the official journal of The International Society for Autism Research, provides an excellent platform to showcase the highest quality research on autism spectrum disorder and related conditions. The journal distinguishes itself from other journals by offering rapid decision and publication times and by a strong focus on basic genetic, neurobiological, and psychological mechanisms and how these influence developmental processes. Papers related to the epidemiology of autism as well as treatment studies are also welcome at Autism Research. In 2019, the median time to the first decision on submitted papers was 34 days.
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The Journal publishes 12 issues a year in electronic format. is edited by an outstanding team of editors including David G. Amaral, Ph.D. (Editor-in-Chief); Peter Mundy, Ph.D. (Senior Associate Editor); Emily Jones, PhD, Genevieve Konopka, PhD, Ralph-Axel Müller, PhD, Diana Schendel, PhD, and Jeremy Veenstra-VanderWeele, MD, PhD (Associate Editors). The editorial team ensures a fair and comprehensive evaluation of papers which is supported by a diverse, international editorial board.
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Autism spectrum disorders are a group of neurodevelopmental disorders that are characterized by impaired social interaction and communication skills, and are often accompanied by other behavioural symptoms such as repetitive or stereotyped behaviour and abnormal sensory processing. Individual symptoms and cognitive functioning vary across the autism spectrum disorders.
Children with attention-deficit/hyperactivity disorder and/or autism spectrum disorder show executive function deficits compared to neurotypical peers. In this Review, Kofler et al. question the evidence to examine whether these deficits are shared across both conditions and provide recommendations for future work.
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Miaomiao jiang.
1 National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), NHC Key Laboratory of Mental Health (Peking University), Peking University Sixth Hospital, Peking University Institute of Mental Health, Beijing, China
Liyang zhao.
2 Translational Medicine Center of Chinese Institute for Brain Research, Beijing, China
3 Guangdong Key Laboratory of Mental Health and Cognitive Science, Institute for Brain Research and Rehabilitation (IBRR), South China Normal University, Guangzhou, China
Associated data.
The original contributions presented in the study are included in the article/ Supplementary material , further inquiries can be directed to the corresponding authors.
In recent years, a large number of studies have focused on autism spectrum disorder (ASD). The present study used bibliometric analysis to describe the state of ASD research over the past decade and identify its trends and research fronts.
Studies on ASD published from 2011 to 2022 were obtained from the Web of Science Core Collection (WoSCC). Bibliometrix, CiteSpace, and VOSviewer were used for bibliometric analysis.
A total of 57,108 studies were included in the systematic search, and articles were published in more than 6,000 journals. The number of publications increased by 181.7% (2,623 in 2011 and 7,390 in 2021). The articles in the field of genetics are widely cited in immunology, clinical research, and psychological research. Keywords co-occurrence analysis revealed that “causative mechanisms,” “clinical features,” and “intervention features” were the three main clusters of ASD research. Over the past decade, genetic variants associated with ASD have gained increasing attention, and immune dysbiosis and gut microbiota are the new development frontiers after 2015.
This study uses a bibliometric approach to visualize and quantitatively describe autism research over the last decade. Neuroscience, genetics, brain imaging studies, and gut microbiome studies improve our understanding of autism. In addition, the microbe-gut-brain axis may be an exciting research direction for ASD in the future. Therefore, through visual analysis of autism literature, this paper shows the development process, research hotspots, and cutting-edge trends in this field to provide theoretical reference for the development of autism in the future.
Autism spectrum disorder (ASD) refers to a group of early-onset, lifelong, heterogeneous neurodevelopmental conditions with complex mechanisms of emergence ( 1 ). The prevalence of ASD has increased from 1 in 69 by 2012 to 1 in 44 by 2018, as reported by the Centers for Disease Control and Prevention for 2012–2018 ( 2 , 3 ). Recent research estimates the male-to-female ratio is closer to 2:1 or 3:1, indicating a higher diagnostic prevalence of autism in males compared to females ( 4 – 6 ). Some studies have shown a high heritability of 80–93% in ASD and reported hundreds of risk gene loci ( 7 ).
Specific autistic characteristics usually appear before the age of 3 years, and some children on the spectrum may have limited nonverbal and verbal communication by the age of 18–24 months ( 8 , 9 ). The diagnosis of ASD is based on the core features of social communication impairment and unusual and repetitive sensory-motor behavior ( 10 ). Some autistic individuals can be definitively diagnosed with autism as early as 2–3 years of age and the mean age of diagnosis for autistic children is still 4–5 years ( 1 , 11 ). It is important to stress that more adults are getting assessed for possible autism ( 5 ). As autism is increasingly diagnosed, multidisciplinary involvement can help have a positive impact on the well-being and quality of life for both children and adults on the spectrum ( 12 ). Several mental diseases also affect autistic individuals, increasing the diagnosis complexity ( 13 ).
Over the past decade, researchers have struggled to explain the neurological etiology, and great progress has been made in the genetics, epigenetics, neuropathology, and neuroimaging of ASD ( 9 ). However, there is a lack of systematic review of field research and discussion of future research hotspots. Bibliometrics ( 14 ) belongs to interdisciplinary research, which has been widely used in science by analyzing highly cited papers, field keyword clustering, and the internal cooperation links of countries, thus providing a comprehensive interpretation of the development process of autism research field ( 15 ).
In some of the previous bibliometrics studies on ASD, a single software was used to focus on a specific field or research aspect of the autism ( 16 – 18 ), and the trend in the past decade has not yet been displayed. The present study comprehensively combines Bibliometrix package, CiteSpace, and VOSviewer to (1) dynamically assess quantitative indicators of ASD research publications and use different index indicators to measure the quality of research; (2) further identify the most contributing countries, institutions, journals, and authors; (3) analyze the citation network architecture; (4) determine the top 100 most cited papers; (5) conduct keyword analysis. Subsequently, bibliometrics was used to understand the current hotspots and trends in the field of ASD research for further in-depth investigation.
Data collection and search strategies.
We comprehensively searched the Web of Science Core Collection (WoSCC) database from 2011 to 2022. WoSCC is a daily updated database covering an abstract index of multidisciplinary literature that exports complete citation data, maintained by Thomson Reuters (New York, NY, USA) ( 19 ). The articles’ data were independently searched by two researchers on May 29, 2022, to avoid bias caused by database updates. The scientometric retrieval process is illustrated in Figure 1 . A total of 68,769 original articles in English language were retrieved, excluding 11,661 irrelevant articles, such as meeting abstracts, editorial materials, corrections, and letters. A total of 57,108 documents were exported, and the retrieved documents would be exported in the form of all records and references.
Flowchart of the screening process.
Grey models (GM) are used to construct differential prediction models with limited and incomplete data ( 20 ). The GM (1,1) model, with high accuracy and convenient calculations, is extensively utilized in the energy and medical industries ( 21 ). We used the standard GM (1,1) model to forecast the annual publication volume over the next 5 years. The operation of GM (1,1) model was done by using Python software.
The records of the retrieved publications were exported to Bibliometrix, CiteSpace, and VOSviewer for further bibliometric analysis.
Bibliometrix package (running on R4.0.3) was utilized to capture and extract the bibliographic information on selected publications, including topic, author, keywords, and country distribution ( 22 ). The productivity of authors/journals in the field was measured by the number of publications (Np) and assessing metrics, such as the number of citations, publication h-index value, and m-index value. The h-index is used to quantify the scientific output and measure the citation impact, and two people with similar h-index may have a similar impact in the scientific field, even if the total number of papers or total citations are different ( 23 ). The m-index can be used to compare the influence of scholars with different academic career years. The number of citations of a document is a measure of its scientific impact to a certain extent ( 24 ). Bibliometrix package was also used to screen the top 100 articles and explore research trends and hotspots.
VOSviewer is a free computer program to visualize bibliometric maps ( 25 ). The keyword co-occurrence network was constructed using VOSviewer. CiteSpace is based on the Java environment and uses methods, such as co-occurrence analysis and cluster analysis, for the visualization of scientific literature research data in specific disciplines. The visual knowledge maps were constructed using the procedural steps of CiteSpace ( 26 ), including time slicing, threshold, pruning, merging, and mapping; then, the contribution of countries and institutions of ASD over the past decade was assessed based on centrality scores. The co-citation network and dual-map of references were constructed by CiteSpace. A dual-map ( 27 ) overlay is a bipartite overlay analysis method by CiteSspace, which uses the distribution map cited journals in the WoS database as the base map, and the map generated by the cited literature data as the overlay map.
A total of 57,108 articles were included in this study, consisting of 46,574 articles, 2,643 conference papers, and 7,891 reviews. From 2011 to 2022, the number of publications maintained a steady growth rate ( Figure 2A ), and the grey prediction model predicted the trend of increasing publication volume in the next 5 years ( Figure 2B ). The main information for all publications is shown in Supplementary Table S1 .
Global trends in publications of ASD research. (A) Single-year publication output over the past decade. (B) Model forecast curves for publication growth trends.
Autism-related research has been conducted by researchers from a variety of countries and institutions, and articles in this field have been cited 1,231,588 times ( Tables 1 , ,2). 2 ). CiteSpace visualizes collaborative networks between institutions and countries ( Figures 3A , ,B). B ). As shown in the international collaborations network of autism research ( Figure 3C ), the USA and UK are the leading countries working closely with other countries.
Publications in top 10 most productive countries.
Countries | Ranking based on output | Output (%) | SCP | MCP | Ranking based on citations | Total citation | Average article citation |
---|---|---|---|---|---|---|---|
USA | 1 | 22,615 (39.60) | 19,373 | 3,242 | 1 | 616,323 | 27.25 |
UK | 2 | 4,961 (8.69) | 3,440 | 1,521 | 2 | 123,685 | 24.93 |
China | 3 | 3,211 (5.63) | 2,357 | 854 | 6 | 40,561 | 12.63 |
Australia | 4 | 2,659 (4.65) | 1870 | 789 | 4 | 52,335 | 19.68 |
Canada | 5 | 2,582 (4.52) | 1794 | 788 | 3 | 60,919 | 23.59 |
Italy | 6 | 2,317 (4.06) | 1,656 | 661 | 5 | 42,136 | 18.19 |
Japan | 7 | 1883 (3.29) | 1,572 | 311 | 9 | 24,927 | 13.24 |
Netherlands | 8 | 1,362 (2.38) | 857 | 505 | 7 | 35,425 | 26.01 |
Germany | 9 | 1,246 (2.18) | 718 | 528 | 8 | 33,395 | 26.8 |
France | 10 | 1,126 (1.97) | 689 | 437 | 10 | 24,579 | 21.83 |
Publications in top 10 most productive Institutions.
Institutions | Country | Counts |
---|---|---|
Kings College London | UK | 1,214 |
University of Toronto | Canada | 1,022 |
Vanderbilt University | USA | 978 |
University of California, Davis | USA | 938 |
University of California, Los Angeles | USA | 910 |
University of North Carolina | USA | 863 |
University College London | UK | 836 |
University of Washington | USA | 794 |
Harvard University | USA | 776 |
Harvard Medical School | USA | 775 |
The distribution of countries and institutions. Map of countries (A) and institutions (B) contributed to publications related to ASD research. (C) Network diagram showing international collaborations involved in ASD research. The nodes represent the countries and institutions; the color depth and size of the circle are positively correlated to the number of posts. The thickness of the curved connecting lines represents the strength of collaboration in the countries and institutions.
The h-index combines productivity and impact; typically, a high h-index means a high recognition. As presented in Table 3 , the Journal of Autism and Developmental Disorders, PLOS One, and Molecular Psychiatry were among the top three of the 20 journals with the highest h-index. The Journal of Autism and Developmental Disorders has the highest number of articles (3478) and cited number of publications (90308). Among the top 20, four journals with impact factors >10 include Molecular Psychiatry (IF: 13.437), Biological Psychiatry (IF: 12.810), Proceedings of the National Academy of Sciences of the United States of America (IF: 12.779), Journal of the American Academy of Child and Adolescent Psychiatry (IF: 13.113), which have been cited more than 10,000 times. In addition, 75% of journals belong to Q1 ( Table 3 ). The cited journals provided the knowledge base of the citing journals. The yellow paths illustrate that studies published in “molecular, biology, immunology” journals tended to cite journals primarily in the domains of “molecular, biology, genetics,” and “psychology, education, social.” The paths colored with grass-green paths illustrate that studies published in “medicine, medical, clinical” journals tended to cite journals primarily in the domains of “molecular, biology, and genetics.” The pale blue paths showcase that research published in “psychology, education, health” journals preferred to quote journals mostly in the domains of “molecular, biology, genetics,” “health, nursing, medicine,” and “psychology, education, social ( Figure 4 ).”
Top 20 journals ranked by h_index.
