Algorithms, algorithmic literacy and mental health
Dr Lizzy Winstone,
NIHR SPHR Launching Fellow, University of Bristol, UK
Churchill Fellow, 2023-24
Social media content and young people’s mental health
Self-harm and eating disorder content
Self-regulation of social media use
Avoiding risky content and contacts
Kostyrka‐Allchorne, K., Stoilova, M., Bourgaize, J., Rahali, M., Livingstone, S., & Sonuga‐Barke, E. (2023). Digital experiences and their impact on the lives of adolescents with pre‐existing anxiety, depression, eating and nonsuicidal self‐injury conditions–a systematic review. Child and adolescent mental health, 28(1), 22-32.
Social media content and young people’s mental health
• Diet and ED content – body image, comparison, thin/fit ideal internalization, selfobjectification
• Self-harm content –disturbing imagery, competition, normalization
• Discriminatory content –chronic stress, hopelessness, poor self-esteem
Social media algorithmic literacy
“being aware of the use of algorithms in online applications, platforms, and services, knowing how algorithms work, being able to critically evaluate algorithmic decision-making as well as having the skills to cope with or even influence algorithmic operations”
(Droguel, in Oeldorf-Hirsch & Neubaum, 2023).
Why might algorithmic literacy be important for mental health?
Informed content consumption: Awareness of algorithmic bias
Personalised content
Reduced anxiety and stress: Transparency and control Setting boundaries
Combatting negative effects: Critical thinking
Enhanced digital wellbeing: Healthy digital habits
Mental health resources
Mitigating echo chambers Empowerment and agency: Control over digital footprint Advocacy and change
Why might algorithmic literacy be important for mental health?
Informed content consumption: Awareness of algorithmic bias
Personalised content
Reduced anxiety and stress: Transparency and control Setting boundaries
Combatting negative effects: Critical thinking
Enhanced digital wellbeing: Healthy digital habits
Mental health resources
Mitigating echo chambers Empowerment and agency: Control over digital footprint Advocacy and change
Why might algorithmic literacy be important for mental health?
Informed content consumption: Awareness of algorithmic bias
Personalised content
Reduced anxiety and stress: Transparency and control Setting boundaries
Combatting negative effects: Critical thinking
Enhanced digital wellbeing: Healthy digital habits
Mental health resources
Mitigating echo chambers Empowerment and agency: Control over digital footprint Advocacy and change
Why might algorithmic literacy be important for mental health?
Informed content consumption: Awareness of algorithmic bias
Personalised content
Reduced anxiety and stress: Transparency and control Setting boundaries
Combatting negative effects: Critical thinking
Enhanced digital wellbeing: Healthy digital habits
Mental health resources
Mitigating echo chambers Empowerment and agency: Control over digital footprint Advocacy and change
Why might algorithmic literacy be important for mental health?
Informed content consumption: Awareness of algorithmic bias
Personalised content
Reduced anxiety and stress: Transparency and control Setting boundaries
Combatting negative effects: Critical thinking
Enhanced digital wellbeing: Healthy digital habits
Mental health resources
Mitigating echo chambers Empowerment and agency: Control over digital footprint Advocacy and change
How can we improve algorithmic literacy in the UK?
1. Commission a UK Media
Literacy Week
How can we improve algorithmic literacy in the UK?
2. Review current provision of algorithmic literacy
How can we improve algorithmic literacy in the UK?
3. Develop teacher confidence
How can we improve algorithmic literacy in the UK?
4. Introduce a digital literacy qualification
New study: Adolescent perspectives of the role of social media algorithms on their wellbeing
•We will interview 25 young people, including some people who have mental health difficulties.
•We will ask young people who use TikTok or Instagram to take screenshots of content that the algorithm thinks they will be interested in.
•The researcher will then talk to the young people about what is in the pictures, why they think the pictures have been suggested to them, and how they make them feel.
•We will record the interviews and analyse the data to describe themes.
