Diagnosis Of Autism Research Articles

Typy zaburzeń językowych w zespole Aspergera

For many years, both the DSM‑IV and ICD-10 have built up the misconception that there are no language disorders in Asperger’s syndrome. This has had a significant impact on the problems with the diagnosis of Asperger syndrome, and has been the cause of many misdiagnoses. The current editions: DSM-5 and ICD-11 have not changed the established approach. Many years of research and clinical experience have allowed the author of this article to verify the view of normal speech and communication development in Asperger syndrome. We now know that children with ZA may manifest different types of disorders, concerning both systemic and communicative competence. The author of the article characterises the types of language problems observed in ZA, including: the specificity of early speech development, alalia (delayed speech development), aphasia, comprehension of speech and intonation of speech and indicates their sources and examples. This is of great importance in the context of the correct diagnosis and therapy of children on the autism spectrum, including the differential diagnosis of autism and Asperger syndrome.

An Updated Guide to Autism Screening: A Primer for Nurse Practitioners

Research indicates that children with autism experience gains in cognitive, linguistic, and behavioral functioning when recipients of early identification and intervention. Although there has been a significant increase in autism identification, it appears that there is a general hesitancy to conduct standardized screenings for autism in a pediatric health care clinics. The available data suggest that there is an extensive delay between when parents first report developmental concerns to when a child is finally evaluated and receives a formal autism diagnosis. To help meet the developmental needs of children, practitioners should regularly screen for the early signs of autism.

Impact of Receiving Genetic Diagnoses on Parents' Perceptions of Their Children with Autism and Intellectual Disability.

To assess whether genetic test results identifying the cause of a child's autism, when accompanied by other neurodevelopmental disorders (NDD), including intellectual disability, alter how parents perceive and treat their child. 28 parents of 22 individuals with autism (mean age: 15years), usually with other NDDs, were interviewed after receiving genetic diagnoses indicating a de novo mutation through the Simons Foundation Powering Autism Research for Knowledge study. Diagnosis of a de novo genetic variant can alter parental perceptions of offspring with autism and other NDDs. Parents often blamed their child less, saw their child as less in control of symptoms, and developed more patience, framing expectations accordingly. Parents had mixed feelings about receiving genetic diagnoses, with sadness sometimes accompanying reframed expectations. Genetic diagnoses could change views of the child among extended family members, teachers, social service agencies, insurers, and broader communities and society. Genetic testing might also reduce delays in diagnoses of autism among African American, Latino and other children. These data, the first to examine several critical aspects of how parents and others view children with autism and other NDDs after receiving genetic diagnoses, highlight vital needs for education of multiple stakeholders (including geneticists, other physicians, genetic counselors, parents, individuals with autism, social service agencies, insurers, policymakers, and the broader public), research (to include perspectives of extended family members, insurers, social service agencies and teachers) and practice (to increase recognition and awareness of the potential benefits and effects of genetic testing for such children).

If I were a Teacher… - Cogitations of People on the Autism Spectrum About the Teacher’s Vision

This article is part of a broader study on adults with autism. The main assumption of the series of studies is concerned with listening to and hearing the voices of those most affected - those with a diagnosis of autism. The collected material, which is based on our own experiences of people with autism, allows us to present views on the teacher’s role- the educational space’s creator. Thus far, we have introduced the experiences and comments of teachers and therapists; now, we can listen to the voices of students, parents, and people with autism. This study employed the netnographic method. The study involved a group of people diagnosed with autism, and a meeting closed online for those who agreed to participate. Reaching out to a large group made it possible to analyze the results of the statements given by ranking and creating meaning bundles. Furthermore, by differentiating according to age and gender, it became possible to conduct a deeper qualitative analysis concerning specific statements that seem representative of this group of people. The first conclusion is that the approach to the teaching/learning process differs. This is due to symptoms that are specific to autism, as well as the different educational and therapeutic approaches. The second is related to the use of punishment that, in addition to the forbidden ones (such as physical), often evolve into psychological and social punishments, such as isolation, marginalization, or a lack of interest. It seems equally important to draw attention to the ineffective attempts to impose (often referred to as violating) recognized normative forms of functioning and the treatment of these people as not fully intellectually capable, which is not a condition. Purpose of the research. The research aims to present the educational reality described by the people who are the most concerned in this study, i.e., those who have been diagnosed with autism at various stages in their lives.