Rank | Name | h_index | Count | TC | IF (2022) | JCR (2022) |
---|---|---|---|---|---|---|
1 | Journal of Autism and Developmental Disorders | 110 | 3,478 | 90,308 | 4.345 | Q2 |
2 | PloS One | 75 | 856 | 27,049 | 3.752 | Q2 |
3 | Molecular Psychiatry | 74 | 292 | 18,125 | 13.437 | Q1 |
4 | Autism | 73 | 1,130 | 27,510 | 6.684 | Q1 |
5 | Pediatrics | 71 | 227 | 17,360 | 9.703 | Q1 |
6 | Biological Psychiatry | 70 | 222 | 13,457 | 12.810 | Q1 |
7 | Proceedings of the National Academy of Sciences of the United States of America | 70 | 199 | 12,960 | 12.779 | Q1 |
8 | Research in Autism Spectrum Disorders | 68 | 1,289 | 26,452 | 3.293 | Q3 |
9 | Journal of Child Psychology and Psychiatry | 67 | 281 | 14,921 | 8.265 | Q1 |
10 | Autism Research | 64 | 1,154 | 24,293 | 4.633 | Q1 |
11 | Molecular Autism | 61 | 577 | 17,470 | 6.476 | Q1 |
12 | Neuroscience and Biobehavioral Reviews | 60 | 220 | 12,396 | 9.052 | Q1 |
13 | Translational Psychiatry | 59 | 344 | 11,574 | 7.989 | Q1 |
14 | Journal of the American Academy of Child and Adolescent Psychiatry | 57 | 184 | 12,313 | 13.113 | Q1 |
15 | Research in Developmental Disabilities | 56 | 711 | 14,422 | 3.000 | Q1 |
16 | Journal of Neuroscience | 54 | 220 | 10,231 | 6.709 | Q1 |
17 | Frontiers in Human Neuroscience | 47 | 241 | 7,842 | 3.473 | Q3 |
18 | Human Molecular Genetics | 47 | 163 | 6,846 | 5.121 | Q1 |
19 | Neuroimage | 47 | 156 | 7,508 | 7.400 | Q1 |
20 | Journal of Neurodevelopmental Disorders | 45 | 259 | 6,856 | 4.074 | Q2 |
TC: total citation; IF: impact factor.
A dual-map overlay of journals that published work related to ASD. A presentation of citation paths at a disciplinary level on a dual-map overlay. The width of the paths is proportional to the z-score-scale citation frequency. The labels on the map represent the research subjects covered by the journals, and the wavy curve connects the citing articles on the left side of the map and the cited articles on the right side of the map.
The top 10 most effective authors who have contributed to autism research are listed in Table 4 . The g-index and m-index are derivatives of the h-index, and if scientists publish at least 10 articles, of which 7 papers have been cited cumulatively 51 (>49), the g-index is 7; the m-index is related to the academic age of the scientists. The large g-index, h-index, and m-index indicate a great influence on the scholar’s academic influence and high academic achievement. Professor Catherine Lord from the USA is ranked first and has made outstanding contributions to autism research over the past 10 years. In terms of the number of publications, Simon Baron-Cohen was the most productive author ( n = 278), followed by Tony Charman ( n = 212) and Christopher Gillberg ( n = 206). In terms of citations in this field, Daniel H. Geschwind was ranked first (18,127 citations), followed by Catherine Lord (14,830 citations) and Joseph D. Buxbaum (14,528 citations).
Top 10 most effective authors contributing to autism research.
Author | Country | h_index | g_index | m_index | TC | NP |
---|---|---|---|---|---|---|
Catherine Lord | USA | 64 | 121 | 5.333 | 14,830 | 146 |
Simon Baron-Cohen | UK | 60 | 109 | 5 | 14,432 | 278 |
Daniel H. Geschwind | USA | 58 | 103 | 4.833 | 18,127 | 103 |
Lonnie Zwaigenbaum | Canada | 57 | 106 | 4.75 | 12,246 | 193 |
Tony Charman | UK | 55 | 89 | 4.583 | 9,514 | 212 |
Stephen W. Scherer | USA | 51 | 115 | 4.25 | 13,444 | 136 |
Christopher Gillberg | Sweden | 48 | 83 | 4 | 8,193 | 206 |
Joseph D. Buxbaum | USA | 48 | 120 | 4 | 14,528 | 123 |
Paul Lichtenstein | Sweden | 47 | 93 | 3.917 | 8,898 | 132 |
Evan E. Eichler | USA | 47 | 96 | 3.917 | 13,393 | 96 |
TC: total citation; NP: number of papers.
The co-citation analysis network of 1,056,125 references ( Figure 5A ) showed that two articles appear simultaneously in the bibliography of the third cited document. The top 20 co-cited references (over the past decade) summarized in ASD studies are listed in Supplementary Table S2 . Most of this highly cited literature focuses on the genetic field, discovering genetic risk loci and associated mutations, constructing mutation networks highly associated with autism, and identifying genes associated with autism synaptic destruction. Some studies indicated that de novo mutations in ASD might partially explain the etiology. Multiple studies have revealed genetic variants associated with ASD, such as rare copy number variants (CNVs), de novo likely gene-disrupting (LGD) mutations, missense or nonsense de novo variants, and de novo duplications. In the cluster network graph, different colors represent varied clusters, and each node represents a cited paper, displaying the distribution of topics in the field ( Figure 5B ). The network is divided into 25 co-citation clusters ( Figure 5B ), primarily related to the diagnosis, etiology, and intervention of autism. The etiological studies include five clusters, de novo mutation, inflammation, gut microbiota, mitochondrial dysfunction, and mouse model. Intervention literature focuses on early intensive behavioral intervention, intranasal oxytocin, video modeling, and multisensory integration. The diagnostic aspects of ASD include neuroimaging functional connectivity and Diagnostic and Statistical Manual of Mental Disorders (DSM-5). In addition, some of the references focus on gender/sex differences and sleep problems. Coronavirus disease 2019 (COVID-19) is a new cluster for autism research.
Mapping on co-cited references. (A) A network map showing the co-cited references. (B) Co-cited clusters with cluster labels.
The co-occurrence analysis of keywords in ASD research articles was performed using VOSviewer software; the keywords that occurred ≥200 times were analyzed after being grouped into four clusters of different colors ( Figure 6A ); the temporal distribution of keywords is summarized in Figure 6B . This map identifies various categories of research: Etiological mechanisms (red), Clinical features (green), Intervention features (blue), and the Asperger cluster (yellow). In the “Etiological mechanisms” cluster, the research includes brain structure and function, genetics, and neuropathology. In the “Clinical features” cluster, the common keywords were “symptoms,” “diagnosis,” “prevalence,” and its comorbidities, including “anxiety” and “sleep.” In the “Intervention features” cluster, the research population of ASD is concentrated in “young children,” “intervention,” and “communication.” These interventions improve the learning and social skills through the involvement of parents and schools.
Keywords co-occurrence network. (A) Cluster analysis of keywords. There are four clusters of keywords: red indicates Cluster 1 ( n = 145), green indicates Cluster 2 ( n = 104), blue indicates Cluster 3 ( n = 78), yellow indicates Cluster 4 ( n = 80). (B) Evolution of keyword frequency. A minimum number of occurrences of a keyword = 200. Overall, 407 keywords met the threshold criteria. The yellow keywords appear later than purple keywords.
The screening of the 100 most cited publications on ASD between 2011 and 2022 by Bibliometrix software package, each with >500 citations. The detailed evaluation index information for countries, institutions, journals, and authors ( Supplementary Tables S3 – S6 ).
Taken together, the results indicated that the United States is the country that publishes the most highly cited articles ( n = 64), including single-country publications ( n = 37) and multiple-country publications ( n = 27); most articles are from academic institutions within the USA ( Figures 7A , ,B B ).
Analysis of the 100 top-cited publications Characteristics of 100 top-cited publications. The most relevant countries (A) , affiliations (B) , journals (C) and authors (D) . Trend topics (E) and thematic evolution (F) of 100 top-cited publication. Coupling Map (G) : the coupled analysis of the article, references and keywords is carried out, the centrality of the x -axis is displayed, the y -axis is the impact, and the confidence (conf%) is calculated.
The 100 top-cited ASD publications were published in 48 journals; 17 articles were published in Nature ( n = 17), making it the highest h-index journal in this list ( Supplementary Table S5 ). In addition, 10 articles were published in Cell, and 7 articles were published in Nature Genetics ( Figure 7C ). When considering the individual authors’ academic contributions, Bernie Devlin provided 13 publications, followed by Kathryn Roeder and Stephan J Sanders, with 11 publications each ( Figure 7D ). The details of the top 10 top-cited papers are summarized in Table 5 . An article titled “A general framework for estimating the relative pathogenicity of human genetic variants” published by Martin Kircher in Nature Genetics, received the highest number of citations ( n = 3,353).
Detail of top 10 citation paper.
Article title | Author/Published year | Journal | IF (2022) | TC |
---|---|---|---|---|
A general framework for estimating the relative pathogenicity of human genetic variants | Kircher et al., 2014 | Nature genetics | 41.307 | 3,353 |
Prevalence of Autism Spectrum Disorder Among Children Aged 8 Years - Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2014 | Baio et al., 2018 | Morbidity and Mortality Weekly Report | 35.301 | 2,104 |
Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis | Smoller et al., 2013 | Lancet | 202.731 | 1878 |
Microbiota modulate behavioral and physiological abnormalities associated with neurodevelopmental disorders | Hsiao et al., 2013 | Cell | 66.85 | 1746 |
Large-scale brain networks and psychopathology: a unifying triple network model | Menon et al., 2011 | Trends in cognitive sciences | 24.482 | 1737 |
Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs | Lee et al., 2013 | Nature genetics | 41.307 | 1,449 |
Synaptic, transcriptional and chromatin genes disrupted in autism | De Rubeis et al., 2014 | Nature | 69.504 | 1,436 |
Sporadic autism exomes reveal a highly interconnected protein network of mutations | O’Roak et al., 2012 | Nature | 69.504 | 1,426 |
Neocortical excitation/inhibition balance in information processing and social dysfunction | Yizhar et al., 2011 | Nature | 69.504 | 1,405 |
mutations revealed by whole-exome sequencing are strongly associated with autism | Sanders et al., 2012 | Nature | 69.504 | 1,329 |
The 100 top-cited ASD articles encompassed a range of keywords ( Figure 7E ) and displayed the main cluster of themes through specific periods (2011–2022) by analyzing those in the selected literature. The Sankey diagrams of thematic evolution explain the topics that evolved throughout the years ( Figure 7F ). In summary, the core topics of the ASD field in 2011–2014 consisted of the risk of childhood ASD and further developed into the field of human genetic variants, such as CNV and de novo mutations. In the subperiod 2015–2020, the further expansion of studies in this field leads to new clusters, such as “immune system,” “brain development,” and “fecal microbiota.” Genome research in the upper right quadrant, including mutations and risk, is a major and evolving theme. The coupled map showing the brain-gut axis field, including intestinal microbiota and chain fatty acids, located in the lower right corner is crucial for autism research but is not yet well-developed ( Figure 7G ). The research on autism, including animal models, schizophrenia, is a well-developed field, but that on high-functioning autism and diagnosis is a marginal field.
This study used various bibliometric tools and software to analyze the published articles on ASD based on the WoSCC database from 2011 to 2022. By 2022, the annual number of publications and citations of ASD-related research showed an overall upward trend, reflecting the sustained interest and the diversity of areas.
In terms of regional distribution, researchers from different countries and regions have participated in autism research, and international cooperation has been relatively close over the past decade. The scientific research is supported by several countries and institutions, as well as by large-scale international cooperation ( 28 , 29 ). The USA has the highest collaboration performance, especially with UK, Canada, Australia and China. In addition to the limitations of financial aid, ethical, cultural, and racial issues are complex constraints that should be overcome for more diversity in autism research ( 30 , 31 ). We speculated that further collaboration between institutions and countries could promote autism research.
Among the top 20 academic journals, most of the papers were in the Journal of Autism and Developmental Disorders. The frequent publishing of ASD-related papers indicates the interest of readers and journal editors in Autism. Also, substantial studies have been carried out on ASDs, autism, and molecular autism. These journals are ascribed to the field of ASD, focusing on autism research and communication ASD science. However, the analysis of the 10 most cited publications revealed that they were published in such as Nature, Cell, Lancet; these ASD studies were all from high-impact journals.
From the perspective of authors, some of them have made outstanding contributions to global ASD research. Professor Catherine Lord, the top rank for h-index, m-index analysis conducted by the author, and who developed the two gold standards for autism diagnosis ( 32 , 33 ), are the most influencing factors in the field. ASD is a disease with complex genetic roots. Dr. Catherine Lord has conducted multiple studies using genome-wide association study (GWAS) and gene set analysis to identify variant signatures in autism ( 34 ). A recent meta-analysis showed that 74–93% of ASD risk is heritable, with an analysis of CNVs that highlights the key role of rare and de novo mutations in the etiology of ASD ( 35 ). Variation-affected gene clusters on networks associated with synaptic transmission, neuronal development, and chromatin regulation ( 36 , 37 ). The identification of the cross-disorder genetic risk factors found by assessing SNP heritability in five psychiatric disorders ( 38 ). Five of the top 10 cited papers in Table 5 focus on genetic variation, suggesting that over the past decade, research has shifted from a general concept of genetic risk to the different types of genetic variations associated with autism.
Simon Baron-Cohen of the Autism Research Center at the University of Cambridge was the most published author between 2011 and 2021. He contributed to the mind-blindness hypothesis of autism, developed the autism spectrum quotient (AQ) screening tool for autism, and focused on gender differences in autism ( 39 – 41 ). There are gender/sex differences in the volume and tissue density of brain regions, including the amygdala, hippocampus, and insula, and the heart-blind hypothesis links emotional recognition in individuals with autism to deficits in the amygdala ( 41 – 43 ). Then, Simon et al. backed up the “extreme male brain” theory of autism in a study of 36,000 autistic individuals aged 16–89 ( 44 ). Recently, an increasing number of studies from different perspectives have focused on how sex/gender differences are related to autism ( 4 , 5 , 45 ). In the future, studies of neural dimorphism in brain development in autism need to be conducted across the lifespan to reduce age-induced biases ( 41 ).
