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Disruption of sustained attention and orbitofrontal cortex engagement by incoming social media messages vary as a function of problematic social media use

Liu, X.; Liu, H.; Kendrick, K. M.; Montag, C.; Becker, B.

2024-06-14 neuroscience
10.1101/2024.06.13.598945 bioRxiv
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BackgroundSmartphones and social media have become ubiquitous in our lives, and while debates about their negative impact on mental health, addictive potential, and disruptive effects on daily activities have surged, neurobiological evidence remains scarce. Here, we investigated whether the behavioral and neural effects of interference of continuous attention by incoming social media messages on WeChat varies according to its problematic use as assessed via an addiction framework. MethodsN = 60 healthy individuals were stratified based on their level of problematic WeChat usage as measured by the WeChat Addiction Scale (WAS): LOW (15 males and 15 females) and HIGH (15 males and 15 females) addictive tendencies. Participants underwent an AX-Continuous Performance Task (AX-CPT) with WeChat-associated (incoming message) and neutral auditory distractors as well as a no distractor condition. Concurrent functional Near-Infrared Spectroscopy (fNIRS) assessments of the orbitofrontal cortex (OFC) were implemented to determine the underlying neurofunctional mechanisms. ResultsOn the behavioral level the HIGH group demonstrated faster reaction times during the WeChat and no distractor condition compared to the LOW group. Exploratory analyses indicated that the WeChat distraction decreased left lateral OFC activity in the LOW but enhanced activity in this region in the HIGH group. ConclusionAgainst our hypotheses WeChat distraction enhanced behavioral performance specially in individual with a tendency for problematic WeChat use, with the neural data pointing to less suppression of the OFC in individuals with a tendency for problematic usage. Findings underscore the complexity of the potential effects of new technology on daily live and indicate that addiction models might not be simply extendable to problematic social media usage.

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