scholarly journals Information and Communication Technologies to Support Early Screening of Autism Spectrum Disorder: A Systematic Review

Children ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 93
Author(s):  
Lorenzo Desideri ◽  
Patricia Pérez-Fuster ◽  
Gerardo Herrera
Keyword(s):  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Information And Communication Technologies ◽  
Digital Libraries ◽  
English Language ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Screening Tools ◽  
Early Screening

The aim of this systematic review is to identify recent digital technologies used to detect early signs of autism spectrum disorder (ASD) in preschool children (i.e., up to six years of age). A systematic literature search was performed for English language articles and conference papers indexed in Pubmed, PsycInfo, ERIC, CINAHL, WoS, IEEE, and ACM digital libraries up until January 2020. A follow-up search was conducted to cover the literature published until December 2020 for the usefulness and interest in this area of research during the Covid-19 emergency. In total, 2427 articles were initially retrieved from databases search. Additional 481 articles were retrieved from follow-up search. Finally, 28 articles met the inclusion criteria and were included in the review. The studies included involved four main interface modalities: Natural User Interface (e.g., eye trackers), PC or mobile, Wearable, and Robotics. Most of the papers included (n = 20) involved the use of Level 1 screening tools. Notwithstanding the variability of the solutions identified, psychometric information points to considering available technologies as promising supports in clinical practice to detect early sign of ASD in young children. Further research is needed to understand the acceptability and increase use rates of technology-based screenings in clinical settings.

A systematic review of screening tools in non-young children and adults for autism spectrum disorder

2018 ◽  
Vol 80 ◽  
pp. 1-12 ◽  
Author(s):  
Tomoya Hirota ◽  
Ryuhei So ◽  
Young Shin Kim ◽  
Bennett Leventhal ◽  
Richard A. Epstein
Keyword(s):  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Young Children ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Screening Tools

A systematic review of screening tools for the detection of autism spectrum disorder in mainland China and surrounding regions

Autism ◽  
2019 ◽  
Vol 24 (2) ◽  
pp. 285-296 ◽  
Author(s):  
Ji Wang ◽  
Darren Hedley ◽  
Simon M Bury ◽  
Josephine Barbaro
Keyword(s):  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
Public Awareness ◽  
Mainland China ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Screening Tools ◽  
Assessment Instruments ◽  
Detection And Diagnosis ◽  
Outcomes For Children

Screening for autism spectrum disorder is the first step toward early detection and diagnosis, thereby impacting the likelihood of children accessing early intervention and, importantly, improving long-term outcomes. This systematic review aimed to (a) establish a clear baseline of autism spectrum disorder screening tools currently used throughout mainland China and surrounding regions, (b) identify the strengths and limitations of these instruments, and (c) develop specific recommendations regarding screening for autism spectrum disorder throughout Chinese-speaking countries. Databases were searched for recent (2015–2018) articles published in Chinese or English languages. Twenty-two studies (13 Chinese, 9 English) met inclusion criteria; two from Taiwan and the remainder from mainland China. Studies varied greatly in the extent of psychometric analyses and reported autism spectrum disorder prevalence. The majority of diagnoses were based on Diagnostic and Statistical Manual of Mental Disorders (4th ed. (DSM-IV) or 5th ed. (DSM-5)) criteria, although a small number of studies utilized gold-standard diagnostic assessment instruments. It is recommended that a systematic, multi-tiered, screening network be established to improve the identification of autism spectrum disorder in China and surrounding regions. Assessment and diagnosis need to be culturally appropriate, and amenable to low-resource settings. In addition, increased public awareness programs to reduce stigma will be important in improving outcomes for children with autism spectrum disorder.