Keyword analysis was a major indicator for research trends and hotspot analysis. This study shows that keywords for autism research include etiological mechanism, clinical characteristics, and intervention characteristics. Genetic, environmental, epigenetic, brain structure, neuropathological, and immunological factors have contributed to studying its etiological mechanism ( 46 , 47 ). The studies on the abnormal cortical development in ASD have reported early brain overgrowth ( 48 ), reduced resting cerebral blood flow in the medial PFC and anterior cingulate ( 49 ), focal disruption of neuronal migration ( 50 ), and transcriptomic alterations in the cerebral cortex of autism ( 51 ). Genomics studies have identified several variants and genes that increase susceptibility to autism, affecting biological pathways related to chromatin remodeling, regulation of neuronal function, and synaptic development ( 51 – 54 ). In addition, many autism-related genes are enriched in cortical glutamatergic neurons, and mutations in the genes encoding these proteins result in neuronal excitation-inhibitory balance ( 51 , 55 ). A recent study using single-cell sequencing of the developing human cerebral cortex found strong cell-type-specific enrichment of noncoding mutations in ASD ( 56 ). Interestingly, genes interact with the environment; some studies have shown that environmental exposure during pregnancy is a risk factor for brain development ( 57 ), and there are changes in DNA methylation in the brains of ASD patients, reflecting an underlying epigenetic dysregulation.
Presently, the diagnosis of ASD is mainly based on symptoms and behaviors, but the disease has a high clinical heterogeneity, and the individual differences between patients are obvious ( 58 ). In this study, the keywords of the intervention cluster show the importance of early individualized intervention. Patient data are multidimensional, and individualized diagnoses could be made at multiple levels, such as age, gender, clinical characteristics, and genetic characteristics ( 59 ). Early individual genetic diagnosis aids clinical evaluation, ranging from chromosomal microarray (CMA) to fragile X genetic testing ( 60 ). However, the results of genetic research cannot guide the treatment. Notably, the treatment of autism is dominated by educational practices and behavioral interventions ( 61 ). Medication may address other co-occurring conditions, such as sleep disturbances, epilepsy, and gastrointestinal dysfunction ( 9 ). Professor Catherine Lord pointed out that the future of autism requires coordinated, large-scale research to develop affordable, individualized, staged assessments and interventions for people with ASD ( 62 ). Professor Baron-Cohen noted that increasing the sample size and collecting data from the same individual multiple times could reduce heterogeneity ( 58 ). In addition, screening for objective and valid biomarkers in the future would help to stratify diagnosis and reduce heterogeneity.
According to the keyword trend analysis of 100 highly cited documents, the genetic risk of autism was determined as the hot focus of research, and immune dysregulation and gut microbiome are the new development frontiers after 2015. Patients with ASD have altered immune function, microglia activation was observed in postmortem brain samples, and increased production of inflammatory cytokines and chemokines was observed in cerebrospinal fluid. The microglia are involved in synaptic pruning, and cytokines also affect neuronal migration and axonal projections ( 63 – 65 ). In addition, abnormal peripheral immune responses during pregnancy might affect the developing brain, increasing likelihood of autism ( 66 ). Several studies have pointed to abnormalities in immune-related genes in the brain and peripheral blood of autistic patients ( 51 , 67 , 68 ). Immune dysfunction is involved in the etiology of ASD and mediates the accompanying symptoms of autism. The patients have multiple immune-related diseases, asthma, allergic rhinitis, Crohn’s disease, and gastrointestinal dysfunction ( 69 – 71 ). Children with frequent gastrointestinal symptoms, such as abdominal pain, gas, constipation, or diarrhea, had pronounced social withdrawal and stereotyped behavior ( 70 – 72 ). Several studies suggested that these autism-related gastrointestinal problems might be related to intestinal microbiota composition ( 72 – 74 ). Accumulating evidence suggested that the microbiota-gut-brain axis influences human neurodevelopment, a complex system involving immune, metabolic, and vagal pathways in which bacterial metabolites directly affect the brain by disrupting the gut and blood–brain barrier ( 75 – 78 ). Fecal samples from children with autism contained high Clostridium species and low Bifidobacterium species ( 79 , 80 ). Probiotics can modulate gut microbiota structure and increase the relative abundance of Bifidobacteria , and clinical studies have shown that supplementation with probiotic strains improves attention problems in children with autism ( 81 , 82 ). Recent clinical trials have shown that microbiota transfer therapy improves gastrointestinal symptoms and autism-like behaviors in children with ASD ( 83 , 84 ).
This scientometric study comprehensively analyzes about a decade of global autism research. Research in the field of autism is increasing, with the United States making outstanding contributions, while neuroscience, genetics, brain imaging studies, or studies of the gut microbiome deepen our understanding of the disorder. The study of the brain-gut axis elucidates the mechanism of immunology in autism, and immunological research may be in the renaissance. The current data serve as a valuable resource for studying ASD. However, the future of autism needs further development. In the future, relevant research should be included for a complete representation of the entire autism population, and further collaboration between individuals, institutions, and countries is expected to accelerate the development of autism research.
Author contributions.
MJ, DZ, JL, and LW conceived and designed the study. MJ, TL, XL, KY, and LZ contributed to data collection and data analysis. MJ wrote the original manuscript. DZ, JL, and LW revised the article and contributed to the final version of the manuscript. All authors contributed to the article and approved the submitted version.
This work was supported by grants from the Key-Area Research and Development Program of Guangdong Province (2019B030335001) and the National Natural Science Foundation of China (grant numbers 82171537, 81971283, 82071541, and 81730037).
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1096769/full#supplementary-material
Citing journal articles.
APA: Citing Journal Articles from Lawrence W. Tyree Library on Vimeo . View a transcript here.
In this tutorial, you will learn the basics for citing journal articles with and without a DOI and how to cite open access journal articles.
Every APA reference needs four parts: author, date, title, and source . As you go through these examples, you will learn how to identify these four parts and how to place and format them into a proper APA reference.
For the first example, you will learn how to cite a journal article with a DOI. Often, you will find journal articles online using the library's databases or other online resources.
The first step is to identify the author of the article. The author of this article is Brittanie Atteberry-Ash,
To list an author, write the last name , a comma , and the first and middle initials .
Example: Atteberry-Ash.
Next, identify when this article was published. For journal articles, you typically only need the year . In this case, this article was published in 2022. You can usually find the date at the top of the article, the cover of the journal, or, for online articles, the article's record.
List the date after the author(s), in parentheses , followed by a period .
Example: Atteberry-Ash, B. (2022).
Now, identify the title of the article . The title will usually be at the very top of the article, in a larger size font.
List the title of the article after the date. Make sure you only capitalize the first word of the title , the first word of the subtitle , which comes after a colon, and any proper nouns . End with a period. In this title, only the words Social and A are capitalized.
Example: Atteberry-Ash, B. (2022). Social work and social justice: A conceptual review.
For the last component, you need the source . For an article, this is the title of the journal, volume, issue , which is sometimes called number , and page numbers of the article. Usually this information can be found on the cover of the journal, on the table of contents, or at the top of the article. For the page numbers, you should look at the first and last pages of the article. For online articles, this information is usually found in the article's record.
Type the journal title , in italics , capitalizing all major words, a comma, the volume , also in italics , the number or issue in parentheses, a comma, and then the page numbers of the article.
Example: Atteberry-Ash, B. (2022). Social work and social justice: A conceptual review. Social Work, 68 (1), 38-46.
The last element of the source is the DOI , which stands for Digital Object Identifier. A DOI can be found in the article’s record or on the first page of the article.
Type the DOI , using the prefix https://doi.org/ . There is no period after the DOI.
Example: Atteberry-Ash, B. (2022). Social work and social justice: A conceptual review. Social Work, 68 (1), 38-46. https://doi.org/10.1093/sw/swac042
If you refer to a work in your paper, either by directly quoting, paraphrasing, or by referring to main ideas, you will need to include an in-text parenthetical citation. There are a number of ways to do this. In this example, a signal phrase is used to introduce a direct quote. The author's name is given in the text, and the publication date and page number(s) are enclosed in parentheses at the beginning and end of the sentence.
Example: Atteberry-Ash (2022) notes "social workers are called on to practice socially just values and to address the consequences of oppression, specifically lost opportunity, social disenfranchisement, and isolation" (p. 38).
In this example, most of the components needed for the reference can be found in the article’s record. This article, however, has multiple authors and does not have a DOI listed in its record or in the article itself.
Format all the citation components of this journal article like the first example. For multiple authors, list the authors in the order they are listed in the article. Use a comma to separate each author and an ampersand (&) should be placed before the last author’s name. This applies for articles with up to twenty authors. Since there is no DOI listed for this article, simply omit that element. The reference will conclude after the page numbers.
Example: Penprase, B., Mileto, L., Bittinger, A., Hranchook, A. M., Atchley, J. A., Bergakker, S., Eimers, T., & Franson, H. (2012). The use of high-fidelity simulation in the admissions process: One nurse anesthesia program’s experience. AANA Journal, 80 (1), 43–48.
If you refer to a work in your paper that has three or more authors, the in-text citation will include the first author's name only, followed by et al. which means "and all the rest."
Example: Penprase et al. (2012) states that "Admission into nurse anesthesia programs is known to be a competitive process among a diverse pool of candidates" (p. 43).
This article was found in PLOS One which is an open access journal. Open access journal articles are articles with the full text freely available online and do not require logging in.
You will need all of the same information from the previous examples to cite an open access article. In this example, most of this information can be found at the top of the article.
In this example, the article's volume, issue, and the article number are found in the citation provided by the journal. Article numbers are used in place of page numbers in some online journals.
The format for open access journals is the same as the other examples. In this example, an article number is used in place of the page numbers. After the issue number, type Article and then the article number. If an open access journal does not provide a DOI, you may provide the URL of the article instead. Only include the URL if it directly brings you to the full text of the article without logging in.
Example: Francis, H. M., Stevenson, R. J., Chambers, J. R., Gupta, D., Newey, B., & Lim, C. K. (2019). A brief diet intervention can reduce symptoms of depression in young adults – A randomised controlled trial. PLOS ONE, 14 (1), Article e0222768. https://doi.org/10.1371/journal.pone.0222768
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This manuscript provides a comprehensive overview of the impact of applied behavior analysis (ABA) on children and youth with autism spectrum disorders (ASD). Seven online databases and identified systematic reviews were searched for published, peer-reviewed, English-language studies examining the impact of ABA on health outcomes. Measured outcomes were classified into eight categories: cognitive, language, social/communication, problem behavior, adaptive behavior, emotional, autism symptoms, and quality of life (QoL) outcomes. Improvements were observed across seven of the eight outcome measures. There were no included studies that measured subject QoL. Moreover, of 770 included study records, only 32 (4%) assessed ABA impact, had a comparison to a control or other intervention, and did not rely on mastery of specific skills to mark improvement. Results reinforce the need for large-scale prospective studies that compare ABA with other non-ABA interventions and include measurements of subject QoL to provide policy makers with valuable information on the impacts of ABA and other existing and emerging interventions.
Avoid common mistakes on your manuscript.
Neurodevelopmental disorders and disabilities (ndd/d).
NDD/D consist of a range of diagnoses and functional impairments of a neurological origin that can present as functional deficits in developmental milestones such as language, communication, social skills, intellect, executive functioning, and motor development (American Psychiatric Association, 2013 ; Miller et al., 2013 ; World Health Organization [WHO], 2001 , 2020 ). The prevalence of NDD/D across developed countries in children and youth 18 years of age and younger ranges from 8% to 15% (Arim et al., 2017 ; Boyle et al., 2011 ; Olusanya et al., 2018 ). Many different conditions and functional limitations are included within the scope of NDD/D, including autism spectrum disorders (ASD), attention deficit/hyperactivity disorder (ADHD), Down syndrome, and intellectual disabilities (ID). In particular, ASD has garnered much attention worldwide due to its high prevalence and associated socioeconomic and familial costs (Reichow et al., 2018 ).
ASD is a spectrum of diagnosable neurodevelopmental disorders that include pervasive developmental disorders (PDD), Asperger’s syndrome (AS) and autism. ASD typically presents during the developmental period and includes social communication and interaction difficulties, along with restricted and repetitive behaviors, interests, or activities (WHO, 2020 ). The prevalence of these disorders has increased over the past 20 years due to many combining factors. The global estimated prevalence in children and youth 18 years of age or younger is 0.62%–0.70% but could be as high as 1%–2% (Elsabbagh et al., 2012 ; Fombonne, 2009 ; Idring et al., 2012 ; Russell et al., 2014 ). The lifetime cost for families with a member diagnosed with ASD can range from approximately US$1.4 million in the United States and the United Kingdom, when diagnosed without an additional ID, to US$2.4million in the United States and US$2.2million in the United Kingdom if diagnosed concurrently with an ID (Buescher et al., 2014 ). Due to its increasing prevalence, the need for effective, evidence-based interventions for ASD has grown exponentially. Applied behavior analysis (ABA) and the interventions that are developed from its principles are some of the most often cited evidence-based interventions developed for the treatment of those diagnosed with ASD. As such, ASD will be the primary diagnosis of consideration within the current scoping review.
At its core, ABA is the practice of utilizing the psychological principles of learning theory to enact change on the behaviors seen commonly in individuals diagnosed with ASD (Lovaas et al., 1974 ). Ole Ivar Lovaas produced a method based on the principles of B. F. Skinner’s theory of operant conditioning in the 1970s to help treat children diagnosed with ASD (or “autism” at the time) with the goal of altering their behaviors to improve their social interactions (Lovaas et al., 1973 ; Skinner, 1953 ; Smith & Eikeseth, 2011 ). To evaluate this method, the University of California at Los Angeles (UCLA) Young Autism Project model was developed and empirically tested by measuring the effects of the intervention when administered one-to-one to children diagnosed with ASD for 40 hr per week over the span of 2–3 years (Lovaas, 1987 ). The remarkable findings revealed that 47% of the children who participated in this treatment reached normal intellectual and educational functioning compared to only 2% of a control group (Lovaas, 1987 ).
