Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ IRIS - Institutional...arrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
https://doi.org/10.31219/osf.i...
Article . 2023 . Peer-reviewed
License: CC BY
Data sources: Crossref
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
Addictive Behaviors
Article . 2023 . Peer-reviewed
License: CC BY
Data sources: Crossref
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
Serveur académique lausannois
Article . 2023
License: CC BY
versions View all 7 versions
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

Deconstructing the components model of addiction: an illustration through "addictive" use of social media

Authors: Loïs Fournier; Adriano Schimmenti; Alessandro Musetti; Valentina Boursier; Maèva Flayelle; Ilaria Cataldo; Vladan Starčević; +1 Authors

Deconstructing the components model of addiction: an illustration through "addictive" use of social media

Abstract

The components model of addiction posits that all addictions share six components, namely salience, tolerance, mood modification, relapse, withdrawal, and conflict. This highly influential model has resulted in the development of numerous psychometric instruments that measure addictive behaviors according to these criteria. However, recent research suggests that, in the context of behavioral addictions, certain components constitute peripheral features that do not distinguish non-pathological from pathological behavior. Using “addictive” use of social media as a representative example, we examined this perspective by testing whether these six components actually assess central features of addiction, or whether some of them constitute peripheral features that are not indicative of a disorder. Four independent samples totaling 4,256 participants from the general population completed the Bergen Social Media Addiction Scale, a six-item psychometric instrument derived from the components model of addiction to assess social media “addiction”. By performing structural equation modeling and network analyses, we showed that the six components did not form a unitary construct and, crucially, that some components (i.e., salience, tolerance) were not associated with measures assessing psychopathological symptoms. Taken together, these results suggest that psychometric instruments based on the components model conflate central and peripheral features of addiction when applied to behavioral addictions. This implies that such instruments pathologize involvement in appetitive behaviors. Our findings thus call for renewing the conceptualization and assessment of behavioral addictions.

Countries
Switzerland, Italy
Keywords

Psychometrics, 150, Humans; Social Media; Behavior, Addictive/epidemiology; Psychometrics; Behavioral addiction; Components model; Network analysis; Social media use; Structural equation modeling analysis, Network analysi, Components model, Behavior, Addictive, Structural equation modeling analysis, Humans, Network analysis, Behavioral addiction, Social media use, Social Media, Behavioral addiction; Components model; Network analysis; Social media use; Structural equation modeling analysis

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    68
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
68
Top 1%
Top 10%
Top 1%
Green
hybrid