Assessing Sensory Processing Dysfunction in Adults and Adolescents with Autism Spectrum Disorder: A Scoping Review
Bibliographic record
Abstract
Sensory reactivity is a diagnostic criterion for Autism Spectrum Disorder (ASD), and has been associated with poorer functional outcomes, behavioral difficulties, and autism severity across the lifespan. Yet, there is little consensus on best practice approaches to assessing sensory processing dysfunction in adolescents and adults with ASD. Despite growing evidence that sensory symptoms persist into adolescence and adulthood, there is a lack of norms for older age groups, and pediatric assessments may not target appropriate functional outcomes or environments. This review identified approaches used to measure sensory processing in the scientific literature, and to describe and compare these approaches to current best practice guidelines that can be incorporated into evidence-based practice. Method and Analysis: A search of scientific databases and grey literature (professional association and ASD society websites), from January 1987–May 2017, uncovered 4769 articles and 12 clinical guidelines. Study and sample characteristics were extracted, charted, and categorized according to assessment approach. Results: There were 66 articles included after article screening. Five categories of assessment approaches were identified: Self- and Proxy-Report Questionnaires, Psychophysical Assessment, Direct Behavioral Observation, Qualitative Interview Techniques, and Neuroimaging/EEG. Sensory research to date has focused on individuals with high-functioning ASD, most commonly through the use of self-report questionnaires. The Adolescent and Adult Sensory Profile (AASP) is the most widely used assessment measure (n = 22), however, a number of other assessment approaches may demonstrate strengths specific to the ASD population. Multi-method approaches to assessment (e.g., combining psychophysical or observation with questionnaires) may have clinical applicability to interdisciplinary clinical teams serving adolescents and adults with ASD. Contribution: A comprehensive knowledge of approaches is critical in the clinical assessment of a population characterized by symptomatic heterogeneity and wide-ranging cognitive profiles. This review should inform future development of international interdisciplinary clinical guidelines on sensory processing assessment in ASD across the lifespan.
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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 | 0.006 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.019 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".