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青少年网络使用问题类型及其相关因素。

Problematic internet use profiles and their associated factors among adolescents.

机构信息

Forensic Psychology Unit of the Centre for Applied Psychology, Miguel Hernández University of Elche, Alicante, Spain.

Department of Psychology, Faculty of Medicine, Catholic University of Murcia, Murcia, Spain.

出版信息

J Res Adolesc. 2024 Dec;34(4):1471-1485. doi: 10.1111/jora.13014. Epub 2024 Aug 20.

Abstract

The cognitive-behavioral model of generalized Problematic Internet Use (PIU) is the theoretical approach that has obtained the most evidence on the study of this problem, which includes four components: Online Social Preference, Mood Regulation, Deficient Self-Regulation, and Negative Outcomes. This study aimed to identify PIU profiles using Latent Profile Analysis, and to analyze the differences in them attending to some of the principal PIU risk and protective factors. A total of 675 Spanish adolescents completed questionnaires assessing PIU, Internet usage, mental health problems, personality, psychological strengths, and family relationships. Four profiles were obtained: Nonproblematic use (68.30% of the sample), Slightly problematic use (17.90% of the sample), Problematic use (8.50% of the sample), and Severe problematic use (5.40% of the sample). Results showed differences between them, with the profile with more PIU having more risk factors and less protective factors. Results showed that many different personal and social variables included in the study play a role in PIU. Knowing the different PIU profiles can help in the design of more specific and precise procedures and instruments for risk assessment, as well as aiding in prevention and in the design of more individualized treatments.

摘要

广义网络成瘾问题的认知-行为模型是研究这一问题最具证据的理论方法,它包括四个组成部分:在线社交偏好、情绪调节、自我调节不足和负面后果。本研究旨在使用潜在剖面分析来识别网络成瘾问题的不同类型,并分析它们在一些主要的网络成瘾风险和保护因素方面的差异。共有 675 名西班牙青少年完成了评估网络成瘾、互联网使用、心理健康问题、人格、心理优势和家庭关系的问卷。共得到四个类型:非问题性使用(样本的 68.30%)、轻度问题性使用(样本的 17.90%)、问题性使用(样本的 8.50%)和严重问题性使用(样本的 5.40%)。结果表明,它们之间存在差异,具有更多网络成瘾问题的类型具有更多的风险因素和更少的保护因素。研究结果表明,研究中包含的许多不同的个人和社会变量在网络成瘾问题中发挥了作用。了解不同的网络成瘾类型可以帮助设计更具体和精确的风险评估程序和工具,以及促进预防和设计更个性化的治疗方法。

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