- Email: [email protected]
3.26 Development of the Extended Strengths and Weaknesses Assessment of Normal Behavior Rating Scale (E-SWAN)
NEW RESEARCH POSTERS 3.25 — 3.27
psychotic illness. Such epidemiological data may be helpful in planning services that are responsive to the target population’s needs.
EPI, PSY, SUD http://dx.doi.org/10.1016/j.jaac.2017.09.172
3.25 SEASONAL PATTERNS OF CHILD AND ADOLESCENT PSYCHIATRIC DISORDERS Katelin J. Williamson, DO, Palmetto Health and the University of South Carolina School of Medicine, katelin.krummrey@ gmail.com Objectives: There is a widely held belief in child and adolescent psychiatry that there is a decrease in mental illnesses during the summer months. It has been postulated that the stressors and demands of school contribute to an increase in psychiatric symptoms outside of the summer months. In existing literature, there are currently no objective data to support or disprove this observation. If a seasonal pattern is identified, further investigation can be pursued to determine factors driving admission patterns. This, in turn, would allow for an area of intervention to aid in decreasing psychiatric admissions and ultimately healthcare costs. Methods: A total of 159,629 hospitalizations, with primary mental health discharge diagnoses for children ages 3–20 years, were sampled in the Kids’ Inpatient Database (KID). The population proportion was estimated by year for children and adolescents meeting inclusion criteria who were admitted during the summer months. In addition to population estimates, we computed 95 percent confidence intervals and determined whether the null value is included in this interval. Results: All psychiatric diagnoses from the DSM-IV-Text Revision were categorized in three broad groups as follows: 1) mood; 2) psychotic; and 3) behavioral. The data showed that across all three groups, primary psychiatric discharge diagnoses for children and adolescents were less than the expected null value during the summer. The data showed the largest difference from the null to be in the mood category. Conclusions: Statistically significant evidence was found to support that, during the summer months, there are fewer primary psychiatric discharge diagnoses made in children and adolescents. Mood disorders had the largest difference from the expected null value. These data statistically support the observational belief that there is a decrease in admission rates for treatment of mental illnesses in children and adolescents during the summer months. It should be noted, however, that the absolute difference from the expected null is shown to be quite small in all datasets. The largest difference from the expected null was found to be a decrease of 8.58 percent (mood disorders in 2003). The average difference from the expected null was found to be a 4.09 percent decrease in primary psychiatric discharge diagnoses compared with the rest of the year. How clinically significant a decrease of four percent is debatable.
EPI, RCR, MCS Supported by the Department of Neuropsychiatry at the University of South Carolina School of Medicine http://dx.doi.org/10.1016/j.jaac.2017.09.173
3.26 DEVELOPMENT OF THE EXTENDED STRENGTHS AND WEAKNESSES ASSESSMENT OF NORMAL BEHAVIOR RATING SCALE (E-SWAN) Lindsay Alexander, MPH, Child Mind Institute, lindsay. [email protected]; Giovanni A. Salum, MD, PhD, Universidade Federal do Rio Grande do Sul, gsalumjr@gmail. com; James M. Swanson, PhD, University of California, Irvine Child Development Center, [email protected]; Michael P. Milham, MD, PhD, Child Mind Institute, michael.milham@ childmind.org Objectives: The Strengths and Weakness of ADHD-symptoms and Normalbehavior (SWAN) rating scale assesses behavior on a dimensional scale of strengths and weaknesses. A number of studies have demonstrated the ability of this method to capture more variance within populations and yield more
JOURNAL OF THE AMERICAN ACADEMY OF CHILD & ADOLESCENT P SYCHIATRY VOLUME 56 NUMBER 10S OCTOBER 2017
normally distributed data than traditional ADHD scales. Here we present the preliminary findings from the Extended Strengths and Weaknesses Assessment of Normal Behavior (E-SWAN)—an open effort focused on the extension of the SWAN methodology. Initial efforts presented here focus on the following: panic disorder, social anxiety, major depression, and disruptive mood dysregulation disorder. Methods: Data were collected from 500 participants from the Child Mind Institute Healthy Brain Network, a community-based sample group focused on the generation and open sharing of data from 10,000 children and adolescents (ages 5–21 years) in the New York City area. Parents completed each of the four E-SWAN scales and their traditional counterparts (i.e., Mood and Feelings Questionnaire, Screen for Childhood Anxiety and Related Disorders, Affective Reactivity Index). Distributional properties were examined for all scales. Item response theory (IRT) analysis was used to explore the performance of each item of the scales. Results: In contrast to the traditional scales, which exhibited truncated distributions (as expected), all four E-SWAN scales were found to have near-normal, bipolar distributions, spanning from those with substantive strengths to those with clinically significant weaknesses. IRT analyses indicate that the E-SWAN subscales provided reliable information on respondents lying at any place of the latent trait (z-scores from 3 to +3; reliabilities range from 0.77 to 0.96); in contrast, the traditional scales only provided reliable information at the high end of the latent trait (z-scores from 0 to +3). Conclusions: Building on the wisdom of the SWAN, the E-SWAN was developed to capture the full spectrum of the latent trait of several DSMclassified disorders. This type of scale has the potential to capture more variance and information on participants in a population-based study or epidemiological sample group. This is useful for both research and clinical practice. It is noteworthy that, by capturing information on strengths, there is greater potential to provide insight into factors related to resiliency.
