A scoping review on the study of siblings in pediatric pain
Bibliographic record
Abstract
Background: Sibling relationships are longstanding across an individual’s life and are influential in children’s development. The study of siblings in pediatric pain is, although in early stages, a growing field.Aims: This scoping review sought to summarize and map the type of research available examining siblings and pediatric pain to identify gaps and directions for future research.Methods: Studies were identified based on a search of PubMed, CINAHL, PsycInfo, Embase, and Web of Science (up to November 2016). We extracted data about study methods, the sample, outcome assessment, and the influence/relationships investigated.Results: Thirty-five studies were included. Most studies used quantitative methods (n = 28), and participants typically included children (i.e., aged 6–12; n = 24) and adolescents (i.e., aged 13–18; n = 18). The majority of studies examined siblings in the context of chronic and disease-related pain (n = 30). Though quantitative studies primarily focused on the genetic influence of pain conditions (n = 18), qualitative and mixed-methods studies typically focused on exploring the impact of siblings with and without pain on one another (n = 2) and the impact of pain on the broader dyadic relationship/functioning (n = 4).Conclusions: Sibling research in pediatric pain has been primarily focused on the biological/physical components of pain, using quantitative approaches. Conducting more studies using qualitative or mixed-methods designs, incorporating multiple assessment measures (e.g., observational, self-report) and multiple perspectives (e.g., siblings, health professionals), may provide an opportunity to gain richer and more comprehensive information regarding the experience of siblings.
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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 | 0.007 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".