You're probably less addicted to Instagram than you think

Publicly released:
International
Photo by Solen Feyissa on Unsplash
Photo by Solen Feyissa on Unsplash

Excessive social media use may be driven by habit rather than genuine addiction, according to international research, which found that Instagram users tend to overestimate the extent to which they are addicted to the platform and this may be driven by news media mislabelling frequent social media use as an addiction. The researchers surveyed 380 Instagram users on how addicted they felt to Instagram, and then assessed them for symptoms of addictive Instagram use. They found that although 18% of people thought they were addicted to Instagram, only 2% displayed symptoms indicating risk of addiction. A subsequent study of 824 US adult Instagram users investigated the negative impacts of labelling frequent Instagram use as an addiction, and found that prompting participants to frame their social media use as an addiction was associated with lower feelings of control over their Instagram use and assigning higher levels of blame to both themselves and the platform for their excessive use. The researchers suggest that labelling frequent social media use as an addiction by news media and other institutions may contribute to Instagram users overestimating the extent to which they are addicted to the platform and may also negatively impact their perceptions of their social media use.

Media release

From: Springer Nature

Psychology: Instagram users overestimate social media addiction

Instagram users may overestimate the extent to which they are addicted to the platform, according to research conducted on 1,204 US adults published in Scientific Reports. The findings suggest that for most social media users, excessive use is driven by habit rather than genuine addiction.
Addiction towards a substance or action is typically characterised by a cluster of symptoms including difficulties controlling use, experiencing cravings to use, experiencing withdrawal symptoms when not using, and continuing to use despite negative consequences or risk of harm.
Ian Anderson and Wendy Wood surveyed an approximately representative sample of 380 US Instagram users, who were 50% women and had an average age of 44 years. Participants described how addicted they felt to Instagram and were assessed for symptoms of addictive Instagram use. The authors found that although 18% of participants at least somewhat agreed that they were addicted to Instagram — with 5% substantially agreeing — only 2% displayed symptoms indicating risk of potential addiction.
The authors explored a potential cause of this discrepancy by assessing descriptions of social media use in news articles published in US news media outlets between November 2021 and November 2024. They identified 4,383 articles mentioning the phrase “social media addiction” and 50 mentioning the phrase “social media habit”. This suggests that frequent social media use tends to be described as an addiction in US news articles. The authors suggest that this may influence how users perceive their social media use.
Using a second sample of 824 US adult Instagram users, the authors investigated potential negative impacts of labelling frequent Instagram use as an addiction. The authors found that prompting participants to frame their social media use as an addiction was associated with lower feelings of control over their Instagram use and assigning higher levels of blame to both themselves and the platform for their excessive use.
Together, the findings suggest that labelling frequent social media use as an addiction by news media and other institutions may contribute to Instagram users overestimating the extent to which they are addicted to the platform and may also negatively impact their perceptions of their social media use. More selective use of the term addiction by policymakers and the news media in relation to social media use may reduce this effect, according to the authors.

Journal/
conference:
Scientific Reports
Research:Paper
Organisation/s: California Institute of Technology, USA
Funder: None stated
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