
Four simple questions helped frame the opportunities: What if social platforms were designed to consider their effect on mental health? What if they took more responsibility for their users’ mental wellbeing? Could we track our mental health the way we do physical health? And should we count digital content ‘calories’ like nutritional calories?
Our research explored a range of challenges, from addictive tendencies to personal control and content trends. A complex picture emerged of the positive and negative impact social media has on mental health. Could we make a difference through design?
Our vision is to explore platform, interface and content design to reduce the negative impacts on mental health of image-led social platforms. We aim to:
Rather than a single solution we developed a range of starting concepts, both on- and off-platform. These could begin to foster more positive mental health benefits, and reduce the negative impact for users who may be at risk.
A mindful algorithm on-platform would consider mental health before serving content. It might look at biometric data around stress, analyse your past posting and interactions for signs of anxiety or depression, consider your time spent online and the current time of day. Using this data it would carefully select what content to show in your feed. This would:
If depression can be predicted from social content, social platforms can respond with relevant coaching. Using content patterns, machine learning and analysis, we could develop a suite of content for coaching digital skills. This is posted from the platform to users identified as being at potential risk. The aim would be to make positive coaching hints to those most in need – developing skills, encouraging use of product features and fostering healthy habits.
We’re used to a traffic light system on food packaging, but what about social accounts that promote an unhealthy body image? Could we develop a profile ranking system for feed ‘safe modes’, with individual accounts marked on a health scale? This would consider factors like posting cadence, engagement, photo-manipulation, sentiment, content reporting and body image. In this way we could tailor recommendations for new follows based on a balanced diet of social content, not just subjective association.
Research shows we can only hold close relationships with a small number of people. Social media helps to develop these connections, so why not allow people to prioritise posts from a small network of friends? These would be given preference in feeds, with less restricted notifications and the potential to discuss and report content. This would help to develop valuable, trusted relationships instead of mass follows.
One of the most addictive qualities with social platforms is the endless stream of content. There’s always more out there, so we keep scrolling. Giving people the ability to digest and snooze notifications for a set period of time could encourage less addictive behaviour, improve concentration and promote healthier interactions with apps. We could also create smart notification settings based on time of day, geo-fencing notification activity, sleep windows and predictive well-being.
If we monitor our fitness and generate goals for physical health, could we do something similar for mental health, particularly around social media usage? An app or social platform could help set goals, monitor usage and provide contextual tips and insight that helps us make more informed healthy choices.
Social platforms can lock us into habitual behaviour with the routine of scrolling rewarded by the dopamine hit of something new. What if we could replace one potentially unhealthy habit with more constructive ones? Often we just need inspiration to shake us out of a routine, so an app full of randomly-chosen ideas could be just the kickstart we need.
To empower people and encourage healthier usage, we could provide customised control of these settings at operating system level. The intention is to help users control how their social apps deliver content and features:
Some key research pieces and studies have informed this project:
EPJ Data Science – Instagram photos reveal predictive markers of depression
RSPH and the Young Health Movement – #StatusOfMind report
Microsoft Research – Predicting depression with social media
Our short discover/design projects unpick challenging problems and drive innovation through a rapid design process.