Development Of A Smartphone Overuse Classification Scale

Ding, Jianyong; Liu, Wenjuan; Wang, Xiaoyi; Lan, Yukun; Hu, Dandan; Xu, Yuhua; Jiang, Li; Fu, Hua

doi:10.1080/16066359.2018.1474204

Cited by 7 publications

(7 citation statements)

References 29 publications

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“…The construct underlying the SIS tool displayed its validity when compared to an existing measure of smartphone addiction and misuse. 7 , 11 , 38 These data provide support for its use in research examining problematic smartphone use in healthcare institutes, as it could be a good strategy to assess healthcare professionals' awareness of the magnitude of negative outcomes resulting from the overuse of smartphones.…”

Section: Discussionmentioning

confidence: 75%

“…36 , 37 This generated a wide range of items included on the SIS based via a thorough literature review and FGD. This is similar to the process of development of the SOCS, 11 in which Ding and his team conducted two sessions of FGD to identify the items of the scale. According to the guidelines outlined by Yusoff 28 the CVI was calculated for individual items, the I-CVI was more than 0.8, and the overall item CVI was 0.82, which is within the accepted standard.…”

Section: Discussionmentioning

confidence: 99%

“…This study has a large number of participants in comparison with other standardisation samples from existing scales such as SAS, 6 , 7 PMPUQ, 8 SUQ-G&A, 10 and SOCS. 11 In this study, the validity of the scale was established through expert FGD and by determining the CVI as a standard protocol for its development. As the literature was not sufficiently rich to provide a comprehensive conceptual framework of the proposed study, the investigators adopted expert FGD and a biopsychosocial model to develop the preliminary test items.…”

Section: Discussionmentioning

confidence: 99%

“…Many measures and scales focusing on smartphone overuse and addiction have been developed to capture smartphone behaviour, such as the Nomophobia Questionnaire (NMP-Q), 5 Smartphone Addiction Scale (SAS), 6 , 7 Problematic Mobile Phone Use Questionnaire (PMPUQ), 8 Media and Technology Usage and Attitudes Scale (MTUAS), 9 Smartphone Use Questionnaires (SUQ-G&A), 10 and Smartphone Overuse Classification Scale (SOCS). 11 Moreover, some researchers have developed scales that measure smartphone addiction, such as the Chinese Smartphone Addiction Inventory (SPAI), 12 and the Korean Smartphone Addiction Proneness Scale (SAPS). 13 These measures have been developed to assess specific aspects of interactions between human beings and smartphones.…”

Section: Introductionmentioning

confidence: 99%

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Development and validation of a Smartphone Impact Scale among healthcare professionals

Altamimi

Alex

Khan

et al. 2020

Journal of Taibah University Medical Sciences

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Objectives Smartphone overuse is prevalent among healthcare professionals. There is no standard scale that can measure the impact of smartphone usage on healthcare professionals. This study aimed to develop and validate a tool, the Smartphone Impact Scale (SIS), that can effectively measure the use of smartphone among healthcare professionals. Methods We developed a generic instrument to study the impact of smartphone usage among healthcare professionals. A total of 1436 healthcare professionals from various regions of KSA participated in this study through an online questionnaire-based survey. The psychometric properties of the SIS were developed using content validity index (CVI), factor analysis, internal consistency, and test-retest reliability analysis. Results A 23-item scale was selected for reliability and validity analysis. The average CVI was found to be 0.824. The internal consistency with Cronbach's alpha value was 0.91, and test-retest reliability was 0.85. The Cronbach's alpha values for Factors 1 and 2 were 0.875 and 0.803, respectively. The confirmatory factor analysis indices were as follows: root mean square of approximation = 0.0710, comparative fit index = 0.861, Tucker–Lewis index = 0.845, and the coefficient of determination = 0.969. The correlation between two factors was 0.66. After factor analysis, we developed a final questionnaire with 23 items. Conclusions Our SIS showed a three-factor structure and appropriate psychometric characteristics. Due to its adequate reliability and validity, SIS can be conveniently used to evaluate the impact of smartphone usage on healthcare professionals.

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Section: Discussionmentioning

confidence: 75%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Development and validation of a Smartphone Impact Scale among healthcare professionals

Altamimi

Alex

Khan

et al. 2020

Journal of Taibah University Medical Sciences

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“…En la tercera parte, se utilizó es una escala (escala S) para evaluar el uso excesivo de aplicaciones de medios sociales desarrollada por Ding [12], que fueron 7 ítems (ver tabla 2), cada ítem de tipo Likert de 5 opciones, que fue codificada de la forma, (1) muy en desacuerdo y (5) muy de acuerdo.…”

Section: Materiales Y Métodosunclassified

Social media, habits and their relationship with academic performance in university students

Quiñonez-Choquecota,

Flores-Quispe,

Larico-Mamani

et al. 2023

Proceedings of the 21th LACCEI International Multi-Conference for Engineering, Education and Technology (LACCEI 2023): “Leaders

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The objective of this research was to identify the forms of use of social media, lifestyle habits and identify whether there are links with academic performance. A structured selfadministered questionnaire was applied to a sample of 588 undergraduate students from two public universities in Peru. To identify the relationships between variables, bivariate correlation analysis and hierarchical correlation analysis were performed. The results indicate that students are characterized by a lifestyle of few hours of sleep, very little time devoted to physical activity and considerable time devoted to social media for entertainment and non-academic purposes. Likewise, there is a direct relationship between the time spent on social media and the scale measuring excessive use of social media, which reveals that there are indications of excessive use of social media that would negatively affect academic performance.

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Rethinking classifications and metrics for problematic smartphone use and dependence: Addressing the call for reassessment

Nawaz

2023

Computers in Human Behavior Reports

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Development Of A Smartphone Overuse Classification Scale

Cited by 7 publications

References 29 publications

Development and validation of a Smartphone Impact Scale among healthcare professionals

Development and validation of a Smartphone Impact Scale among healthcare professionals

Social media, habits and their relationship with academic performance in university students

Rethinking classifications and metrics for problematic smartphone use and dependence: Addressing the call for reassessment

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