“It Helped Me Understand What I Was Walking into:” Youth and Caregiver Acceptability and Satisfaction with a Psychological Perioperative Pain Management Intervention
Bibliographic record
Abstract
Background: Chronic postsurgical pain (CPSP) occurs in approximately one in five children who undergo surgery. Youth with anxiety and depressive symptoms are at greater risk of developing CPSP. Psychological interventions hold promise to prevent CPSP; however, existing psychological interventions are often brief and offered exclusively pre-surgically. Objective: The Perioperative Pain Program (PPP) was designed to address psychological risk factors for CPSP. This study aimed to explore acceptability and satisfaction with the PPP, from the perspective of youth and caregivers. Method: In this mixed-methods study, 24 youth and caregivers completed a satisfaction questionnaire, and six dyads participated in semi-structured interviews. Quantitative data was analyzed using descriptive statistics. Qualitative data was analyzed using inductive content analysis. Results: The qualitative analysis generated four categories: (1) developing support and a sense of preparedness for surgery; (2) connection matters between families and the team; (3) personal characteristics may impact intervention use; (4) the need for adaptable content and delivery. Quantitative data indicated overall satisfaction and acceptability of the intervention. Conclusions: Psychological interventions that facilitate interpersonal connections in a timely manner may be key to facilitating more meaningful engagement and help prevent CPSP in youth.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".