Parent–Child Reminiscing about Past Pain as a Preparatory Technique in the Context of Children’s Pain: A Narrative Review and Call for Future Research
Bibliographic record
Abstract
Pain permeates childhood and remains inadequately and/or inconsistently managed. Existing research and clinical practice guidelines have largely focused on factors influencing the immediate experience of pain. The need for and benefits of preparing children for future pain (e.g., painful procedures) has been well established. Despite being a robust predictor of future pain and distress, memories of past painful experiences remain overlooked in pediatric pain management. Just as autobiographical memories prepare us for the future, children's memories for past pain can be harnessed to prepare children for future painful experiences. Children's pain memories are malleable and can be reframed to be less distressing, thus reducing anticipatory distress and promoting self-efficacy. Parents are powerful agents of change in the context of pediatric pain and valuable historians of children's past painful experiences. They can alter children's pain memories to be less distressing simply by talking, or reminiscing, about past pain. This narrative review summarizes existing research on parent-child reminiscing in the context of acute and chronic pediatric pain and argues for incorporation of parent-child reminiscing elements into preparatory interventions for painful procedures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".