Patient-Provider Communications in Outpatient Clinic Settings: A Clinic-Based Evaluation of Mobile Device and Multimedia Mediated Communications for Patient Education
Bibliographic record
Abstract
BACKGROUND: Many studies have provided evidence of the importance of quality provider-patient communications and have suggested improvements to patient understanding by using video-based instruction. OBJECTIVE: The objective of this study was to understand how mobile information technology assisted video and three-dimensional (3D) image instruction, provided by a health care worker, influences two categories of outcome: (1) patient understanding of information about their condition and detailed medical discharge instructions; and (2) patient perceptions and attitudes toward their health care providers, which included physicians, nurses, and staff. We hypothesize that video and 3D image instruction, provided on a mobile, tablet hardware platform, will improve patient understanding about the diagnostic testing, diagnoses, procedures, medications, and health topics provided to them. We also propose that use of the tablet/video combination will result in improved attitudinal evaluation by patients of their providers and the treatment plan. METHODS: This study evaluated a hospital clinic-based trial (patient N=284) of video and 3D image instruction, provided on a mobile, tablet hardware platform, and its potential to improve patient understanding about the diagnostic testing, diagnoses, procedures, medications, and health topics provided to them. RESULTS: Results showed strong evidence that the system was perceived as helpful for improving patient understanding, and that it improved communication between physicians and patients (P<.001). The advanced age of some patients had no effect on their perceptions of the tablet-based mediation. Physician comments provided useful insights on effective use of such systems in the future. Implications for further development and future research are discussed. CONCLUSIONS: This study added to the body of evidence that computer-assisted video instructional systems for patients can improve patient understanding of medical instructions from their health care providers and assist with patient compliance. In addition, such systems can be appealing to both patient and provider.
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".