Patient-provider communication during consultations for elective dental procedures: A scoping review
Bibliographic record
Abstract
INTRODUCTION: Patient-provider communication (PPC) is a critical component of patient-centered care. Original studies have examined specific factors related to PPC during consultations for elective dental procedures, but this evidence has yet to be comprehensively summarized. This scoping review aimed to understand better the extent and depth of the available literature regarding factors that influence PPC during consultations for elective dental procedures. METHODS: The authors considered electronically available, English-language, original research published since 1990 assessing communication during consultations for elective dental procedures. Four electronic databases, Google Scholar, and reference lists of inclusions were searched until August 2023. No quality assessment was completed. Two independent researchers assessed article eligibility. Data were charted with a narrative review approach. RESULTS: A total of 37 studies were included. The most popular discipline studied was orthodontics. Prospective cohorts and cross-sectional were the most common study designs. Information recall, patient satisfaction, and patient comprehension were the most common outcome measures. Most studies employed questionnaires, surveys, or interviews for data collection. Nineteen factors related to PPC during elective dental consultations were identified and categorized into information delivery (4), patient-related (9), and provider-related factors (6). CONCLUSIONS: This scoping review is the first to present a list of evidence-supported factors related to PPC in elective dental consultations. Identifying these factors is an important first step to better understanding their influence on PPC and designing interventions targeting those that may be modifiable. PPC during elective dental consultations is a dynamic, ongoing process. Several recommendations emerged that may help improve PPC, including appropriate information delivery, patient engagement, providing adequate time, and educating ourselves on approaches to PPC.
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 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 | 0.009 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".