A study using functional magnetic resonant imaging (fMRI) compared brain activities of persons suffering from smartphone addiction (excessive smartphone use) and those who use their smartphones in a less intrusive way. It reported systematic differences in brain activity during rest between the two groups.
Additionally, two fMRI indicators of neural activity were found to be correlated with psychological assessments of excessive smartphone use. The study was published in Brain and Behavior.
A growing number of studies in recent years emphasized negative physical and psychosocial effects of excessive use of smartphones, also known as “smartphone addiction”. Studies have shown that excessive smartphone use has many similarities to other addictive disorders.
These include the failure to resist the use of the smartphone, withdrawal from social relations, continuation of use despite being aware of negative consequences and deception of others regarding the amount of time spent using it.
Excessive smartphone use is very similar to the “internet gaming disorder (IGD)”, which is a recognized disorder included in the Diagnostic and Statistics Manual of Mental Disorders, the handbook health practitioners in the US use as a guide for diagnosing mental disorders.
Studies have shown that individuals with excessive smartphone use behaviors may exhibit structural and functional changes to their brains such as reduced gray matter volume or intrinsic neural activity in the region of the brain called anterior cingulate cortex, altered functional connectivity and changes in activity in various parts of the cortex during processing of emotions.
“Because of its similarities to internet gaming disorder (IGD), there is an ongoing debate on if excessive smartphone use (ESU) is a facet of IGD or a distinct form of addictive behavior,” said study authors Mike M. Schmitgen and Robert Christian Wolf of the Cognitive Neuropsychiatry working group at Heidelberg University.
“In this paper, we wanted to expand the extant knowledge on putative neural mechanisms underlying ESU by using multivariate data fusion methods to capture joint information in brain structure and resting-state activity.”
To study whether people with excessive smartphone use behaviors differ from the general population in gray matter volume in certain areas of the brain and indicators of spontaneous brain activity (amplitude of low frequency fluctuations – ALFF), the researchers conducted a study using functional magnetic resonance imaging.
After recruiting participants through ads, flyers and social media, they selected a group of 44 participants. These were divided into a smartphone addiction group (SPA, 20 persons, 14 females) and a group without smartphone addiction (n-SPA, 24 persons, 17 females) based on psychological assessments (short version of the Smartphone Addiction Scale). Wanting to differentiate between smartphone addiction and the internet gaming disorder, researchers excluded any persons showing this disorder from the sample.
All participants completed another, more comprehensive, smartphone addiction assessment (Smartphone addiction inventory – SPAI-I) and an assessment of depression (Beck Depression Inventory – BDI). Participants underwent functional magnetic resonance imaging (fMRI) four times, “a resting-state scan, three experimental paradigms and a structural scan.” This particular paper reported on results of the resting-state scan — a scan taken while participants were at rest and instructed to close their eyes.
Two resting-state fMRI components that differed between the two groups were found. “One of these networks mainly comprised areas of the frontal cortex, whereas the other one predominantly comprised parietal and cerebellar regions,” Schmitgen and Wolf told PsyPost.
“Aberrant activity of both networks has been previously suggested in addictive disorders, including IGD. It is possible that in persons with ESU, the very same systems could drive addictive behavior, at least partly. In this regard, it is noteworthy that we found associations between neural network strength and time spent with the device as well as for sleep difficulties.”
The study sheds light on specificities of neural functioning of people prone to excessive use of smartphones, but it also has certain limitations. Notably, the sample was small and mental disorders that might have an impact on neural functioning were not reported by the participants.
“The sample size was relatively modest and a structured clinical evaluation of potentially confounding comorbid mental disorders was not performed,” the researchers explained. “In this regard, it should be noted that we excluded persons with IGD using screening tools only. Also, it is important to note that this was a cross-sectional study, so that no definitive conclusions can be made regarding the temporal stability of our findings.”
“Future studies should comprise more subjects, take a closer look at the role of depressiveness or anxiety in ESU, should include specific tasks to establish convincing brain-behavior relationships, enable comparisons between persons with ESU and IGD and should follow a longitudinal design to allow robust inference on temporal development and stability.”
“As always, we’d like to thank all study participants for their interest in this study and for the time that they were willing to spend with us while performing the investigations,” the researchers added.
The paper, “Aberrant intrinsic neural network strength in individuals with “smartphone addiction”: An MRI data fusion study”, was authored by Mike M. Schmitgen, Nadine D. Wolf, Fabio Sambataro, Dusan Hirjak, Katharina M. Kubera, Julian Koenig, and Robert Christian Wolf.
