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Six addiction components of problematic social media use in relation to depression, anxiety, and stress symptoms: a latent profile analysis and network analysis

Peng P, Liao Y

BMC psychiatry · 49 citas

Cómo se estudió

Diseño
Estudio transversal (clasificado por nuestro filtro de IA)
Estudiado en
Personas
Resultado principal
Marcadores de salud y funcionamiento

Quién lo pagó

Financiación
Financiación independiente
Gobierno
STI 2030—Major Projects - "Brain Science and Brain-like Research" Project

Según 1 financiador declarado y la declaración de financiación del texto completo.

Publicación

Publicado
2023-05-08 · BMC Psychiatry · vol. 23 · número 1 · pág. 321
Editorial
BioMed Central
Citado
109 citas · más que el 100% de estudios similares · 50.2× el promedio de su campo
Impacto
Entre el 10 % más citado de su campo
Referencias
53 trabajos
Acceso
Acceso abierto (revista) · CC-BY
Áreas de investigación
Impact of Technology on Adolescents · Mental Health via Writing · Mental Health Research Topics
Palabras clave
social media addiction, salience, tolerance, mood modification, relapse, withdrawal, conflict, depression, anxiety, stress, Bergen Social Media Addiction Scale, symptom networks
MeSH
humans, depression, anxiety, anxiety disorders, mood disorders, social media

2 autores

  • Pu Peng🇨🇳Sir Run Run Shaw Hospital; Second Xiangya Hospital of Central South University; Zhejiang University
  • Yanhui Liao🇨🇳 · autor de correspondenciaSir Run Run Shaw Hospital; Zhejiang University

Resumen

El texto original del estudio, en el idioma en que se publicó.

Backgrounds

Components of addiction (salience, tolerance, mood modification, relapse, withdrawal, and conflict) is the most cited theoretical framework for problematic social media use (PSMU). However, studies criticized its ability to distinguish problematic users from engaged users. We aimed to assess the association of the six criteria with depression, anxiety, and stress at a symptom level.

Methods

Ten thousand six hundred sixty-eight participants were recruited. Bergen Social Media Addiction Scale (BSMAS) was used to detect six addiction components in PSMU. We applied the depression-anxiety-stress scale to assess mental distress. Latent profile analysis (LPA) was conducted based on BSMAS items. Network analysis (NA) was performed to determine the symptom-symptom interaction of PSMU and mental distress.

Results

(1) Social media users were divided into five subgroups including occasional users (10.6%, n = 1127), regular users (31.0%, n = 3309), high engagement low risk users (10.4%, n = 1115), at-risk users (38.1%, n = 4070), and problematic users (9.8%, n = 1047); (2) PSMU and mental distress varied markedly across subgroups. Problematic users had the most severe PSMU, depression, anxiety, and stress symptoms. High engagement users scored high on tolerance and salience criteria of PSMU but displayed little mental distress; (3) NA showed conflict and mood modification was the bridge symptoms across the network, while salience and tolerance exhibited weak association with mental distress.

Conclusions

Salience and tolerance might not distinguish engaged users from problematic users. New frameworks and assessment tools focusing on the negative consequences of social media usage are needed.

Resumen vía Europe PMC. Los derechos de autor siguen siendo de los autores o la editorial (CC BY).

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