Children and pain: Assessment and management according to parents' perspective
Bibliographic record
Abstract
Pain in children is frequent. Parents evaluate their children's pain to decide how to manage it or to share information with caregivers. This qualitative descriptive study aims to identify elements influencing the evaluation and management of pain in children from a parent's perspective. Participants were recruited through a pediatric center and university family medicine clinic. Participants had to have used medication for their child that was prescribed "as needed" to manage their child's pain in the month preceding the interview, whether it was a prescription-strength medication or an over-the-counter strength prescription. Semi-directed interviews 30-45 min in duration were conducted with 16 parents in the Outaouais region of Quebec (Canada), either at the participant's home or by phone (after the declaration of the COVID-19 pandemic). A thematic analysis was completed to identify themes in the data from these individual interviews. The evaluation of children's pain by their parents is influenced by the parents' experience with pain and the expression of the pain by the children, whereas the actions to relieve the pain are based on the beliefs surrounding pain management in children. Evaluation of pain is complex since many parents' beliefs influence this evaluation and the subsequent pain management. The study results raise healthcare professionals' awareness regarding several elements which influence the evaluation of children's pain and its management by their parents.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".