个人健康观念对网络成瘾行为的影响

Mustafa Filiz, Y. Karagöz
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摘要

研究目的本研究旨在确定个人健康感知对网络成瘾倾向的影响,并根据各种人口统计学变量确定个人健康感知和网络成瘾倾向的差异。材料和方法:研究样本包括居住在土耳其伊斯坦布尔的 400 名 18 岁以上的人。数据收集工具为个人健康认知量表和网络成瘾严重程度量表。采用 t 检验和方差分析进行差异分析,采用相关分析检验量表各子维度之间的关系方向和多重联系问题,并采用多元回归分析确定个人健康感知对网络成瘾倾向的影响。结果显示结果表明,参与者表现出低于平均水平的网络软弱症倾向,但对自己的健康状况保持良好的认知。经研究发现,婚姻状况、性别、年龄、收入水平、居住地、医疗机构类型或每年到医院就诊的频率在健康认知方面没有明显差异。值得注意的是,与拥有副学士学位或高中文凭的人相比,拥有学士学位的人表现出更明显的网络ondria 行为。数据还强调了个人健康观念与网络软弱症倾向之间的显著相关性。结论研究得出结论,49% 的个人网络成瘾水平是由健康观念造成的。研究发现,教育因素对个人健康认知和网络成瘾倾向有显著影响,但性别、年龄、收入、居住地类型、医院类型和每年医院就诊情况等人口统计学因素没有任何影响。建议针对特定教育群体设计个性化的宣传活动或干预措施,以纠正潜在的误解,提高健康素养。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
THE IMPACT OF INDIVIDUAL HEALTH PERCEPTION ON CYBERCHONDRIA BEHAVIOR
Objectives: The aim of this study is to determine the effect of individual health perception on cyberchondria tendency and to identify differences in individual health perception and cyberchondria tendency according to various demographic variables. Material and Methods: The sample of the study consists of 400 individuals over the age of 18, residing in Istanbul, Turkiye. The individual health perception scale and cyberchondria severity scale were used as data collection tools. The t-test and ANOVA tests for difference analyses, correlation analysis to examine the direction of the relationship and multiple connection problem between sub-dimensions of the scale, and multiple regression analysis were used to determine the effect of individual health perception on cyberchondria tendency. Results: The results indicate that participants exhibit sub-average tendencies towards cyberchondria but maintain favorable perceptions of their health. Upon examination, no significant variations in health perception were identified based on marital status, gender, age, income level, place of residence, healthcare facility type, or annual frequency of hospital visits. Notably, individuals with a bachelor's degree manifested more pronounced cyberchondria behaviors compared to those with associate degrees or high school diplomas. The data also underscores a significant correlation between individual health perceptions and the propensity towards cyberchondria. Conclusion: It was concluded that 49% of individuals' cyberchondria levels are explained by health perception. It was found that the education factor had a significant effect on individual health perception and cyberchondria tendency, but demographic factors such as gender, age, income, type of settlement, type of hospital, and annual hospital visit status did not have any effect. It is recommended to design customized informational campaigns or interventions aimed at specific educational groups to correct potential misunderstandings and improve health literacy.
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