102 Optimizing the Management of Pain and Irritability in Children with Severe Neurological Impairments: A Qualitative Study
Bibliographic record
Abstract
Abstract Introduction/Background Pain and irritability of unknown origin (PIUO) is reported to effect 73% of children with severe neurological impairments (SNI), and is a source of stress for children and families alike. Currently, there is no consensus among clinicians on how to manage PIUO and it is often difficult to determine the source of pain. Lacking an explanation for the source leaves clinicians unable to effectively treat the pain and increases a caregiver’s obstacles in providing care. Limited research exists on the effect of PIUO on children with SNI and their families. Objectives To explore and characterize the overall experience of PIUO for children with SNI and their families. Design/Methods Semi-structured interviews were conducted with parental caregivers of children with SNI who experience PIUO and are followed by the Complex Care Program at SickKids. Interview guide topics included pain expression and management, healthcare-team support and family coping. Interviews were conducted until saturation was reached. Interviews were audio-recorded, transcribed verbatim, coded and analyzed by two independent reviewers using an inductive six-step thematic analysis process on NVivo software. Results Fifteen caregivers were interviewed, with 93% being mothers and 33% being a visible minority. Interviews revealed two major themes and associated subthemes (in parentheses): 1) Day-to-day life with PIUO (pain expression and frequency, management, and quality of life) and, 2) Areas for improvement (diagnostic process, resources and support, healthcare-team interactions). Characterizing the PIUO experience is an important area of research as findings can be used to guide clinical teams in providing holistic family-centered care to children with SNI. The findings support the need for clinical innovation by adjusting practice guidelines through the creation and implementation of an integrated clinical pathway to identify treatable causes of pain and irritability in children with SNI. Conclusion Diagnostic tests for PIUO are often inconclusive and stressful for patient-families. Limited pharmacological and non-pharmacological treatments exist for PIUO. Parental caregivers describe the experience as emotionally challenging and requested support for coping. Future research should focus on interventions for PIUO in children with SNI and reducing caregiver stress and burden.
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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 | 0.011 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".