The effect of digital obesity and phubbing level on life satisfaction: latent profile analysis.

IF 2.7 3区心理学 Q1 PSYCHOLOGY, MULTIDISCIPLINARY

BMC Psychology Pub Date : 2024-12-18 DOI:10.1186/s40359-024-02256-w

Muhammet Ali Aydin, Metin Yıldız, Mübin Kiyici, Mehmet Yildiz, Ali Kirksekiz, Şeyda Kızıloğlu

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Abstract

Background: In this study, the effects of individuals' digital obesity and phubbing behaviors on their life satisfaction were investigated by latent profile analysis (LPA) method. LPA is a statistical technique used to identify unobserved subgroups within a population based on individuals' responses to various observed variables.

Methods: The present study was conducted in a correlational cross-sectional descriptive design between November 2023- January 2024. Digital obesity scale, phubbing scale, life satisfaction scale were used in this study.

Results: As a result of LPA, Class 1 (Low Digital Addicts) has the lowest arithmetic mean in all indicators. When life satisfaction was analyzed on the basis of the classes, it was found out that Class 2 (High Digital Addicts), which was collected in the group with high levels of digital obesity and phubbing, had lower life satisfaction. Considering the demographic levels of individuals according to class level, it was concluded that high digital addiction was more common among individuals with secondary and postgraduate education.

Conclusions: In the present study, two classes were found as a result of LPA. In the analysis, Class 1(Low Digital Addicts) was found to have the lowest arithmetic mean in all indicators. On the other hand, when life satisfaction was analyzed according to the classes, it was detected that Class 2 (High Digital Addicts) life satisfaction was lower in the group with high levels of digital obesity and phubbing. In the study, the life satisfaction of class 1, which is characterized as low digital addicts, was found to be higher. Longitudinal studies on digital addictions affecting life satisfaction are recommended.

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数字肥胖和低头水平对生活满意度的影响：潜在剖面分析。

背景：本研究采用潜在特征分析（latent profile analysis， LPA）方法，研究了数字肥胖和低头行为对生活满意度的影响。LPA是一种统计技术，用于根据个体对各种观察变量的反应来识别人群中未观察到的亚群。方法：本研究采用相关横断面描述性设计，时间为2023年11月至2024年1月。本研究采用数字肥胖量表、低头症量表、生活满意度量表。结果：由于LPA， 1类（低数字成瘾）在所有指标中的算术平均值最低。在对生活满意度进行分类分析的结果显示，2类（高数字成瘾者）的生活满意度较低，这些人是数字肥胖和低头症的高发人群。考虑到不同阶层个体的人口统计水平，结论是高数字成瘾在中学和研究生学历的个体中更为常见。结论：在本研究中，LPA可分为两类。在分析中发现，1类（低数字成瘾）在所有指标中的算术平均值最低。另一方面，当生活满意度根据类别进行分析时，发现第2类（高数字成瘾者）生活满意度在数字肥胖和低头症水平较高的群体中较低。在这项研究中，被认为是低数字成瘾的第一类人的生活满意度更高。建议对影响生活满意度的数字成瘾进行纵向研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

BMC Psychology Psychology-Psychology (all)

CiteScore

3.90

自引率

2.80%

发文量

265

审稿时长

24 weeks

期刊介绍： BMC Psychology is an open access, peer-reviewed journal that considers manuscripts on all aspects of psychology, human behavior and the mind, including developmental, clinical, cognitive, experimental, health and social psychology, as well as personality and individual differences. The journal welcomes quantitative and qualitative research methods, including animal studies.