Testing the social motivation theory of autism: the role of co-occurring anxiety.

The Social Motivation Theory proposes that social reward processing differences underlie autism. However, low social motivation has also been linked to higher anxiety. Given the co-occurrence between autism and anxiety, it is possible that anxiety drives the association between social motivation and autistic characteristics. This study tests the mechanisms underlying the association between social motivation and autistic traits. Participants were 165 adolescents (71 male), aged 10-16 years, from the Mapping profiles of cognition, motivation and attention in childhood (C-MAPS) study, enriched for autistic traits (70 participants with an autism diagnosis, 37 male). Participants completed a battery of online experimental tasks, including a Choose-a-Movie social motivation task and social cognition measures (theory of mind; emotion recognition), alongside parent-reported child anxiety and autistic traits. Higher social motivation was significantly associated with lower autistic traits (β = -.26, p < .001). Controlling for social cognition did not change the association between social motivation and autistic traits. Controlling for anxiety did significantly reduce the strength of the association (unstandardized coefficient change: p = .003), although social motivation remained associated with autistic traits (β = -.16, p = .004). Post hoc analyses demonstrated differential sex-effects: The association between social motivation and autistic traits was significant only in the females (β = -.38, p < .001), as was the attenuation by anxiety (unstandardized coefficient change: p < .001). The association between social motivation and autistic traits could be partially attributed to co-occurring anxiety. Sex-specific effects found in females may be due to environmental factors such as increased social demands in adolescent female relationships. Results are consistent with self-report by autistic individuals who do not identify as having reduced social motivation.

Differentiation of the clinical diagnoses of autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD) and post-traumatic stress disorder (PTSD)

Introduction and objective: The aim of the presented research was to analyse the differentiation of clinical diagnoses of autism spectrum disorder, attention-deficit/hyperactivity disorder and post-traumatic stress disorder with the use of diagnostic tools. Materials and methods: The study involved 110 carers of 2–10-olds, patients of a psychiatric treatment ward. Medical records were assessed for the diagnosis obtained by the child in the course of treatment, then parents were interviewed. The usefulness of individual methods for differentiating clinical diagnoses of autism, Asperger’s syndrome, attention-deficit/hyperactivity disorder and post-traumatic stress disorder was assessed using ROC (receiver operating characteristic) curves. Results: In many cases, the diagnoses obtained by the children were found to be different from those indicated by the tools. In addition, the tools themselves were in some cases found to be ineffective in diagnosing the disorder for which they were designed. The analyses also showed that crisis experiences can moderate the symptoms observed in children, thus influencing the diagnosis and the clinical picture. Conclusions: The presented analyses confirmed the thesis that the differential diagnosis of children is not an easy task, and that a potentially traumatic factor can affect the clinical picture of a disorder, as well as be its cause. The issues of unreliability of some tools used in the diagnosis and/or their inconsistency with the diagnoses obtained in the course of treatment were also found to be significant.

Engaging with autistic children and their families: Strategies for effective partnerships

Background: Autism diagnoses for children are becoming more commonplace due to greater understanding and insight concerning neurodiversity and an increased awareness of the importance of inclusion. Consequently, greater numbers of health and social care professionals, educators and practitioners in the community are more likely to find themselves supporting autistic children and their families. Understanding the needs, wishes and hopes of families who you interact with will enable you to plan your professional response to their needs more effectively.&#x0D; Target audience: This presentation is intended for professionals responsible for supporting autistic children and their families within clinical, residential or community settings, in addition to those working in education settings. This presentation will explore the needs of autistic children and their families when they present at appointments or for services, and how you as the professional can make the most positive impact through your interactions.&#x0D; Key messages: Supporting parents to support their children has fast become the mantra of disability support services here in Ireland. But what do parents universally really need from professionals to truly empower and enable them to support their autistic child?&#x0D; A partnership approach between professionals and parents is instrumental in promoting more positive outcomes for autistic children. Yet what parents need more than anything else when they meet you is hope. They need to feel listened to, that their worries and concerns have been heard and they need to have hope that things can improve for their child and their family. You may not always be in a position to provide the level of service an autistic child truly needs. You can however maximise the effectiveness of your intervention with their family by establishing and developing good working relationships with their parents.&#x0D; Learning outcomes: This presentation will provide you with strategies and tangible methods of supporting autistic children, via enabling and empowering parents. Actual case studies will be provided to demonstrate to attendees the effectiveness of active listening, being present and creating a space of hope, within interactions with parents. Examples of both effective and non-effective ways of engaging families will be presented, to maximise understanding and enhance positive outcomes.&#x0D; &#x0D;