ABA has evolved over the past 60 years from the core principles established in the early Lovaas model and subsequent UCLA Young Autism Project into many comprehensive treatment models and focused intervention practices, methods, and teaching strategies, all of which aim to address deficits for children and youth with ASD across all levels of functioning, including cognition, language, social skills, problem behavior, and daily living skills (Reichow et al., 2018 ). One notable and often cited foundational model is “antecedents, behavior, and consequences,” otherwise known as the ABC model, in which manipulating either or both the antecedents and consequences of behavior is intended to increase, decrease, or modify the behavior, thus resulting in a transferrable tool to target behaviors of interest effectively (Bijou et al., 1968 ; Dyer, 2013 ). There are also a number of techniques commonly associated with ABA that are worth noting, including reinforcement, extinction, prompting, video modeling, as well as the Picture Exchange Communication System (PECS), though many of these are widely used in other intervention and education settings (Granpeesheh et al., 2009 ; Sandbank et al., 2020 ; Stahmer et al., 2005 ).
Some specific comprehensive ABA-based treatment models that are investigated in this review include early intensive behavioral intervention (EIBI), Early Start Denver Model (ESDM), and Learning Experiences: An Alternative Program for Preschoolers and Their Parents (LEAP). EIBI is an intensive, comprehensive ABA-based treatment model for young children diagnosed with ASD. EIBI targets children under the age of 5 and is often administered 20–40 hr per week for multiple consecutive years (Matson & Smith, 2008 ; Reichow et al., 2018 ). It is conducted one-to-one in a structured setting such as in the home or school, and often utilizes the discrete trial training (DTT) method (Cohen et al., 2006 ; Smith, 2001 ) in conjunction with other, less structured teaching methods such as natural environment training (Granpeesheh et al., 2009 ). Because this is a comprehensive treatment model, the target of the intervention is across all aspects of functioning such as independent living skills, social skills, motor skills, pre-academic and academic skills, and language (Granpeesheh et al., 2009 ). Another comprehensive ABA-based treatment model is ESDM. This model was developed for children with ASD that fall within the age range of 12–60 months. This intervention builds upon the naturalistic teaching methods within ABA to provide a comprehensive, developmental, and relationship-based behavioral intervention targeted at children early in development (Dawson et al., 2010 ). More recently, some comprehensive ABA treatment models have further shifted away from intensive, operant conditioning based one-to-one models into more naturalistic and generalizable programming. LEAP is one such model for children with ASD because it takes place in public school settings (Strain & Bovey, 2011 ). LEAP was developed from fundamental principles of ABA and includes a variety of methods commonly used in ABA such as Pivotal Response Training (PRT), time delay and incidental teaching, in addition to utilizing peer-mediated interventions and the PECS (Strain & Bovey, 2011 ). It is significant that a core principle of LEAP is to strongly emphasize parental and peer involvement with respect to teaching behavioral strategies and relies on naturally occurring, incidental teaching arrangements, in contrast to the directional, adult-driven instruction used in most other segregated ABA intervention strategies (Hoyson et al., 1984 ; Strain & Bovey, 2011 ).
Within these comprehensive treatment models, focused intervention practices that are often utilized and independently investigated can include, but are not limited to, DTT and naturalistic teaching strategies such as PRT and functional communication training (FCT). DTT is one of the most fundamental focused intervention practices of ABA and utilizes sequences of instruction and repetition in a distraction free, one-to-one setting (Smith, 2001 ). The primary focus of DTT is to teach children new behaviors and discriminations. These new behaviors encompass any behavior that was not previously performed by the child knowingly or unknowingly (Smith, 2001 ). Naturalistic teaching forms of ABA have sought to improve the ability to generalize and maintain the positive effects of behavioral interventions while upholding many of the fundamental principles and behaviorism of ABA (Schreibman et al., 2015 ). One such method of naturalistic teaching is through the focused intervention practice of PRT, developed by Koegel and Koegel ( 2006 ), which is focused on improving the self-initiative and motivation of a child to communicate effectively in common real-life settings (Mohammadzaheri et al., 2015 ). Of note, most of these treatments can involve a professional, though many of the more recent studies and iterations of these treatments seek to involve peers, siblings and family members to encourage generalization to real-world settings and people in the child’s personal life (Mohammadzaheri et al., 2015 ; Steiner et al., 2012 ). Another focused intervention practice and naturalistic teaching method is FCT, a differential reinforcement-based procedure developed by Carr and Durand ( 1985 ) that reduces problem behaviors by replacing them with more appropriate communicative responses. This training is commonly used in conjunction with other ABA methods.
Given the history and range in interventions, there is a degree of variability and confusion in the definition of ABA as a system. Definitions range from rigid protocols for some ABA-based programs to collections of specific techniques associated with ABA, to ABA as a system to evaluate practices rather than as an intervention itself. Granpeesheh et al. ( 2009 ) define ABA as “the application of principles of learning and motivation to the solution of problems of social significance” (p. 163). This definition of ABA as a research strategy echoes that of Baer et al. ( 1968 ) through the later 20th century, in particular in terms of behavior study being: (1) applied, (2) behavioral, (3) analytic, (4) technological, (5) conceptually systematic, (6) effective, and (7) capable of generalized outcomes. Agency definitions tend to define it as a therapy, likewise noted by Schreibman et al. ( 2015 ), with different approaches listed as types. For instance, the Centers for Disease Control and Prevention (CDC) defines ABA as a treatment approach, with examples such as DTT, EIBI, ESDM, PRT, and verbal behavior intervention (VBI; CDC & National Center on Birth Defects & Developmental Disabilities, 2019 ). The National Institute of Child Health and Human Development (NIH) lists positive behavioral support (PBS), PRT, EIBI, and DTT as types of ABA (Eunice Kennedy Shriver National Institute of Child Health & Human Development, 2021 ). The Autism Society( n.d. ) follows the same definition as Baer et al., whereas other intervention types such as PRT and extinction are described as ABA procedures or as sharing principles of ABA. Many ABA-derived programs define certain expectations of their practices specifically, such as EIBI setting, intensity, duration, and personnel, although their methods list a variety of techniques deemed ABA-based, such as DTT, precision teaching, and incidental teaching. As combined approaches become more common, it is becoming more difficult to differentiate interventions considered to be ABA-derived from other non-ABA labeled interventions (Smith, 2012 ).
All of the research into these methods, programs, and comprehensive models, combined with the continued investigations into the traditional applications of the ABA-based interventions, results in a wealth of research about the impact of ABA on children and youth with ASD, in particular with respect to improvements in cognitive measures, language skills, and adaptive skills (Eldevik et al., 2009 ; Virués-Ortega, 2010 ). The ensuing amount of scientific evidence has resulted in ABA being considered a “best practice” and thus endorsed by the governments of Canada and the United States for the treatment of children and youth with ASD (Government of Canada, 2018 ; U.S. Department of Health & Human Services, 1999 ).
As ABA is a broad intervention which includes many different methods and programs, reviews of the entire scope of the current research are uncommon. To our knowledge, a comprehensive review of the current ABA literature that spans all ABA methods and outcomes for children and youth with ASD, and that includes randomized controlled trials (RCT), clinical controlled trials (CCT), and single-case experimental design (SCED) studies, has not been completed. The current literature consists primarily of systematic reviews and meta-analyses that have investigated the quantifiable and qualitative outcomes of ABA on children with ASD, but few of these studies include SCED, and the results across the reviews inconsistently show significant improvement with ABA interventions.
For example, in a meta-analysis by Virués-Ortega ( 2010 ), the effectiveness of ABA was investigated across 22 included studies with respect to as many outcomes as possible, including language development, social functioning, intellectual functioning, and daily living skills, for those diagnosed with ASD (Virués-Ortega, 2010 ). The results of this meta-analysis suggested that ABA interventions that were implemented in early childhood and were long-term and comprehensive in design did result in a positive medium to large effect in the areas of language development (pooled effect size of 1.48 for receptive language, 1.47 for expressive language), intellectual functioning (pooled effect size 1.19), acquisition of daily living skills (pooled effect size 0.62), and social functioning (pooled effect size 0.95), when compared to a control group that did not receive ABA intervention. This mirrors the meta-analysis of 29 articles conducted by Makrygianni et al. ( 2018 ), where it was found that ABA programs for children with ASD resulted in moderate to very effective improvements in expressive and receptive language skills, communication skills, nonverbal IQ scores, total adaptive behavior, and socialization, but lesser improvements in daily living skills. In a 2018 meta-analysis by Reichow et al. ( 2018 ), the changes in autism severity, functional behaviors and skills, intelligence, and communication skills were investigated across five articles that included one RCT and four CCTs for EIBI. After conducting meta-analyses of these studies, it was found that the evidence for EIBI improving adaptive behavior compared to treatment as usual comparison groups was positive but weak (mean difference [ MD ] = 9.58; 95% confidence interval ( CI ) 5.57–13.60), whereas there was no evidence that EIBI improved autism symptom severity (standardized mean difference [ SMD ] = −0.34; 95% CI −0.79–0.11; Reichow et al., 2018 ). Therefore, the current literature appears to indicate inconsistent results with respect to the magnitude of improvements seen as a result of ABA interventions for children and youth with ASD.
With respect to the wealth of SCEDs included throughout the ABA literature, Wong et al. ( 2013 ) have noted that existing reviews rarely capture these types of studies, with two notable exceptions conducted by the National Autism Center ( 2009 ) and the National Professional Development Center on ASD (NPDC; Odom et al., 2010 ). These studies still had some key exclusions: the National Autism report excluded articles that (1) did not have statistical analyses, (2) did not include linear graphical presentation of the data for SCEDs, or (3) used qualitative methods, whereas the NPDC report searched for studies on behavioral strategies that fulfilled the requirements of being an evidence-based practice, as defined by the authors (National Autism Center, 2009 , 2015 ; Odom et al., 2010 ). Neither of these reports evaluated the entire scope of the available ABA research with respect to children and youth with ASD, potentially missing the value of the studies that were excluded.
The purpose of the current review therefore is to evaluate the available literature on ABA as an intervention approach in the treatment of ASD in children and youth in an effort to help instruct the scientific community on the most beneficial directions for future research. Moreover, as ABA is commonly recognized at a governmental level as evidence-based, a review of the current ABA literature will help inform other existing and emerging therapies and interventions, researchers, policy makers, and the public of the standard to which established, evidence-based interventions are held. This is accomplished by collecting, compiling, and discussing the available data on the most common outcomes and methods. This includes the most common journals of publication, population metrics, and the transferability of this prominent therapy approach to the real world. As such, the objectives of this scoping review are to examine the extent, range, and nature of research activities regarding the impact of ABA on children and youth with ASD and to identify any gaps in the existing literature regarding ABA outcomes and research designs.
A scoping review study design was selected for the current investigation. According to Colquhoun et al. ( 2014 ), “a scoping review is a form of knowledge synthesis that addresses an exploratory research question aimed at mapping key concepts, types of evidence, and gaps in research related to a defined area or field by systematically searching, selecting, and synthesizing existing knowledge” (p. 1293). Scoping reviews differ from systematic reviews in that they provide an overview of existing evidence regardless of the quality (Tricco et al., 2016 ), and may not formally assess study rigor (Arksey & O’Malley, 2005 ).
The current scoping review was conducted to gather an understanding of the scope of available research regarding the use of ABA as an intervention for children and youth living with NDD/D, and in particular ASD. For the purposes of the current review, ABA will be defined as an intervention informed and developed from behavioral analytic approaches for the treatment of children and youth with ASD. The effect of ABA is defined as the measurable changes in a participant's various outcomes as a result of receiving ABA intervention. These outcomes were not predefined to prevent missing any possible impact. The review comprised a database search, as well as a reference search of selected reviews. A second phase of the literature search was conducted to update the sample to reflect more recent literature. A guiding document by Tricco et al. ( 2016 ) was used for direction and as a reference for conducting this review.
An initial search was conducted across PubMed, MEDLINE (EBSCOHost), Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsychINFO, Educational Resources Information Center (ERIC), Cochrane Central Register of Controlled Trials (CENTRAL), and Cochrane Database of Systematic Reviews (CDSR) utilizing medical subject heading (MeSH) search terms and limitations to describe the relevant population in the initial search (children and youth with NDD/D) and intervention (ABA) (see Appendix 1 for a full list of search terms for each database). Additional limitations of the search were English language publications, subject age range of 0–18 years, and publication date range. The search was conducted in two phases: January 1, 1997 through December 31, 2017, and January 1, 2018 through December 31, 2020.
Several reviews were selected for a further text search. Data were not extracted directly from eligible reviews. Instead, their selected articles were screened and added to the sample if they were not already included in the initial search. This process was repeated for any secondary reviews that occurred as well. These additions were excluded from the publication date limitation, resulting in the inclusion of a number of studies outside of the initial search date range. Review and meta-analysis results were not coded.
A PICO (population, intervention, comparison, outcome) framework was used to guide the selection of articles. Population and intervention were used as eligibility criteria. Although the intervention was restricted to ABA, the population was originally defined broadly as NDD/D in an effort to capture as much of the applicable literature as possible, and later revised to focus on ASD and mixed diagnoses (ASD and other). This included populations where some subjects had other non-ASD diagnoses, such as ADHD, Down syndrome, or ID, whether they co-occurred with ASD within subjects or presented across subjects. Non-ASD diagnoses observed in the mixed-diagnoses category of the current review are described in the results (“Results: Description of Included Studies”) and in Appendix 2 . Outcome was not considered because one objective of the current scoping review was to identify the measured outcomes. Comparison was not used so as not to limit the scope of the review. Study design was not limited in the initial search.
