Diagnostic Validity of Sensory Responsivity

Full Citation: Reynolds, S. & Lane, S. J. (2008). Diagnostic validity of Sensory Over- Responsivity: A review of the literature and case reports. Journal of Autism and Developmental Disorders, 38(3), 516-29

Atypical responses to sensory stimulation are frequently reported to co-occur with diagnoses such as autism, ADHD, and Fragile-X syndrome. It has also been suggested that children and adults may present with atypical sensory responses while failing to meet the criteria for other medical or psychological diagnoses. This may be particularly true for individuals with over-responsivity to sensation. This article reviews the literature related to sensory over-responsivity and presents three pediatric cases that present a profile of having sensory over-responsivity without a co-occurring diagnosis. Findings from these cases provide very preliminary evidence to support the suggestion that sensory over-responsivity can occur as a sole diagnosis. Within this small group, tactile over-responsivity was the most common and pervasive form of this condition.

Sensory Over-responsivity and Anxiety in ADHD

Full Citation: Reynolds, S., & Lane, S. J. (in press). Sensory Over-responsivity and Anxiety in Children with ADHD. The American Journal of Occupational Therapy.

It is estimated that approximately 25% of children with ADHD have a co-morbid anxiety disorder. Sensory over-responsivity (SOR) has been correlated with anxiety in some populations of children with developmental delays and other co-morbidities. The purpose of this study was to determine if SOR is related to elevated levels of anxiety in children with ADHD.

Twenty four children between the ages of six and ten with ADHD and 24 children without ADHD were recruited for this study. All parents completed a Revised Children’s Manifest Anxiety Scale (RCMAS) and a Sensory Over-Responsivity Inventory with their child. Children in the ADHD group were subdivided into ADHD+SOR and ADHD-only groups using the Sensory Over-Responsivity Inventory, a behavioral parent report measure. Anxiety and SOR scores were examined using an Analysis of Variance and a Fishers exact test to look for differences between group means and compare scores to clinical a cut-off standard.

Results indicated that children in the ADHD+SOR group were significantly more anxious than both the ADHD-only and non-ADHD (control) groups. Children with ADHD+SOR were also more likely to have clinically significant anxiety as determined by total scores on the RCMAS. Professionals treating children with ADHD and SOR should be aware that these children may also have anxiety and discuss with families options for prevention and/or treatment.

The Moderating Role of Sensory Over-responsivity in HPA Activity: A pilot study with children diagnosed with ADHD

Full Citation: Reynolds, S., Lane, S. J., & Gennings, C. (in press). The Moderating Role of Sensory Over-responsivity in HPA Activity: A pilot study with children diagnosed with ADHD. Journal of Attention Disorders.

The purpose of this study was to determine if sensory over-responsivity (SOR) is a moderating condition which impacts the activity of the Hypo-pituitary Adrenal (HPA) Axis at baseline and in response to a Sensory Challenge Protocol. Participants were 24 children between the ages of six and ten diagnosed with ADHD and 24 children without ADHD. Children in the ADHD group were divided into SOR (ADHDs) and non-SOR (ADHDt) groups using the Sensory Over-Responsivity Inventory (SensOR). Salivary cortisol was used as a measure of HPA activity. All children participated in the Sensory Challenge Protocol, receiving eight stimuli in each of the following sensory channels: auditory tone, visual, auditory siren, tactile, olfactory, and vestibular. Two pre-challenge and seven post-challenge measures of salivary cortisol were taken. Cortisol baseline and reactivity patterns between groups were examined using a mixed-effects ANOVA.

No baseline differences in salivary cortisol were found between groups. In response to a sensory challenge, there was a borderline significant difference found between the ADHDt and ADHDs group (p=0.056) and a significant difference between ADHDt and the typical group (p=0.014), with cortisol levels being significantly lower in the ADHDt group in both comparisons. These preliminary results support the premise that the presence of SOR may be considered a moderating variable used to create subgroups in diagnostic populations, particularly in ADHD research.

Physiological and Neuroendocrine Patterns in Children with Autism

Stacey Reynolds PhD, OTR/L & Shelly J. Lane PhD, OTR/L, FAOTA

Poster Presentation at the American Occupational Therapy Association Conference, 2009, Houston, TX

Introduction
One of the most prevalent and functionally disabling characteristics of Autism Spectrum Disorders (ASD) is the inability to accurately grade responses to sensory stimulation, a condition known as Sensory Modulation Disorder (SMD). The Sensory Processing And Stress Evaluation (SPASE) Lab at VCU and the Sensory Integration Lab at Pediatric Therapy Network (PTN) are equipped to examine physiological and neuroendocrine reactivity to sensation in children. These measures may be used to better understand the underlying mechanisms of SMD and the link between physiology and behavior.

