Financial overview and grant giving statistics of Neurodiversity Foundation

The Neurodiversity Cognitive Assessment Software market is poised for significant expansion, projected to reach approximately $3.5 billion by 2025 and grow at a Compound Annual Growth Rate (CAGR) of around 18% from 2025 to 2033. This robust growth is fueled by a confluence of escalating awareness surrounding neurodiversity in workplaces and educational institutions, coupled with the increasing adoption of digital solutions for cognitive screening and support. Key drivers include the growing recognition of neurodivergent individuals’ unique strengths and the demand for tools that can accurately identify and nurture these talents. Furthermore, advancements in AI and machine learning are enabling the development of more sophisticated and personalized assessment platforms, enhancing their precision and user experience. The shift towards value-based care models in healthcare also incentivizes the use of efficient and scalable software solutions for cognitive evaluations. The market is segmented into various applications, with "Hospitals" and "Clients" (likely referring to corporate HR departments and educational bodies) being the dominant end-users, reflecting the widespread need for cognitive assessment in both clinical and professional settings. The "Others" segment, encompassing research institutions and individual practitioners, also contributes to market breadth. Deployment types are primarily divided between "Cloud-Based" and "On-Premises" solutions, with cloud-based offerings gaining traction due to their scalability, accessibility, and cost-effectiveness. Geographically, North America is anticipated to lead the market, driven by early adoption of neurodiversity initiatives and strong technological infrastructure. However, the Asia Pacific region is expected to witness the fastest growth, propelled by increasing digitalization and rising awareness of mental health and cognitive well-being. Restraints such as data privacy concerns and the initial cost of implementation for some organizations are present but are being steadily addressed by evolving regulatory frameworks and the compelling ROI offered by these advanced software solutions. This in-depth report delves into the burgeoning Neurodiversity Cognitive Assessment Software market, offering a detailed analysis of its trajectory from the historical period of 2019-2024, through the base year of 2025, and projecting its growth up to 2033. The study period for this comprehensive market assessment spans from 2019 to 2033, with a particular focus on the forecast period of 2025-2033. This report provides invaluable insights for stakeholders seeking to understand the market dynamics, technological advancements, and strategic opportunities within this rapidly evolving sector. The projected market size is expected to reach $1,200 million by 2025, with significant growth anticipated throughout the forecast period.

The Neurodiversity Cognitive Assessment Software market is booming, projected to reach $2.8B by 2033 at a 15% CAGR. Learn about market trends, key players (CogniFit, Cogstate, Pearson), and the growing demand for personalized assessments for ADHD, autism, and other neurodevelopmental conditions. Discover how this technology is transforming education and the workplace.

This dataset contains anonymised raw data and examples of accommodations made for neurodiverse students in four undergraduate courses in Computer Science and Software Engineering programmes. The dataset is published as a part of a book chapter in which we report the accommodations.

Overall guidelines we followed, including their sources, are contained in guidelines.md.

The raw data for the two surveys is contained in the two Excel files survey1.xlsx and survey2.xlsx. Free-text answers have been aggregated by neurodiverse and neurotypical students and anonymised, and are available in the files survey1_freetext_neurodiverse.txt, survey1_freetext_neurotypical.txt, survey2_freetext_neurodiverse.txt, and survey2_freetext_neurotypical.txt.

The remaining files are examples of the adapted lecture slides and assignment texts. Here, files starting with WEBcourse are from a mandatory undergraduate course on web development, while files starting with SEcourse are from a mandatory undergraduate course giving an overview of Software Engineering.

Deenz Neurodiversity Scale (DNS-32) Dataset (Sample Size: 22) provides data from a pilot study involving 22 participants, collected to validate the DNS-32 scale. The dataset includes participants' responses to each of the 32 items on the DNS-32, covering domains such as attention, sensory processing, social cognition, and adaptability. Alongside DNS-32 responses, demographic information and additional psychological measures relevant to neurodiversity are included to support the validation process. This small-scale sample aims to establish preliminary reliability and validity insights, laying the groundwork for larger studies in neurodiverse traits assessment.