Inclusion criteria for article selection during the initial search comprised (1) English language articles that are (2) about the effects of ABA on (3) children and youth (birth to 18 years) with NDD/D, within (4) the timeframe of January 1, 1997 through December 31, 2020. As described above, screened articles included from selected reviews and secondary reviews were exempt from the date range limitations.
Exclusion criteria comprised (1) hospital-based (inpatient) settings and mixed-setting studies (i.e., those including some inpatient subjects); (2) use of qualitative research methods; (3) publications that are not “research-based” (e.g., newsletters, books); (4) populations exceeding 18 years of age; and (5) combined interventions if not looking specifically at the effectiveness of ABA intervention. In cases of mixed age (i.e. including subjects over 18 years of age) or mixed population (i.e., including typically developing subjects), studies were excluded if it was not possible to extract results for the target population separately. Inpatient settings were excluded because the focus of the current scoping review was on community offerings, not hospital services. A small number of studies were excluded when the methods did not align with typical ABA outcome measures, such as those training response hierarchies or attempting to condition new reinforcers. A library search was conducted for studies that could not be accessed in full online, and any that could not be found were subsequently excluded.
When the diagnostic criteria were narrowed to focus primarily on ASD, articles that contained only non-ASD diagnoses were excluded.
Articles from the original search of online databases were exported to Mendeley® Desktop versions 1.19–2.62.0, a reference management software, where most duplicate studies were automatically identified and removed. Any remaining duplicates from both the database and review search were removed manually. Titles and abstracts of all retrieved articles were then independently reviewed by two researchers following the outlined inclusion and exclusion criteria. Studies were included if the independent reviewers reached agreement, or after further discussion with a third reviewer. Retained articles then underwent full text review for inclusion, following the same steps.
Articles included following the full text review then underwent data extraction. Extracted data comprised first author, title, year of publication, origin of study, funding sources, study aim, study design, duration of intervention, duration of study, population size, population description, setting, measurement outcomes, measurement tools, and key findings. In cases where results were reported individually for each subject, they were extracted as such. In larger scale studies where only group results were reported, group results were extracted, so long as the group included only the target population.
In general, the entire sample of records included for coding and synthesis was subdivided into three sections concerned with: (1) general ABA Impact, (2) Comparisons of ABA Techniques, and (3) Between-Groups Comparisons of ABA to control or other interventions. These divisions are visually summarized in Figure 1 and are described below. All records underwent general data coding of basic study information, as well as specific outcome coding, also described below. (Details about coding definitions can be found in Appendix 2 .) Simplified extraction tables for these three subdivisions are available in Appendix 3 (Tables S1 , S2 , and S3 ).
Flowchart Describing the Process of the Current Scoping Review Search, Screening, Data Extraction, and Coding. Note. From an initial search comprising 2,948 records, after screening studies and subdividing multipart studies, a total of 770 study records remained. These were coded in three categories: Comparisons of ABA Techniques, ABA Impact, and Between-Groups Comparisons. Designed with reference to Tricco et al. ( 2016 ) and created using diagrams.net ™/draw.io® from JGraph Ltd. Note that three study records were included in both the ABA Impact section and the Comparisons of ABA Techniques section (Mello et al., 2018 ; Rad et al., 2019 ; Vietze & Lax, 2020 ), and three study records were included in all three coding sections (Dugan, 2006 ; Kalgotra et al., 2019 ; Kovshoff et al., 2011 ).
During the process of coding, articles containing multiple concurrent or consecutive studies were separated into discrete rows, and will hereafter be treated as self-contained studies in this review. In all figures and further text, all coded rows are referred to as “study records.” Once separated, researchers identified and excluded (1) functional analyses or studies focused on their use, (2) preference assessments or studies focused on their use, and (3) predictive studies. Study records were coded independently by two researchers and then discussed to obtain agreement, or referred to a third researcher to obtain agreement. During coding, any further study records found to satisfy the exclusion criteria were excluded.
Items selected for general data coding included publication details, population metrics, and several specific study methods. The population metrics were age, sex, and diagnosis of participants. (Detail on the population coding values can be found in Appendix 2 ). Study records were additionally coded and compared by two independent researchers to identify inclusion of the following methods: (1) follow-up or maintenance, (2) mastery or criterion measures, (3) generalization. Studies including comparison groups were further coded by one researcher to identify the presence of (1) a control group (typically consisting of “eclectic” or treatment as usual), (2) comparisons to other non-ABA intervention/s, or (3) a mix of these.
After general data coding, the sample was separated into two groups for outcome coding: ABA Impact and Comparisons of ABA Techniques. The majority of study records fell into the ABA Impact section, in which study records measured the change in outcomes (e.g., amount improved) as a result of exposure to ABA intervention. In contrast, study records that were primarily concerned with comparing multiple techniques or intensities of ABA were reserved for the Comparisons of ABA Techniques section, because general ABA impact could not easily be determined for the entire study population in these studies. Finally, a select number of study records from the ABA Impact section where ABA interventions were also compared to a control or different intervention were coded a second time to describe these comparisons in the Between-Groups Comparisons section. As noted in Fig. 1 , some studies from the ABA Impact section also fell into the Comparisons of ABA Techniques section, or into all three sections.
Although the search was not restricted, the observed outcome measures were classified into eight categories: cognitive, language, social/communication, problem behavior, adaptive behavior, emotional, autism symptoms, and quality of life (QoL) outcomes. At first, QoL was included to help describe the generalizability and real-life utility of ABA interventions, following the example of Reichow et al. ( 2018 ). However, as no instances of subject QoL measures occurred in this search, this outcome is not included in the subsequent synthesis. Within each category, outcomes were generally classified as improvement, regression, mix, or no change, as can be seen in the extraction tables (Tables S1 , S2 , and S3 in Appendix 3 ).
When more than two variables or interventions were compared, which sometimes occurred in the Comparisons of ABA Techniques and Between-Groups Comparison sections, study records were discussed and split into discrete rows by two researchers to represent simplified or single-variable comparisons in each row. These are termed “comparison records” for the purpose of coding and synthesis. As seen in Tables S2 and S3 in Appendix 3 , further detail was extracted regarding the category of techniques or interventions compared and the relative effectiveness of each.
Prior to coding, researchers categorized outcome measures, measurement scales or strategies, and intervention categories observed during the extraction process into tables in an effort to mitigate potential inconsistencies in coding. For example, in the Comparisons of ABA Techniques section, categories were broadly defined as Teaching, Stimulus Characteristics, Reinforcement, Subject/Setting Characteristics, and Comparisons of ABA Interventions. Further descriptions of these and other categories can be found in Appendix 2 .
Further details on general data coding, as well as outcome coding for ABA Impact, Comparisons of ABA Techniques, and Between-Groups Comparisons can be found in Appendix 2 . Extractions for all three sections can be found in Tables S1 , S2 , and S3 , respectively, in Appendix 3 .
All statistical analyses, compilations, and tabulations were completed using Microsoft® Excel® versions 1805-2111. Descriptive analyses (means, medians, etc.) were calculated using native Excel® functions. Pivot tables were utilized to tabulate frequencies. Figures were generated using Microsoft® Excel® version 2016 MSO, Microsoft® Word® versions 2011–2111, and diagrams.net ™/draw.io® by JGraph Ltd.
In addition, some qualitative characteristics were explored as well, such as observations about the types of methods used in the interventions encountered, the degree of mastery and generalization measures, and how targeted the interventions and measurement tools were.
As shown in Fig. 1 , the record selection process differed slightly between the two searches spanning 1997–2017 and 2018–2020. This is because the diagnostic criteria for the current manuscript were updated to exclude populations that only contained non-ASD diagnoses, and the removal of records satisfying the new criteria took place at different points for each search.
The database searches yielded a total of 2,074 entries after import to Mendeley®, and 874 entries from selected reviews and secondary reviews. Ten systematic reviews were identified and investigated for the literature search (Brunner & Seung, 2009 ; Dawson & Bernier, 2013 ; Makrygianni et al., 2018 ; Mohammadzaheri et al., 2015 ; Reichow et al., 2014 , 2018 ; Rodgers et al., 2020 ; Shabani & Lam, 2013 ; Spreckley & Boyd, 2009 ; Virués-Ortega, 2010 ). After pulling references from the first five (Brunner & Seung, 2009 ; Dawson & Bernier, 2013 ; Makrygianni et al., 2018 ; Rodgers et al., 2020 ; Shabani & Lam, 2013 ), it was found that the references in the remaining five reviews were duplicates of previously identified references. Secondary reviews from Seida et al. ( 2009 ) and Dawson and Burner ( 2011 ), both cited by Dawson and Bernier ( 2013 ), were also investigated for references (Bassett et al., 2000 ; Bellini & Akullian, 2007 ; Delano, 2007 ; Diggle et al., 2002 ; Horner et al., 2002 ; Hwang & Hughes, 2000 ; Lee et al., 2007 ; McConachie & Diggle, 2007 ; Odom et al., 2003 ; Reichow & Volkmar, 2010 ; Smith, 1999 ). Records from Brunner and Seung ( 2009 ) that were categorized into treatment models that did not fulfill the definition of ABA as per the current review were not considered. In addition, the secondary review by Vismara and Rogers ( 2010 ) was not considered because it was a narrative review. After removing duplicates or entries already existing in the database search, 1,577 entries remained from the database search and 525 from reviews, for a total of 2,102 records.
A total of 1,337 records were removed during title, abstract, and full-text screening because they met the exclusion criteria, were duplicate records, were reviews, or contained only non-ASD diagnoses. Multipart studies were separated into discrete records, yielding a total of 849 study records. A further 34 were excluded at this stage as they were preference assessments, functional analyses, or were concerned with training response hierarchies or conditioning reinforcers, leaving 815 study records. When the diagnostic inclusion criteria were revised, any remaining records containing only non-ASD diagnoses were excluded.
Thus, the total sample included in the quantitative and qualitative synthesis comprised 770 study records. This entire sample was analyzed for general data metrics (see Fig. 1 ). References for the 709 included articles can be found in Appendix 4 .
Overall, agreement between raters was approximately 80% across all coding categories. The range of included outcome categories was selected in order not to limit the scope of the literature search and synthesis for this review so that a comprehensive review of the application of ABA for ASD and mixed-diagnosis populations across the entire time span and age range of the search could be conducted. Frequently occurring other diagnoses in the mixed-diagnoses category included ADHD; ID; global developmental delay (GDD) or other developmental delays; oppositional defiant disorder (ODD); Down syndrome; cerebral palsy (CP); fetal alcohol spectrum disorders (FASD); Angelman syndrome; Fragile X; obsessive-compulsive disorder (OCD); Tourette syndrome; traumatic brain injury (TBI); epilepsy or seizure disorders; sensory integration or processing disorders; speech/language delays; learning disabilities; and behavior, emotional, or mood disorders.
The most frequently occurring publication year was 2020. The earliest publication reviewed was from 1977 and the most recent from 2020. Thirty percent were from 2000–2009 and 61% were from 2010–2020. The remaining years comprised 9% of the journals reviewed.
The 5-year impact factor (IF) characteristics were determined by removing duplicate journals prior to calculation. IFs were accessed from Journal Citation Reports, via Clarivate™. The unique median IF was 2.56. The lowest impact journal had an IF of 0.71 and the highest had an IF of 9.92. Most of the reviewed study records were from the Journal of Applied Behavior Analysis (55%). The next most frequent journal was the Journal of Autism and Developmental Disorders , representing 4% of the journal cohort. Dissertations accounted for 4% of the cohort. Analysis of Verbal Behavior and Behavioral Interventions each made up 3% of our journal cohort, and the remaining journals contributed 1%–2% each. Journals contributing less than 1% were grouped as “Other,” making up 16% of the total cohort. Within the cohort of study records, 48% of records had participants that were solely male, 45% were of mixed sex, and 4% of the publications had solely female participants. Seventy-six percent of study records had participants with only ASD, and 24% had participants in the mixed-diagnoses category.
In the study records reviewed, 33% had one or two participants, whereas 31% of the publications had three participants, and 13% had four. Study records with 5 to 9 participants accounted for 11% of the total and 13% had more than 10 participants. The median number of participants was 3, whereas the mean number of participants was 8.12.
Overall, it was found that study records that included a smaller sample size (e.g., N ≤ 4) often investigated specific skills, tasks, or responses that varied based on each specific child (Gongola, 2009 ; Plavnick & Ferreri, 2011 ; Sullivan et al., 2020 ). Many studies modified the intervention or the definition of mastery dependent on the child or task given (Charlop-Christy & Daneshvar, 2003 ; Charlop et al., 1985 ; Ezzeddine et al., 2020 ; Lyons et al., 2007 ; Romaniuk et al., 2002 ).
Within the cohort of study records, 41% had some follow-up measure, 40% had some criterion or mastery measure, and 31% of publications had some generalization measure.
After the general data coding stage, any study records from the total sample ( N = 770) looking only at ABA Impact were coded for outcomes ( N = 551), i.e., improvement, regression, mix, or no change in the eight outlined outcome categories. Any study records comparing different ABA techniques ( N = 225) were designated for the next section (see “Comparisons of ABA Techniques,” below). The eight outcomes considered were cognitive, language, social/communication, problem behavior, adaptive behavior, emotional, autism symptoms, and QoL outcomes. Subject QoL is not reported in any tables, as there were no instances of this outcome being measured in the current cohort of study records.
The majority of study records reported improvement across all outcome categories, with 63%–88% of study records reporting improvement across the various outcome measures. In contrast, 0%–2% reported regression, 13%–36% reported mixed results, and 0%–13% reported no change (Fig. 2 ).
