A study using functional magnetic resonance imaging (fMRI) compared the brain activities of people with smartphone addiction (excessive smartphone use) and those who use their smartphone less intrusively. He reported systematic differences in brain activity during rest between the two groups.
Additionally, two fMRI indicators of neural activity were found to correlate with psychological ratings of excessive smartphone use. The study was published in Brain and behavior.
A growing number of studies in recent years have highlighted the negative physical and psychosocial effects of excessive smartphone use, also known as “smartphone addiction”. Studies have shown that excessive smartphone use has many similarities to other addictive disorders.
These include inability to resist smartphone use, withdrawal from social relationships, continued use despite awareness of negative consequences, and deceiving others regarding time spent on the phone. utilize.
Excessive smartphone use is very similar to “Internet gaming disorder (IGD),” which is a recognized disorder included in the Diagnostic and Statistical Manual of Mental Disorders, the manual that health practitioners in the United States States use as a guide to diagnose mental disorders.
Studies have shown that people with excessive smartphone use behaviors may experience structural and functional changes in their brains, such as reduced gray matter volume or intrinsic neural activity in the region of the brain called the cingulate cortex. anterior, impaired functional connectivity and activity changes in various parts. of the cortex when processing emotions.
“Because of its similarities to Internet gaming disorder (IGD), there is an ongoing debate as to whether excessive smartphone use (ESU) is a facet of IGD or a distinct form. addictive behavior,” study authors Mike M. Schmitgen and Robert Christian said. Wolf from the Cognitive Neuropsychiatry Working Group at the University of Heidelberg.
“In this article, we wanted to expand existing knowledge about the putative neural mechanisms underlying ESU using multivariate data fusion methods to capture joint information in brain structure and resting-state activity.
To investigate whether excessive smartphone use behaviors differ from the general population in terms of gray matter volume in certain areas of the brain and indicators of spontaneous brain activity (amplitude of low-frequency fluctuations – ALFF), researchers conducted a study using functional magnetic resonance imaging.
After recruiting participants through advertisements, flyers and social media, they selected a pool of 44 participants. These were divided into a smartphone addiction group (SPA, 20 people, 14 women) and a no smartphone addiction group (n-SPA, 24 people, 17 women) based on psychological assessments (short version Smartphone Addiction Scale). Wanting to differentiate between smartphone addiction and Internet gaming disorder, the researchers excluded anyone with this disorder from the sample.
All participants completed another more comprehensive assessment for smartphone addiction (Smartphone Addiction Inventory – SPAI-I) and depression assessment (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 article reported on the results of resting-state analysis – a scan taken while participants were at rest and asked to close their eyes.
Two resting-state fMRI components that differed between the two groups were found. “One of these networks primarily comprised areas of the frontal cortex, while the other primarily comprised parietal and cerebellar regions,” Schmitgen and Wolf told PsyPost.
“Aberrant activity of both networks has previously been suggested in addictive disorders, including IGD. It is possible that in people with ESU, the same systems may drive addictive behavior, at least in part. At this In this regard, it should be noted 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 the specifics of neural functioning in people prone to excessive smartphone use, but it also has some limitations. Notably, the sample was small and mental disorders that might impact neural functioning were not reported by participants.
“The sample size was relatively small and a structured clinical assessment of potentially confounding comorbid mental disorders was not performed,” the researchers explained. “In this regard, it should be noted that we excluded people with IGD using only screening tools. Also, it is important to note that this was a cross-sectional study, so no firm conclusions can be drawn regarding the temporal stability of our results.
“Future studies should include more subjects, examine more closely the role of depressivity or anxiety in ESU, should include specific tasks to establish convincing brain-behavior relationships, allow comparisons between people with of ESU and IGD and should follow a longitudinal design to allow robust inference on temporal development and stability.
“As always, we would like to thank all study participants for their interest in this study and for the time they were willing to spend with us while conducting the surveys,” the researchers added.
The article, “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.
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