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Univariate and multivariate logistic regression analyses to identify factors associated with high mobile phone dependency.
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... 2 shows personal characteristics related to mo- bile phone dependence category. Univariate logistic re- gression results revealed a statistically significant rela- tionship between mobile phone dependence and health-related lifestyle (OR = 2.34, p < 0.05), predomi- nance of Type A behavior traits (OR = 2.49, p < 0.05), and depressive state (OR = 3.04, p < 0.05) ( Table 3). In addition to these variables, gender and mode of residence (variables with a p value < 0.2) were included in age- adjusted multivariate logistic regression analysis. ...
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Amaç: Depresyonun gelişmesinde ve prognozunda hastanın kişiliği, perspektifi, olumsuz yaşam olayları ve bireylerin stresle baş etme becerileri gibi psikolojik faktörler etkilidir. Özellikle stres düzeyinin artması bireylerin nörotransmitterlerini olumsuz etkileyerek depresyona neden olabilir. Bu nedenle, bireylerin stres düzeyini azaltıcı girişimle...
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... In addition, Brezing et al. (2010) in their review of behavioral addictions in youth alluded to the positive association between depression and problematic internet use in adolescents and college students, where internet use is used as a coping strategy. Likewise, we had similar expectation with regard to the effect of personality type A; once more presumed by findings from earlier studies revealing significant positive association between neurotic personality trait and smartphone addiction in Korean college students (Mok et al., 2014), personality type A and problematic mobile phone use in Turkish university students (Sahin et al., 2013), and type A behavior traits and mobile phone dependence after adjustment for health-related lifestyle habits and depressive state in Japanese medical university students (Masahiro & Satoko, 2013). ...
BACKGROUND: Recent evidence highlighted the potential of habitual smartphone use among youth to become an addiction analogous to established behavioral and substance-related addictions. While investigators revealed independent predictive effects of several sociodemographic factors, personality traits, psychological conditions, and smartphone usage patterns on smartphone addiction (SPA) in university students, none examined the independent effect of age at first smartphone use, a potential predictor variable, on subsequent development of SPA.OBJECTIVE: This study aims to examine the independent association between age at first smartphone use and SPA score in a sample of 688 Lebanese undergraduate university students.METHODS: A random sample of 688 undergraduate students selected from Notre Dame University, Lebanon filled out survey forms that included a) questions on socio-demographics, academics, smartphone use, personality type, depression, anxiety, and lifestyle habits; b) 26-item Smartphone Addiction Inventory (SPAI) Scale. Multiple linear regression analyses were used to examine the independent association between age at first use and SPA level.RESULTS: Mean age at first smartphone use was about 15 years. Younger age at first use of smartphone was found to be significantly associated with several SPA symptoms and correlated with higher total SPAI score. In the unadjusted regression model, higher total SPAI scores were found to be significantly associated with younger age at first smartphone use. This association remained significant in the partially adjusted model, but disappeared in the fully adjusted one when controlling additionally for smartphone use habits.CONCLUSION: Younger age at smartphone use did not independently predict SPA in this sample of students.
... Since MPWD is a complex and multi-dimensional behaviour, there was some evidence found in personality and behaviour literature establishing relationship between mobile phone dependency and health-related lifestyle factors [13,16]. Notably, smoking habits and alcohol consumption was found to be correlated with phone use dependency [13]. ...
... This might subsequently make a LHTD continue to engage in risky phone use behaviour during driving. This is consistent with the findings from previous studies [16,39]. Figure 5E shows the relationship between impact of educational qualification of LHTDs on prediction of MPWD. ...
Mobile phone use while driving (MPWD) is one of the most critical behaviours contributing to distraction related fatalities and injuries. However, MPWD is not well understood among long-haul truck drivers (LHTDs) especially in developing countries like India. The present study aims to develop a
prediction model for MPWD and attempts to identify the underlying factors and patterns affecting
MPWD among LHTDs travelling across India. A total of 756 valid samples were collected utilising a
questionnaire in Salem city, Tamil Nadu, India. Machine learning algorithms including Decision tree,
Random Forest, Adaptive Boosting, and Extreme gradient boosting were employed to model MPWD.