Distribution of Improved, Regressed, Mixed, and Unchanged Results in the ABA Impact Section across the Measured Outcomes ( N = 551 study records)
Percentage Distribution of Results Where One Method Improved More, Results were Mixed, Results had No Change, or Results were Unknown (had No Quantifiable Measure) in Comparisons of ABA Techniques Group across the Measured Outcomes ( N = 225 comparison records)
When observing outcome measures by age group (see Appendix 5 , Table S4 ), among study records conducted with participants between ages 0–5 years, cognitive, language, and social/communication were the most commonly studied outcomes, at 22%, 23%, and 23% respectively. Of these, 66%, 68%, and 57% reported an improvement, respectively. Meanwhile, for ages 6–12, problem behavior and language were the most commonly studied outcomes at 25% each. Among these respective outcomes, 86% and 71% reported improvement. For ages 13–18, the most commonly studied outcome was cognitive (26%), followed by adaptive behavior (20%). Of these, 83% and 86% reported improvement, respectively. Finally, in the mixed-age groups, the most commonly studied outcome was language (28%), followed by social/communication (20%) and cognitive (20%). Of these three most studied outcomes, improvement was reported at 61%, 65%, and 62%, respectively. Detailed findings are available in Table S4 of Appendix 5 .
Outcome measures were also divided by sex. Among the study records that only observed females, the most commonly studied outcome was problem behavior at 33%, with social/communication following at 23%. Improvement was recorded 85% and 67% of the time, respectively, for these outcomes. Among records looking at only males, language was the most studied outcome at 26%, followed by cognitive and social/communication at 21% each. These improved at 62%, 66%, and 59%, respectively. Among publications with mixed sexes, the most studied outcome measures were language (25%), cognitive (22%), and social/communication (21%). Of these, 65%, 71%, and 67% showed improvement, respectively.
Outcome measures were then divided by diagnosis (Tables S5 and S6 ). Among study records solely studying ASD, the most commonly studied outcomes were language, cognitive, and social/communication, making up 25%, 22%, and 22% respectively. Among these respective outcome measures, 68%, 68%, and 63% reported improvement. In the mixed-diagnoses category, the most studied outcomes were problem behavior (31%) and language (22%), with 70% and 58% reporting improvements, respectively. Detailed findings are available in Tables S5 and S6 in Appendix 5 .
Next, secondary measures were classified. These included the presence of follow-up, whether interventions assessed mastery or criterion, and whether interventions assessed generalization. Out of the ABA Impact cohort, 41% had some follow-up, 40% had some measure of mastery/criterion, and 31% had some measure of generalization. Among study records that showed improvement within the various outcome measures, use of follow-up measures varied. Records that recorded improvements in cognitive, language, social/communication, and problem behavior outcomes had follow-up measures 47%–59% of the time. Records recording improvement in adaptive behavior and emotional outcomes had follow-up measures 67% and 64% of the time, respectively. Studies reporting improvement in autism symptoms had follow-up measures 100% of the time (see Appendix 5 , Table S7 ). Within the current cohort, out of the study records that signified some improvement, the frequency of mastery/criterion measures varied. Measures of mastery/criterion ranged from 0% and 14%, respectively, for autism symptoms and problem behavior improved outcomes, to 25% and 29%, respectively, for adaptive behavior and social/communication, and 43%–49% for cognitive, language, and emotional improved outcomes (Table S7 ). With regard to generalization, no study records showing improvements in autism symptoms assessed any measure of generalization. Among other outcomes, generalization measures ranged from 14% for emotional improved outcomes, 24%–29% for problem behavior, adaptive behavior, and cognitive improved outcomes, and 39% and 46%, respectively, for language and social/communication improved outcomes (Table S7 ).
Many records from the current search investigated the effectiveness of different ABA methods or variables in delivery. This section of study records was further divided into discrete records wherever more than two variables were compared, for a total of 307 comparison records, which were then coded for outcomes. In this case, coding included which category of comparison was studied, and indicated whether one ABA method performed better, or if the results were mixed or had no change.
Five categories of variables were defined: Teaching, Stimulus Characteristics, Reinforcement, Subject/Setting Characteristics, and Comparing ABA Interventions. These are further described in Appendix 2 . Within these categories, most comparison records were unique in the methods examined and thus could not be easily compared across this selection of records. That said, some trends were identified. First, many different teaching procedures were compared, such as how instructions were provided, tact versus listener training, or serial versus concurrent training (Arntzen & Almås, 2002 ; Delfs et al., 2014 ; Lee & Singer-Dudek, 2012 ). Several comparison records investigated the quality of the teaching procedures, commonly with respect to the integrity of reinforcement or teaching techniques (Carroll et al., 2013 ; Odluyurt et al., 2012 ). Others investigated the differences in personnel delivering the ABA interventions, such as a parent or clinician (Hayward et al., 2009 ; Lindgren et al., 2016 ), or differences in program delivery, such as via specific modeling, reinforcing, or prompting techniques (Campanaro et al., 2020 ; Jessel et al., 2020 ; Quigley et al., 2018 ). A number of comparison records compared time characteristics, such as reinforcement schedules or delays (Majdalany et al., 2016 ; Sy & Vollmer, 2012 ). Factors related to reinforcement in general were commonly compared and diverse in nature, spanning the quality, preference, presentation, and other aspects of reinforcement (Allison et al., 2012 ; Carroll et al., 2016 ; Fisher et al., 2000 ; Groskreutz et al., 2011 ). A few comparison records examined subject characteristics, such as the effectiveness of an ABA intervention based on the age of participant entry into the program or their diagnosis (Luiselli et al., 2000 ; Schreck et al., 2000 ), but slightly more commonly measured was the effectiveness of interventions administered in different settings such as at school, at a clinic, or at home (Hayward et al., 2009 ; Sallows & Graupner, 2005 ; Schreck et al., 2000 ). Some comparison records compared specific ABA intervention techniques, such as PRT, the Lovaas/UCLA model, or response interruption and redirection (RIRD), to one another (Dwiggins, 2009 ; Fernell et al., 2011 ; Lydon et al., 2011 ; Mohammadzaheri et al., 2014 ; Saini et al., 2015 ).
Table S8 (located in Appendix 5 ) displays the Comparisons of ABA Techniques group analysis of various intervention categories compared in the outcome measures. Teaching was the most commonly compared intervention category across six outcome measures, ranging from 38% to 64%, except for emotional (25%), and autism symptoms (10%). Comparing ABA interventions was the most commonly studied comparison in the emotional outcome (50%; 2 out of 4 comparison records), and subject/setting characteristics was the most commonly studied comparison in the autism symptom outcome (70%; 7 out of 10 comparison records). The improvement of one method over another was not always prevalent (Fig. 3 ). Within the cognitive, language, and social/communication outcomes, 37%–40% of comparison records found that one method exhibited greater improvement than the other, whereas 47%–56% had mixed outcomes. This is similar for adaptive behavior, where 52% found that one method exhibited greater improvement and 39% were mixed. On the other hand, outcome measures for problem behavior and autism symptoms more clearly showed that one method exhibited greater improvement, at 65% and 70% (7 out of 10 records), respectively.
Many records also investigated the effectiveness of ABA against other interventions or control groups. From the ABA Impact section, these study records comparing measures between groups ( N = 49) were coded a second time. These were also divided into discrete records whenever more than two groups were compared, for a total of 58 comparison records, which were then coded for outcomes. In this section, coding indicated whether one intervention performed better, or whether there was a mix, no change, or regression. The main interventions of interest in this section were categorized into ABA, EIBI, and I-ABA. Frequent comparisons were to control, which included eclectic (nonspecified), treatment as usual (TAU), or waitlist groups; nursing; portage; the Developmental, Individual Differences, Relationship-based intervention (DIR); or other interventions such as sensory integration therapy and the modified sequential-oral-sensory approach (M-SOS). These categories are further detailed in Appendix 2 .
Due to the nature of these interventions, most were longitudinal in study duration, as results were measured after 1 or more years. Moreover, validated measurement tools including Vineland Adaptive Behavior Scales (VABS), Reynell Developmental Language Scales (RDLS), and Bayley Scales of Infant Development-Revised (BSID-R), were more often used to measure changes in this section than in the ABA Impact and Comparisons of ABA Techniques sections, as well as validated parent/caregiver surveys such as the Achenbach Child Behavior Checklist or the Nisonger Child Behavior Rating (Eikeseth et al., 2007 ; Kovshoff et al., 2011 ; Smith et al., 2000 ). Few study records in this category included specific and differentiated probes into the generalization of the improvements seen ( n = 3; Dugan, 2006 ; Leaf et al., 2017 ; Peterson et al., 2019 ), and few included measurements of mastery or criterion ( n = 3; Birnbrauer & Leach, 1993 ; Dugan, 2006 ; Hilton & Seal, 2007 ).
Among the Between-Groups Comparisons (see Appendix 5 , Table S9 ), the ABA coding category was the most often improved, showing improvement over the comparison group at least 36% of the time across all outcomes. I-ABA showed improvement over the comparison 18%–30% of the time among cognitive, language, social/communication, adaptive behavior, and autism symptom outcomes. EIBI showed improvement over the comparison 21%–25% of the time among the cognitive, language, social/communication, and adaptive behavior outcomes. TAU and Other interventions occasionally showed greater improvement in some outcome measures (≤ 22% of the time). Nursery, portage, and DIR showed little to no improvement over ABA treatment groups.
Figure 4 shows the distribution of the number of participants across the whole sample, ABA Impact, Comparisons of ABA Techniques, and Between-Groups Comparisons cohorts. The highest number of participants in a study record was 332, whereas the lowest was 1. The Between-Groups Comparisons section had the highest median number of participants at 34, and the largest variation in the number of samples with an interquartile range (IQR) of 37. The entire cohort, ABA Impact section and Comparisons of ABA Techniques section each had a median number of 3 and an IQR of 1, respectively.
Distribution of the Number of Participants in the Entire Cohort, ABA Impact, Comparisons of ABA Techniques, and Between-Groups Comparisons sections. Note. The entire cohort, ABA Impact section, and Comparisons of ABA Techniques section each had a median of 3 participants and an IQR of 1, whereas the Between-Groups Comparisons section had a median of 34 participants and an IQR of 37
In addition to having larger sample sizes and more frequent use of validated measurement scales, records in the Between-Groups Comparisons section more often incorporated statistical analyses, approximately 85% of the time compared with approximately 15% of the entire cohort. Although statistical significance was not considered when initially coding the results in order to align with the rest of the sample, an informal review was conducted based on the reported statistical significance of the improvement of one condition over another. Overall, it was found that not all improvements were significant or assessed for statistical significance (Dawson et al., 2010 ; Dugan, 2006 ; Howard et al., 2014 ; Kovshoff et al., 2011 ). Among the outcome measures defined in the current review, some records showed significant improvement in some but not all contributing measures (Eikeseth et al., 2002 ; Reed et al., 2007a ; Zachor et al., 2007 ). Others had statistically significant improvement in all contributing measures of a given outcome (Dixon et al., 2018 ; Howard et al., 2005 ; Lovaas, 1987 ; Novack et al., 2019 ; Smith et al., 2000 ; Zachor et al., 2007 ).
The entire cohort of records explored had few occurrences of RCTs, the “gold standard” of research. Of the 12 identified RCTs, 5 were categorized into this review’s Comparisons of ABA Techniques section, whereas the remaining 7 included comparisons to controls or other interventions (Cihon et al., 2020 ; Dawson et al., 2010 ; Koenig et al., 2010 ; Landa et al., 2011 ; Leaf et al., 2017 , 2020 ; Mohammadzaheri et al., 2014 , 2015 ; Peterson et al., 2019 ; Reitzel et al., 2013 ; Scheithauer et al., 2020 ; Smith et al., 2000 ). In the interest of identifying a subset of more rigorous records, a three-step filter was conducted (Fig. 5 ). This was not a formal assessment of study quality, but rather a way to identify the proportion of investigated studies with several specific characteristics. After removing the section of studies looking at Comparisons of ABA Techniques, as well as any studies assessing mastery or criterion, and following with a filter for any inclusion of a comparison to control or other intervention, 32 study records (4%) remained out of 770. That is, only 4% of the entire sample assessed ABA impact, had a comparison group, and did not rely on mastery of specific skills to mark improvement.
Filter Flow Sheet Representing Study Records after the Subsequent Removal of Various Factors. Note. The first filter removed study records that compared various ABA techniques, where 551 of 770 (72%) of records remained. Next, study records that assessed mastery/criterion were removed, leaving 361 of 770 (47%) of records. Next, study records without any comparison group were removed, leaving 32 of 770 (4% records)
There was an observed increase in the amount of ABA literature between 2018 and 2020 compared to the 20-year search between 1997 and 2017. There was also an observed increase in larger scale studies between 2018 and 2020, as also evidenced by the higher frequency of RCTs ( N = 4; Cihon et al., 2020 ; Leaf et al., 2020 ; Peterson et al., 2019 ; Scheithauer et al., 2020 ) compared to the preceding 20-year period ( N = 8, Dawson et al., 2010 ; Koenig et al., 2010 ; Landa et al., 2011 ; Leaf et al., 2017 ; Mohammadzaheri et al., 2014 , 2015 ; Reitzel et al., 2013 ; Smith et al., 2000 ), but overall no notable change in the demographics, sample size, frequencies of outcomes measured, or teaching procedures.
