Psychopathological Symptoms and Personality Traits as Predictors of Problematic Smartphone Use in Different Age Groups

Wickord, Lea-Christin; Quaiser-Pohl, Claudia

doi:10.3390/bs12020020

Cited by 15 publications

(11 citation statements)

References 85 publications

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“…42 Indeed, the prevalence of ASU and the predisposing factors for ASU among digital natives and digital immigrants may differ. 43 However, this should not give the illusion that ASU is unique to digital natives and is not to be found in elderly people who have migrated from digital culture to the most remote distances.…”

Section: Discussionmentioning

confidence: 99%

“…Prensky defined students born after 1980 as digital natives, and the previous generations as digital immigrants, and stated that the technology use habits of these two generations may differ 42 . Indeed, the prevalence of ASU and the predisposing factors for ASU among digital natives and digital immigrants may differ 43 . However, this should not give the illusion that ASU is unique to digital natives and is not to be found in elderly people who have migrated from digital culture to the most remote distances.…”

Section: Discussionmentioning

confidence: 99%

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Addictive smartphone use in the elderly: relationship with depression, anxiety and sleep quality

Karaş

Özbek²,

Yılmaz

2022

Psychogeriatrics

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Background The aim of the present study was to explore the relationship between addictive smartphone use (ASU) and depressive symptoms, anxiety and sleep quality in elderly adults. Methods The study sample included smartphone users over the age of 65 years. The research data were obtained from social networking sites via a Google survey link. In addition to filling out a sociodemographic data form, the participants were also assessed with Smartphone Addiction Scale (SAS), Geriatric Depression Scale, Beck Anxiety Inventory and Pittsburgh Sleep Quality Index tools. Results The correlation analysis revealed the SAS score to be positively correlated with depression and anxiety, and negatively correlated with sleep quality. In the regression analysis, depressive symptoms, anxiety level and sleep quality were all found to have an effect on the SAS total score. Furthermore, the SAS score was found to have an effect on depressive symptoms, anxiety and sleep quality. Conclusions Our findings reveal a bidirectional relationship between ASU and depressive, anxiety symptoms and impaired sleep quality in elderly adults. It is important to question smartphone use patterns in people with sleep problems, symptoms of depression or anxiety.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Addictive smartphone use in the elderly: relationship with depression, anxiety and sleep quality

Karaş

Özbek²,

Yılmaz

2022

Psychogeriatrics

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“…Prensky [ 62 ] dates the time point that differentiates the two digital generations to 1980; those born after that date are considered digital natives and the rest are digital immigrants. Following Prensky’s original work, many studies interested in analyzing the digital divide between the aforementioned generations have taken 1980 as the date that differentiates them [ 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 ]. The distinction between digital generations depends on age as well as on the socio-cultural aspects involved.…”

Section: Introductionmentioning

confidence: 99%

Variables Influencing Professors’ Adaptation to Digital Learning Environments during the COVID-19 Pandemic

Vergara

Antón‐Sancho

Fernández‐Arias

2022

IJERPH

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This paper conducts quantitative research on the influence of the COVID-19 pandemic on the adaptation to digital learning environments (DLE) of a group of 908 university professors. We compared the perceptions of participants who were digital natives (born before 1980) with those of digital immigrants (born after 1980). For this purpose, a validated survey was used and the obtained responses statistically analyzed. The results show a negative correlation between pandemic stress and the digital competence of professors and their adaptation skills to digital environments, which although weak for both of the two groups compared are stronger for digital immigrants. Both self-confidence and digital competence show a positive influence on the perception of adaptation of skills to DLE, and this is weaker in digital natives. Gaps were identified by gender and area of knowledge of the participants; consequently, the need to carry out training actions for university faculty on skills linked to their digital competence in teaching is clear.

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“…Excessive cell phone use affects basic interpersonal relationships and health across generations. 28 According to Bilieux, 29 problematic smartphone use is linked to neuroticism, extraversion, and impulsivity. Studies using various measures of psychological well-being conducted on Australian adults show statistically significant correlations of problematic smartphone use with negative affect, environmental mastery, and sense of autonomy.…”

Section: Introductionmentioning

confidence: 99%

Problematic Smartphone Use and Social Media Fatigue: The Mediating Role of Self-Control

Świątek¹,

Szczęśniak²,

Aleksandrowicz³

et al. 2023

PRBM

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Background Excessive social media consumption leads to addiction and affects mental health. It is a phenomenon that is difficult to avoid. Previous research on the effects of excessive Internet use shows that people who engage in social media (SM) without restraint experience over-involvement, over-disclosure, technostress, and social media fatigue (SMF). SMF, conceptualized as an emotional and cognitive feeling of being overwhelmed, manifests itself in mindless browsing of content, limiting the amount of time spent on SM, or quitting SM altogether. Self-control, although present in the technology addiction literature and psychology research, has been rarely described in relation to both excessive SM use and SMF. Therefore, the main goal of the present study was to verify whether there is a direct relationship between problematic smartphone use and SMF, and whether this association is mediated by self-control. Methods The study included 210 respondents ( M = 25.85, SD = 9.84) living in different Polish cities. The survey was conducted online, and the respondents consented to participate in the study. They completed the following measures: the Mobile Phone Problematic Use, the Self-Control Scale, the Social Media Fatigue Scale, and a brief questionnaire with socio-demographic data. Results Statistical analysis was performed to verify the relationship between problematic mobile phone use, level of self-control, and SMF. The outcomes indicate that there are significant interrelationships between the three studied variables. The association between problematic smartphone use and SMF is mediated by self-control. Conclusion A lack of impulse-inhibition skills, such as compulsive checking of notifications, can be a significant factor in SM exhaustion, fatigue, or frustration. SMF can also be understood as a natural defensive response, triggered in situations where individuals are overwhelmed, when the self-control is insufficient to stop the compulsion to use SM, and the use of a smartphone for this purpose is excessively engaging.

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Psychopathological Symptoms and Personality Traits as Predictors of Problematic Smartphone Use in Different Age Groups

Cited by 15 publications

References 85 publications

Addictive smartphone use in the elderly: relationship with depression, anxiety and sleep quality

Addictive smartphone use in the elderly: relationship with depression, anxiety and sleep quality

Variables Influencing Professors’ Adaptation to Digital Learning Environments during the COVID-19 Pandemic

Problematic Smartphone Use and Social Media Fatigue: The Mediating Role of Self-Control

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