A split ratio of 70:30 was adopted for training and testing purposes. A 10-fold cross validation procedure was carried out during model development. The analysis results showed that XGBoost demonstrated superior performance than other models (accuracy=0.82, F1 score=0.8, and AUROC=0.82).
In addition, SHapley Additive explanations (SHAP) were implemented to reveal the importance of predictors contributing to MPWD. The findings of the study showed that type of commodity, pressured
delivery, calls received during driving, smoking habits, educational level, and continuous driving duration as major factors contributing to MPWD among LHTDs. SHAP values were also utilised to investigate hidden patterns and interaction effects for major factors affecting MPWD. Parcel and food items
coupled with frequent pressured delivery and middle aged LHTDs driving continuously for 5–6 h are
some of the interactive risk factors enhancing MPWD. These findings are useful for road safety authorities and truck companies to draft suitable policies and help to introduce effective interventions for
reducing MPWD among LHTDs.
... Mobile phone dependence, which is considered a form of Internet addiction, is when individuals indulge in mobile activities and cannot extricate themselves and control their own impulses to use mobile phones. Some scholars have suggested that mobile phone dependence is similar to addictive behavior, which will negatively influence the individual's physical and mental health [20][21][22]. By referring to the relevant literature, mobile phone dependence is closely associated with subjective well-being, and those individuals with high degrees of mobile phone dependence will have lower subjective well-being [23]. ...
... Mobile phone dependence will negatively influence the individual's health, such as subjective well-being [20][21][22]. Mobile phone dependence was negatively associated with self-esteem, and the higher the degree of mobile phone dependence, the lower the selfesteem [20,37,38]. Those individuals with high subjective well-being might also have high self-esteem [35,36]. ...
Many studies have shown that mobile phone dependence decreases subjective well-being, but there have been relatively few studies that investigate the specific mechanisms between mobile phone dependence and subjective well-being. In this study, the mediating effect of self-esteem and the moderating effect of social support were investigated to explore the specific mechanisms between mobile phone dependence and subjective well-being. The objective of the study is to explore the mechanism of mobile dependence on subjective well-being by constructing a moderated mediation model. College students from twenty classes in three universities were randomly selected. A total of 550 college students fully participated in the actual evaluation and completed the general well-being scale, mobile phone addiction index scale, self-esteem scale, and social support scale. SPSS17.0 was used to analyze the data. The results show that: (1) Self-esteem partially mediates the relationship between mobile phone dependence and subjective well-being. Mobile phone dependence not only has a direct influence on subjective well-being, but also influences subjective well-being indirectly by self-esteem; (2) The mediating effect of self-esteem between mobile phone dependence and subjective well-being is moderated by social support. Social support moderates the second path of the mediation, and the higher the social support, the greater the degree of self-esteem on subjective well-being. For the management of mobile phone dependence of college students, more attention needs to be paid to the personality characteristics of different students. In addition, there should be efforts to avoid blindly educating students and instead to increase their social support and create a good atmosphere on campus and in society. Only in this way can they improve their subjective well-being.
... It was found that severe depressive symptoms were caused by academic stress, peer relationship problems, resulting in smartphone addiction. This trend has also been suggested in a study by Yen et al. (2009) in adolescents in Southern Taiwan, while Toda and Ezoe (2013) from Japan stated that depressive symptoms independently affect the level of dependence on cell phones in young people. It was found that severe depressive symptoms were caused by academic stress, peer relationship problems, resulting in smartphone addiction. ...
... It was found that severe depressive symptoms were caused by academic stress, peer relationship problems, resulting in smartphone addiction. This trend has also been suggested in a study by Yen et al. (2009) in adolescents in Southern Taiwan, while Toda and Ezoe (2013) from Japan stated that depressive symptoms independently affect the level of dependence on cell phones in young people. ...
... However, despite their convenience, mobile phones have been associated with a series of adverse effects including dependence and addiction. National and international studies have verified that excessive or frequent use of mobile phones can impact physical and psychological functioning, quality of life, and performance at work or school (2,3). Mobile phone dependence refers to an obsessive state in which individuals are unable to control their use of mobile phones, resulting in impaired physiological, psychological, and social functioning (4). ...