ADOL, RI http://dx.doi.org/10.1016/j.jaac.2017.09.174
3.27 ASSESSING WHITE MATTER CORRELATES OF COGNITIVE AND VISUOMOTOR CONTROL DEFICITS IN CHILDREN WITH SENSORY PROCESSING DISORDERS Annie Brandes-Aitken, BS, University of California, San Francisco, [email protected]; Joaquin A. Anguera, PhD, University of California, San Francisco, Joaquin.Anguera@ ucsf.edu; Yi-Shin Chang, University of California, San Francisco, [email protected]; Julia P. Owen, PhD, University of California, San Francisco, [email protected]; Pratik Mukherjee, MD, PhD, University of California, San Francisco, [email protected]; Elysa J. Marco, MD, University of California, San Francisco, [email protected] Objectives: Children with sensory processing dysfunction (SPD) are reported to have challenges with cognitive and visuomotor control. In this study, we aimed to quantitatively determine whether children with SPD show deficits in their cognitive control and visuomotor control abilities using a combination of clinical and experimental direct assessments. We then used these behavioral metrics in conjunction with measures of white matter integrity via diffusion tensor imaging (DTI) to better understand the structural underpinnings of these neural processes. Methods: Here we characterized cognitive and visuomotor control and collected DTI neuroimaging data in 14 children with SPD, 13 children with SPD and comorbid attention deficits (SPD+IA), and 16 typically developing control (TDC) subjects. The cognitive control battery included a validated measure of attention (Test of Variables of Attention, TOVA), and a perceptual discrimination and goal management assessment, each presented with a novel diagnostic video game-like platform called Project:EVOTM. The visuomotor battery included the Beery TM VMI copying, matching, and tracing subtests, as well as the EVO TM navigation
www.jaacap.org
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psychotic illness. Such epidemiological data may be helpful in planning services that are responsive to the target population’s needs.
EPI, PSY, SUD http://dx.doi.org/10.1016/j.jaac.2017.09.172
3.25 SEASONAL PATTERNS OF CHILD AND ADOLESCENT PSYCHIATRIC DISORDERS Katelin J. Williamson, DO, Palmetto Health and the University of South Carolina School of Medicine, katelin.krummrey@ gmail.com Objectives: There is a widely held belief in child and adolescent psychiatry that there is a decrease in mental illnesses during the summer months. It has been postulated that the stressors and demands of school contribute to an increase in psychiatric symptoms outside of the summer months. In existing literature, there are currently no objective data to support or disprove this observation. If a seasonal pattern is identified, further investigation can be pursued to determine factors driving admission patterns. This, in turn, would allow for an area of intervention to aid in decreasing psychiatric admissions and ultimately healthcare costs. Methods: A total of 159,629 hospitalizations, with primary mental health discharge diagnoses for children ages 3–20 years, were sampled in the Kids’ Inpatient Database (KID). The population proportion was estimated by year for children and adolescents meeting inclusion criteria who were admitted during the summer months. In addition to population estimates, we computed 95 percent confidence intervals and determined whether the null value is included in this interval. Results: All psychiatric diagnoses from the DSM-IV-Text Revision were categorized in three broad groups as follows: 1) mood; 2) psychotic; and 3) behavioral. The data showed that across all three groups, primary psychiatric discharge diagnoses for children and adolescents were less than the expected null value during the summer. The data showed the largest difference from the null to be in the mood category. Conclusions: Statistically significant evidence was found to support that, during the summer months, there are fewer primary psychiatric discharge diagnoses made in children and adolescents. Mood disorders had the largest difference from the expected null value. These data statistically support the observational belief that there is a decrease in admission rates for treatment of mental illnesses in children and adolescents during the summer months. It should be noted, however, that the absolute difference from the expected null is shown to be quite small in all datasets. The largest difference from the expected null was found to be a decrease of 8.58 percent (mood disorders in 2003). The average difference from the expected null was found to be a 4.09 percent decrease in primary psychiatric discharge diagnoses compared with the rest of the year. How clinically significant a decrease of four percent is debatable.
