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  1. Government Computing
March 2, 2021

Screen time not key indicator for phone addiction in young adults

A new research study from King’s College London reveals that the length of time young adults spend on their phones is not the key indicator to their phone addiction.

Mobile Screen time. Credit: Christian Wiediger/Unsplash

Smartphone addiction though not formally recognised as clinical diagnosis has been the subject of research for quite some time.

King’s College London conducted a study using the smartphone addiction scale as the validated tool for research. The study found that approximately 39% of young adults in the age group of 18 to 30 years suffered from phone addiction experiencing symptoms such as loss of control over their screen time, feeling distressed on not being able to access their phones leading to neglect over other areas of life.

King’s College London’s Institute of Psychology, Psychiatry and Neuroscience (IoPPN), lead author Samantha Sohn, said: “Smartphones are increasingly becoming indispensable parts of our daily lives, and this study is an important step in looking at their impact in terms of dysfunctional use and on sleep in a UK population.”

The study also reported that nearly 69% of respondents that show signs of phone addiction suffer from poor sleep irrespective of the amount of time they spent over their phone. However, the report also found that nearly 57% of those who do suffer from phone addiction are also affected by poor sleep.

Recently, many leading smartphone manufacturers have introduced in-built features and tools in the device that help the users control their screen time on a daily basis and are also designed to minimise the impact on sleep.

South London and Maudsley NHS Foundation Trust, visiting clinical lecturer at IoPPN and addiction psychiatrist Dr Nicola Kalk, while arguing on the fact that screen time is not the key indicator of detrimental phone use, said: “This study makes clear that it is features of behavioural addiction rather than exposure time that is predictive of smartphone-associated harm.”

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