The Relationship of Smartphone Addiction and Alexithymia

Abstract

Objective This study aims to evaluate whether smartphone addiction (SA) is associated with social media use and alexithymia levels in university students.Methods A group of 935 students aged between 18 and 45 years (509 females and 426 males) was recruited from different universities in Istanbul. SAs, alexithymia and social media use were assessed using the Smartphone Addiction Scale Short Version (SAS-SV), Toronto Alexithymia Scale-20 (TAS-20), and ad-hoc questions regarding social media use.Results The mean age of participants was 21.89±3.27 years and 509 of participants were female (54.4%). 455 (48.6%) participants were placed in the “SA” and 198 (21.2%) in the “alexithymia” categories. The study found a high level of positive correlation (p<0.001) between both subscale and total TAS-20 scores and SAS-SV scores. Gender (OR=1.496, 95% CI 1.117–2.002, p=0.007) and number of social media by participants (OR=1.221, 95% CI 1.134–1.315, p<0.001) and TAS (OR=1.074, 95% CI 1.059–1.090, p<0.001) were found to be an independent predictors for SA.Conclusion The study revealed a positive correlation between alexithymia and smartphone use severity, and alexithymia was a significant predictor of SA. Future studies focusing on the causal aspect of this relationship will be useful in planning strategies for treatment.

Effectiveness of Psycho-Motivational Training on Improving Social Skills and Emotional Regulation in Patients with Schizophrenia

“…The results of current study were matched with Rady et al (34) who studied that multiple comparisons between the six age groups demonstrated a developmental aspect of alexithymia and reveled that Total TAS-20 scores of teenagers and group of people who aged between 20-30 years were relatively higher than those aged between 40-50. As reported by Gundogmuş, Aydın and Algul (35) who found that high level of positive correlation between total TAS-20 scores and predictors of their study for instance age, gender, place of residence, monthly income, number of social media.…”

Correlations between smartphone addiction and alexithymia, attachment style, and subjective well-being: A meta-analysis

“…They may overuse smartphones to meet their social needs (ŞahÝn et al, 2009). In line with this, recent research has suggested that alexithymia bears a significant positive relationship with SA (Remondi et al, 2020;Gündogmuş et al, 2021;Xiao et al, 2021). However, the correlation coefficients of different research results are quite different.…”

Problematic smartphone use and specific problematic Internet uses among university students and associated predictive factors: a systematic review

“…In contrast, the study by Jiang and Shi ( 2016 ), using the ‘Problematic Mobile Phone Use Scale (PMPUS)’ and making a dichotomous division, finds that 8.99% display problematic use. Meanwhile, the study by Gündoğmuş et al ( 2021 ), using 'The Smartphone Addiction Scale-Short Version (SAS-SV)', with a score between 10 and 60, and making a dichotomous division (yes/no) finds 48.6% of participants fall within the "addiction" group (SAS-SV ≥ 31 for boys and SAS-SV ≥ 33 for girls). The study by Long et al ( 2016 ) used the Problematic Cellular Phone Use Questionnaire (PCPUQ), a questionnaire composed of 12 items, the first seven of which asked whether in the previous year the participants had symptoms of problematic CPU, while the last five determined the subjective functional impairment of the participants in the previous year caused by CPU, so that participants who had positive responses to four or more of the first seven questions and those who had positive responses to any of the last five questions were classified as having problematic CPU, and found a prevalence of 21.3%.…”

“…However, variability in prevalence rates may be due to other factors. In this respect, studies with the same instrument and the same cut-off point (≥ 31 in men and ≥ 33 in women in the Smartphone Addiction Scale Short Version), prevalence rates ranged from 27.92% (Yuchang et al, 2017) to 48.6% (Gündoğmuş et al, 2021). So, these discrepancies could be explained by socio-cultural differences among users at university (Bányai et al, 2017;Lopez-Fernandez et al, 2017).…”