routes1
Has abstractyes

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