A new study has found smartphones can be instrumental in better understanding depression. A University at Buffalo researcher has found it can help measure symptoms of a patient frequently, in real time.
While extensive research into depression has resulted in the development of models that can explain the cause of the mental health disorder,they are unable to examine what's happening to a patient emotionally moment to moment. The new study has found some emotions can linger and that can predict feelings that relate to later symptoms.
"Clinicians aren't primarily interested in how one person's symptoms compare to someone else, which is what most studies focus on. Rather, they're most interested in how to shift the feelings of someone with anxiety or depression. In other words, they want to understand how to change the emotional experiences of a given individual over time and across different situations," said Kristin Gainey, an expert on emotion and affect in mood and anxiety disorders and a recent recipient of one of the American Psychological Association's Early Career Distinguished Scientific awards. Adding, "The only way to get at that directly is to measure these processes repeatedly within a person as they're happening."
For the study, researchers assessed 135 participants, who were all seeking some sort of treatment for depression. Participants had to complete a survey (three times a day) on their smartphones about their feelings and symptoms for close to 10 weeks. "That generated enough reports to provide a good sense for each person's fluctuations and trajectories of symptoms and affect (defined as the objective feeling state that's part of an emotion)," Gainey revealed.
The smartphones helped provide a clear understanding of what participants were feeling at the moment. "We can't always remember accurately how we felt days and weeks ago, especially if there were some days you felt really bad and other days you felt great," she explained. "That's not easy to summarize in a single index."
While negative emotions like fear and sadness are common for depression patients, researchers don't know which emotion tends to persist. "This study let us see that some affects were short-lived, but for depression, if you were feeling high levels of negative affect, even if we control for how depressed a participant was at that time, it was still predictive of increased depression 24 hours later," Gainey revealed. Adding, "If we can identify specific risk factors for increased symptoms in real time, we could even use smartphones to send suggestions about helpful strategies or alert the person's mental health care provider," she says.
Researchers hope their findings can provide better treatment options for patients struggling with the mental health disorder.