Xu Jiayao, Ma Yuyin, Tan Minghui, Lou Jiaxue, Lu JingJing, Zhou Xudong
The Institute of Social Medicine, Zhejiang University School of Medicine, 866 Yuhangtang Road, Hangzhou, 310058, China.
MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK.
BMC Public Health. 2025 Jul 30;25(1):2599. doi: 10.1186/s12889-025-23817-7.
BACKGROUND: With more than 90% penetration of personal digital devices, digital addiction in children has emerged as a significant concern in China. Environmental and socioeconomic stressors in China-a highly collectivist society-may contribute to a higher prevalence of digital addiction. However, there is a lack of culturally adapted tools to assess digital addiction among children in China. OBJECTIVES: This study aimed to: (1) linguistically and culturally adapt the Digital Addiction Scale for Children (DASC) to the Chinese context; (2) examine its psychometric properties, including validity (i.e., construct and convergent validity) and reliability (i.e., internal consistency and test-retest reliability); and (3) establish a potential cut-off score for identifying children at risk of digital addiction. METHODS: The DASC was translated into Chinese and adapted following forward translation, back translation, harmonization and pilot testing with 24 students in grades four to eight to ensure conceptual and semantic equivalence, clarity and cultural relevance. The final Chinese DASC consists of 24 items after excluding item 11. This study employed a cross-sectional design to validate the Chinese version of the DASC. Based on convenience sampling, Nanling County in Anhui Province, China was selected as the study site. Six schools were then chosen using a stratified randomised cluster sampling method, with three strata: urban, peri-urban, and rural areas. Given the feasibility of completing questionnaires independently, students in grades five to eight (aged 12-16 years old) from primary and secondary schools were invited. One class of students in each grade in each selected school was randomly invited to participate. To assess the psychometric properties of the DASC, both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were conducted using SPSS 30.0 and AMOS 28.0, respectively. Convergent validity was evaluated using Pearson correlation coefficients between the DASC and Young's Internet Addiction Test (IAT). Reliability was assessed using Cronbach's alpha for internal consistency, split-half reliability, and test-retest reliability over a two-week interval. Receiver operating characteristic (ROC) curve analysis was conducted to determine the optimal cut-off score, using the IAT as a reference criterion for identifying at-risk individuals. RESULTS: After forward translation, back translation, harmonization and pilot testing, the English version of the DASC was adapted into Chinese. In total, 592 students (age 12.8 ± 1.7 years; 285 girls and 307 boys) participated in the validation study. The 24-item Chinese version of DASC was validated, with item 11 excluded due to cross-loading. Two components (i.e., interpersonal and intrapersonal dimensions) were identified for the Chinese version of the DASC based on exploratory and confirmatory factor analysis (RMSEA = 0.06, CFI = 0.94). The interpersonal dimension includes 19 items related to conflict, problems, displacement, deception, withdrawal and relapse. The intrapersonal dimension comprises 5 items related to mood modification and the perceived importance of digital devices. The DASC demonstrated acceptable convergent validity (r = 0.83 [95% confidence interval (CI) 0.80, 0.85], p < 0.001), internal consistency reliability (Cronbach's alpha 0.95; split-half reliability coefficient 0.885) and test-retest reliability (intraclass correlation coefficient = 0.71 (0.67, 0.75), p < 0.001). Using the IAT as the criterion, the suggested cut-off score for the risk of digital addiction was 53, yielding a sensitivity of 85.9% and specificity of 92.3%. CONCLUSION: The linguistically and culturally adapted Chinese version of the DASC is a reliable and valid instrument, with an established cut-off score for identifying at-risk individuals. However, the results are limited by the use of a single-county sample, the exclusion of younger children (grade 4 and below) and those with cognitive or reading difficulties, and reliance on self-reported data. When appropriately generalized, the Chinese version of the DASC has potential applications in routine school mental health screening, paediatric check-ups to identify at-risk children and national health surveys. Tracking and understanding digital addiction using the DASC enables the development of evidence-based interventions and supports policy recommendations to address digital addiction.
背景:随着个人数字设备普及率超过90%,儿童数字成瘾在中国已成为一个重大问题。在中国这样一个高度集体主义的社会中,环境和社会经济压力因素可能导致数字成瘾的患病率更高。然而,在中国缺乏经过文化调适的工具来评估儿童的数字成瘾情况。 目的:本研究旨在:(1)在语言和文化上对儿童数字成瘾量表(DASC)进行调适,使其适用于中国背景;(2)检验其心理测量特性,包括效度(即结构效度和聚合效度)和信度(即内部一致性和重测信度);(3)确定一个潜在的临界值,以识别有数字成瘾风险的儿童。 方法:通过正向翻译、回译、协调和对24名四至八年级学生进行预测试,将DASC翻译成中文并进行调适,以确保概念和语义等效、清晰以及文化相关性。排除第11项后,最终的中文DASC由24个项目组成。本研究采用横断面设计来验证中文版DASC。基于便利抽样,选取中国安徽省南陵县作为研究地点。然后采用分层随机整群抽样方法选择6所学校,分为三个层次:城市、城郊和农村地区。鉴于学生能够独立完成问卷,邀请了五至八年级(12 - 16岁)的中小学生参与。在每所选定学校的每个年级随机邀请一个班级的学生参与。为了评估DASC的心理测量特性,分别使用SPSS 30.0和AMOS 28.0进行探索性因素分析(EFA)和验证性因素分析(CFA)。使用DASC与杨氏网络成瘾测试(IAT)之间的Pearson相关系数评估聚合效度。使用Cronbach's alpha评估内部一致性信度、分半信度以及两周间隔的重测信度。以IAT作为识别高危个体的参考标准,进行受试者工作特征(ROC)曲线分析以确定最佳临界值。 结果:经过正向翻译、回译、协调和预测试后,DASC的英文版被调适为中文版。共有592名学生(年龄12.8±1.7岁;285名女生和307名男生)参与了验证研究。经过验证,排除第11项后,24项中文版DASC具有良好的效度。基于探索性和验证性因素分析,中文版DASC确定了两个维度(即人际和个人内部维度)(RMSEA = 0.06,CFI = 0.94)。人际维度包括19个与冲突、问题、替代、欺骗、退缩和复发相关的项目。个人内部维度包括5个与情绪调节和对数字设备重要性的认知相关的项目。DASC显示出可接受的聚合效度(r = 0.83 [95%置信区间(CI)0.80,0.85],p < 0.001)、内部一致性信度(Cronbach's alpha 0.95;分半信度系数0.885)和重测信度(组内相关系数 = 0.71(0.67,0.75),p < 0.001)。以IAT作为标准,数字成瘾风险的建议临界值为53,灵敏度为85.9%,特异度为92.3%。 结论:经过语言和文化调适的中文版DASC是一种可靠且有效的工具,具有确定的识别高危个体的临界值。然而,研究结果受到单县样本、排除年幼儿童(四年级及以下)和有认知或阅读困难儿童以及依赖自我报告数据的限制。经过适当推广后,中文版DASC在常规学校心理健康筛查、儿科检查以识别高危儿童以及国家健康调查中具有潜在应用价值。使用DASC追踪和了解数字成瘾情况有助于制定基于证据的干预措施,并支持针对数字成瘾的政策建议。
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