Validation of plasma protein glycation and oxidation biomarkers for the diagnosis of autism

Autism Spectrum Disorder (ASD) is a common neurodevelopmental disorder in children. It is currently diagnosed by behaviour-based assessments made by observation and interview. In 2018 we reported a discovery study of a blood biomarker diagnostic test for ASD based on a combination of four plasma protein glycation and oxidation adducts. The test had 88% accuracy in children 5–12 years old. Herein, we present an international multicenter clinical validation study (N = 478) with application of similar biomarkers to a wider age range of 1.5–12 years old children. Three hundred and eleven children with ASD (247 male, 64 female; age 5.2 ± 3.0 years) and 167 children with typical development (94 male, 73 female; 4.9 ± 2.4 years) were recruited for this study at Sidra Medicine and Hamad Medical Corporation hospitals, Qatar, and Hospital Regional Universitario de Málaga, Spain. For subjects 5–12 years old, the diagnostic algorithm with features, advanced glycation endproducts (AGEs)—Nε-carboxymethyl-lysine (CML), Nω-carboxymethylarginine (CMA) and 3-deoxyglucosone-derived hydroimidazolone (3DG-H), and oxidative damage marker, o,o’-dityrosine (DT), age and gender had accuracy 83% (CI 79 – 89%), sensitivity 94% (CI 90–98%), specificity 67% (CI 57–76%) and area-under-the-curve of receiver operating characteristic plot (AUROC) 0.87 (CI 0.84–0.90). Inclusion of additional plasma protein glycation and oxidation adducts increased the specificity to 74%. An algorithm with 12 plasma protein glycation and oxidation adduct features was optimum for children of 1.5–12 years old: accuracy 74% (CI 70–79%), sensitivity 75% (CI 63–87%), specificity 74% (CI 58–90%) and AUROC 0.79 (CI 0.74–0.84). We conclude that ASD diagnosis may be supported using an algorithm with features of plasma protein CML, CMA, 3DG-H and DT in 5–12 years-old children, and an algorithm with additional features applicable for ASD screening in younger children. ASD severity, as assessed by ADOS-2 score, correlated positively with plasma protein glycation adducts derived from methylglyoxal, hydroimidazolone MG-H1 and Nε(1-carboxyethyl)lysine (CEL). The successful validation herein may indicate that the algorithm modifiable features are mechanistic risk markers linking ASD to increased lipid peroxidation, neuronal plasticity and proteotoxic stress.

Language-assisted deep learning for autistic behaviors recognition

Correctly recognizing the behaviors of children with Autism Spectrum Disorder (ASD) is of vital importance for the diagnosis of Autism and timely early intervention. However, the observation and recording during the treatment from the parents of autistic children may not be accurate and objective. In such cases, automatic recognition systems based on computer vision and machine learning (in particular deep learning) technology can alleviate this issue to a large extent. Existing human action recognition models can now achieve impressive performance on challenging activity datasets, e.g., daily activity, and sports activity. However, problem behaviors in children with ASD are very different from these general activities, and recognizing these problem behaviors via computer vision is less studied. In this paper, we first evaluate a strong baseline for action recognition, i.e., Video Swin Transformer, on two autism behaviors datasets (SSBD and ESBD) and show that it can achieve high accuracy and outperform the previous methods by a large margin, demonstrating the feasibility of vision-based problem behaviors recognition. Moreover, we propose language-assisted training to further enhance the action recognition performance. Specifically, we develop a two-branch multimodal deep learning framework by incorporating the ”freely available” language description for each type of problem behavior. Experimental results demonstrate that incorporating additional language supervision can bring an obvious performance boost for the autism problem behaviors recognition task as compared to using the video information only (i.e., 3.49% improvement on ESBD and 1.46% on SSBD). Our code and model will be publicly available for reproducing the results.

