Diagnostic uncertainty in pediatric chronic pain: nature, prevalence, and consequences
Bibliographic record
Abstract
INTRODUCTION: Diagnostic uncertainty (DU), which is the perception that a label or explanation for a patient's health problem is missing or inaccurate, has been linked to distress, anxiety, and difficulty coping among adults with pain. This study examined the prevalence of DU among youth with chronic pain and their parents and the relation of parent and youth DU with youth pain, pain-related constructs, and health-related quality of life (HRQoL). METHODS: = 14.28 years; 73% female) and one of their parents (91% mothers) recruited from a tertiary-level pediatric chronic pain program in Canada. Youth and parent DU was assessed using a brief measure of 3 empirically derived yes/no questions regarding whether the youth and parent had received a clear diagnosis/explanation for their/their child's pain and whether they believed there was something else happening with their/their child's pain that doctors had not yet found. Youth reported on their pain intensity, pain interference, pain catastrophizing, fear of pain, and HRQoL. RESULTS: Thirty-one percent of youth and 28% of parents experienced DU. Seventy percent of parents and youth were in agreement regarding their experience of DU. Youth DU was linked to higher youth catastrophic thinking about their pain. Parent DU was linked to greater youth pain interference and intensity and lower youth HRQoL. CONCLUSION: Diagnostic uncertainty is experienced by nearly a third of youth with chronic pain and their parents and is linked to worse youth pain, pain catastrophizing, and HRQoL.
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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".