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Depression leads to more social media usage, not the other way around!

Recent longitudinal research from Brock University in Canada suggests that depression leads to people spending more time on social media, rather than those who spend more time of social media being more likely to develop depression.

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This study contradicts many of the ‘moral panic’ type headlines which suggests a link between heavy social media use and depression. Such headlines tend to be based on studies which look at correlations between indicators of depression and indicators of social media use at the same point in time, which cannot tell us which comes first: the depression or the heavy social media use.

This Canadian study followed a sample of teenagers from 2015 (and university students for 6 years) and surveyed them at intervals using a set of questions designed to measure depression levels and another set designed to measure social media usage and other aspects of screen time.

What they found was that teenage girls who showed signs of depression early on in the study were more likely to have higher rates of social media usage later on, leading to the theory that teenage girls who are depressed may well turn to social media to make themselves feel better.

The study found no relationship between boys or adults of both sexes and depression and social media.

This is an interesting research study which really goes to show the advantages of the longitudinal method (researching the same sample at intervals over time) in possibly busting a few myths about the harmful effects of social media!

 

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Longitudinal Studies

Longitudinal Studies are studies in which data is collected at specific intervals over a long period of time in order to measure changes over time. This post provides one example of a longitudinal study and explores some the strengths and limitations of this research method.

With a longitudinal study you might start with an original sample of respondents in one particular year (say the year 2000) and then go back to them every year, every five years, or every ten years, aiming to collect data from the same people. One of the biggest problems with Longitudinal Studies is the attrition rate, or the subject dropout rate over time.

The Millennium Cohort Study

One recent example of a Longitudinal study is the Millennium Cohort Study, which stretched from 2000 to 2011, with an initial sample of 19 000 children.

The study tracked children until the age of 11 and has provide an insight into how differences in early socialisation affect child development in terms of health and educational outcomes.

The study also allowed researchers to make comparisons in rates of development between children of different sexes and from different economic backgrounds.

Led by the Centre for Longitudinal Studies at the Institute of Education, it was funded by the Economic and Social Research Council and government departments. The results below come from between 2006 and 2007, when the children were aged five.

Selected Findings

  • The survey found that children whose parents read to them every day at the age of three were more likely to flourish in their first year in primary school, getting more than two months ahead not just in language and literacy but also in maths
  • Children who were read to on a daily basis were 2.4 months ahead of those whose parents never read to them in maths, and 2.8 months ahead in communication, language and literacy.
  • Girls were consistently outperforming boys at the age of five, when they were nine months ahead in creative development – activities like drama, singing and dancing, and 4.2 months ahead in literacy.
  • Children from lower-income families with parents who were less highly educated were less advanced in their development at age five. Living in social housing put them 3.2 months behind in maths and 3.5 months behind in literacy.

The strengths of longitudinal studies

  • They allow researchers to trace developments over time, rather than just taking a one-off ‘snapshot’ of one moment.
  • By making comparisons over time, they can identify causes. The Millennium Cohort study, for example suggests a clear correlation between poverty and its early impact on low educational achievement

The limitations of longitudinal studies

  • Sample attrition – people dropping out of the study, and the people who remain in the study may not end up being representative of the starting sample.
  • People may start to act differently because they know they are part of the study
  • Because they take a long time, they are costly and time consuming.
  • Continuity over many years may be a problem – if a lead researcher retires, for example, her replacement might not have the same rapport with respondents.

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