Revisiting the ownership effect in adults with and without autism.

Self-owned items are better remembered than other-owned items; this ownership effect reflects privileged processing of self-related information. The size of this ownership effect has been shown to decrease in neurotypical adults as the number of autistic traits increases, and is reduced in autistic adults. However, emerging evidence has questioned the reliability of these findings. This paper aimed to replicate previous work using well-powered, pre-registered designs, and Bayesian analyses. Experiment 1 (N = 100) found a significant ownership effect in neurotypical adults; however, the size of this was unrelated to individual differences in autistic traits. Experiment 2 (N = 56) found an ownership effect in neurotypical but not autistic adults. The findings suggest that individual differences in autistic traits in the neurotypical population do not impact the ownership effect, but a clinical diagnosis of autism might. We discuss how these findings can be explained by differences in psychological self-awareness in autism.

Wearable Biosensing to Predict Imminent Aggressive Behavior in Psychiatric Inpatient Youths With Autism

Aggressive behavior is a prevalent and challenging issue in individuals with autism. To investigate whether changes in peripheral physiology recorded by a wearable biosensor and machine learning can be used to predict imminent aggressive behavior before it occurs in inpatient youths with autism. This noninterventional prognostic study used data collected from March 2019 to March 2020 from 4 primary care psychiatric inpatient hospitals. Enrolled participants were 86 psychiatric inpatients with confirmed diagnoses of autism exhibiting operationally defined self-injurious behavior, emotion dysregulation, or aggression toward others; 16 individuals were not included (18.6%) because they would not wear the biosensor (8 individuals) or were discharged before an observation could be made (8 individuals). Data were analyzed from March 2020 through October 2023. Research staff performed live behavioral coding of aggressive behavior while inpatient study participants wore a commercially available biosensor that recorded peripheral physiological signals (cardiovascular activity, electrodermal activity, and motion). Logistic regression, support vector machines, neural networks, and domain adaptation were used to analyze time-series features extracted from biosensor data. Area under the receiver operating characteristic curve (AUROC) values were used to evaluate the performance of population- and person-dependent models. There were 70 study participants (mean [range; SD] age, 11.9 [5-19; 3.5] years; 62 males [88.6%]; 1 Asian [1.4%], 5 Black [7.1%], 1 Native Hawaiian or Other Pacific Islander [1.4%], and 63 White [90.0%]; 5 Hispanic [7.5%] and 62 non-Hispanic [92.5%] among 67 individuals with ethnicity data). Nearly half of the population (32 individuals [45.7%]) was minimally verbal, and 30 individuals (42.8%) had an intellectual disability. Participant length of inpatient hospital stay ranged from 8 to 201 days, and the mean (SD) length was 37.28 (33.95) days. A total of 429 naturalistic observational coding sessions were recorded, totaling 497 hours, wherein 6665 aggressive behaviors were documented, including self-injury (3983 behaviors [59.8%]), emotion dysregulation (2063 behaviors [31.0%]), and aggression toward others (619 behaviors [9.3%]). Logistic regression was the best-performing overall classifier across all experiments; for example, it predicted aggressive behavior 3 minutes before onset with a mean AUROC of 0.80 (95% CI, 0.79-0.81). This study replicated and extended previous findings suggesting that machine learning analyses of preceding changes in peripheral physiology may be used to predict imminent aggressive behaviors before they occur in inpatient youths with autism. Further research will explore clinical implications and the potential for personalized interventions.

Strategic social decision making undergoes significant changes in typically developing and autistic early adolescents.