The increasing prevalence of ASD in children and youth across the world has placed evidence-based interventions that treat these disabilities and disorders in high demand. ABA has been at the forefront of these interventions for decades and is recommended by many governments, including in the United States and Canada, as a well-established, scientifically proven therapy (Government of Canada, 2018 ; U.S. Department of Health & Human Services, 1999 ). Due to these prominent endorsements, existing and emerging interventions should be held to the same standard as established ABA interventions. That said, to our knowledge, a scoping review into all of the pertinent scientific evidence surrounding ABA has not yet been undertaken. This may result in knowledge gaps regarding this long-standing and widely used intervention and was the reasoning behind the current scoping review.
The results of the current scoping review are consistent with previous review articles and meta-analyses into the overall trend of positive effects of ABA. For example, there were overwhelming positive improvements in the majority of study records with respect to cognition, language development, social skills and communication, and adaptive behavior, along with reductions in problem behavior (Dawson & Bernier, 2013 ). In the ABA Impact section of the current review, 63%–88% of study records reported improvement across these same outcome measures, in addition to improvements in emotional and autism symptoms outcome measures (Fig. 2 ). The results of the current analysis into the demographics of these studies are also consistent with the existing literature, as the majority of the participants were male (48%) or there was a mix of females and males (45%) within multiparticipant studies (Kim et al., 2011 ; Lai et al., 2014 ; Miller et al., 2016 ). Further, the sole diagnosis of ASD was more common than mixed diagnoses, as 76% of study records recorded ASD without other diagnoses or comorbidities, again consistent with previous research into ABA (Dawson & Bernier, 2013 ). With respect to age distribution within the current review, the current results further mirror the previously published literature on EIBI, as children of a younger age tended to be predominately measured on outcomes of cognition, language skills, and social skills (Dawson & Burner, 2011 ; Reichow et al., 2012 ; Virués-Ortega, 2010 ). Children aged 6–12 years were most often measured with respect to changes in problem behavior and language skills, and those 13–18 years of age were most often measured with respect to changes in adaptive behavior and cognitive outcomes, again similar to previous research in older children and youth (Granpeesheh et al., 2009 ). As reported in other research, participants diagnosed solely with ASD were most often measured upon changes in cognition, language, and social skills and communication (Reichow et al., 2012 ). It is interesting that the mixed-diagnoses category was also commonly measured on language outcomes, but the most common outcome measure was problem behavior, at 31% of study records in the ABA Impact section.
Based on the number of study records ( N = 770, Fig. 1 ), the current findings confirm there is a wealth of scientific knowledge regarding the effect of ABA on children and youth with ASD. Many studies have been published in peer-reviewed journals, but the quality of these studies requires further consideration. The lack of non-ABA comparison groups, rigorous study design, follow-up measures or investigation into generalization of reported outcomes, as well as factors such as small sample sizes, assessment of mastery or criterion, and the use of individualized methods to attain a particular skill or behavior for individual participants, could all contribute to and potentially confound the overarching positive findings seen in ABA research studies.
The gold standard of research is typically denoted as a RCT, followed by CCT or prospective studies. As evident through this scoping review, 64% of all the study records included three or fewer participants, and the median number of participants was three, indicating methods more consistent with SCED. SCEDs are exceedingly valuable within the field of ABA as they inform practitioners of the most effective methods and improve the delivery of ABA services (Tincani & Travers, 2019 ), in addition to facilitating innovation and detecting changes upon intervention (Smith, 2012 ). Specific attention can be given to measuring individual changes over time, across differing experimental conditions, in repeated conditions, and with other individuals in order to help establish validity (Perone, 2018 ). However, this type of study design may not measure statistical significance, lacks generalizability (Tincani & Travers, 2019 ), and does not assess long-term global effects (Smith, 2012 ). Although the overall positive results seen across all outcome measures may reflect the individualized impact of ABA, they may not reflect the more global changes or potential impacts on other children or youth with ASD that undergo the same treatment. In addition, many of these study records investigated specific skills, tasks, or responses that varied based on the child (Plavnick & Ferreri, 2011 ; Romaniuk et al., 2002 ), potentially making replication and generalization of the overall positive findings to the general population of children and youth with ASD difficult (Smith, 2012 ).
Few (6%) study records compared ABA interventions to control groups or other non-ABA interventions. Study records that did investigate ABA compared to a control group (typically TAU) or other intervention more often measured statistical significance, had larger sample sizes (Kamio et al., 2015 ; Koenig et al., 2010 ), and/or used validated measurement tools such as RDLS and BSID-R (Cohen et al., 2006 ; Eikeseth et al., 2002 ; Howard et al., 2005 ; Kovshoff et al., 2011 ; Remington et al., 2007 ). It is interesting that more recent meta-analyses have trended towards fewer statistically significant improvements than what has been previously reported (Reichow et al., 2018 ; Rodgers et al., 2020 ). The comparison records in the current review that did have large enough sample sizes to warrant a statistical analysis against a comparison group often did not find significance across all values or measurement tools used (Cohen et al., 2006 ). That said, a number of study records in the current review, some of which were also investigated by Reichow and colleagues (Cohen et al., 2006 ; Howard et al., 2014 ; Magiati et al., 2007 ; Remington et al., 2007 ), had comparison groups that differed to varying degrees from the treatment groups in terms of intensity, duration, location, or qualifications of intervention administrators, potentially raising questions about comparisons made between the groups (Reichow et al., 2018 ).
The current findings are also consistent with other publications with respect to the comparison of ABA techniques, as 225 of the study records investigated the efficacy of various ABA methods compared to one another. Another review found that approximately half of the comparison articles investigated found that one method was better than the other(s), and the other half of the sample indicated that the methods were equally effective (Shabani & Lam, 2013 ). Thus, this result indicated that only half of the comparisons analyzed truly contributed to the best practices of ABA (Shabani & Lam, 2013 ). In the current review, this was showcased through cognitive and language outcome measures, which found that only 38% and 37% of the comparison records, respectively, reported greater improvement with one method over the other. These investigations, often SCED, are undoubtedly important within the ABA field of research and to further analyze the effectiveness of one technique or method over another in order to optimize intervention strategies, particularly if rigorously designed (Lobo et al., 2017 ; Smith, 2012 ), or designed with an effort to assess and understand social validity (Snodgrass et al., 2021 ), but do not provide enough information on the overall effectiveness of ABA as a whole on the larger population of children and youth with ASD (Shabani & Lam, 2013 ).
Approximately 40% of the study records measured success in the given treatment through the assessment or attainment of some level of mastery or criterion for the desired skill or behavior (Grannan & Rehfeldt, 2012 ; Grow et al., 2011 ; Toussaint et al., 2016 ). Because study methods frequently continue until mastery or criterion in order to solidify behaviors and promote better maintenance (Luiselli et al., 2008 ; McDougale et al., 2020 ), positive improvements occur organically as subjects attain these desired measures. However, this may not accurately indicate the ability of a participant to maintain such a skill, particularly if the mastery criterion is low (McDougale et al., 2020 ; Richling et al., 2019 ). In some instances, criterion parameters and/or experimental procedures were altered in order to reach the desired measure (Charlop et al., 1985 ; Valentino et al., 2015 ). Thus, discretion should be taken when evaluating outcomes reliant on the mastery or extinction of skills or behaviors (McDougale et al., 2020 ). In addition, only 41% of the records conducted some form of investigation into follow-up or maintenance of the given outcome measure(s). This may not be reflective of the long-term effects of the overall positive outcomes. Likewise, generalization was only investigated in 31% of the study records, again prompting the question of whether or not these task- or behavior-specific improvements resulted in overall changes in the child’s skills, function, or behaviors. Further research may be required to assess retained changes rather than changes upon intervention (Bishop-Fitzpatrick et al., 2013 ; Smith, 2012 ).
In summary, the above results can be visualized through a filter of the study records (Fig. 5 ). Out of the 770 (100%) study records that were reviewed in depth, most showed positive results. When study records that used a method with a potential bias for positive results—such as those that compared one ABA treatment to another or assessed the mastery or criterion of a skill or behavior—were excluded, 361 (47%) study records remained. Furthermore, when study records that did not compare to a control or other intervention were excluded, 32 (4%) of the study records remained. These results may indicate gaps in the current ABA research approach, further supporting previous research about the standard of existing ABA literature (Reichow et al., 2018 ; Smith, 2012 ). These findings also support recommendations from Smith ( 2012 ), suggesting that RCTs comparing ABA to other interventions may be instrumental in evaluating both individual and global changes, as well as revising existing intervention models.
The limitations of the current scoping review are: (1) the broadness of the outcome measures investigated; (2) the potential confounding measure of generalization independently versus within a standardized scale; (3) the definition of ABA itself versus its many treatment derivatives; and (4) the continual development of the diagnostic tools used to assess ASD. Each of these will be described in turn below.
Many of the study records investigated specific tasks, responses, or skills. Thus, improvements in areas such as cognition may be misleading, because both improvements on specific tasks and improvements on full-scale cognitive assessments were scored as improvements in the cognitive outcome category (Grow et al., 2011 ; Howard et al., 2005 ). In addition, some of the outcome measures had considerable overlap in definitions, such as the cognition, language, social/communication, and adaptive behavior categories, thus potentially resulting in the coding of multiple outcome measures for a similar task. For example, receptive labeling tasks were coded under both cognitive and language outcome measures (Grow et al., 2011 ).
The infrequent use of generalization seen in the Between-Groups Comparison section could be a result of the greater use of validated tools in this section of records (Cohen et al., 2006 ; Remington et al., 2007 ). Measurement tools such as VABS incorporate measures of generalization into the scale, and though not often specified as an independent measure of generalization, multiple environmental locations for the interventions (e.g., home and school) or multiple individuals interacting with the participants may have been measured.
Given the length of time that ABA has been utilized in treating children with ASD, and its having become the basis for many intervention techniques, it can be difficult to discern whether a particular treatment follows all of the principles of ABA and to what extent. This was seen in a recent review investigating all available interventions for children and youth with ASD (Whitehouse et al., 2020 ). It may be difficult for families, governments, and policy makers to evaluate available evidence appropriately (Whitehouse et al., 2020 ). For example, PECS was developed utilizing ABA principles and is commonly used in conjunction with ABA therapy, but it is also used throughout speech and language therapy, education systems that are not solely ABA, and simply as a communication-based intervention (Howlin et al., 2007 ; Lerna et al., 2012 ; Pasco & Tohill, 2011 ). Even within the ABA field there are conflicting definitions of ABA between the research community and public sector (Schreibman et al., 2015 ), adding another layer of complexity for policy makers when it comes to deciding whether to fund specific programs, specific types of professionals, or a combination of both. For the same reason, there may be some treatments, methods or techniques that have not been included within this scoping review. Further, although the use of “applied behavior analysis” as a search term may not have captured the full extent of behavioral research, its inclusion as both a MeSH term and keyword will have returned any records indexed by the reviewed databases as “applied behavior analysis,” satisfying the initial search criteria for the current scoping review.
As the understood spectrum of ASD and the diagnostic tools for ASD have changed drastically over the decades in which the investigated articles were published, the represented population may have also changed throughout the years, potentially influencing the acceptability of study findings (Reichow et al., 2018 ). Furthermore, the initial objective for this scoping review included searching across all NDD/D, not just ASD. Thus, the ASD MeSH term of “autistic disorder and autism spectrum disorder” may have potentially resulted in missed studies that included only AS or PDD-NOS diagnoses. That said, as this review was intended to find the scope of the research surrounding the impact of ABA on children and youth with ASD over a time frame of 23 years and across all available research, the authors believe all of the applicable scope was covered within reason.
Recommendations for the further advancement in the field of ABA interventions for children and youth with ASD often include increasing the duration of the study, investigating comparisons to other non-ABA interventions, conducting follow-up studies for adults who participated in ABA interventions as children, and increasing the overall sample sizes. There has been an ongoing recommendation for larger scale studies over the last 20 years with respect to children and youth with ASD (Eldevik et al., 2009 ; Reichow et al., 2018 ; Smith, 2012 ), as well as for long-term outcomes for adults with ASD (Bishop-Fitzpatrick et al., 2013 ; Rodgers et al., 2020 ). With respect to EIBI in particular, there is increasing importance for large-scale studies comparing the effectiveness of EIBI against other non-ABA interventions, including developmental social pragmatic (DSP) interventions (Rodgers et al., 2020 ), which was also evident in the current review, as most comparison records that measured the effectiveness of EIBI compared their results to those of TAU or eclectic treatment approaches (90%; 9 out of 10 comparison records). Overall, although there are merits to both SCEDs and larger-scale group study designs (Lobo et al., 2017 ; Smith, 2012 ) there is a greater need for the latter when evaluating ABA. Our findings are in line with the perspective that ABA literature already has a wealth of SCEDs and is overdue for large scale studies such as RCTs to assess existing practices and, perhaps more importantly, to reevaluate and revise evolving ABA practices in the rapidly developing field of intervention for ASD (Smith, 2012 ).
An important note in terms of finding appropriate and effective interventions in the treatment for ASD, which is not limited to ABA, is the establishment of standards of care (SoC). Unfortunately, even though there is a wealth of knowledge regarding the assessment, diagnosis and treatment of ASD, there is still no clear SoC for the treatment of ASD (Department of Defense, 2019 , 2020 ). In general, outcome measures should indicate a true measure of benefit to the child and their family, in addition to providing relevance within practice and the ability to replicate across research (Rodgers et al., 2020 ). Recent studies have questioned outcome measures such as cognition and adaptive behaviors when evaluating ASD treatments, and a call for standardized outcome measures that are truly reflective of the benefit for the child and family is beginning to grow (Rodgers et al., 2020 ). Our recommendation is for more rigorous large-scale prospective comparison studies between ABA and emerging interventions, such as DSP interventions, to be conducted in order to develop gold standard treatment options with a defined SoC for children and families with ASD.