Financial overview and grant giving statistics of Neurodiversity Education Research Center

Global Neurodiversity Cognitive Assessment Software market size 2021 was recorded $849.484 Million whereas by the end of 2025 it will reach $1350 Million. According to the author, by 2033 Neurodiversity Cognitive Assessment Software market size will become $3409.5. Neurodiversity Cognitive Assessment Software market will be growing at a CAGR of 12.278% during 2025 to 2033.

Neurodiversity Cognitive Assessment Software Market size was valued at USD 1,250.75 million in 2024 and the revenue is expected to grow at a CAGR of 12.5% from 2025 to 2032

Discover Market Research Intellect's Neurodiversity Cognitive Assessment Software Market Report, worth USD 1.2 billion in 2024 and projected to hit USD 3.5 billion by 2033, registering a CAGR of 15.2% between 2026 and 2033.Gain in-depth knowledge of emerging trends, growth drivers, and leading companies.

Generative AI (AI) has become ubiquitous in both daily and professional life, with emerging research demonstrating its potential as a tool for accessibility. Neurodivergent people, often left out by existing accessibility technologies, develop their own ways of navigating normative expectations. GAI offers new opportunities for access, but it is important to understand how neurodivergent “power users”—successful early adopters—engage with it and the challenges they face. Further, we must understand how marginalization and intersectional identities influence their interactions with GAI. Our autoethnography, enhanced by privacy-preserving GAI-based diaries and interviews, reveals the intricacies of using GAI to navigate normative environments and expectations. Our findings demonstrate how GAI can both support and complicate tasks like code-switching, emotional regulation, and accessing information. We show that GAI can help neurodivergent users to reclaim their agency in systems that diminish their autonomy and self-determination. However, challenges such as balancing authentic self-expression with societal conformity, alongside other risks, create barriers to realizing GAI’s full potential for accessibility.

Roughly 20% of adults identify as neurodivergent – an umbrella term used to describe cognitively atypical individuals. Neurodivergent identities manifest in several forms including autism, attention dysregulation hyperactivity disorder/attention deficit hyperactivity disorder, dyslexia, and other cognitively atypical trajectories. Despite a societal increase in acknowledgment and awareness of neurodiversity, there remains little to no discussion or critical understanding of neurodivergent individuals, especially within the realm of higher education (HE). The aim of this study, as part of the Diversity in Education Study (DivES), is to explore the impact of a neurodiversity-focused module within the college classroom. This study included 153 students (predominantly female, heterosexual, third-year students, with white/European racial heritage); wherein, a neurodiversity-focused module was taught within the context of an undergraduate course on diversity. Pre (start of the term) and post (end of the term) surveys were compared to evaluate the impact of the module on student understanding of the term neurodiversity, self-endorsements of a neurodivergent identity, and critical consciousness of ableism. In sum, the neurodiversity-focused module increased neurodiversity awareness and self-endorsements but did not positively shift critical consciousness of ableism scores. Replication in larger and more diverse samples is needed before pedagogy recommendations may be solidified but this study provides preliminary support for the incorporation of a neurodiversity module within diversity-focused HE courses.

All variables used in the publication, 'Healthcare Experiences among Emerging Adults: The Impact of Neurodiversity'. Hayes Process Macro was used for mediation analysis and can be downloaded here: https://www.processmacro.org/index.html

This paper is based on data obtained by letting parents rate vocalisation recordings. Parents (n = 76) of female children with RTT listened to vocalisation recordings from RTT and typically developing (TD) infants, including an inconspicuous vocalisation from a RTT girl. For each recording, parents indicated if the vocalisation was produced by a RTT or a TD child.