Information sampling about others' trustworthiness prior to cooperation allows humans to minimize the risk of exploitation. Here, we examined whether early adolescence or preadolescence, a stage defined as in between childhood and adolescence, is a significant developmental period for strategic social decisions. We also sought to characterize differences between autistic children and their typically developing (TD) peers. TD (N=48) and autistic (N=56) 8- to 12-year-olds played an online information sampling trust game. While both groups adapted their information sampling and cooperation to the various trustworthiness levels of the trustees, groups differed in how age and social skills modulated task behavior. In the TD group social skills were a stronger overall predictor of task behavior. In the autistic group, age was a stronger predictor and interacted with social skills. Computational modeling revealed that both groups used the same heuristic information sampling strategy-albeit older TD children were more efficient as reflected by decreasing decision noise with age. Autistic children had lower prior beliefs about the trustee's trustworthiness compared to TD children. These lower priors indicate that children believed the trustees to be less trustworthy. Lower priors scaled with lower social skills across groups. Notably, groups did not differ in prior uncertainty, meaning that the priors of TD and autistic children were equally strong. Taken together, we found significant development in information sampling and cooperation in early adolescence and nuanced differences between TD and autistic children. Our study highlights the importance of deep phenotyping of children including clinical measures, behavioral experiments and computational modeling. RESEARCH HIGHLIGHTS: We specified how early adolescents with and without an autism diagnosis sampled information about their interaction partners and made cooperation decisions in a strategic game. Early adolescence is a significant developmental period for strategic decision making, marked by significant changes in information sampling efficiency and adaptivity to the partner's behavior. Autistic and non-autistic groups differed in how age and social skills modulated task behavior; in non-autistic children behavior was more indicative of overall social skills. Computational modeling revealed differences between autistic and non-autistic groups in their initial beliefs about cooperation partners; autistic children expected their partners to be less trustworthy.

Enlarged Perivascular Spaces in Infancy and Autism Diagnosis, Cerebrospinal Fluid Volume, and Later Sleep Problems

Perivascular spaces (PVS) and cerebrospinal fluid (CSF) are essential components of the glymphatic system, regulating brain homeostasis and clearing neural waste throughout the lifespan. Enlarged PVS have been implicated in neurological disorders and sleep problems in adults, and excessive CSF volume has been reported in infants who develop autism. Enlarged PVS have not been sufficiently studied longitudinally in infancy or in relation to autism outcomes or CSF volume. To examine whether enlarged PVS are more prevalent in infants who develop autism compared with controls and whether they are associated with trajectories of extra-axial CSF volume (EA-CSF) and sleep problems in later childhood. This prospective, longitudinal cohort study used data from the Infant Brain Imaging Study. Magnetic resonance images were acquired at ages 6, 12, and 24 months (2007-2017), with sleep questionnaires performed between ages 7 and 12 years (starting in 2018). Data were collected at 4 sites in North Carolina, Missouri, Pennsylvania, and Washington. Data were analyzed from March 2021 through August 2022. PVS (ie, fluid-filled channels that surround blood vessels in the brain) that are enlarged (ie, visible on magnetic resonance imaging). Outcomes of interest were enlarged PVS and EA-CSF volume from 6 to 24 months, autism diagnosis at 24 months, sleep problems between ages 7 and 12 years. A total of 311 infants (197 [63.3%] male) were included: 47 infants at high familial likelihood for autism (ie, having an older sibling with autism) who were diagnosed with autism at age 24 months, 180 high likelihood infants not diagnosed with autism, and 84 low likelihood control infants not diagnosed with autism. Sleep measures at school-age were available for 109 participants. Of infants who developed autism, 21 (44.7%) had enlarged PVS at 24 months compared with 48 infants (26.7%) in the high likelihood but no autism diagnosis group (P = .02) and 22 infants in the control group (26.2%) (P = .03). Across all groups, enlarged PVS at 24 months was associated with greater EA-CSF volume from ages 6 to 24 months (β = 4.64; 95% CI, 0.58-8.72; P = .002) and more frequent night wakings at school-age (F = 7.76; η2 = 0.08; P = .006). These findings suggest that enlarged PVS emerged between ages 12 and 24 months in infants who developed autism. These results add to a growing body of evidence that, along with excessive CSF volume and sleep dysfunction, the glymphatic system could be dysregulated in infants who develop autism.

