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How Technological Advances Could Transform Psychiatry

September 16, 2019

Addictive disorders will continue to be a challenge, and we will be much more aware of the potential of new technologies to cause addiction-like conditions. I suspect we will have a range of digital addiction disorders. Interventions to address these will also be digital in nature, and the concept of a digital detox will have been proven ineffective. We will also see a major transformation in how we experience social media, with continuing concern about its impact on our attention and real-world interactions. Social media may very well move off of the smartphone and become part of our perceptual experience of the world through advanced versions of augmented reality (mixed reality and beyond). The closer the proximity of social media to our cognitive and perceptual organs, the greater the potential positive and negative impact on our daily lives.

All these advances may even change the diagnoses we use today. Some of them may be found to have a range of subtypes, for example schizophrenia, while others may have their symptoms changed or weighted differently. Quantitative and objective ways of assessing patient symptoms may produce research findings that lead to certain diagnoses being withdrawn or substantially redefined.

Q: What near-term technologies will start to make an impact over the next 2 to 3 years?

A: One of the most obvious is telepsychiatry. Its ability to improve access and decrease costs will benefit patients. We will also see the approval of several prescriptive digital therapeutics—software running on smart devices shown to be efficacious in treating mental health disorders. It is likely the earliest areas of success will be in ADHD and substance use disorders.

Smartphones are being researched as a tool that could help with digital phenotyping—a way of helping quantify behavior and cognition through analyzing how a person uses the different features of a smartphone (monitoring the duration, timing, and frequency of phone calls or text messages, for example). Information such as movement monitoring via GPS or voice/speech analysis are being explored. These technologies could assess large amounts of free text data in patient records or evaluate what patients say (language, such as syntax or pragmatics) and how they say it (acoustic qualities of speech) as a means of monitoring symptom severity or treatment response.

Also Coming at Psych Congress: Advancements Aim to Build Trust in ECT

Another area of near-term impact is the use of big data gathered from health records or national registries. Machine learning will allow for previously unknown insights into mental health conditions. This may include finding previously unknown risk factors that would heighten suicide risk or the identification of demographic factors or specific symptoms/ signs that help predict a patient’s response to a particular treatment.

Q: What about technology to help advance research?

A: A huge range of changes are coming to research and clinical trials. One could be tempted to think the enormous amount of data from all of the monitoring technologies around us and the rapid increase in affordable computing power and storage would lead to rapid research discoveries. Unfortunately, the huge amount of data has led to a huge amount of questions. How do we ensure these data are reliable or accurate? Are our traditional statistical approaches appropriate? How do we choose an area of data to focus on and not become overwhelmed?

The pharmaceutical industry has already embraced the use of artificial intelligence, such as machine learning and neural networks, to help it discover candidate drugs, find new insights in clinical research, and help improve the chance of taking drugs to approval. Certain disease areas have had greater focus in this area, such as metabolic, immunological, and oncological conditions. Brain conditions may be a tougher nut to crack but could very well follow.

Some of the technological advances may mean that neuroimaging becomes more promising as imaging modalities and data analysis improve. We are already witnessing artificial intelligence programs becoming more accurate at interpreting imaging tests in other fields, such as chest x-rays and mammograms. The hope is that advancements in neuroimaging will allow us to find a variety of markers based on functional or structural findings that will help us understand disease severity, predict response to a particular treatment, and even predict risk of associated conditions.The field of genomics has also seen an explosion of research interest and potentially helpful tools, although many ethical concerns have also been raised about our ability to potentially “edit” the genome of humans. One area of special interest to mental health is the growth in interest in pharmacogenomics, an emerging field that studies a person’s genome to determine their likely response to a specific medication. The ability to tailor treatment in this personalized way is certainly appealing, especially if we consider a condition such as depression.

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