The Canadian Congenital Diaphragmatic Hernia Collaborative Mobile App: A National Guideline Implementation Strategy
Bibliographic record
Abstract
OBJECTIVE: Coinciding with the publication of the Canadian congenital diaphragmatic hernia (CDH) Collaborative's clinical practice guidelines (CPG), we developed a mobile smartphone app to increase guideline utilization and promote knowledge translation. STUDY DESIGN: This mobile app was organized into sections corresponding to the phases of CDH care (prenatal, perinatal/postnatal, and child/adolescent), and contained 22 recommendations supported by evidence summaries, PubMed links, levels of evidence, and strength of expert consensus. Download statistics were collected from September 2018 to June 2020 after release of two iOS versions and an Android platform. Data regarding user numbers/location, most visited sections, and individual session details were analyzed. RESULTS: During the study period, the CDH app had 1,586 users predominantly from Canada (40%), United States (30%), and Brazil (12%). The Android release increased app visibility, particularly in Brazil, which had the largest number of new users. Of 3,723 sessions, roughly one-third were returning users. The average session duration and screens viewed/session was 4 minutes and seven screens, respectively. Postnatal ventilation was the most frequently visited subsection after prenatal diagnosis/risk stratification. Measurement of observed-to-expected lung head ratio was the most visited individual recommendation. The guideline compliance checklist was the most frequently accessed resource highlighting its utility. CONCLUSION: The CDH app is an innovative platform to disseminate guidelines. The increasing global reach of the app suggests worldwide CPG relevance. With additional features planned, the CDH app will continue to support clinical decision-making and empower patients and families as they navigate the short and long-term challenges associated with CDH. KEY POINTS: · Mobile smartphone technology provides an optimal platform for guideline dissemination.. · International uptake supports worldwide CPG relevance.. · Future initiatives include the development of patient and family resources..
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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 | 0.023 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".