Determining the Validity and Reliability of Clinical Communication Assessment Tools for Dental Patients and Students
Bibliographic record
Abstract
A shortcoming identified in the dental education literature is the scarcity of patient assessment of the quality of communication between student clinicians and patients. This study, the second in a series, attempts to address this scarcity by testing the communication components deemed critical to patients identified in the first article. Two instruments were tested: the Patient Communication Assessment Instrument (PCAI) and the Student Communication Assessment Instrument (SCAI). Item-to-total correlations and Cronbach's alpha were used to determine internal consistency reliability. Construct validity was examined through principal components factor analysis with varimax rotation using a total of 820 participants (410 patients and 410 students), who completed communication skills questionnaires collected in the 2006-07 school year as part of dental and dental hygiene clinical courses. Each component in the assessment instruments demonstrated internal consistency (alpha range=0.779-0.960). Based on a principal components analysis, six new factors were found to be significantly associated with communication skills: being caring and respectful, sharing information, interacting with team members, tending to comfort, professional relationship-building, and appointment preparation/follow-up. Correlational analysis demonstrated a core of critical instrument items to be considered for future assessment of the quality of communication between student clinicians and patients. Adequate estimates of reliability and validity for the PCAI and SCAI were demonstrated. Further research is needed in other countries and cultures to test and confirm the constructs.
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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 | 0.034 | 0.122 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".