The role of narrative in the development of children's pain memories: influences of father– and mother–child reminiscing on children's recall of pain
Bibliographic record
Abstract
Negatively biased memories for pain (ie, recalled pain is higher than initial report) robustly predict future pain experiences. During early childhood, parent-child reminiscing has been posited as playing a critical role in how children's memories are constructed and reconstructed; however, this has not been empirically demonstrated. This study examined the role of parent-child reminiscing about a recent painful surgery in young children's pain memory development. Participants included 112 children (Mage = 5.3 years; 60% boys) who underwent a tonsillectomy and one of their parents (34% fathers). Pain was assessed in hospital and during the recovery phase at home. Two weeks after surgery, parents and children attended a laboratory visit to participate in a structured narrative elicitation task wherein they reminisced about the surgery. Four weeks after surgery, children completed an established pain memory interview using the same previously administered scales through telephone. Narratives were coded for style (elaboration) and content (pain and emotion) based on coding schemes drawn from the developmental psychology literature. Findings revealed that a more elaborative parental reminiscing style in addition to greater use of emotional words predicted more accurate/positively biased pain memories. Greater parental use of pain words predicted more negatively biased pain memories. Although there were no sex and parent-role differences in pain memory biases, mothers and fathers differed in how they reminisced with their boys vs girls. This research underscores the importance of parent-child reminiscing in children's pain memory development and may be used to inform the development of a parent-led memory reframing intervention to improve pediatric pain management.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".