Evidence map›Paper›PMID 40256627›Full record

ReviewAddictive behaviors reports2025

Toward the classification of social media use disorder: Clinical characterization and proposed diagnostic criteria.

Tania Moretta, Elisa Wegmann

Abstract readReview
In one paragraph

Review in Addictive behaviors reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Tania MorettaInstitute of Cognitive Sciences and Technologies, National Research Council of Italy, Rome, Italy.
Elisa WegmannDepartment of General Psychology: Cognition, University of Duisburg-Essen, Forsthausweg 2, 47057 Duisburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Empirical studies and theoretical models highlight that problematic use of social media can lead to significant functional impairments in several domains, such as social, relational, occupational, and psychological functioning, as well as physical health. However, social media use disorder is not currently recognized as an official disorder in major diagnostic systems, limiting comparability among studies, precise prevalence estimation, and ad-hoc preventive and treatment program development. The present work aims to classify social media use disorder as a pathological condition sharing main mechanisms and maladaptive patterns with addictive behaviors. We discuss diagnostic criteria for social media use disorder by integrating peculiar features of this maladaptive behavior with criteria for substance use disorders and behavioral addictions from major diagnostic systems (i.e., DSM-5 and ICD-11). Moreover, we address some controversies related to the classification of social media use disorder as a behavioral addiction and highlight literature findings indicating social media use disorder shares main alterations in mechanisms and processes characterizing addiction (i.e., maladaptive activation of reward systems and impairment of inhibitory control mechanisms). Despite the lack of studies including clinical populations and the need for future research to validate the proposed criteria and refine knowledge of the mechanisms underlying this condition, our work provides a structured framework for classifying and identifying social media use disorder.

Indexed as

AddictionDiagnostic criteriaInhibitiory controlProblematic social networking sites useRewardSocial media use disorderSubstance use disorders

Identifiers

PMID40256627
PMCPMC12008647

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.