Current Gender Disparities in Diagnosis
Learning disorders such as dyslexia, ADHD, and autism affect a significant number of people worldwide. According to the Center for Disease Control and Prevention (CDC), approximately one in 36 children is diagnosed with Autism Spectrum Disorder (ASD), with boys being four times more likely to be diagnosed than girls as of 2020. Similarly, according to the International Dyslexia Association, dyslexia affects up to 20% of the population, with boys being diagnosed at higher rates than girls. ADHD, on the other hand, affects about 8.4% of children, with boys being diagnosed at three times the rate of girls.   These statistics show that learning disorders affect a large proportion of the population, with boys being more likely to be diagnosed and receive support.
However, girls and women with learning disorders are frequently undiagnosed, leading to a lack of support or a delay in receiving the necessary treatment. This issue is often attributed to the fact that learning disorder diagnosis is based on research carried out primarily on men. As a result, the criteria used to diagnose learning disorders may not be applicable to women and girls, leading to inaccurate diagnoses or no diagnosis at all. The gender bias in learning disorder diagnosis is influenced by cultural sexism and misogyny, both in clinical research and society at large.
The NHS states that “girls are more likely to have symptoms of inattentiveness only and are less likely to show disruptive behaviour that makes ADHD symptoms more obvious. This means girls who have ADHD may not always be diagnosed.” Healthcare institute Unique Mindcare elaborates: “The symptoms are often more subtle and, as a result, harder to identify. Research has shown that boys with ADHD usually show externalized symptoms, such as running and impulsivity. Girls with ADHD, on the other hand, typically show internalised symptoms. These symptoms include inattentiveness and low self-esteem. Boys also tend to be more physically aggressive, while girls tend to be more verbally aggressive”. The gender bias in learning disorder diagnosis also affects how women and girls receive support and treatment. Within the field of neuroscience and behavioural studies, the general consensus is that girls with learning disorders often do not receive the same level of intervention as boys because they tend to pass under the radar.
The Emerging Role of Technology and Diagnosis
Fortunately, emerging technology can facilitate the diagnosis of learning disorders in women and girls. One example is the use of machine learning algorithms to analyse speech patterns and identify markers of autism. Researchers at the University of California, Los Angeles, have developed the "Autism and Beyond” app that uses the front-facing camera on mobile devices to analyse a child's facial expressions and detect signs of autism. According to Disabled World, the app uses machine learning algorithms to screen children for autism and other neurodevelopmental disorders by analysing facial expressions and vocalisations. The app has been approved by doctors, researchers, and software developers. This technology can be particularly helpful for girls, who often present differently than boys with autism, making diagnosis more challenging due to the factors discussed earlier.
Another promising technology is the use of eye-tracking devices to diagnose dyslexia. Dyslexia affects reading ability, and those affected usually struggle to track text smoothly. Eye-tracking devices can measure how a person's eyes move when reading and identify irregularities which may indicate dyslexia. Dr Matthew Schneps, director of the Laboratory for Visual Learning at Harvard University from 2015 to 2018, explained that tracking eye movements and understanding how people read can help better understand why some people struggle with reading and identify the appropriate support. As such, by incorporating gender-informed diagnostic tools and leveraging advancements in technology, we can ensure that dyslexic women and girls can be diagnosed and receive the support they need to thrive.
Technology is also being developed to aid the diagnosis of ADHD through the use of virtual reality (VR), for instance, to assess attention and impulse control. Researchers at the University of Central Florida have developed a VR program that simulates classroom environments to test children's attention and impulse control. The program allows researchers to monitor how children respond to distractions and therefore assess their ability to focus.These emerging technologies can help improve the lives of women and girls with ADHD by facilitating accurate diagnosis and providing them with the required support and treatment.