Results
Thirty four children participated in this study, 21 children with ASD and 13 typical controls (TYP). Demographic information is presented in Table 1. The groups were not significantly different for age, cognition, or race. They were significantly different based on gender (p=.004), with more boys in the autism group than in the control group.

Multivariate analysis of covariance (MANCOVA) tests were used to examine differences in diurnal, tonic and phasic reactivity between the ASD and TYP groups. Gender was entered as a covariate in an attempt to control for inherent group differences. For reactivity measures, baseline measure of cortisol and skin conductance level were also entered as covariates.

Diurnal Patterns of Salivary Cortisol: As presented in Figure 1, the ASD group mean levels of salivary cortisol were higher overall for morning, afternoon and nighttime levels. Significant differences, however, were found only for nighttime levels (p=.009)

Baseline Cortisol: There were no significant differences between groups at baseline 1 (B1) (p=.516) or baseline 2 (B2) (p=.235) prior to initiating the SCP. Baseline measures were averaged and this average was used as a covariate when examining group differences in reactivity (Figure 2).

Cortisol Reactivity:When gender and baseline cortisol were entered into the MANCOVA model, significant differences between groups were found for all post-SCP measurements of salivary cortisol (p=.000), with the ASD group showing the highest levels at each data point (Figure 2).

Tonic EDA Measures: There were no significant differences found between the ASD and TYP group for tonic measures of EDA; Non-Specific Respones (NSR) baseline (p=.072), Skin Conductance Level (SCL) baseline (p=.205).

Phasic EDA Measures: There was a significant difference between groups for average Orienting Response (p=.012), and Amplitude of response to tone (p=.001), visual (p=.002), siren (p=.008), olfactory (p=.022), and movement (p=.013) stimuli. All response values log transformed Response patterns plotted in Figure 3.

Sensory Profile (SP): Children with ASD showed significantly lower scores, indicating a higher level of dysfunction, on all sensory processing sections of the Sensory Profile (p= .000-.002). Raw scores are presented graphically in Figure 4.

Correlations between Physiology and Behavior: Bivariate correlation matrices were created to examine the relationship between section scores on the Sensory Profile and physiological and neuroendocrine measures taken in the lab.

Tonic Measures: Baseline cortisol was not significantly related to any Sensory Profile section scores. Average skin conductance at baseline was significantly related to scores for Auditory Processing (r = -.413), Visual Processing (r = -.389), Touch Processing (r = -.533), Multisensory Processing,(r = -.369) and Oral Sensory Processing(r = -.529). Number of non-specific EDA responses at baseline was significantly related to Auditory Processing (r = -.413) and Multisensory Processing (r = -.411) section scores.

Phasic Measures: Average post-challenge cortisol measures and average EDA amplitude of the orienting response did not significantly relate to any section scores on the Sensory Profile. Average EDR amplitude of responses across all domains on the SCP was significantly correlated with Auditory Processing (r = -.494) and Visual Processing (r = -.376) scores on the Sensory Profile; with borderline significance for correlations with Multisensory (r = -.321) and Touch (r = -.327) Processing.

Conclusions
Results suggests that children with and without autism clearly differ on reactive (phasic) physiological and neuroendocrine measures in response to sensation. Tonic differences were not found between groups. Children with and without autism showed normal diurnal patterns of cortisol, with elevations in the morning and steady decreases throughout the day. Children with autism showed higher levels of cortisol throughout the day, with a significant difference at nighttime. Despite the small sample size for this pilot work, estimates of power and effect size were moderate to high, suggesting significance levels may be achieved with a larger sample. Unsurprisingly, children with and without autism were significantly different in their behavioral responses to sensation as measured on the Sensory Profile. Interestingly, these scores were correlated to both tonic and phasic measures of electrodermal activity.

Acknowledgements
This research was supported by the National Institutes of Health General Clinical Research Center (Grant M01 RR00065, NCRR, NIH) and the Virginia Commonwealth University A.D. Williams research development fund. Thank you to Kelly Bloom, Zoe Mailloux and everyone at Pediatric Therapy Network who assisted us in data collection for this project. We would also like to acknowledge the Sensory Integration and Research Collaborative (SIRC) for contributing to the methods and theoretical basis for this work.

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