From addiction to anxiety to bullying, technology and social media get a bad rap at times for their negative impact on mental health, but those same tools can also be wielded to help those in need.
Large-scale intervention programs such as the Crisis Text Line are on the rise. CTL not only allows trained counsellors to support Americans in crisis 24/7 (and at no cost) through the ease of texting, but it has become one of the world's largest health data sets, and a real-time way to look at crisis trends. (In Australia, Lifeline's Crisis Text service is due to begin trials this year.)
I'm very bad at processing my feelings alone. If I don't want to spiral into anxiety, I need to process with a conversation partner. my wife, my friends, my therapist. But what do I do with all the passing feelings that aren't worth draining someone else's time? I'm excited to try offloading this emotional labour to Woebot, a new chatbot therapist built by Stanford psychologists and AI developers.
Smaller-scale research is also on the rise — with Instagram being the latest service to capture a picture of what's going on with a users's mental health.
According to a study published last week in the EPJ Data Science journal, researchers at Harvard University and the University of Vermont questioned whether markers of depression could be identified through photos posted on the popular social media site.
After using a variety of computational methods including machine-learning and image processing to review nearly 44,000 photographs posted by 166 study participants (identified as "healthy" or "depressed" based on a past clinical diagnosis), their answer was yes.
Machines analysed user activity, how many "likes" and comments a photo received, and the number of faces in a photo. Interestingly, depressed individuals shared posts at a higher frequency, and while those posts received a higher rate of comments, they received fewer likes. Their photos did feature faces, but fewer faces than the healthier participants.
The researchers also analysed photo hue, saturation and value, and whether or not a filter (and what type of filter) was used. Photos posted by depressed individuals tended to be, pixel-by-pixel, bluer, darker and greyer, and were less likely than those from the healthy participants to have a filter applied. When depressed participants used filters, they favoured converting colour photos to black and white.
Perhaps even more interesting though is that the researchers were not only able to confirm depression in a person who had already received a formal diagnosis, but the data was able to predict depression pre-diagnosis.
In an interview with the New York Times, the researchers were clear to state that while the sample size was small, and of a very specifically recruited group of active Instagrammers who were willing to share a past clinical diagnosis of depression, "the results speak more to the promise of their techniques".
If depression is affecting you or someone you know, call Lifeline on 13 11 14.