2020
DOI: 10.1016/j.chbr.2020.100011
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Examining the psychometric properties of the Smartphone Addiction Scale and its short version for use with emerging adults in the U.S

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Cited by 35 publications
(31 citation statements)
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“…Total scores of 31 and 33 were used as diagnostic thresholds for males and females respectively, in accordance with the original study which found strong internal consistency (Cronbach's alpha = 0.91, AUC = 0.96 for boys, AUC = 0.89 for girls). This scale has been widely used internationally and has been found to have similarly strong internal consistencies using the same thresholds for this study's age group (31,32).…”
Section: Smartphone Addiction Scale -Short Version (Sas-sv)mentioning
confidence: 85%
“…Total scores of 31 and 33 were used as diagnostic thresholds for males and females respectively, in accordance with the original study which found strong internal consistency (Cronbach's alpha = 0.91, AUC = 0.96 for boys, AUC = 0.89 for girls). This scale has been widely used internationally and has been found to have similarly strong internal consistencies using the same thresholds for this study's age group (31,32).…”
Section: Smartphone Addiction Scale -Short Version (Sas-sv)mentioning
confidence: 85%
“…The Smartphone Addiction Scale‐Short Version (SAS‐SV; Kwon, Kim, Cho, & Yang, 2013) is a 10‐item measure of PSU, using a Likert‐type scale from “1 = Strongly disagree” to “6 = Strongly agree.” We voiced items in the first‐person for improved consistency (Duke & Montag, 2017). The SAS‐SV has been validated previously (Harris, McCredie, & Fields, 2020; Lopez‐Fernandez, 2017).…”
Section: Methodsmentioning
confidence: 99%
“…For example, research on problematic smartphone use typically focuses on the negative consequences of seeking social reassurance without clearly distinguishing between active bi-directional communication and passive checking on what is happening in one's social network (Elhai et al, 2017 , 2020 ). Furthermore, when examining the items used in scales that are commonly used to measure smartphone problematic use, such as the smartphone addiction scale (Kwon et al, 2013 ; Harris et al, 2020 ) or the smartphone addiction inventory (Pavia et al, 2016 ), it is clear that most of the negative consequences found in studies that use them are driven by social networking app usage rather than communication app usage (e.g., “Constantly checking my smartphone so as not to miss conversations between other people on Twitter or Facebook.”). Additionally, these inconsistent effects are found in pre-pandemic contexts when smartphone usage, in terms of both social networking and messaging apps, interferes with face-to-face interactions (e.g., “I find myself indulged on the smartphone at the cost of hanging out with friends.”).…”
Section: Conceptual Backgroundmentioning
confidence: 99%