The connection between risk of smartphone addiction, type of smartphone use, life satisfaction, and perceived stress dataset
The data were collected to test the hypothesis that problematic smartphone use, defined as the risk of smartphone addiction, is positively related to the type/purpose of device use (hedonic, meaning pleasure/gratification) and perceived stress, while it is negatively related to life satisfaction. Th...
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| Autores principales: | , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Elsevier
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/b466fc506f7f474891a65cd46beccf74 |
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| Sumario: | The data were collected to test the hypothesis that problematic smartphone use, defined as the risk of smartphone addiction, is positively related to the type/purpose of device use (hedonic, meaning pleasure/gratification) and perceived stress, while it is negatively related to life satisfaction. The data were collected online between October 2020 and January 2021, using Qualtrics online research platform. The participants were aged 18 years or over, had a good command of the English language. They were recruited by posting the survey link on popular social media platforms, such as Facebook, LinkedIn, and Twitter, as well as by using applications such as WhatsApp and Instagram. Participation was voluntary, anonymous, and without material compensation. In addition to demographic questions (age, gender, level of education), respondents completed three questionnaires, including the Smartphone Application-Based Addiction Questionnaire (SABAS), Satisfaction with Life Scale (SWLS), Perceived Stress Scale (PSS), and answered two questions about the proportion of time they use their smartphone to access the Internet and the proportion of time they use smartphone for hedonic purposes. In the course of the data analysis, our aim was to predict the risk of smartphone addiction by the type or purpose of smartphone use, perceived stress, life satisfaction, age, and gender. The reuse potential of the data lies in the possibility to examine the relationships between the hedonic use of smartphones and other variables in the dataset. Researchers could also examine differences of gender or education level in the specific components of smartphone addiction, since each item of the SABAS represents a distinct component in the ‘Components model’ of addiction [4]. Furthermore, since we have data on Internet access via a tablet, laptop, and desktop computer, it is possible to analyse the relationships of the dependent variables with these paths of accessing the Internet. |
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