Family risk communication preferences in pediatric surgery: A scoping review
Bibliographic record
Abstract
BACKGROUND: Effective patient-surgeon communication is vital in pediatric surgical practice. However, family (including child) preferences for the format and content of risk communication information are largely unknown. In order to optimize the shared-decision making process, this scoping review explored the family-preferred methods for risk communication in pediatric surgery. METHODS: A search was conducted in 7 databases from inception until June 2020 to identify family risk communication preferences in pediatric surgical patients, with language restricted to English and French. Two independent reviewers completed the screening in Rayyan software following PRISMA protocol. Included publications were reviewed for data extraction, analyzed, and assessed for risk of bias using standardized instruments. RESULTS: A total of 6370 publications were retrieved, out of which 70 were included. Studies were predominantly from ENT (30.0%), general surgery (15.7%), and urology (11.4%). Family-preferred risk communication methods were classified as visual, verbal, technology-based, written, decision aids or other. Technological (32.4%) and written tools (29.7%) were most commonly chosen by families as their preferred risk communication methods. Written tools were frequently used in general surgery and urology, while technology-based tools were widely used in ENT. Most studies were cross-sectional and had a significant risk of bias. CONCLUSION: Eliciting families' preferences for risk communication methods is critical for the implementation of shared decision-making. Different risk communication media appear to be preferred within specific surgical domains. To further improve shared-decision making in pediatric surgery, the development and usage of robust, validated risk communication tools are necessary. LEVEL OF EVIDENCE: Level IV (Scoping Review).
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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 | 0.118 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.016 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".