Sunday January 19, 2020

Over Exercising Can Result in Poor Mental Health, Reveals a Lancet Study

Doing exercise more than 23 times a month, or exercising for longer than 90 minute sessions is associated with worse mental health

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over exercising, mental health , exercising addiction
Over Exercising Can Result in Poor Mental Health. Exercising for more than 90 minutes daily can be harmful. Image: Wikimedia Commons

Over exercising or exercising addiction does more harm than good.  Engaging in exercises such as cycling, aerobics and gymming for more than three hours a day can worsen mental health than not exercising at all, a study has found.

The study, published in journal The Lancet Psychiatry, found that people who exercised between three and five times a week had better mental health than people who exercised less or more each week.

Conversely, people doing extreme amounts of exercise might have obsessive characteristics which could place them at greater risk of poor mental health, the researchers said.

Over exercising, mental health, exercise addiction
Over exercising: Doing exercise more than 23 times a month, or exercising for longer than 90 minute sessions is associated with worse mental health. Image: Wikimedia Commons

“Previously, people have believed that the more exercise you do, the better your mental health, but our study suggests that this is not the case,” said Adam Chekroud, Assistant Professor at Yale University in the US.

“Doing exercise more than 23 times a month, or exercising for longer than 90 minute sessions is associated with worse mental health,” he added.

Exercise reduces the risk of cardiovascular disease, stroke, diabetes, and mortality from all causes, but its association with mental health remains unclear.

You may like to read: Obesity During Pregnancy May up Kids’ Risk of Epilepsy

For the study, the team used data from 1.2 million adults across all 50 US states and included all types of physical activity, ranging from childcare, housework, lawn-mowing and fishing to cycling, going to the gym, running and skiing.

Team sports, cycling, aerobics and going to the gym were associated with the biggest reductions — 22.3 per cent, 21.6 per cent, and 20.1 per cent, respectively.

For people who had previously been diagnosed with depression, exercise was associated with 3.75 fewer days of poor mental health. (IANS) 

Next Story

Researchers Develop AI Tool To Detect Mental Health Issues

Tracking changes in clinical states is important to detect if there is a change that shows whether the condition has improved or worsened that would warrant the need for changing treatment

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The USC Signal Analysis and Interpretation Lab (SAIL), which has long applied artificial intelligence (AI) and machine learning to identify and classify video, audio and physiological data, partnered with researchers to analyse voice data from patients being treated for serious mental illnesses. Pixabay

Researchers, including one of Indian-origin, have developed an artificial intelligence (AI) tool that can accurately detect changes in clinical states in voice data of patients with bipolar, schizophrenia and depressive disorders as accurately as attending doctors.

“Machine learning allowed us to illuminate the various clinically-meaningful dimensions of language use and vocal patterns of the patients over time and personalised at each individual level,” said Indian-origin researcher and study senior author Shri Narayanan from University of Southern California (USC) in the US.

The USC Signal Analysis and Interpretation Lab (SAIL), which has long applied artificial intelligence and machine learning to identify and classify video, audio and physiological data, partnered with researchers to analyse voice data from patients being treated for serious mental illnesses.

For the results, the researchers used the ‘MyCoachConnect’ interactive voice and mobile tool, created and hosted on the Chorus platform to provide voice diaries related to their mental health states.

SAIL team then collaborated with researchers to apply artificial intelligence to listen to hundreds of voicemails using custom software to detect changes in patients’ clinical states. According to the study, the AI was able to match clinicians’ ratings of their patients.

Tracking changes in clinical states is important to detect if there is a change that shows whether the condition has improved or worsened that would warrant the need for changing treatment, the researchers said.

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Researchers, including one of Indian-origin, have developed an artificial intelligence (AI) tool that can accurately detect changes in clinical states in voice data of patients with bipolar, schizophrenia and depressive disorders as accurately as attending doctors. Pixabay

This project builds on SAIL’s body of work in behavioural machine intelligence to analyse psychotherapy sessions to detect empathy of addiction counselors-in-training in order to improve their chances of better outcomes, in addition to the Lab’s work analysing language for cognitive diagnoses and legal processes.

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“Our approach builds on that fundamental technique to hear what people are saying about using the modern AI. We hope this will help us better understand how our patients are doing and transform mental health care to be more personalised and proactive to what an individual needs,” said study lead author Armen Arevian. (IANS)