PSYCHOPHYSICAL CORRELATES OF CHILDREN WITH SENSORY MODULATION DISORDER
Bibliographic record
Abstract
Objective: Sensory modulation disorder (SMD) is a generalised disorder that affects the modulation of sensory input across different modalities. Children with SMD are characterised by an abnormal processing of the sensory-discriminative and affective-aversive attributes of naturally occurring stimuli and are limited in their ability to participate fully and attain optimal quality of life. Approximately 5% of the paediatric population in the USA demonstrate over or underresponsiveness to sensory stimuli that is severely maladaptive, interfering with their daily life functions. Our aim in this study was to phenotype children with SMD psychophysically using low and high mechanical tactile stimulation. Method: Using the short sensory profile followed by the sensory profile, 44 children were diagnosed as having SMD (33 boys and 11 girls on average 7.5 years old (SD 1.20 months)) and 34 as SMD-free (18 boys and 16 girls, 7.67 years old (SD 1.33 months)). All participants underwent tests to determine the detection and tolerance thresholds to warm, hot, cold, light touch, vibration, prickliness and pinprick stimuli. Results: We found no differences between the groups in the detection thresholds of vibration, light touch, warm stimuli and pain thresholds of heat and cold stimuli. However, significant group differences were found for the detection of cold stimuli. The groups also differed significantly in the level of pain elicited in response to punctate tests. Conclusion: This is the first psychophysical assessment of children with SMD, identifying quantifiable sensory abnormalities in various somatosensory submodalities that can be used as diagnostic tests.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".