Distinguishing Sensory Sensitivity and Reactivity, and How They Relate to Autistic Traits
Bibliographic record
Abstract
Sensory processing issues are common across neurodevelopmental disorders, including attention-deficit/hyperactivity disorder, obsessive compulsive disorder and intellectual disabilities, as well as other mental health disorders such as schizophrenia, anxiety, and depression. This study uses a novel behavioural paradigm and a questionnaire to assess sensory issues and these two methods are directly compared to distinguish sensory sensitivity and sensory reactivity. We also used autistic traits as an empirical testbed to shed light on the relationships between sensory processing issues and traits associated with neurodevelopmental disorders. Sensory processing issues are highly prevalent in the autistic population, and previous findings have strongly supported a relationship between parent or self-reported sensory sensitivity and autistic traits, whereas studies that have examined this relationship through behavioural assessments of sensitivity are less consistent. The current study explores these differences and suggests that sensory sensitivity and sensory reactivity are distinct constructs, with questionnaires assessing reactivity whereas behavioural measures assess sensitivity. One hundred and eighteen typically-developed adults completed a visual detection task, an auditory detection task, and questionnaires on sensory processing and autistic traits. Visual thresholds, derived from the behavioural paradigm and self-report visual sensitivity were not correlated, but both were related to and predictive of autistic traits. Auditory thresholds and self-report auditory sensitivity were also unrelated. Overall, sensitivity is highly associated with autistic traits, however, behavioural and questionnaire assessments of sensitivity lack convergent validity and, therefore, likely assess distinct constructs. In conclusion, sensory sensitivity and sensory reactivity are unique concepts that fall under the umbrella of sensory processing differences and need to be researched as such in relation to behavioural traits across clinical populations.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".