Smartphones, Depression, and Anxiety

There is increasing concern on the effects of smartphone use on mental health. Several researchers have highlighted associated problems, including the effects upon sleep (see previous article), depression, and anxiety. In fact, there are several papers that consider certain smartphone use to be an addictive behavior. At the same time, if you do a literature search using the term “smartphone” you will find that the majority of research involves interventions using smartphones to help mental health outcomes.

So which is it? Are smartphones a help or a hindrance? I suspect it’s both. That is, smartphones can enhance our lives and be a tool for treating mental health problems, AND certain use can be highly problematic. Today, I’m going to review a study on smartphone use comparing people who fall into 3 groups: No smartphone use, low smartphone users, and heavy smartphone users. You can check out the study yourself here.

The authors recruited 319 people to participate in the study and gave them a few questionnaires about sleep, depression, and anxiety. In addition, they gave those who used smartphones a questionnaire called the Smartphone Addiction Scale (SAS).

How Did They Make Groups?

  • Those who didn’t report using smartphones were obviously in the “non-user” group. There were 71 people in this group.
  • To decide who was a “low user” and a “high user” they used the median on the Smartphone Addiction Scale. Those below the median were categorized into the low group (n = 121), and those about it were categorized into the high group (n = 127). Just so you know, some statisticians would probably object to this method of categorizing them as it can inflates the differences. Consider this when you see the results.

What Did They Find?


In general, the results showed that more smartphone use was highly correlated with more depressive symptoms. Those who were in the high-user group had by far the highest levels of depressive symptoms (30% more than other groups).

Non-User vs. Low-User Non-User vs. High-User Low-User vs. High-User
Non-users had more depressive symptoms No differences High-users had more depressive symptoms

They also looked at the amount of people in each group who met criteria for depression, finding that 20% of the high-user group were depressed whereas 7% of the low-user group were depressed.


Again, more smartphone use was very highly correlated with more anxiety. And again, those in the high-user group had the highest anxiety (30% more than other groups). Interesting that low users had less anxiety than people without smartphones, but the researchers didn’t go into this finding at all.

Non-User vs. Low-User Non-User vs. High-User Low-User vs. High-User
Non-users had more anxiety symptoms No differences High-users had more anxiety symptoms


More smartphone use was in general correlated with more sleep problems. It was also correlated to other problems including subjective quality of sleep, sleep disturbance, and daytime dysfunction. However, the groups did not significantly differ with each other across the board.

Non-User vs. Low-User Non-User vs. High-User Low-User vs. High-User
No differences No differences No differences

Prediction Analyses

They found that depression and anxiety predicted poorer sleep. They found that the combinations of high phone use and poor sleep predicted both depression and anxiety.


This paper showed that depression and anxiety are related to smartphone use. This is a consistent result with previous research. In their discussion the researchers went into depth on the relation between sleep, mood, and electronics. Basically, much of the research shows that heavy electronics use is related to mood and sleep problems. Several researchers have shown that electronics use affect sleep, which then impairs mood. However, the current researchers argued that their data shows that heavy smartphone use leads to depression/anxiety, which then leads to sleep problems. They didn’t actually compute mediational analyses to fully support this conclusion, however. Nor did they conduct a study that gives causal data.


There were a few weaknesses with the study. First, the analyses are correlational. As such, the entire focus of smartphones predicting problems in mood and sleep could be backwards. Remember, there have not been any experimental studies to date using smartphones that looked at mood and anxiety. As such, it is possible that it is low mood and high anxiety that result in more smartphone use. Conceptually this makes as much sense as smartphones resulting in more mood/anxiety problems.

The data that sleep is affected by electronics use has more support in the literature than research with mood and anxiety. However, to date the research shows that high smartphone use is related to mood and anxiety problems, and the authors pointed out a few possible mechanisms including the interference with sleep and that it can be an avoidance and withdrawal strategy.

Second, remember how they split the groups? This could really affect the conclusions in a meaningful way. There will have been people only 1 or 2 points different on the Smartphone Addiction Scale that will have been categorized as high or low respectively. I wish they had plotted the actual data so we could see the real results of each participant in order to better interpret the data.

Third, this was only in college students and at one-point in time, so how it relates to both teen and adult populations over time is unclear.

More research on this topic will be done in the coming years and I’m excited to see what comes out. This is good data to start understanding the specific role of smartphones in mental health.

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