‘Drawing a line in the sand’: Physician diagnostic uncertainty in paediatric chronic pain
Bibliographic record
Abstract
BACKGROUND: Diagnostic uncertainty is the subjective perception of an inability to provide an accurate explanation of the patient's health problem or that a label is missing or incorrect. While recently explored in youth with chronic pain and families, this is the first study to investigate diagnostic uncertainty from the perspectives of physicians. METHODS: Individual, semi-structured interviews were conducted with 16 paediatricians who assess and/or treat youth who experience complex chronic pain. Interviews explored paediatricians' perceptions, beliefs and confidence regarding the assessment and management of chronic pain in youth and how they manage uncertainty regarding the diagnosis. Interviews were analysed using inductive reflexive thematic analysis. RESULTS: Analyses generated one prominent theme: 'drawing a line in the sand'. Within this theme, physicians discussed uncertainty as inherent to their role treating youth with chronic pain. The metaphor of 'drawing a line in the sand' was used to describe a process of identifying a point at which physicians no longer sought a new diagnosis for the child's pain or continued diagnostic investigations. This line was influenced by numerous factors, which are highlighted through four subthemes: physician training, experience and mentorship; individual patient and family factors; perceived reassurance of diagnostic investigations; and the broader social context and implications. CONCLUSIONS: How physicians manage diagnostic uncertainty must be understood, as it is likely to critically impact how a diagnosis of chronic pain is communicated, the diagnostic investigations undertaken, the wait time to receiving a diagnosis, and ultimately youths' pain experiences.
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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 | 0.018 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.021 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| 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".