W12. BEHAVIORAL MANIFESTATIONS IN GENETIC RODENT MODELS OF AUTISM SPECTRUM DISORDER: A SYSTEMATIC REVIEW AND META-ANALYSES

BackgroundComorbid physical conditions may be more common in people with autism spectrum disorder (ASD) than other people.AimsTo identify what is and what is not known about comorbid physical conditions in people with ASD.MethodWe undertook an umbrella systematic review of systematic reviews and meta-analyses on comorbid physical conditions in people with ASD. Five databases were searched. There were strict inclusion/exclusion criteria. We undertook double reviewing for eligibility, systematic data extraction and quality assessment. Prospective PROSPERO registration: CRD42015020896.ResultsIn total, 24 of 5552 retrieved articles were included, 15 on children, 1 on adults, and 8 both on children and adults. Although the quality of included reviews was good, most reported several limitations in the studies they included and considerable heterogeneity. Comorbid physical conditions are common, and some are more prevalent than in the general population: sleep problems, epilepsy, sensory impairments, atopy, autoimmune disorders and obesity. Asthma is not. However, there are substantial gaps in the evidence base. Fewer studies have been undertaken on other conditions and some findings are inconsistent.ConclusionsComorbid physical conditions occur more commonly in people with ASD, but the evidence base is slim and more research is needed. Some comorbidities compound care if clinicians are unaware, for example sensory impairments, given the communication needs of people with ASD. Others, such as obesity, can lead to an array of other conditions, disadvantages and early mortality. It is essential that potentially modifiable physical conditions are identified to ensure people with ASD achieve their best outcomes. Heightening clinicians’ awareness is important to aid in assessments and differential diagnoses, and to improve healthcare.

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A Systematic Review of Law Enforcement Training Related to Autism Spectrum Disorder

Focus on Autism and Other Developmental Disabilities ◽

10.1177/1088357620922152 ◽

2020 ◽

Vol 35 (4) ◽

pp. 221-233 ◽

Cited By ~ 1

Author(s):

Kirsten S. Railey ◽

Abigail M. A. Love ◽

Jonathan M. Campbell

Keyword(s):

Systematic Review ◽

Autism Spectrum Disorder ◽

Law Enforcement ◽

Autism Spectrum ◽

Spectrum Disorder ◽

Future Research ◽

Law Enforcement Training ◽

Training Format ◽

Effectiveness Of Training ◽

Meta Analyses

Although research confirms the effectiveness of training to improve law enforcement officers’ (LEOs) awareness and knowledge of people with intellectual disability and learning disabilities, review of the efficacy of autism-specific law enforcement training is needed. To provide up-to-date information regarding training for LEOs related to autism spectrum disorder (ASD), a systematic review of the literature was conducted. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Protocols (PRISMA), we conducted a search of 13 professional databases and 28 journals using search terms related to both ASD and law enforcement training. From 606 articles identified during the initial search, only two articles met inclusion criteria, which suggests that limited research exists that explores ASD and law enforcement training. Included studies were summarized in terms of participants as well as training format, content, and outcomes. Limitations of the current literature, directions for future research, and current implications for practice are discussed.

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The Prevalence of Psychotic Experiences in Autism Spectrum Disorder and Autistic Traits: A Systematic Review and Meta-analysis

Schizophrenia Bulletin Open ◽

10.1093/schizbullopen/sgaa046 ◽

2020 ◽

Vol 1 (1) ◽

Author(s):

Tomoki Kiyono ◽

Masaya Morita ◽

Ryo Morishima ◽

Shinya Fujikawa ◽

Syudo Yamasaki ◽

...

Keyword(s):

Systematic Review ◽

Autism Spectrum Disorder ◽

Meta Analysis ◽

Correlation Coefficients ◽

Autistic Traits ◽

Autism Spectrum ◽

Spectrum Disorder ◽

Psychotic Experiences ◽

Meta Analyses ◽

Statistical Results

Abstract Several reports have highlighted an association between psychotic experiences (PEs) and autism spectrum disorder/autistic traits; however, no systematic review of the evidence has been done. We searched PubMed, PsycINFO, Web of Science, and Cochrane database on November 20, 2018, for studies providing statistical results on the association between PEs and autism spectrum disorder/autistic traits. Meta-analyses were conducted for both the prevalence of PEs in autism spectrum disorder and the correlation coefficients between PEs and autistic traits. Subgroup analyses were conducted for each PE subtype. Among the 17 included studies, 9 had data about prevalence and 8 had data about correlation. The pooled prevalence of PEs in autism spectrum disorder was 24% (95% confidence interval [CI] 14%–34%). However, subanalyses found that prevalence varied between PE subtypes (hallucinations, 6% [95% CI 1%–11%] and delusions, 45% [95% CI 0%–99%]). Pooled results showed that PEs and autistic traits had a weak to medium correlation (r = .34 [95% CI 0.27–0.41]). Based on our meta-analysis, PEs seem to be more prevalent in individuals with autism spectrum disorder/autistic traits than in the general population, but this finding may vary according to the PE subtype. Future studies should focus on statistical results for each PE subtype separately. More studies should be conducted to clarify the relationship between autism spectrum disorder/autistic traits and PEs by subtype.

