The vast social experiment that is underway in the time of COVID-19 is going to yield fascinating data about human behavior for years to come. Some scientists are already examining the first samples of such data to formulate hypotheses about how interventions such as lockdown may be affecting people.
A study conducted jointly between the Icahn School of Medicine at New York's Mount Sinai Hospital and researchers in Spain found that people took more steps during lockdown when using social media apps such as Facebook and WhatsApp, according to write-up of the workposted Sunday on the pre-print server medRxiv.
The study design itself is an interesting window into the trends in research. It comes out of prior work done with smartphones and wearable technology to track people's behavior over time, and so it represents the new angle that mobile technology is having on research.
In the study, 127 volunteers in Spain who were psychiatric out-patients volunteered to carry a smartphone that tracked how many steps they took per day, and how much they used apps like Facebook. The volunteers were recorded for 38 days before Spain went into its COVID-19 lockdown on March 14th, and then another 45 days following the start of the lockdown, to compare patterns. A statistical model calculated whether there was any link between steps taken and social media use.
The principal drive of the study was concern over the "potential negative effects" of measures such as quarantine on health, especially such basic things as reduced physical activity. The authors were exploring whether social media can be a help to people in lockdown.
As they write, "we tested the hypothesis that people who experienced greater digital social interaction would be less vulnerable to negative effects of strict social distancing measures imposed during the Covid-19 pandemic."
The primary finding was that the amount of social media app use on the phone predicted how many steps a person would take the next day to a statistically significant degree.
"Increased social media and smartphone use on a particular day predicted an increased number of steps recorded by that user the next day," states the study.
The study, titled, "Social media and smartphone app use predicts maintenance of physical activity during Covid-19 enforced isolation in psychiatric outpatients," was written by lead author Agnes Norbury of the Icahn School's department of psychiatry, and co-senior authors M. Mercedes Perez-Rodriguez of the Icahn School and Enrique Baca-Garcia of Spain's University Hospital Jimenez Diaz Foundation in Madrid. Multiple researchers from participating institutions in Spain, Chile and France also collaborated on the work; and the study was helped by a Spanish firm that develops artificial intelligence-based mobile apps,Evidence-Based Behavior.
Because the study is a pre-print and has not yet been peer-reviewed, its findings should be taken with caution.
While the findings show a positive link between social apps and taking steps, the findings themselves don't explain what causal link, if any, there may be.
However, Norbury and team offer a conjecture as to what the findings may be saying.
"We propose that social interaction promotes engagement in physical activity by guarding against inertia and apathy associated with low mood," they write.
The study draws upon statistical methodology that has been developed over the past decade known as a network approach. In a network approach, mental phenomena are seen as interactions of symptoms that can be observed through a time-series statistical analysis.
In the network model, phenomena such as fatigue and insomnia can be plotted as nodes on the graph of a network and the edges between nodes are the weights given to how one phenomenon may be related to the other. The tool used to model those interactions is an approach known as a vector autoregression.
Norbury and team take a particular approach to autoregression that is called aGaussian graphical model, developed by Sacha Epskamp and colleagues at the psychology departments of the University of Amsterdam and the University of Edinburgh. The Gaussian approach lets one compare things that happen in time to a single individual with so-called cross-sectional measures that see how subjects in a study compare to one another.
What forms the background to the work are recent studies suggesting the deleterious effects of lockdown. One study, by Sandro Galea and colleagues at Boston University,published in the Journal of the American Medical Association in April, notes that "large-scale disasters," including natural disasters, "are almost always accompanied by increases in depression, posttraumatic stress disorder (PTSD)," and other negative mental health effects.
The Icahn study is particularly concerned with people in vulnerable populations, in particular people with pre-existing psychological disorders. Over half the subjects in the study had been diagnosed with anxiety, trauma, or stress-related disorder. A large percentage had been diagnosed with unipolar or bipolar depression.
The work builds on two prior research studies in Spain that rely heavily on mobile technology and statistics gathering.
One study, titled "Assessment of e-Social Activity in Psychiatric Patients," was written up a year ago. Authored by Pablo Bonilla-Escribano of Spain's Universidad Carlos III de Madrid, and colleagues, that study tracked "daily usage patterns of phone calls and social and communication apps" in order to detect patterns of behavior between patients.
Another study published in 2018, calledSmartcrises, lead by Sofian Berrouiguet of the Brest Medical University in Brest, France, followed out-patients in Madrid by smartphone app and via digital armbands. The purpose of the study was to detect the "relationship between suicide risk and changes in sleep quality and disturbed appetite."
As such, the Icahn study is part of an ongoing trend of monitoring and assessment heralded by the smartphone age. As Berrouiguet writes of the Smartcrises study, "the data digital footprints, which is the automatically accumulated by-products of technological devices, offer a promising opportunity for research and clinical decision making."
How sure are Norbury and colleagues about the link between social media and physical activity? Causal certainty is a challenge for such statistical studies in general. The authors acknowledge there could be hidden factors that explain both higher social media usage and more physical activity, rather than one directly affecting the other.
"It is possible that some unmeasured factor influenced both smartphone use and physical activity with varying time delays, resulting in spurious dependencies between the two," they write.
At the very least, their work, they suggest, is cause to look more carefully at the role of technology in life. The effect of social media on wellbeing is a complex matter, they write, and some who worry about the role of social media may want to take another look. "We second recent calls for a greater emphasis on nuance in this debate."
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