Early warning mechanism for college student adaptation: a network analysis and computational intervention simulation study based on mind wandering and problematic short video use
Mao Z, Yang Y, Jiang Y
Frontiers in psychology · 0 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
- National Social Science Fund of China
Según 1 financiador declarado y la declaración de financiación del texto completo.
Publicación
- Publicado
- 2026-03-17 · Front Psychol · vol. 17 · pág. 1739818
- Editorial
- Frontiers Media
- Citado
- 0 citas · más que el 18% de estudios similares · 0.0× el promedio de su campo
- Referencias
- 66 trabajos
- Acceso
- Acceso abierto (revista) · CC-BY
- Áreas de investigación
- Mind wandering and attention · Mental Health Research Topics · Impact of Technology on Adolescents
- Palabras clave
- mind wandering, academic adjustment, attention deficits, cognitive control, early warning indicators, intervention simulation, first-year students, digital media use, mental health education
3 autores
- Zheng Mao🇨🇳Inner Mongolia Normal University
- Yisheng Yang🇨🇳Inner Mongolia Normal University
- Yongzhi Jiang · autor de correspondencia
Resumen
El texto original del estudio, en el idioma en que se publicó.
Introduction
The adaptation challenges of college freshmen represent a core issue in higher education psychology research. With the rapid development of digital media, this study aims to examine the complex interactions between mind wandering and problematic short video use during the critical period of academic adaptation from a cognitive control perspective.
Methods
A total of 1,989 Chinese college freshmen (M = 18.3, SD = 0.6) participated in this cross-sectional study. An Ising model network was constructed to estimate the conditional dependency relationships between specific symptoms of mind wandering and problematic short video use. Subsequently, the NodeIdentifyR algorithm (NIRA) was applied to conduct computational intervention simulations to identify the most effective intervention targets within the network.
Results
The network analysis identified two distinct but interconnected symptom communities. Mind wandering during lectures (MW5), inability to pay full attention when doing things (MW3), and difficulty maintaining focus on simple or repetitive tasks (MW1) were identified as key bridge symptoms connecting the two sub-networks. Furthermore, computational simulation results indicated that an alleviating intervention targeting MW5 (reducing its activation level) most effectively decreased the overall severity of problematic short video use.
Discussion
These findings reveal early warning signals of academic adaptation difficulties among college freshmen. By highlighting the pivotal role of specific attention deficits-particularly mind wandering during lectures-this study provides new insights and empirical evidence for designing precise, prevention-oriented interventions in college student mental health education and digital health support.
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