Background: We aimed to investigate the relationship among mobile phone dependence, self-efficacy for self-regulated learning, time management disposition, and academic procrastination in Chinese students majoring in physical education. In addition, we explored the mediating roles of self-efficacy for self-regulated learning and time management disposition in the relationship between mobile phone dependence and academic procrastination.
Methods: We adopted a random sampling method to identify 324 physical education majors at five universities in Shaanxi Province, China in 2020. Data were analyzed via exploratory factor analysis, confirmatory factor analysis, correlation analysis, structural equation model analysis, and path analysis.
Results: Mobile phone dependence had significant positive effects on academic procrastination (P
... The overall score is the sum of the answers and therefore ranges from 0-60. The higher the score, the higher the mobile phone dependence and vice versa [19]. Empathy was measured using the Toronto Empathy Questionnaire (TEQ) [20], consisting of 16 questions on empathy on a five-point scale from "never" to "always" and with a Cronbach's α of 0.87 [21]. ...
This study examined the relationship between empathy and mobile phone dependence levels of the nursing staff in a public hospital in the island of Crete, using a cross-sectional study design. Data from 109 staff nurses and healthcare assistants (HCAs) were collected via the Greek version of the Mobile Phone Dependence Questionnaire (MPDQ) and the Toronto Empathy Questionnaire (TEQ). Multiple linear regression was used to determine the correlation between empathy and mobile phone dependency. The total mean score for TEQ was 33.9 (±5.7). Accordingly, the total mean score for MPDQ was 22.9 (±6.1). High mobile phone dependence was found in 4.7% of the participants. A statistically significant difference was found between HCAs and staff nurses, with HCAs presenting a higher mean empathy levels (TEQ) (36.5 vs. 32.6) and lower dependence levels (MPDQ) (18.9 vs. 24.5) than staff nurses. A significant correlation between empathy and dependence was found between dependence and the altruism empathy subscale, with higher dependence being correlated with lower altruism. The participants’ levels of empathy do not seem to be affected by mobile phone dependence. However, empathy appears to be strongly determined by increased age and professional status. Nurses’ dependence on mobile phones is a complex phenomenon that requires attention. Educational programs on empathy and information on the proper use of mobile phones by the nursing staff should be provided.
... Because much smartphone content is based on the Internet, the overuse of smartphones leads to similar adverse consequences (Zhang, Chen, & Lee, 2014). Subjects with ESU are more likely to have financial problems (Billieux, Van der Linden, & Rochat, 2008;James & Drennan, 2005); health problems including headaches, and sleep disturbances (Kundi, 2010;Thomée, Härenstam, & Hagberg, 2011;Toda & Ezoe, 2013); and cognitive deficits in areas such as attention, memory, and executive function (Wilmer, Sherman, & Chein, 2017). ...
Adolescent Internet addiction is an important social issue entailing extensive use of Internet and smartphones and its side effects. This study identified relevant psychological factors that affect excessive Internet use (EIU) and excessive smartphone use (ESU) in adolescents using structural equation modeling (SEM). A sample of 714 individuals drawn from lists of middle school students in South Korea completed self-administered questionnaires, including Young’s Internet Addiction Test (Y-IAT), the Smartphone Addiction Scale (SAS), and various clinical and psychological scales measuring depression, anxiety, attention deficit/hyperactivity disorder (ADHD), aggression, expression of anger, and the behavioral inhibition system (BIS)/activation system (BAS). The final model, fitted using SEM, showed that both clinical characteristics, including ADHD symptoms, aggression, expression of anger, depression, and anxiety, and personality characteristics, represented by BIS/BAS, played important roles in the severity of EIU or ESU. In particular, affective components such as depression and anxiety were significantly associated with both EIU and ESU, whereas aggression, the expression of anger, and ADHD symptoms affected only EIU. Furthermore, the association between ESU and EIU was significant. Although personality characteristics measured by the BIS and BAS scores did not have direct effects on addiction, they were associated with clinical features and might be risk factors for addiction. The model revealed significant pathways from personality and clinical features to EIU and ESU in adolescents and informed our basic understanding of the meaningful predictors of these addictions and their direct and indirect influences.