The results of the between-groups comparisons in this scoping review indicated that 23 comparison records compared intensive ABA (20–40 hr of intervention per week) to control or other interventions. Existing literature indicates that 30–40 intervention hours per week for children under the age of 6 results in greater improvements in cognition, language development, social skills, and more (Kovshoff et al., 2011 ; Reed et al., 2007b ). That said, more recent large-scale analyses on children who received 12 months of ABA services indicated that increased intensity does not necessarily predict better outcomes (Department of Defense, 2020 ). In a meta-analysis completed by Rodgers et al. ( 2020 ), autism symptoms showed no statistically significant improvements with higher intensity EIBI treatments as opposed to lower intensity EIBI treatments. It was also found that no one age group demonstrated improvement when correlated with the number of hours of rendered ABA services (Department of Defense, 2020 ). This evidence suggests there may be insufficient recent research justifying the need for high-intensity interventions, indicating that more research studies need to be conducted in the field of ABA in terms of assessing ABA impact with different or lower intensity interventions.
Most of the current literature surrounding ABA-based interventions lacks investigations into the QoL of children with ASD and instead focuses on aberrant behaviors (Reichow et al., 2018 ; Whitehouse et al., 2020 ). A recent meta-analysis found that, upon analyzing five articles of higher scientific credence, none conducted investigations into the changes with respect to QoL for the children or parents (Reichow et al., 2018 ). The present scoping review likewise found no occurrences of subject QoL measures in the sample analyzed. Overall changes in QoL for children living with ASD is of the utmost importance, as QoL is “individuals’ perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns” (WHO, 1997 , p. 1). The continued lack of research into long-term effectiveness of ABA treatments is an ongoing concern and should be a focus of future research to help measure QoL (Whitehouse et al., 2020 ) and also to investigate any possible adverse effects (Rodgers et al., 2020 ). For example, recent literature investigating adults with ASD who participated in ABA treatments when they were young has shown increases in incidences of posttraumatic stress disorder (PTSD); this is an emerging field of research in adults with ASD and should be further investigated through long-term studies (Kupferstein, 2018 ).
Future research into the cost-effectiveness of ABA-based interventions compared to existing and emerging interventions should be conducted, as only a few articles within the current review discussed the cost effectiveness of the ABA interventions in use (Farrell et al., 2005 ; Kamio et al., 2015 ; Magiati et al., 2007 ; Park et al., 2020 ). In the few incidences where cost-effectiveness was measured, the results varied. For example, one study found that higher ABA program cost was associated with lesser improvements in language development (Kamio et al., 2015 ), one reported higher costs for the Lovaas/ABA model program (Farrell et al., 2005 ), one found little difference in cost between nursery and ABA interventions (Magiati et al., 2007 ), whereas Park et al. ( 2020 ) found lower costs for their specific ABA model (Korean Advancement of Behavior Analysis [KAVBA]) children’s center as compared to other Comprehensive Application of Behavioral Analysis to Schooling (CABAS) centers. In conclusion, these long-term and intensive interventions should be further investigated with respect to their cost-effectiveness and overall improvements in QoL (Rodgers et al., 2020 ; Whitehouse et al., 2020 ).
As ever in the scientific process, interventions and treatments need consistent and replicative investigations under stringent protocols to ensure the continued efficacy and generalizability of a given intervention. According to the U.S. Department of Health and Human Services ( 1999 ), ABA is the gold standard treatment for ASD, and is funded almost exclusively across North America. The current scoping review spanning 770 study records showed positive and beneficial effects of ABA for children with ASD across seven outcome measures. However, only 32 (4%) assessed ABA impact, had a comparison group, and did not rely on mastery of specific skills to mark improvement.
Without ongoing research and the development of a SoC, governments and policy makers will not have the most up-to-date information that reflects ABA-based and other interventions in terms of the ever-changing landscape of diagnoses, modern technological advancements, changes within the intervention implementation, and measurement tools of treatment efficacy. One such example is the measure of subject QoL, which, as made evident by this scoping review, was not measured in any study record included, but is of utmost importance to truly indicate the overall long-term impact of ABA. Moreover, as the children and youth who participated in ABA-based and other interventions become adults, the long-lasting effects of these interventions should be investigated more thoroughly.
Therefore, large longitudinal prospective studies comparing ABA-based and different interventions treating children and youth with ASD are needed. As ABA is historically based on an operant conditioning approach to treatment whereas many emerging interventions typically use a social pragmatic approach (Whitehouse et al., 2020 ), continued research comparing these two differing ideologies is particularly important, as ABA is currently the bar to which other interventions are held at the governmental level. With a holistic view of all of the scientific evidence behind ABA, governments will be able to more accurately compare any existing and emerging interventions to the well-established norm of ABA. Until a SoC is established, all interventions for children and youth with ASD must be held to the existing standard set by ABA to be considered effective.
Not applicable.
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This scoping review would not be possible without the help of the people who took the time to move this project forward. We thank Jonathan Agyeman for his assistance in the data analysis, synthesis, and creation of tables and figures following the search update and subsequent revisions. For his detailed refinements during the final stage of our submission, we thank our copy editor, Henry Sporn. We also thank Jake Choi, Sam Brimacombe, Ciara McDaniel, Elizabeth Steczko, and Kristyn Jorgenson for their hard work and contributions with the initial search phase, publication screening, and journal extractions. Likewise, thank you to Alesia DiCicco, and Zachary Betts for their contributions to journal extractions. For their contributions in cleaning publication information for referencing, a special thank you to Sophia Shalchy-Tabrizi, Jodiline Lacsamana, Ghazaleh Bazazan Nowghani, and finally Madeleine Teasell, who also assisted with extractions and numerous revisions throughout the project. We would also thank Alison Davidson and Suk Chan Oh with their help in the initial search and screening; we further thank Alison for her keen eye in proofreading, and Kelley Lloyd-Jones for her perspective as a Behavior Consultant. Last but not least, we give a heartfelt thank-you to Dr. Patrick Myers for taking the time to review our work. His expert feedback was invaluable in completing this vast project.
Research was supported by Club Aviva Recreation Ltd.
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Mojgan Gitimoghaddam
Club Aviva Recreation Ltd., Coquitlam, British Columbia, Canada
Natalia Chichkine, Laura McArthur, Sarabjit S. Sangha & Vivien Symington
University of Melbourne Faculty of Medicine, Dentistry and Health Sciences, Melbourne, Australia
Sarabjit S. Sangha
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Mojgan Gitimoghaddam, MD, PhD(c), led and designed the project, wrote and reviewed the article; Natalia Chichkine, BSc, collected data, extracted and coded data, and wrote and reviewed the article; Laura McArthur, BSc, collected data, extracted and coded data, and wrote and reviewed the article; Sarabjit S. Sangha, MSc, coded data, contributed data or analysis tools, assisted with analysis, and wrote and reviewed the article; and Vivien Symington, BA/BPHE, conceived and designed the analysis, extracted and coded data, and wrote and reviewed the article.
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Gitimoghaddam, M., Chichkine, N., McArthur, L. et al. Applied Behavior Analysis in Children and Youth with Autism Spectrum Disorders: A Scoping Review. Perspect Behav Sci 45 , 521–557 (2022). https://doi.org/10.1007/s40614-022-00338-x
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Accepted : 21 April 2022
Published : 18 May 2022
Issue Date : September 2022
DOI : https://doi.org/10.1007/s40614-022-00338-x
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Autism can be defined as a spectral disorder that makes a child seem to have a world of their own. Many parents misinterpret this disorder and assume that the child does not notice them. However, this is usually not the case. Parents are the first people to notice this disorder. With more children being diagnosed with this disorder, educators ...
Exploring Autism in the Drama Film Rain Man. Charlie Babbitt, the brother to Raymond, is the actor who portrays Raymond's autism on the way to Los Angeles to secure his fair share in the Babbitt's $3 million fortunes in form of inheritance. We will write a custom essay specifically for you by our professional experts.
Autist Students Identification: Distinctive Features of Autism. In identifying autism, there is the triad of autism which consists of autistic aloneness; speech and language disorder, and obsessive desire for sameness. Genetics and Autism Development. Autism is associated with a person's genetic makeup.
Prominent public figures that lived with autism for years. The impact of maternal age on autism. Asperger's syndrome and autism- An explorative study. Analyzing the genome's dark regions and their effect on autism mutation. Gene expression control and its impact on autism mutation.
Autism Research is an international journal which publishes research relevant to Autism Spectrum Disorder (ASD) and closely related neurodevelopmental disorders. ... theoretical papers, clinical trials, and more. The journal is co-owned and supported by The International Society for Autism Research (INSAR) and Wiley. ... Related Titles LATEST ...
Advances in autism research, 2021: continuing to decipher the secrets of autism. 1427. trimester average and maximal daily exposure to ne air. fi. particulate matter of diameter ≤2.5 μm (PM2.5 ...
Autism is a major, peer-reviewed, international journal, published 8 times a year, publishing research of direct and practical relevance to help improve the quality of life for individuals with autism or autism-related disorders. It is interdisciplinary in nature, focusing on research in many areas, including: intervention; diagnosis; training; education; translational issues related to ...
Lauren M Little. Winnie Dunn. Scott Tomchek. Preview abstract. Restricted access Research article First published March 3, 2024 pp. 2140-2145. xml Get Access. Table of contents for Autism, 28, 8, Aug 01, 2024.
In late 2001-early 2002 we received four exciting papers with findings on the genetics of autism that were published together in our March 2002 issue, with an accompanying editorial [2,3,4,5,6].
Take a look at these excellent autism research analysis paper topics: Analyze Asperger's syndrome. Analyze the Rett syndrome. Analyze the childhood disintegrative disorder. Analyze Kanner's syndrome. Analyze the pervasive developmental disorder. Discuss the unusual interest in objects characteristic. Discuss the overreaction to touch.
About the journal. Research in Autism Spectrum Disorders (RASD) publishes high quality empirical articles and reviews that contribute to a better understanding of Autism Spectrum Disorders (ASD) at all levels of description; genetic, neurobiological, cognitive, and behavioral. The primary focus of the journal is to …. View full aims & scope.
Abstract. Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication and the presence of restricted interests and repetitive behaviors. There have been recent concerns about increased prevalence, and this article seeks to elaborate on factors that may influence prevalence rates, including ...
Autism Research is an ideal venue to publish your most exciting results. As one indication of the impact of papers published in the journal, there were 333,701 full-text downloads of articles in 2019. The five countries with the largest number of downloads are The United States, The United Kingdom, China, Australia, and Canada.
Several key issues have emerged in relation to research, clinical and sociological aspects of autism. Shifts in research focus to encompass the massive heterogeneity covered under the label and appreciation that autism rarely exists in a diagnostic vacuum have brought about new questions and challenges. Diagnostic changes, increasing moves ...
Autism Research is an international journal which publishes research relevant to Autism Spectrum Disorder (ASD) and closely related neurodevelopmental disorders. ... theoretical papers, clinical trials, and more. The journal is co-owned and supported by The International Society for Autism Research (INSAR) and Wiley. ... Related Titles LATEST ...
INTRODUCTION. Autism (or autism spectrum disorders, ASD) is defined on the basis of social and communication problems and repetitive and restrictive behaviors that can vary in individuals along a continuum of severity (Lord et al., 2018).A diagnosis of autism can be made as early as 18-24 months of age; it is around this age that characteristic symptoms can be distinguished from typical ...
People with intellectual disability are underrepresented and often actively excluded from autism research. A better understanding of autism requires inclusive research approaches that accurately ...
Abstract. Autism is a neuropsychiatric disorder characterised by severe and sustained impairment in social interaction, deviance in communication, and patterns of behaviour and interest that are ...
Applied Behavior Analysis. At its core, ABA is the practice of utilizing the psychological principles of learning theory to enact change on the behaviors seen commonly in individuals diagnosed with ASD (Lovaas et al., 1974).Ole Ivar Lovaas produced a method based on the principles of B. F. Skinner's theory of operant conditioning in the 1970s to help treat children diagnosed with ASD (or ...
The following case studies present three different children with ASD and describe the SLP's strategies to enhance communication and quality of life. The three case studies demonstrate various options in AAC intervention that can be used by children of different ages. —Ann-Mari Pierotti, MS, CCC-SLP. Case Study 1: Anderson | Case Study 2 ...
Autism. Pages: 7 Words: 2247. Autism is a disorder that starts early in the childhood and stays until adulthood. It has now been known that many conditions are considered co morbid to autism spectrum disorders. These conditions are variable but some of the most common ones include fragile X syndrome and epilepsy.
Introduction. Autism spectrum disorder (ASD) refers to a group of early-onset, lifelong, heterogeneous neurodevelopmental conditions with complex mechanisms of emergence ().The prevalence of ASD has increased from 1 in 69 by 2012 to 1 in 44 by 2018, as reported by the Centers for Disease Control and Prevention for 2012-2018 (2, 3).Recent research estimates the male-to-female ratio is closer ...
End with a period. In this title, only the words Social and A are capitalized. Example: Atteberry-Ash, B. (2022). Social work and social justice: A conceptual review. For the last component, you need the source. For an article, this is the title of the journal, volume, issue, which is sometimes called number, and page numbers of the article ...
This manuscript provides a comprehensive overview of the impact of applied behavior analysis (ABA) on children and youth with autism spectrum disorders (ASD). Seven online databases and identified systematic reviews were searched for published, peer-reviewed, English-language studies examining the impact of ABA on health outcomes. Measured outcomes were classified into eight categories ...
Despite an increasing number of studies which examine the interplay between autism and offending mechanisms, there has been a lack of research investigating the interplay between autism and stalking. It was anticipated that findings from this investigation would inform future interventions with individuals with autism who stalk. This secondary data analysis research used a qualitative case ...