As well as diagnosis, technology can be used to identify the genetic data that indicates a neurobiological disposition towards a learning disorder. Dr Sarah Spence, chief of the Neurodevelopmental Disorders Branch at the National Institute of Mental Health, has worked to develop Autism Genetic Resource Exchange (AGRE), a large autism gene-bank, using biomedical technology. This genetic data can help researchers uncover the aetiology of autism and related learning disorders. Spence also writes in her 2018 medical research paper ‘Evaluation and Management of the Child With Autism Spectrum Disorder’ that “a strong genetic component exists [to autism] that interacts with various environmental risk factors” and that “current research is identifying overlapping neurobiological pathways that are involved in pathogenesis”. This shows that technology has a role not only in diagnosing and improving the lives of women and girls with autism but also in analysing the genetic and neurobiological causes of the disorder, helping to improve early screening tools, to predict the likelihood of the disorder arising in children based on environmental and biological combinations, and even to predict the probability of it being passed down generations. This biomedical technology can also be extended to other learning disorders, including dyslexia and ADHD.
Legal Safeguards - Privacy and Data Protection to Ensure Fairness and Non-Discrimination
As technology becomes more prevalent in diagnosing learning disorders, it is crucial to establish robust legal safeguards to protect privacy and data. It is important that legislative frameworks ensure that individuals' consent is obtained, data is anonymised and encrypted, and strict regulations are in place to prevent unauthorised access or misuse of personal information. Legal protections will inspire trust and encourage individuals to seek diagnosis and support without fear of privacy breaches.
By means of an illustration, the autism gene bank will be monitored by medical legislation designed to ensure the ethical treatment of genetic data. The Genetic Information Non-Discrimination Act (GINA) in the United States is a federal law that prohibits discrimination based on genetic information in employment and health insurance, as well as restrictions on collection and disclosure. In the EU and the UK, genetic data is protected under the General Data Protection Regulation (GDPR) and categorised as highly sensitive. Furthermore, facial recognition technology designed to spot autism in children would be subject to the classical rules concerning informed consent such as explicit and informed consent from parents or legal guardians of the children. The use of VR classrooms would also be regulated by the ePrivacy Directive in the EU.
While technology presents exciting opportunities for diagnosis, it is crucial to safeguard against potential biases and discrimination. Algorithmic bias can inadvertently perpetuate social inequalities if these are not addressed effectively. Machine-learning algorithms must be thoroughly tested and continuously refined to ensure fairness and accuracy across gender and ethnic backgrounds. Additionally, professionals and policymakers must promote awareness and education about the potential biases in these technologies to foster a more inclusive and equitable approach to diagnosis.
How legal protections are specifically needed to protect women with learning difficulties
Legal safeguards put in place to protect women and girls with learning difficulties have the central motive to ensure that they enjoy fair and non-discriminatory treatment, but this multi-faceted goal can be segmented into many aspects. The guarantee of equal access to education for girls with learning difficulties, such as support services and resources adapted to their needs, ensures that they can fully participate in education opportunities and reach their full potential in their academic and professional careers.
These safeguards also exist to prevent potential abuse and exploitation that could arise from their difficulties. For example, symptoms of ADHD include forgetfulness and misplacing items. Dr Stephanie Sarkis, therapist and ADHD specialist, observes that “more and more people with ADHD are in relationships or [workplaces] where gaslighting is happening”. An example is an emotionally abusive partner may gaslight a woman with ADHD, using her symptoms to make her further doubt her abilities. Dr Sarkis has also researched heightened abuse that neurodivergent children may suffer from frustrated parents, concluding that “childhood maltreatment was associated with increased risk of ADHD symptoms in young adulthood”. Therefore, legal safeguards allow the effective protection of women and girls with these learning disorders, both in equipping them and their loved ones with resources to recognise their conditions, and to prevent them suffering abuse.
In conclusion, learning disorders affect a significant proportion of the population, subject to gender bias which is rooted in societal expectations of gender roles and has led to inaccurate diagnoses or no diagnosis at all for many women and girls. However, emerging technologies such as machine learning, eye-tracking devices, and VR programs offer promising avenues for accurately diagnosing learning disorders in women and girls. Biomedical technology can also provide scientific revelations about its genetic and neurological causes. The use of technology to identify and diagnose neurodevelopmental disorders like autism, ADHD, and dyslexia in women and girls is critical to reducing the gender gap in diagnosis and treatment. It is crucial to invest in these technologies and develop gender-informed diagnostic tools to ensure that all individuals, regardless of gender, have access to the required an
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