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Identifying Problematic Internet Users: Development and Validation of the Internet Motive Questionnaire for Adolescents (IMQ-A)

BACKGROUND: Internationally, up to 15.1% of intensive Internet use among adolescents is dysfunctional. To provide a basis for early intervention and preventive measures, understanding the motives behind intensive Internet use is important. OBJECTIVE: This study aims to develop a questionnaire, the I...

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Detalles Bibliográficos
Autores principales: Bischof-Kastner, Christina, Kuntsche, Emmanuel, Wolstein, Jörg
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications Inc. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4210952/
https://www.ncbi.nlm.nih.gov/pubmed/25299174
http://dx.doi.org/10.2196/jmir.3398
Descripción
Sumario:BACKGROUND: Internationally, up to 15.1% of intensive Internet use among adolescents is dysfunctional. To provide a basis for early intervention and preventive measures, understanding the motives behind intensive Internet use is important. OBJECTIVE: This study aims to develop a questionnaire, the Internet Motive Questionnaire for Adolescents (IMQ-A), as a theory-based measurement for identifying the underlying motives for high-risk Internet use. More precisely, the aim was to confirm the 4-factor structure (ie, social, enhancement, coping, and conformity motives) as well as its construct and concurrent validity. Another aim was to identify the motivational differences between high-risk and low-risk Internet users. METHODS: A sample of 101 German adolescents (female: 52.5%, 53/101; age: mean 15.9, SD 1.3 years) was recruited. High-risk users (n=47) and low-risk users (n=54) were identified based on a screening measure for online addiction behavior in children and adolescents (Online-Suchtverhalten-Skala, OSV(K)-S). Here, “high-risk” Internet use means use that exceeds the level of intensive Internet use (OSV(K)-S sum score ≥7). RESULTS: The confirmatory factor analysis confirmed the IMQ-A’s 4-factor structure. A reliability analysis revealed good internal consistencies of the subscales (.71 up to .86). Moreover, regression analyses confirmed that the enhancement and coping motive groups significantly predicted high-risk Internet consumption and the OSV(K)-S sum score. A mixed-model ANOVA confirmed that adolescents mainly access the Internet for social motives, followed by enhancement and coping motives, and that high-risk users access the Internet more frequently for coping and enhancement motives than low-risk users. Low-risk users were primarily motivated socially. CONCLUSIONS: The IMQ-A enables the assessment of motives related to adolescent Internet use and thus the identification of populations at risk. The questionnaire enables the development of preventive measures or early intervention programs, especially dealing with internal motives of Internet consumption.