Deep Longevity has released a free online mental health tool based on recent advances in digital psychology.

A group of scientists from Deep Longevity, a longevity startup based in Hong Kong, and the Harvard Medical School has published a research paper on psychological aging, depression and a new digital approach to mental health [1].

Longevity.Technology: Publishing in Aging, the researchers detail how deep learning approaches have been applied to create an ensemble of models describing human psychology. One is an aging clock that produces an estimate of one’s psychological age based on a short survey. The results show those with a low psychological age have a clearer purpose in life and are more dedicated to personal growth. However, those of a high psychological age have more meaningful relationships and depend less on others’ opinions.

Having clear purpose and a dedicated interest in self-improvement bode well for personal longevity. Add in the growing body of research that suggests better mental health leads to improved longevity and Deep Longevity’s free tool would seem to be a no-brainer.

As Dr Nancy Etcoff, one of the paper authors, comments: “I see this work as a momentous step forward in happiness research and in measuring and predicting future well-being.”

Other models in the ensemble have been trained to predict one’s well-being in 10 years using the same survey. The ensemble has shown that one’s current level of life satisfaction is not a significant factor in determining future life satisfaction. The authors hypothesised that prioritising the features in the survey provides the shortest path toward self-improvement and long-term mental resilience.

To further this point, they created a self-organising map that presents the interpretation of the task of self-improvement as a geometric problem. People with low overall well-being and high depression risk gravitate toward a particular region of the map, while the most fulfilled individuals concentrate in another region. The authors propose that this map can guide psychotherapy or serve as a recommendation engine for mental health applications.

Users of such an application will receive personalised recommendations that consider their current location on the map, their life priorities and the relative difficulty of improving different personality traits.

READ MORE: Deep Longevity reveals highly-accurate aging clock

As a proof of concept, Deep Longevity has released a web service, FuturSelf, that offers free access to those willing to test the models described in the original publication. FuturSelf provides a report showing people’s weakest and strongest personality aspects, as well as their psychological age and predicted future well-being. At the end of the assessment, users can join a self-improvement program and receive daily recommendations aimed at maximising their potential well-being.

Fёdor Galkin, Director of Scientific Business Development at Deep Longevity, told Longevity.Technology that people have believed that it is essential to train both your body and your mind to have a fulfilling life since antiquity.

“Now, we have the ability to break down such complicated concepts as “mental health” into manageable, and importantly, quantifiable pieces,” he told us. “We are still not quite at the point where we can build a tool that could be applied to study both body and soul, but our FuturSelf platform is an important stepping stone.

“Later this year, we are going to publish a follow-up study with the University of Hong Kong to show that mental health has as strong an impact on the pace of aging as smoking, among other findings. We are moving toward creating multi-modal models of aging that are able to grasp aging in all its complexity. At this point, it is clear to us that to fight aging one needs to have as many viewpoints as possible; epigenetics, blood biomarkers, psychology, lifestyle – none of them tells the whole story, but the tech at the core of FuturSelf provides us with the backbone that can be used unite these different dimensions of aging.”

[1] https://www.aging-us.com/article/204061/text