Screening of Egyptian toddlers for autism spectrum disorder using an Arabic validated version of M-CHAT; report of a community-based study (Stage I)

2016 ◽  
Vol 34 ◽  
pp. 43-48 ◽  
Author(s):  
F.E. Mohamed ◽  
E.A. Zaky ◽  
A. Youssef ◽  
R. Elhossiny ◽  
S. Zahra ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Screening Tool ◽  
Delayed Diagnosis ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Stage I ◽  
Screening Tools ◽  
Early Screening ◽  
Community Based ◽  
Cross Sectional

AbstractBackgroundAlthough there is a recommendation that toddlers be screened for Autism spectrum disorder (ASD) during their 18- and 24-month well-care child visits, diagnosis often occurs well after the child turns 4 years old. Such delayed diagnosis hinders the implementation of early intervention thus worsens the long-term prognosis of ASD.ObjectivesThe current community-based study in its stage I aimed at early screening of Egyptian toddlers for ASD using an Arabic validated version of Modified Checklist for Autism in Toddlers (M-CHAT).MethodologyA cross-sectional community-based descriptive study was carried out enrolling 5546 Egyptian toddlers. They were randomly recruited from those attending Primary Health Care Units in six Egyptian governorates with a fair representation of the urban, semi-urban, and rural Egyptian populations. An Arabic validated version of M-CHAT was used as a screening tool for ASD.ResultsThe current study revealed failure of M-CHAT (suspected to have ASD and needs further evaluation) in 1320 out of the enrolled 5546 Egyptian toddlers (23.8%).ConclusionsM-CHAT as a screening tool for ASD has flagged a considerable percent of the enrolled toddlers that necessitates referral for further evaluation (stage II) to settle the diagnosis of ASD in the true positive cases. Perfecting the delicate balance between sensitivity and specificity for ASD screening tools is crucial in order not to miss early detection of ASD cases and at the same time, to avoid over-diagnosis with subsequent abuse of the limited healthcare resources in developing countries.

scholarly journals Reward processing in autism spectrum disorder and psychopathy: a systematic review

BJPsych Open ◽  
2021 ◽  
Vol 7 (S1) ◽  
pp. S41-S42
Author(s):  
Patrick McLaughlin ◽  
Marija-Magdalena Petrinovic ◽  
Nigel Blackwood
Keyword(s):  
Systematic Review ◽  
Autism Spectrum Disorder ◽  
English Language ◽  
Treatment Strategies ◽  
Autism Spectrum ◽  
Reward Processing ◽  
Spectrum Disorder ◽  
Social Reward ◽  
Social Dysfunction ◽  
The Social

AimsEmerging research suggests that aberrant reward processing may underpin much of the social dysfunction we see in psychiatric disorders. Two conditions associated with marked social dysfunction are Autism Spectrum Disorder (ASD) and Psychopathy. However, no review to date has directly contrasted reward processing in both conditions and incorporated literature on social and non-social rewards. This systematic review aims to: (i) identify and compare reward processing abnormalities in ASD and Psychopathy as demonstrated in task-based functional magnetic resonance imaging (fMRI) studies; and (ii) identify correlations between fMRI reward processing abnormalities and manifested symptoms, with a focus on those giving rise to social dysfunction.MethodThe electronic databases PubMed, PsycINFO and EMBASE were searched to identify studies satisfying the following criteria: (i) a validated measure was used to assess ASD or Psychopathy; (ii) the study was published in an English language peer review journal; (iii) the age of participants was 18 years or older; (iv) individuals participated in a reward-based experimental paradigm; and (v) the response to the reward was measure using fMRI.ResultA total of 12 articles were identified that satisfied inclusion criteria. Six studies examined reward processing in ASD and six studies examined reward processing in Psychopathy. All studies in both conditions indicated some degree of abnormal reward-related neural response. The most replicated findings were aberrant responses in the Ventral Striatum (VS). Autism Spectrum Disorder was typified by VS hypoactivation to social and non-social reward, while Psychopathy was associated with VS hyperactivation in response to non-social reward anticipation. No studies were identified of social reward in Psychopathy.ConclusionThe reported fMRI findings correlate with clinical observations in both conditions. Reduced reward response in ASD to a range of social and non-social stimuli would provide a parsimonious account of the social and non-social deficits that characterise the condition. Enhanced responses to the anticipation of reward in Psychopathy provides an account of the ruthless and destructive pursuit of reward-driven behaviours not inhibited by immoral or aversive signals. If, as the literature suggests, reward circuitry dysfunction plays a role in the development and manifestation of symptoms in both conditions, reward processing and its underlying neural circuitry may represent important targets for the development of novel treatment strategies.

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

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.

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

2018 ◽  
Vol 19 (5) ◽  
pp. 454-459 ◽  
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

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

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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