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Parent Education in Studies With Nonverbal and Minimally Verbal Participants With Autism Spectrum Disorder: A Systematic Review

American Journal of Speech-Language Pathology ◽

10.1044/2019_ajslp-19-00007 ◽

2020 ◽

Vol 29 (2) ◽

pp. 890-902

Author(s):

Lynn Kern Koegel ◽

Katherine M. Bryan ◽

Pumpki Lei Su ◽

Mohini Vaidya ◽

Stephen Camarata

Keyword(s):

Systematic Review ◽

Autism Spectrum Disorder ◽

Parent Education ◽

Autism Spectrum ◽

Verbal Communication ◽

Fidelity Of Implementation ◽

Spectrum Disorder ◽

Education Programs ◽

Minimally Verbal ◽

Parent Education Programs

Purpose The purpose of this systematic review was to identify parent education procedures implemented in intervention studies focused on expressive verbal communication for nonverbal (NV) or minimally verbal (MV) children with autism spectrum disorder (ASD). Parent education has been shown to be an essential component in the habilitation of individuals with ASD. Parents of individuals with ASD who are NV or MV may particularly benefit from parent education in order to provide opportunities for communication and to support their children across the life span. Method ProQuest databases were searched between the years of 1960 and 2018 to identify articles that targeted verbal communication in MV and NV individuals with ASD. A total of 1,231 were evaluated to assess whether parent education was implemented. We found 36 studies that included a parent education component. These were reviewed with regard to (a) the number of participants and participants' ages, (b) the parent education program provided, (c) the format of the parent education, (d) the duration of the parent education, (e) the measurement of parent education, and (f) the parent fidelity of implementation scores. Results The results of this analysis showed that very few studies have included a parent education component, descriptions of the parent education programs are unclear in most studies, and few studies have scored the parents' implementation of the intervention. Conclusions Currently, there is great variability in parent education programs in regard to participant age, hours provided, fidelity of implementation, format of parent education, and type of treatment used. Suggestions are made to provide both a more comprehensive description and consistent measurement of parent education programs.

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Herbal Medicine as an Alternative Treatment in Autism Spectrum Disorder: A Systematic Review

Current Drug Metabolism ◽

10.2174/1389200219666171227202332 ◽

2018 ◽

Vol 19 (5) ◽

pp. 454-459 ◽

Cited By ~ 2

Author(s):

Francielly Mourao Gasparotto ◽

Francislaine Aparecida dos Reis Lívero ◽

Sara Emilia Lima Tolouei Menegati ◽

Arquimedes Gasparotto Junior

Keyword(s):

Systematic Review ◽

Autism Spectrum Disorder ◽

Herbal Medicine ◽

Alternative Treatment ◽

Autism Spectrum ◽

Spectrum Disorder

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Diagnostic test accuracy for use of machine learning in diagnosis of autism spectrum disorder: A Systematic Review and Meta-Analysis (Preprint)

10.2196/preprints.14108 ◽

2019 ◽

Author(s):

Sun Jae Moon ◽

Jin Seub Hwang ◽

Rajesh Kana ◽

John Torous ◽

Jung Won Kim

Keyword(s):

Machine Learning ◽

Systematic Review ◽

Autism Spectrum Disorder ◽

Meta Analysis ◽

Learning Algorithms ◽

Structural Mri ◽

Autism Spectrum ◽

Machine Learning Algorithms ◽

Spectrum Disorder ◽

Test Accuracy

BACKGROUND Over the recent years, machine learning algorithms have been more widely and increasingly applied in biomedical fields. In particular, its application has been drawing more attention in the field of psychiatry, for instance, as diagnostic tests/tools for autism spectrum disorder. However, given its complexity and potential clinical implications, there is ongoing need for further research on its accuracy. OBJECTIVE The current study aims to summarize the evidence for the accuracy of use of machine learning algorithms in diagnosing autism spectrum disorder (ASD) through systematic review and meta-analysis. METHODS MEDLINE, Embase, CINAHL Complete (with OpenDissertations), PsyINFO and IEEE Xplore Digital Library databases were searched on November 28th, 2018. Studies, which used a machine learning algorithm partially or fully in classifying ASD from controls and provided accuracy measures, were included in our analysis. Bivariate random effects model was applied to the pooled data in meta-analysis. Subgroup analysis was used to investigate and resolve the source of heterogeneity between studies. True-positive, false-positive, false negative and true-negative values from individual studies were used to calculate the pooled sensitivity and specificity values, draw SROC curves, and obtain area under the curve (AUC) and partial AUC. RESULTS A total of 43 studies were included for the final analysis, of which meta-analysis was performed on 40 studies (53 samples with 12,128 participants). A structural MRI subgroup meta-analysis (12 samples with 1,776 participants) showed the sensitivity at 0.83 (95% CI-0.76 to 0.89), specificity at 0.84 (95% CI -0.74 to 0.91), and AUC/pAUC at 0.90/0.83. An fMRI/deep neural network (DNN) subgroup meta-analysis (five samples with 1,345 participants) showed the sensitivity at 0.69 (95% CI- 0.62 to 0.75), the specificity at 0.66 (95% CI -0.61 to 0.70), and AUC/pAUC at 0.71/0.67. CONCLUSIONS Machine learning algorithms that used structural MRI features in diagnosis of ASD were shown to have accuracy that is similar to currently used diagnostic tools.

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