Dissemination of Patient Decision-Making Aids Via a Web-Based Platform
Bibliographic record
Abstract
Purposes/Aims: The aim of this study was to create a web-based brokerage of patient decision-making aids, titled Split Decision™, and to evaluate student nurse and student nurse practitioners' intent to use and recommend the prototype website based on their perceived usability, usefulness and satisfaction. Rationale/Background: Adult patients frequently report confusion about treatment options, hindering their ability to fully participate in healthcare decision-making. Over 500 patient decision-aids exist on the internet, but are scattered across dozens of websites. Creation of a web-based decision-aid platform would utilize the existing information-seeking habits of patients, but provide them with evidence-based information when evaluating treatment options. Methods: Exemplar decision-aids were chosen from the 563 decision-aids published in the Ottawa Research Institute database and posted on a decision-aid brokerage website. Online access to the website was offered to study participants (n=29) from May to June 2016. Demographic information, quantitative and qualitative responses were collected from each website user and analyzed to evaluate perceived usability, satisfaction, and intention to use the pilot website. Results: Usability of the Split Decision™ website was found to be above average on Systems Usability Scale ratings. Participants rated the website highest on visual appeal and clear terminology on quantitative measures. Qualitative responses cited confusion with the navigation of pages and hyperlinks as areas of future improvement. Conclusion: Study participants expressed a hope for future expansion of the website to other topics and patient populations. Further study of the Split Decision™ website will be planned to test revisions suggested during by participants during this doctoral project.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".