Pediatric patient engagement in clinical care, research and intervention development: a scoping review
Bibliographic record
Abstract
BACKGROUND: In the last decades, pediatric patient engagement has received growing attention and its importance is increasingly acknowledged. Pediatric patient engagement in health care can be defined as the involvement of children and adolescents in the decision-making of daily clinical care, research and intervention development. Although more attention is paid to pediatric patient engagement, a comprehensive overview of the activities that have been done regarding pediatric patient engagement and the changes over time is lacking. Therefore, the aim of this study is to provide an overview of the literature about pediatric patient engagement. METHODS: The methodological framework of Arksey & O'Malley was used to conduct this scoping review. The bibliographic databases Medline, Embase, and PsycINFO were searched for eligible articles. All retrieved articles were screened by at least two researchers in two steps. Articles were included if they focused on pediatric patient engagement, were carried out in the context of clinical care in pediatrics, and were published as full text original article in English or Dutch. Data (year of publication, country in which the study was conducted, disease group of the participants, setting of pediatric patient engagement, used methods, and age of participants) were extracted, synthesized, and tabulated. RESULTS: A total of 288 articles out of the 10,714 initial hits met the inclusion criteria. Over the years, there has been an increase in the number of studies that engage pediatric patients. Pediatric patients, especially patients with multiple conditions or oncology patients, were most involved in studies in the United States, United Kingdom, and Canada. Pediatric patients were most often asked to express their views on questions from daily clinical care and the individual interview was the most used method. In general, the extent to which pediatric patients are engaged in health care increases with age. DISCUSSION: This scoping review shows that there is an increasing interest in pediatric patient engagement. However, lack of uniformity about the definition of pediatric patient engagement and clear information for clinicians hinders engagement. This overview can inform clinicians and researchers about the different ways in which pediatric patient engagement can be shaped and can guide them to engage pediatric patients meaningfully in their projects.
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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 | 0.060 | 0.185 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.021 | 0.027 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".