Could AI improve mental health and well-being?

A new digital approach to mental health has been developed by researchers from Hong Kong-based longevity startup Deep Longevity and the Harvard School of Medicine. In a new paper, “Optimizing future well-being with artificial intelligence: Self-organizing maps (SOMs) for the identification of islands of emotional stability,” researchers demonstrated that the ability to form meaningful relationships, as well as mental autonomy and environmental mastery, improves with age. They also found that the desire for personal growth steadily declines with age, while the sense of having a purpose in life fades only after about 40 or 50 years.

These findings add to the debate about socioemotional selectivity and hedonic adaptation in adult personality development. According to the socioemotional selectivity theory, when people's time horizons shorten, they become more selective and devote more of their resources to things that are emotionally meaningful to them.

The human tendency to quickly return to a relatively consistent level of enjoyment in the face of substantial happy or unpleasant events or life upheavals is known as the hedonic adaptation theory. According to this theory, as a person makes more money, expectations and desires rise in tandem, which results in no permanent gain in happiness.

The authors built two digital models of human psychology using information from the study Midlife in the United States. The first uses a group of deep neural networks to estimate the respondents' chronological age and their psychological health using data from a psychological survey. The second model is a self-organizing map created to serve as the foundation of a recommendation engine for mental health applications.

An unsupervised learning algorithm splits all respondents into clusters depending on their likelihood of getting depression and identifies the shortest path for any individual to reach a cluster of mental stability. The people with the least overall well-being gather in one area of the map, while those with the highest risk of depression tend to move toward another.

Deep Longevity's chief longevity officer, Alex Zhavoronkov, explains, “Existing mental health applications offer generic advice that applies to everyone yet fits no one. We have built a system that is scientifically sound and offers superior personalization.”

To demonstrate the potential of this technology, Deep Longevity has published FuturSelf, a free web application that allows users to perform the psychological exam detailed in the original journal. At the conclusion of the evaluation, customers receive a report with recommendations for enhancing their long-term mental health, and have the option to enroll in a guidance program that delivers a steady stream of AI-selected recommendations. The information gleaned from FuturSelf will be used to improve Deep Longevity's digital approach to mental health.

Professor Vadim Gladyshev of Harvard Medical School, a leading biogerontology expert, weighs in on the potential of FuturSelf: “This study offers an interesting perspective on psychological age, future well-being, and risk of depression, and demonstrates a novel application of machine learning approaches to the issues of psychological health. It also broadens how we view aging and transitions through life stages and emotional states.”

The authors intend to continue researching human psychology in relation to aging and long-term well-being. A follow-up study on the effect of happiness on physiological measures of aging is currently underway.

Check the links below to take the assessment for yourself!
https://futurself.ai/
https://www.aging-us.com/article/2040...

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