Adaptation and validation of the Chinese version of the digital addiction scale for children (DASC)

Abstract 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. Ho...

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Main Authors: Jiayao Xu, Yuyin Ma, Minghui Tan, Jiaxue Lou, JingJing Lu, Xudong Zhou
Format: Article
Language:English
Published: BMC 2025-07-01
Series:BMC Public Health
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Online Access:https://doi.org/10.1186/s12889-025-23817-7
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author Jiayao Xu
Yuyin Ma
Minghui Tan
Jiaxue Lou
JingJing Lu
Xudong Zhou
author_facet Jiayao Xu
Yuyin Ma
Minghui Tan
Jiaxue Lou
JingJing Lu
Xudong Zhou
author_sort Jiayao Xu
collection DOAJ
description Abstract 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.
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spelling doaj-art-0f069c3b5f5643f682f3f798874ebc492025-08-20T03:42:03ZengBMCBMC Public Health1471-24582025-07-0125111410.1186/s12889-025-23817-7Adaptation and validation of the Chinese version of the digital addiction scale for children (DASC)Jiayao Xu0Yuyin Ma1Minghui Tan2Jiaxue Lou3JingJing Lu4Xudong Zhou5The Institute of Social Medicine, Zhejiang University School of MedicineThe Institute of Social Medicine, Zhejiang University School of MedicineThe Institute of Social Medicine, Zhejiang University School of MedicineThe Institute of Social Medicine, Zhejiang University School of MedicineThe Institute of Social Medicine, Zhejiang University School of MedicineThe Institute of Social Medicine, Zhejiang University School of MedicineAbstract 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.https://doi.org/10.1186/s12889-025-23817-7Digital addictionInternet addictionChildrenChinaAdaptationValidation
spellingShingle Jiayao Xu
Yuyin Ma
Minghui Tan
Jiaxue Lou
JingJing Lu
Xudong Zhou
Adaptation and validation of the Chinese version of the digital addiction scale for children (DASC)
BMC Public Health
Digital addiction
Internet addiction
Children
China
Adaptation
Validation
title Adaptation and validation of the Chinese version of the digital addiction scale for children (DASC)
title_full Adaptation and validation of the Chinese version of the digital addiction scale for children (DASC)
title_fullStr Adaptation and validation of the Chinese version of the digital addiction scale for children (DASC)
title_full_unstemmed Adaptation and validation of the Chinese version of the digital addiction scale for children (DASC)
title_short Adaptation and validation of the Chinese version of the digital addiction scale for children (DASC)
title_sort adaptation and validation of the chinese version of the digital addiction scale for children dasc
topic Digital addiction
Internet addiction
Children
China
Adaptation
Validation
url https://doi.org/10.1186/s12889-025-23817-7
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