Cited by 190Impact of Technology on AdolescentsSexuality, Behavior, and TechnologyGambling Behavior and Treatments

Structural and functional correlates of smartphone addiction

Horvath, Juliane, Mundinger, Christina, Schmitgen, Mike M., Wolf, Nadine D., Sambataro, Fabio, Hirjak, Dusan, Kubera, Katharina M., Koenig, Julian +1 more·2020·Addictive Behaviors

Abstract

Popularity and availability of smartphones have dramatically increased in the past years. This trend is accompanied by increased concerns regarding potentially adverse effects of excessive smartphone use, particularly with respect to physical and mental health. Recently, the term "smartphone addiction" (SPA) has been introduced to describe smartphone-related addictive behavior and associated physical and psychosocial impairment. Here, we used structural and functional magnetic resonance imaging (MRI) at 3 T to investigate gray matter volume (GMV) and intrinsic neural activity in individuals with SPA (n = 22) compared to a control group (n = 26). SPA was assessed using the Smartphone Addiction Inventory (SPAI), GMV was investigated by means of voxel-based morphometry, and intrinsic neural activity was measured by the amplitude of low frequency fluctuations (ALFF). Compared to controls, individuals with SPA showed lower GMV in left anterior insula, inferior temporal and parahippocampal cortex (p < 0.001, uncorrected for height, followed by correction for spatial extent). Lower intrinsic activity in SPA was found in the right anterior cingulate cortex (ACC). A significant negative association was found between SPAI and both ACC volume and activity. In addition, a significant negative association between SPAI scores and left orbitofrontal GMV was found. This study provides first evidence for distinct structural and functional correlates of behavioral addiction in individuals meeting psychometric criteria for SPA. Given their widespread use and increasing popularity, the present study questions the harmlessness of smartphones, at least in individuals that may be at increased risk for developing smartphone-related addictive behaviors.

Integrity signals

Registry

Crossref · 10.1016/j.addbeh.2020.106334

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

The citation lists haven’t been fetched yet

References 64 · Cited by 190

Authors
Horvath, J., Mundinger, C., Schmitgen, M. M., Wolf, N. D., Sambataro, F., Hirjak, D., Kubera, K. M., Koenig, J., & Christian Wolf, R.
Affiliations
  • Heidelberg University (DE)
  • University of Padua (IT)
  • University of Bern (CH)
Venue
Addictive Behaviors
Publisher
Elsevier BV
Published
2020-06
Volume
105
Pages
106334
ISSN
0306-4603 (ISSN-L)
OpenAlex
W3003467276
Cited by
190
References
64
Citations by year
2026: 23 · 2025: 20 · 2024: 31 · 2023: 29 · 2022: 35 · 2021: 41 · 2020: 11
FWCI
38.86
Type
journal article
Language
en
Open access
closed
Locations
  • Addictive Behaviors (publishedVersion)
  • PubMed (publishedVersion)
  • Bern Open Repository and Information System (University of Bern) (submittedVersion)
  • Padua Research Archive (University of Padova) (submittedVersion)
Topics
  • Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
  • Social Sciences › Psychology › Clinical Psychology › Sexuality, Behavior, and Technology
  • Social Sciences › Psychology › Clinical Psychology › Gambling Behavior and Treatments
Keywords
smartphone addiction, behavioral addiction, gray matter volume, amplitude of low-frequency fluctuation, anterior insula, anterior cingulate cortex, orbitofrontal cortex, inferior temporal cortex, parahippocampal cortex
MeSH terms
Internet Addiction Disorder, Adolescent, Adult, Brain, Female, Humans, Magnetic Resonance Imaging, Male, Young Adult, Neuroimaging, Gray Matter

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review