Can AI treat teenagers’ depression and mental health disorder?

Representational Image. (Photo via Unsplash/Getty Images)

To use Yann LeCun’s words, "Our intelligence is what makes us human, and AI is an extension of that quality." But can Artificial Intelligence (AI) tackle mental health disorders (MHD)? MHD is a significant public health issue and its treatment costs on a par with that of many chronic physical illnesses.

For starters, AI methods can be used to gain a deeper understanding of mental health now that a greater amount of data is available. In recent years, deep learning (DL) methods have shown promising results in healthcare, particularly in diagnosis, prognosis, and treatment.

AI can enhance access to integrated treatment and address depression, but it has limitations. Recent studies find substantial inadequacies which may signal fast marketing of new AI models that are yet to be tested in the real world in mental health services and research.

What do most teenagers suffer from?

Anxiety and depression affect approximately one in five children but are typically not diagnosed until adolescence or adulthood. It can be challenging to screen for depression and anxiety in children who lack the language skills and emotional maturity to articulate their feelings. Recognising both the physical manifestations of suffering and self-defeating thoughts may aid in preventing adolescent melancholy.

Can we use AI for mental health?

Mental health providers use AI for various purposes, including improving the quality of therapy sessions through enhanced understanding, improving diagnosis by continuously monitoring patient state, and adjusting treatment as needed. AI refers to detectable and treatable technological instruments for depression. These tools may aid in treating and managing depression by administering therapy, gathering feedback, and providing individualised recommendations.

AI for mental disorder diagnosis

Medical diagnosis is one area where AI has proven useful. Diseases are identified and diagnosed using several Machine Learning approaches, including the Boltzmann, support vector machine (SVM), and K-Nearest Neighbour (kNN). The imaging, segmentation, and prediction abilities of AI subfields like Machine Learning (ML) and computer vision have led to their widespread adoption. In the diagnostic process, computer vision is used to identify, segment, and classify images, such as radiological image segmentation and classification into diagnostic categories, metastasis detection, etc. Schizophrenia is a severe mental condition characterised by an altered perception of reality and hallucinations or delusions. To make such a diagnosis, Khan et al. suggested a deep neural network that — given genome sequencing data as input — learns the feature representation of the data to make a Schizophrenia diagnosis.

AI for mental disorder treatment

AI can aid in creating precision medications by assisting in predicting the response to particular drug combinations. Neuroimaging biomarkers have been used to evaluate how well methylphenidate treats ADHD. Normal and cancerous MRI samples are classified using ML models. Classification of neuroanatomical patterns has been utilised to predict the onset of mental disorders.

Challenges

Doctors must learn how to apply AI in their practice effectively. However, while over 70 per cent of psychiatrists surveyed worldwide anticipate using AI as part of their daily clinical routine (primarily for documentation), many remain sceptical of the technology’s therapeutic merits.

What applications are available

Some examples of popular AI-based technology that can aid depression management are provided below. The apps are not meant to replace the guidance of a medical or mental health professional but rather to supplement their efforts.

WoeBot

WoeBot, which debuted in the summer of 2017, is a chatbot or automated conversational agent. Simulating human dialogue and providing self-help-related counsel and companionship aims to make mental health care more accessible for people experiencing depression. The software can recommend content like films and exercises based on your needs. Those with an iOS device and a Facebook Messenger account can have private conversations with WoeBot.

Wysa

Wysa is an "emotionally intelligent" AI-based bot that the business claims can "help you manage your emotions and thoughts." Wysa, like WoeBot, is built on CBT principles to help users challenge and improve their ideas and behaviours. Wysa’s talks include dialectical behavioural therapy (DBT), meditation practises, and motivational interviewing. Wysa can be used anonymously, but it collects data as users interact to improve the accuracy of its understanding of a user’s behavioural and mental health requirements and goals.

Tess

Tess is "a psychological AI that administers highly personalised psycho-education and health-related reminders on demand." Users can participate in the program’s text-based chatting environment via Facebook Messenger, SMS texting, web browsers, and mobile apps.

Youper

This free iOS and Android application employs AI chatbot technology to assist users in discussing their symptoms, behaviours, and patterns. Youper is an "emotional health assistant" that provides personalised feedback and insights based on what it learns from daily text-based conversations with users, as described by the company. At the outset of a chat session, users can tell Youper what they require. For instance, a user may need assistance managing chronic depression or immediate suggestions to feel less anxious.

Conclusion

The concept of producing AI with human society ideals and wisdom is yet to be explored. Likely, human knowledge will never be programmed into computers. However, some examples exist, such as robots serving as physical therapists and social workers and offering cognitive support to the elderly. These advancements aim to construct machines that use intelligent principles to make wise decisions. AI intelligence advances may play a significant role in mental healthcare.