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American Focus > Blog > Tech and Science > One 10-Minute Exercise Can Reduce Depression, Even a Month Later : ScienceAlert
Tech and Science

One 10-Minute Exercise Can Reduce Depression, Even a Month Later : ScienceAlert

Last updated: March 5, 2026 10:35 pm
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One 10-Minute Exercise Can Reduce Depression, Even a Month Later : ScienceAlert
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In a groundbreaking study published in Nature Human Behaviour, researchers found that a well-designed 10-minute online exercise can lead to small reductions in depression. This study challenges the common belief that overcoming depression requires extensive therapy, medication, or drastic lifestyle changes. Instead, it suggests that learning practical skills through brief online interventions can have a measurable impact on depressive symptoms.

The study, conducted in 2024, involved soliciting ideas from various experts in the mental health field on how to best utilize 10 minutes of individuals struggling with depression. After receiving 66 responses from a diverse group of professionals, researchers selected 12 interventions to test in one of the largest randomized controlled trials of mental health interventions ever conducted.

These 12 interventions ranged from traditional psychotherapy techniques to innovative approaches such as an AI-based expressive writing exercise and repurposing a Thai Life Insurance ad to promote helping others as a way to find meaning in life. Each intervention was self-guided and took less than 10 minutes to complete.

The study involved 7,505 American adult participants who were randomly assigned to complete one of the 12 interventions or a control condition where they learned about trout. Participants reported feeling hopeful and motivated after completing the interventions, but only two – Interactive Cognitive Reappraisal and Finding Focus – showed significant reductions in depression a month later.

While the average reduction in depression was modest (around 4%), the study highlights the potential of brief, free interventions to reach a global audience and make a real difference in addressing the burden of depression, which affects millions of people worldwide each year.

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The researchers emphasize the importance of making evidence-based mental health resources accessible to a wider audience. Initiatives like Koko, which offers free short interventions for various mental health challenges, and the availability of all 12 interventions tested in the study online, aim to provide support to individuals who may not have access to traditional forms of therapy.

Moving forward, the research team plans to continue studying and implementing single-session interventions in various settings, including social media, schools, and therapy waitlists. Collaborations with AI experts aim to make these interventions more engaging and personalized to individual needs.

In conclusion, this study highlights the potential of brief online interventions in helping individuals struggling with depression take the first step towards long-term improvement. By offering evidence-based tools in a user-friendly format, researchers hope to make mental health support more accessible to those in need.

This article was originally published on The Conversation and has been republished under a Creative Commons license. The field of artificial intelligence (AI) has been rapidly advancing in recent years, with new breakthroughs and applications being developed at an unprecedented pace. From self-driving cars to facial recognition technology, AI is revolutionizing industries and changing the way we live and work.

One of the most exciting developments in AI is the concept of deep learning. Deep learning is a subset of machine learning that uses artificial neural networks to model and simulate human brain functions. By using multiple layers of interconnected nodes, deep learning algorithms are able to learn and adapt to new information in a way that is similar to how the human brain works.

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Deep learning has already been used in a wide range of applications, from speech recognition to image classification. For example, deep learning algorithms have been used to improve the accuracy of voice assistants like Siri and Alexa, making them more responsive and capable of understanding natural language commands.

In the field of healthcare, deep learning is being used to analyze medical images and diagnose diseases with greater accuracy than ever before. By training deep learning algorithms on large datasets of medical images, researchers are able to identify patterns and anomalies that human doctors may miss, leading to earlier and more accurate diagnoses.

Another area where deep learning is making a big impact is in the field of autonomous vehicles. By using deep learning algorithms to process sensor data from cameras, radar, and lidar, self-driving cars are able to navigate complex environments and make split-second decisions to avoid accidents.

While the potential of deep learning is exciting, there are also concerns about the ethical implications of this technology. For example, there are concerns about bias in AI algorithms, as they can perpetuate existing biases in society. Additionally, there are concerns about privacy and data security, as deep learning algorithms rely on vast amounts of data to learn and make predictions.

Despite these challenges, the potential of deep learning to revolutionize industries and improve our lives is undeniable. As researchers continue to push the boundaries of what is possible with AI, we can expect to see even more exciting developments in the field of deep learning in the years to come.

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