Our lives are filled with linear relationships. Pedaling your bike harder makes you go faster in direct proportion to how hard you pedal. If you always tip 15%, then the amount of your tip will be a linear function of the amount of the bill. But in nature, relationships are not always linear. For example, if your body temperature deviates too much from 98.6° in either direction you’ll be sick. You could say that 98.6° is the sweet spot which you should try to maintain.
An example of a sweet spot from psychology is the Yerkes-Dodson law which describes the inverted U-shaped relationship between motivation and performance. Increased motivational arousal improves performance up to a point; you perform better if you are energized. However, if you are under too much pressure, you get anxious and your performance suffers. There is an optimal level of arousal—a sweet spot—but its exact location varies with the individual, the nature of the task, etc.
Sometimes good social policy is a matter of finding the sweet spot. For example, how much should the government pay in unemployment insurance, so that the unemployed don’t become impoverished but are still motivated to look for work.
The average amount of time adolescents in Great Britain spent online increased from 8 hours per week in 2005 to 19 hours per week in 2015. Is this good or bad for their mental health? Most social critics suggest that the effect is negative. They propose some form of displacement hypothesis—that time spent online displaces other activites that are potentially more valuable, such as studying, exercising or socializing with friends. However, evidence for it is weak. Przybylski and Weinstein note that online activity also teaches valuable social skills. They suggest that there is an inverted U-shaped relationship between time spent online and mental well-being. The call it the “Goldilocks hypothesis,” since, like the temperature of porridge, there is an amount of time spent online that is “just right.” Their research is an attempt to find this sweet spot.
The participants in their survey were slightly over 120,000 15-year-old British young people, recruited from the database of the U. K. Department of Education. They were asked how many hours they spent per day, separately for weekdays and weekends, engaging in these four activites: (A) watching TV and movies, (B) playing video games, (C) using computers, and (D) using smartphones. They were also asked to complete the Warwick-Edinburgh Mental Well-Being Scale, a 14-item self-report scale measuring “happiness, life-satisfaction, psychological functioning and social functioning.” Here it is. It could just as easily be described as a measure of optimism or self-esteem.
Here are the average amounts of time boys and girls reported spending on each of the four activities on weekdays (top) and weekends (bottom). Our gender stereotypes are confirmed. Boys spent more time playing video games, and girls spent more time on each of the other three, but especially the telephone.
The correlations between time spent on the four activites and mental well-being are shown below, separately for weekdays and weekends. (A = TV and movies, B = video games, C = computers, and D = smartphones.) The data analyses statistically controlled for gender, race and socioeconomic status.
The hypothesis that there would be a non-linear relationship between time spent on these activities and mental health is supported. In all cases, doing some of the activity was better than doing none of it. The sweet spots tended to be down around one or two hours per day. Longer times spent at these activities were associated with better mental health when they occurred on weekends than on weekdays.
Although these relationships are statistically significant because of the large sample size, the authors note that the four activities each only accounted for 1% or less of the variability in their measure of mental well-being. This was only about one-third of the size of its association with eating breakfast regularly or getting a good night’s sleep.
Since these data are correlational, it is necessary to remember that correlation does not mean causation. The authors sometimes slip into the habit of thinking that too much online activity is a cause of poor mental health, for example, when they speak of “harmful effects” of online activity. However, the reverse causal order is possible. That is, if a teenager’s psychological or social functioning is poor, he or she may find more satisfaction in solitary pastimes.
It should also be noted that these are self-report measures, and self-report measures share sources of variability that may have little to do with the measures themselves. Consider social desirability bias—the tendency of people to answer questions in a way that they think others will view favorably. It’s usually considered socially desirable to claim to have good mental health. On the other hand, teenagers probably think it’s socially undesirable to admit spending too much time online. Therefore, the relationships found in this survey could be due in part to their joint association with social desirability bias.
The tentative bottom line is that there probably is a sweet spot for time spent in online activities and it is probably a fairly short time each day. However, time spent with electronic media is not strongly associated with mental health, at least as measured by this instrument.
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