Infographic summaries for clinical practice guidelines: results from user testing of the BMJ Rapid Recommendations in primary care
Bibliographic record
Abstract
OBJECTIVES: Infographics have the potential to enhance knowledge translation and implementation of clinical practice guidelines at the point of care. They can provide a synoptic view of recommendations, their rationale and supporting evidence. They should be understandable and easy to use. Little evaluation of these infographics regarding user experience has taken place. We explored general practitioners' experiences with five selected BMJ Rapid Recommendation infographics suited for primary care. METHODS: An iterative, qualitative user testing design was applied on two consecutive groups of 10 general practitioners for five selected infographics. The physicians used the infographics before clinical encounters and we performed hybrid think-aloud interviews afterwards. 20 interviews were analysed using the Qualitative Analysis Guide of Leuven. RESULTS: Many clinicians reported that the infographics were simple and rewarding to use, time-efficient and easy to understand. They were perceived as innovative and their knowledge basis as trustworthy and supportive for decision-making. The interactive, expandable format was preferred over a static version as general practitioners focused mainly on the core message. Rapid access through the electronic health record was highly desirable. The main issues were about the use of complex scales and terminology. Understanding terminology related to evidence appraisal as well as the interpretation of statistics and unfamiliar scales remained difficult, despite the infographics. CONCLUSIONS: General practitioners perceive infographics as useful tools for guideline translation and implementation in primary care. They offer information in an enjoyable and user friendly format and are used mainly for rapid, tailored and just in time information retrieval. We recommend future infographic producers to provide information as concise as possible, carefully define the core message and explore ways to enhance the understandability of statistics and difficult concepts related to evidence appraisal. TRIAL REGISTRATION NUMBER: MP011977.
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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 | 0.013 | 0.383 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".