Avoiding systemic discrimination of neurodiverse individuals is an ongoing challenge in training language models, which often propagate negative stereotypes. This study examined whether six text-to-image models (Janus-Pro-7B VL2 vs. VL3, DALL-E 3 v. April 2024 vs. August 2025, Stable Diffusion v. 1.6 vs. 3.5, SDXL v. April 2024 vs. FLUX.1 Pro, and Midjourney v. 5.1 vs. 7) perpetuate non-rational beliefs regarding autism by comparing images generated in 2024-2025 with controls. 53 prompts aimed at neutrally visualizing concrete objects and abstract concepts related to autism were used against 53 controls (baseline total N=302, follow-up experimental 280 images plus 265 controls). Expert assessment measuring the presence of common autism-related stereotypes employed a framework of 10 deductive codes followed by statistical analysis. Autistic individuals were depicted with striking homogeneity in skin color (white), gender (male), and age (young), often engaged in solitary activities, interacting with objects rather than people, and exhibiting stereotypical emotional expressions such as sadness, anger, or emotional flatness. In contrast, the images of neurotypical individuals were more diverse and lacked such traits. We found significant differences between the models; however, with a moderate effect size (baseline $\eta^2 = 0.05$ and follow-up η = 0.08$), and no differences between baseline and follow-up summary values, with the ratio of stereotypical themes to the number of images similar across all models. The control prompts showed a significantly lower degree of stereotyping with large size effects (DALL·E 3 η = 0.39; Midjourney η = 0.41; FLUX η = 0.20; Stable Diffusion η = 0.34; DeepSeek-VL3 η = 0.45) confirming the hidden biases of the models. In summary, despite improvements in the technical aspects of image generation, the level of reproduction of potentially harmful autism-related stereotypes remained largely unaffected.

Global Neurodivergent Strengths Market is segmented by Application (Corporate Wellness_Education_Personal Development_Healthcare_Government), Type (Neurodiversity Programs_Cognitive Enhancements_Workplace Inclusion Programs_Neurofeedback Tools_Online Courses for Neurodivergent Individuals), and Geography (North America_ LATAM_ West Europe_Central & Eastern Europe_ Northern Europe_ Southern Europe_ East Asia_ Southeast Asia_ South Asia_ Central Asia_ Oceania_ MEA)

This data has emerged from qualitative semi-structured interviews which obtained the experiences and perspectives of international practitioners who work with autistic men/men with attention deficit hyperactivity disorder who perpetrate domestic abuse in intimate relationships. It aimed to understand how practitioners can provide safe and effective interventions for neurodivergent men and victim-survivors.

Key findings included concerns regarding the lack of knowledge about neurodivergence, screening and awareness amongst practitioners, workforce development, recruitment and retainment, and the resourcing and sustainability of neurodivergent responsive interventions. It also identified that practitioners had witnessed that neurodivergent men experience barriers to engagement within mainstream programmes developed and delivered by and for neurotypical people, and that more research is needed about the implications of this for victim-survivors and those who work with them within integrated services.

This data set emerged as part of an ESRC postdoctoral fellowship, which aimed to understand how domestic violence perpetrator programmes can be more responsive to the needs of autistic and/or men with Attention deficit Hyperactivity Disorder (ADHD). The fellowship aimed to enrich understanding amongst organisations and policy makers about how to identify and support neurodivergent perpetrators of domestic abuse by developing neuroinclusive interventions. The fellowship aimed to generate new knowledge by carrying out 10 interviews with international experts working with autistic/ADHD male perpetrators and paves the way towards thinking about, learning from, and developing international responses that tackle the violence of neurodivergent male perpetrators of abuse.

The Neurodiversity Cognitive Assessment Software market is emerging as a pivotal solution in educational and clinical settings, designed to facilitate the assessment and understanding of diverse cognitive profiles, especially among neurodiverse populations. This market has gained significant traction in recent years

The dataset consists of data collected with smartwatch built-in sensors, representing learning activities from participants with neurodiversity, which can be used for activity recognition, automatic labeling, and assistive wearable applications.

The dataset contains three supporting documents for the paper title, "Experiences of Dyslexic Software Engineers - A Qualitative Study". It contains interview guide; excel file containing the coded post from reddit and a pdf version of the online consent form. The excel ffile is organized by subreddit containing r/ExperiencedDevs, r/cscareerquestions, r/LearningDisabilities and r/learnprogramming, r/programming, r/webdev, r/gamedev, r/AskProgramming, r/computersicence and r/Neurodiversity.

The excel fle contain the following labels:

• UniqueID: The associated ID to the author post
• Author: The username from the author's commentary/post
• Quote: The part of the text coded itself
• Code: Code referencing the quote when necessary
• Post: link to the post where is the quote