Exploring the autism “diagnostic odyssey” in the Greater Accra region of Ghana

Introduction: Despite the increasing global prevalence of autism spectrum disorders (ASD), there is limited information about ASD in Africa. Existing research on ASD in Africa shows that autistic children are diagnosed relatively late or not at all. The purpose of this study was to understand the barriers to an autism diagnosis and to engage key stakeholders to action plan steps to reduce the barriers. Methods: We conducted a participatory, mixed methods study using semi-structured interviews, a survey, photo elicitation, and focus groups with 11 participants (four parents and seven health professionals) in the Greater Accra region of Ghana. Findings: Neuro-paediatricians in our study reported that it takes, on average, two to six visits over two weeks to two years or more to diagnose a child. Our thematic qualitative analysis yielded three overarching themes, with barriers and facilitators for each: 1) Systemic, 2) Community, and 3) Parent/Family factors that influence the diagnostic process. The action plan of our stakeholder focus group prioritizes community education to dispel myths and encourage autism acceptance within the Ghanaian community. Conclusion: Knowledge about the diagnostic odyssey can help facilitate early diagnosis and intervention. Implications for practice This research study confirmed known challenges to the autism diagnostic process. It contributed nuanced insights into the role of culture, the importance of education, and the need for community involvement in improving the diagnostic process, early occupational therapy intervention, and autism acceptance within the community.

Computer-aided autism diagnosis using visual attention models and eye-tracking: replication and improvement proposal

BackgroundAutism Spectrum Disorder (ASD) diagnosis can be aided by approaches based on eye-tracking signals. Recently, the feasibility of building Visual Attention Models (VAMs) from features extracted from visual stimuli and their use for classifying cases and controls has been demonstrated using Neural Networks and Support Vector Machines. The present work has three aims: 1) to evaluate whether the trained classifier from the previous study was generalist enough to classify new samples with a new stimulus; 2) to replicate the previously approach to train a new classifier with a new dataset; 3) to evaluate the performance of classifiers obtained by a new classification algorithm (Random Forest) using the previous and the current datasets.MethodsThe previously approach was replicated with a new stimulus and new sample, 44 from the Typical Development group and 33 from the ASD group. After the replication, Random Forest classifier was tested to substitute Neural Networks algorithm.ResultsThe test with the trained classifier reached an AUC of 0.56, suggesting that the trained classifier requires retraining of the VAMs when changing the stimulus. The replication results reached an AUC of 0.71, indicating the potential of generalization of the approach for aiding ASD diagnosis, as long as the stimulus is similar to the originally proposed. The results achieved with Random Forest were superior to those achieved with the original approach, with an average AUC of 0.95 for the previous dataset and 0.74 for the new dataset.ConclusionIn summary, the results of the replication experiment were satisfactory, which suggests the robustness of the approach and the VAM-based approaches feasibility to aid in ASD diagnosis. The proposed method change improved the classification performance. Some limitations are discussed and additional studies are encouraged to test other conditions and scenarios.

Towards an accurate autism spectrum disorder diagnosis: multiple connectome views from fMRI data.

Functional connectome has revealed remarkable potential in the diagnosis of neurological disorders, e.g. autism spectrum disorder. However, existing studies have primarily focused on a single connectivity pattern, such as full correlation, partial correlation, or causality. Such an approach fails in discovering the potential complementary topology information of FCNs at different connection patterns, resulting in lower diagnostic performance. Consequently, toward an accurate autism spectrum disorder diagnosis, a straightforward ambition is to combine the multiple connectivity patterns for the diagnosis of neurological disorders. To this end, we conduct functional magnetic resonance imaging data to construct multiple brain networks with different connectivity patterns and employ kernel combination techniques to fuse information from different brain connectivity patterns for autism diagnosis. To verify the effectiveness of our approach, we assess the performance of the proposed method on the Autism Brain Imaging Data Exchange dataset for diagnosing autism spectrum disorder. The experimental findings demonstrate that our method achieves precise autism spectrum disorder diagnosis with exceptional accuracy (91.30%), sensitivity (91.48%), and specificity (91.11%).

Pre-autism: What a paediatrician should know about early diagnosis of autism‎.

Autism, also known as an autism spectrum disorder, is a complex neurodevelopmental disorder usually diagnosed in the first three years of a child's life. A range of symptoms characterizes it and can be diagnosed at any age, including adolescence and adulthood. However, early diagnosis is crucial for effective management, prognosis, and care. Unfortunately, there are no established fetal, prenatal, or newborn screening programs for autism, making early detection difficult. This review aims to shed light on the early detection of autism prenatally, natally, and early in life, during a stage we call as "pre-autism" when typical symptoms are not yet apparent. Some fetal, neonatal, and infant biomarkers may predict an increased risk of autism in the coming baby. By developing a biomarker array, we can create an objective diagnostic tool to diagnose and rank the severity of autism for each patient. These biomarkers could be genetic, immunological, hormonal, metabolic, amino acids, acute phase reactants, neonatal brainstem function biophysical activity, behavioral profile, body measurements, or radiological markers. However, every biomarker has its accuracy and limitations. Several factors can make early detection of autism a real challenge. To improve early detection, we need to overcome various challenges, such as raising community awareness of early signs of autism, improving access to diagnostic tools, reducing the stigma attached to the diagnosis of autism, and addressing various culturally sensitive concepts related to the disorder.