EPI, RCR, MCS Supported by the Department of Neuropsychiatry at the University of South Carolina School of Medicine http://dx.doi.org/10.1016/j.jaac.2017.09.173
3.26 DEVELOPMENT OF THE EXTENDED STRENGTHS AND WEAKNESSES ASSESSMENT OF NORMAL BEHAVIOR RATING SCALE (E-SWAN) Lindsay Alexander, MPH, Child Mind Institute, lindsay. [email protected]; Giovanni A. Salum, MD, PhD, Universidade Federal do Rio Grande do Sul, gsalumjr@gmail. com; James M. Swanson, PhD, University of California, Irvine Child Development Center, [email protected]; Michael P. Milham, MD, PhD, Child Mind Institute, michael.milham@ childmind.org Objectives: The Strengths and Weakness of ADHD-symptoms and Normalbehavior (SWAN) rating scale assesses behavior on a dimensional scale of strengths and weaknesses. A number of studies have demonstrated the ability of this method to capture more variance within populations and yield more
JOURNAL OF THE AMERICAN ACADEMY OF CHILD & ADOLESCENT P SYCHIATRY VOLUME 56 NUMBER 10S OCTOBER 2017
normally distributed data than traditional ADHD scales. Here we present the preliminary findings from the Extended Strengths and Weaknesses Assessment of Normal Behavior (E-SWAN)—an open effort focused on the extension of the SWAN methodology. Initial efforts presented here focus on the following: panic disorder, social anxiety, major depression, and disruptive mood dysregulation disorder. Methods: Data were collected from 500 participants from the Child Mind Institute Healthy Brain Network, a community-based sample group focused on the generation and open sharing of data from 10,000 children and adolescents (ages 5–21 years) in the New York City area. Parents completed each of the four E-SWAN scales and their traditional counterparts (i.e., Mood and Feelings Questionnaire, Screen for Childhood Anxiety and Related Disorders, Affective Reactivity Index). Distributional properties were examined for all scales. Item response theory (IRT) analysis was used to explore the performance of each item of the scales. Results: In contrast to the traditional scales, which exhibited truncated distributions (as expected), all four E-SWAN scales were found to have near-normal, bipolar distributions, spanning from those with substantive strengths to those with clinically significant weaknesses. IRT analyses indicate that the E-SWAN subscales provided reliable information on respondents lying at any place of the latent trait (z-scores from 3 to +3; reliabilities range from 0.77 to 0.96); in contrast, the traditional scales only provided reliable information at the high end of the latent trait (z-scores from 0 to +3). Conclusions: Building on the wisdom of the SWAN, the E-SWAN was developed to capture the full spectrum of the latent trait of several DSMclassified disorders. This type of scale has the potential to capture more variance and information on participants in a population-based study or epidemiological sample group. This is useful for both research and clinical practice. It is noteworthy that, by capturing information on strengths, there is greater potential to provide insight into factors related to resiliency.
ADOL, RI http://dx.doi.org/10.1016/j.jaac.2017.09.174
3.27 ASSESSING WHITE MATTER CORRELATES OF COGNITIVE AND VISUOMOTOR CONTROL DEFICITS IN CHILDREN WITH SENSORY PROCESSING DISORDERS Annie Brandes-Aitken, BS, University of California, San Francisco, [email protected]; Joaquin A. Anguera, PhD, University of California, San Francisco, Joaquin.Anguera@ ucsf.edu; Yi-Shin Chang, University of California, San Francisco, [email protected]; Julia P. Owen, PhD, University of California, San Francisco, [email protected]; Pratik Mukherjee, MD, PhD, University of California, San Francisco, [email protected]; Elysa J. Marco, MD, University of California, San Francisco, [email protected] Objectives: Children with sensory processing dysfunction (SPD) are reported to have challenges with cognitive and visuomotor control. In this study, we aimed to quantitatively determine whether children with SPD show deficits in their cognitive control and visuomotor control abilities using a combination of clinical and experimental direct assessments. We then used these behavioral metrics in conjunction with measures of white matter integrity via diffusion tensor imaging (DTI) to better understand the structural underpinnings of these neural processes. Methods: Here we characterized cognitive and visuomotor control and collected DTI neuroimaging data in 14 children with SPD, 13 children with SPD and comorbid attention deficits (SPD+IA), and 16 typically developing control (TDC) subjects. The cognitive control battery included a validated measure of attention (Test of Variables of Attention, TOVA), and a perceptual discrimination and goal management assessment, each presented with a novel diagnostic video game-like platform called Project:EVOTM. The visuomotor battery included the Beery TM VMI copying, matching, and tracing subtests, as well as the EVO TM navigation
www.jaacap.org
S211