Bibliographic record
Abstract
Shared decision making (SDM) is rarely used in pediatric clinical practice. The purpose of this dissertation was to explore factors influencing SDM implementation in pediatric clinical practice. We conducted three studies that were guided by the Ottawa Model of Research Use (OMRU): Study 1 was a systematic review using Cochrane methods and the Mixed Methods Appraisal Tool to determine pediatric SDM barriers and facilitators from multiple perspectives. Eighty studies, of low to high quality, were included. At each OMRU level, frequently cited barriers were: option features (decision), poor quality information (innovation), emotional state (adopter), power relations (relational), and insufficient time (environment). Frequently cited facilitators were: lower stake decisions (decision), agreement with SDM (adopter), high quality information (innovation), trust and respect (relational), and SDM tools/resources (environment). Across participant types, frequently cited barriers were: insufficient time (healthcare providers (HCP)), option features (parents), power imbalances (children), and HCPs’ SDM skills (observers). Frequently cited facilitators were: good quality information (HCPs) and agreement with SDM (parents/children). Study 2 was a post-test design that evaluated SDM knowledge and acceptability of learners who completed the Ottawa Decision Support Tutorial (ODST). Most learners were HCPs (62%). Overall, ODST learners had a median knowledge test score of 8/10 (IQR = 7-9; n=6604) and 90% reported good or excellent impressions (n=4276) after completing the tutorial. Few learners suggested improvements. Study 3 used mixed methods to evaluate pediatric HCPs’ perceived SDM barriers and facilitators after training (ODST plus workshop). Participants completed a SDM barrier survey (n=60; 88% response rate) and semi-structured interview (n=11). Their intention to use SDM was high (mean score = 5.6/7, SD=0.8). However, 90% of respondents reported minimal SDM use after training. Main barriers were lack of buy-in (adopter level) and time constraints (environmental level). Healthcare providers wanted a team-based approach to SDM training (training level). Adopters face numerous and diverse barriers to SDM use, before and after SDM training. Pediatric HCPs who completed the ODST were knowledgeable about SDM. Despite positive intentions, training alone was insufficient to achieve routine SDM use. These findings can inform intervention development to promote SDM implementation in pediatric clinical practice.
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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 | 0.141 | 0.329 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".