The use of strengths-based approaches, Personal Construct Psychology (PCP) techniques and psychoeducation about autism with an adolescent in a post-primary school context in the Republic of Ireland: A practitioner report

This intervention case study is written by an Educational and Child Psychologist in the Republic of Ireland, which took place with Leah, a 15-year-old adolescent with a diagnosis of autism attending a post-primary school. Pre- and post-intervention assessment measures included the Strengths and Difficulties Questionnaire (SDQ) and the Rosenberg Self-Esteem Scale (RSE). An individualised intervention plan was designed, focussing on promoting Leah’s self-esteem, as well as her understanding of autism. Therapeutic techniques used throughout the six-session intervention involved strengths-based and Personal Construct Psychology (PCP) approaches, alongside psychoeducation about autism. Leah’s post-intervention scores on the SDQ showed slight improvements in emotional problems and conduct problems following the intervention, while her scores on the RSE demonstrated a significant improvement in self-esteem from pre- to post-intervention. The case outcomes support the adoption of individualised strengths-based approaches and PCP techniques to promote self-esteem, as well as psychoeducation about autism to promote understanding and self-acceptance.

Reduction in Retinal Ganglion Cell Layer, Inner Plexiform Layer, and Choroidal Thickness in Children With Autism Spectrum Disorder.

The aim of this study was to evaluate the retinal nerve fiber layer (RNFL), choroidal layer, inner plexiform layer (IPL), and ganglion cell layer (GCL) in patients with autism spectrum disorder (ASD). In this study, we measured the thickness of the RNFL, GCL, IPL, and choroidal thickness using a spectral optical coherence tomography (OCT) device and we compared the results between the children diagnosed with ASD and healthy controls. Correlation between the Childhood Autism Rating Scale (CARS) and the OCT data was evaluated. Both ASD and control group consisted of 40 subjects (30 males and 10 females). Of the children in the ASD group, 29 had normal intelligence and 11 had mild intellectual disability (MID). The mean age of patients in the ASD group and control groups were 9.77 ± 3.37 years and 9.85 ± 3.97 years (p = 0.928). There was a statistically significant difference between the ASD group and the control group in the nasal and nasal-superior sectors of the RNFL layers in the left eye when all the lower layers of RNFL were assessed. In both eyes, the children with ASD had considerably lower mean choroidal thicknesses than the controls. When compared to the controls, the GCL and IPL volumes in the individuals with ASD were considerably lower in both eyes. Compared to the MID group, the left GCL volume of the nasal-inferior group was noticeably higher. A significant correlation was found between CARS scores and left GCL left IPL. In contrast to RNFL in the ASD group, significant reductions in IPL, GCL, and choroidal thickness were observed in both eyes. It is thought that GCL may be a much more important biomarker than RNFL in terms of representing the structural deterioration in the brain. In addition, these results may form the basis for a new perspective on the use of OCT for the diagnosis and clinical course of autism.

'Maybe more fun and joy in this life of mine would be useful.' Perceptions of play by adults on the autism spectrum

: Introduction: The study presents how adults with ASD experience play, how they understand it and the meaning they assign to it. Method: Four people with a diagnosis of autism (aged 20‒35) participated in individual semi-structured interviews. The collected material was analysed thematically. Results: Five main themes were identified: the difficulty of defining play, the difficulty of experiencing play, the variety of forms of experiencing play, the variety of emotions of experiencing play: the role of the group, play and age. The results show that the play of adults with autism can take different forms and perform different functions. Emotions associated with play are an individual issue and remain related to the physical and social context of play. Conclusions: The study highlights the need for further research related to the functioning of adults on the autism spectrum and exploring the possibilities of play with its applications in therapy.