A mathematical method could predict the chances of recovering from depression. This is demonstrated by a study by the Higher Institute of Health, published in 'Nature Mental Health', which opens up new perspectives for prevention and treatment against the disease and other mental pathologies.
The research – explains the ISS – has developed a method to measure so-called plasticity, i.e. the ability to modify brain activity and behaviour, which is fundamental for moving from psychopathology to mental well-being. “For this purpose – states Igor Branchi of the Reference Center for Behavioral Sciences and Mental Health of the Higher Institute of Health, which coordinated the study – we used a mathematical technique known as network analysis. The objective was to demonstrate how the plasticity can be measured mathematically by evaluating the strength of connectivity in the symptom network, i.e. the frequency with which symptoms of depression change together. The greater the synchrony of changes in different symptoms, the higher the coherence (connectivity) of the system and the lower it is its plasticity: in this work we demonstrate how more connected configurations are more difficult to modify than configurations in which the links between symptoms are less strong”.
To verify the method – reports the ISS – the researchers examined the data from one of the most relevant studies on depression treatment strategies, known as Star*D and provided by the National Institute of Mental Health of the United States, analyzing the trajectory improvement of over 4 thousand depressed individuals. “The analysis – continues Branchi – confirmed how our mathematical approach is able to measure patients' ability to modify their depressive state”.
“In particular – details the specialist – we demonstrated how the strength of the connectivity of the symptoms, measured at the beginning of the study, was weaker in the patients who would subsequently show greater plasticity, presenting a significant improvement (responders) compared to those who would instead showed a less sensitive improvement (non-responders). Furthermore, we highlighted a highly significant correlation between the connectivity of symptoms and both the improvement of the depressive state and the predisposition to change mood based on the perceived quality of life”.
For the authors, “this method allows us to estimate the probability of change, but does not allow us to predict with certainty the future state of health of the individual, which depends on a multitude of factors”, they specify.
“In conclusion – concludes Branchi – this operationalization, i.e. the development of a measure of an abstract concept such as plasticity, provides a useful mathematical tool for predicting resilience, vulnerability and recovery, paving the way for new approaches in prevention and treatment of major depressive disorder and, more generally, psychiatric disorders”.
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