UOC develops method to assess safety and efficacy of depression treatment apps

The UOC's eHealth Lab creates EvalDepApps, a tool to validate mobile applications following an 86% rise in depression incidence in Catalonia.

Imatge genèrica de mans utilitzant una aplicació mòbil relacionada amb la salut mental o el seguiment clínic.

Imatge genèrica de mans utilitzant una aplicació mòbil relacionada amb la salut mental o el seguiment clínic.

The eHealth Lab research team at the Universitat Oberta de Catalunya (UOC) has launched the EvalDepApps project to develop a digital solution that evaluates the quality and effectiveness of mobile applications used for depression treatment.

The incidence of depression, one of the most common mental disorders, increased by nearly 50% globally between 1990 and 2017, according to World Health Organization (WHO) data. In Catalonia, the incidence of depression and mood disorders grew by a notable 86.6% between 2017 and 2022, based on primary care data.
Although the use of mobile applications combined with face-to-face psychological interventions has proven effective, the main challenge is the quality of these tools, as most are not based on scientific evidence. The study, published in the British Medical Journal, seeks to identify the most relevant criteria for patients in order to develop a reliable digital solution.

"In the same way that a drug or a health product is evaluated before it reaches the market to ensure its efficacy and safety, the mobile applications we use to take care of our health and well-being must also be evaluated to know what effect they may have, which is currently not done enough."

Carme Carrion · Project Leader and Principal Investigator of the UOC's eHealth Lab
The EvalDepApps project involved 43 people in a Delphi process to gather priority criteria. Users highlighted data security, clinical efficacy, being evidence-based, and ease of use. It was also positively valued that they allow interaction or urgent contact with mental health professionals or the healthcare system.
Other relevant aspects include considering the gender perspective, as men and women often present different symptoms, and the application's ability to measure the patient's clinical evolution. This feature, according to researcher Noemí Robles, can help the person become more aware of their own emotional state and allow for more personalized monitoring.
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