What’s in a Name? Health Care Providers’ Perceptions of Pediatric Pain Patients Based on Diagnostic Labels
Bibliographic record
Abstract
OBJECTIVES: Diagnostic labels can help patients better understand their symptoms and can influence providers' treatment planning and patient interactions. Recurrent pain is common in childhood; however, there are various diagnostic labels used. The objective of this study was to evaluate the influence of diagnostic labels on pediatric health care providers' perceptions of pediatric chronic pain patients. MATERIALS AND METHODS: Using an online survey, providers were randomly assigned to 1 of 2 vignette conditions (differing only in diagnostic label provided) and completed questionnaires about their perceptions of the vignette patient. RESULTS: Responses from 58 participants were analyzed. The 2 groups, based on diagnostic conditions used (fibromyalgia and chronic widespread pain) did not differ significantly on general demographics and health care providers' perceptions of the patient. Perceived origin of the pain influenced providers' perceptions; pain of a perceived medical origin was negatively correlated with stigmatization and positively correlated with sympathy. Perceived psychological origin was positively correlated with stigmatization and providers' age. DISCUSSION: Health care providers' perceptions of children's pain are more likely influenced by the presumed etiology rather than the diagnostic label used. Pain believed to be more medically based was associated with more positive reactions from providers (ie, less stigmatization). Older providers in particular perceived the patient more negatively if they believe the pain to be psychologically based. The findings of this pediatric study replicated findings from adult literature on chronic pain, suggesting that children and adults are subject to negative perceptions from health care providers when the providers believe the pain to be psychological in origin.
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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".