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Prevalence and severity-based classification of sensory processing issues. An exploratory study with neuropsychological implications.

Adrián GalianaJose Maria Flores-RipollPedro Javier Benito-CastellanosClara Villar-RodriguezMaria Vela-Romero
Published in: Applied neuropsychology. Child (2021)
Sensory processing issues, mainly known as sensory processing disorder or SPD, are frequent in children with neurodevelopmental disorders and are associated with learning and behavioral difficulties. However, previous studies suggest that these disturbances might also be present in typically developing children, reaching prevalence rates of 10-20%. Nevertheless, published studies have been primary been conducted in non-European countries. Therefore, we aim, as first objective, to explore the frequency of sensory processing difficulties in a random sample of school-age children from Spain to contribute to the study of its prevalence. The Sensory Profile-2 (SP2) assessment tool was administered to 369 participants to study their sensory processing patterns, the absence or presence of sensory processing issues, the affected sensory systems, as well as their socioemotional, attentional, and behavioral impact. Furthermore, as second objective, we have developed a novel strategy to classify SPD by severity ranges using SP2 yielded results; accordingly, the sample was classified as follows: no alteration, mild, moderate, and severe sensory processing alteration. The results show prevalence rates consistent with previous findings: 15.9% of participants met the severe alteration criteria and 10.5%, 11.1% and 62.5% were classified as moderate, mild and no alteration, respectively. Finally, we hypothesize about SPD and underlying neuropsychological processes that might be associated with this condition. Our results highlight the necessity of further research efforts to establish whether high-frequency and severity rates of sensory processing alterations are linked to neuropsychological variables. The provided classification system might be useful to determine such associations.
Keyphrases
  • high frequency
  • risk factors
  • young adults
  • mild cognitive impairment
  • machine learning