... Increased sociocultural problems such as technological dependence, unsocial and unhealthy lifestyle has been associated with smart phone addiction 4 . Access to internet enabled applications such as WhatsApp, Facebook and messenger is increasing with a phenomenal rate as the technology is advancing 5 . ...
... In a study conducted at university of Osaka Japan, statistically significant relationship between smart phone dependence and health related lifestyle was observed 4 . In our study, it was observed that dependence was positively associated with academic performance (multivariate analysis) after adjusting all four variables with frequency of smart phone usage at 95% confidence interval ( Table 2). ...
... Increased sociocultural problems such as technological dependence, unsocial and unhealthy lifestyle has been associated with smart phone addiction 4 . Access to internet enabled applications such as WhatsApp, Facebook and messenger is increasing with a phenomenal rate as the technology is advancing 5 . ...
... In a study conducted at university of Osaka Japan, statistically significant relationship between smart phone dependence and health related lifestyle was observed 4 . In our study, it was observed that dependence was positively associated with academic performance (multivariate analysis) after adjusting all four variables with frequency of smart phone usage at 95% confidence interval ( Table 2). ...
Background: Smart phone use is becoming a severe mental health problem as it is becoming dominant with the passage of time leading to dependency and diverting individual’s concentration. The addiction is not only confined to youth, it can be observed among individual of all ages. Through this study our aim was to observe the smart phone usage frequency and its association with academic performance among university students. Methodology: A cross sectional study was conducted on a total of 400 students of Dow university of health sciences between January 2016 – January 2017. The problematic mobile phone usage scale (PUMP) was used to evaluate the smart phone addiction level and grade point average (GPA) of previously attended semester was analyzed to evaluate its association with academic performance. Results: It was observed that 134 out of 400 participants were spending 1-2 hrs. daily on mobile phone usage. A strong association was observed between frequency of smart phone usage and academic performance. Moreover, control loss and dependence were also affecting the academics among the study participants. In this study we observed that female students with frequent smart phone use had greater chances of having poor academic performance as compared to males. Conclusion: It can be concluded form the study results that excessive smart phone usage affects academic performance and hence results in increased dependence leading to lack of concentration, decreased confidence, reduced public dealings and face-to-face interactions. Furthermore, the use must be restricted as in long term it is leading to several health issues especially among youth.
... Akıllı telefon bağımlılarında gözlemlenen durumlar; yalnızlık (Takao vd., 2009;Güzeller ve Coşguner, 2012), depresyon (Güzeller ve Coşguner, 2012), fiziksel ve sosyal aktivitelerde azalma (Yen vd., 2009;Lepp vd., 2014), düşük öz saygı (Takao vd., 2009) gibi olumsuz durumların gözlendiği bildirilmektedir. Bunlara ek olarak akıllı telefon bağımlılığın A Tipi kişilikte ve depresyonlu kişilerde anlamlı bir şekilde daha fazla görüldüğü bildirilmiştir (Toda ve Ezoe, 2013). Brezilya'da icra edilen bir laboratuvar çalışmasında, panik bozukluğu olan hastalar ile kontrol gurubu üzerinde nomofobinin etkisi araştırılmış, akıllı telefonlarından uzaklaştırılan katılımcılardan panik bozukluğu bulunan bireylerin kontrol grubuna göre anlamlı derecede yüksek seviyede endişe, taşikardi, solunum düzensizliği, titreme, terleme, panik, korku ve depresyon sergiledikleri tespit edilmiştir (King vd., 2014). ...
Günümüz toplumunda akıllı telefonlar aracılığıyla kullanılan sosyal medya, özellikle üniversite öğrencileri arasında, günlük yaşamın vazgeçilmez bir parçası haline gelmiştir. Bu durum, beraberinde akıllı telefonlara olan bağımlılık sorunsalını da gündeme getirmekte ve bireyin kişilik özellikleri ile ilişkilendirilerek açıklanabileceği düşünülmektedir. Dolayısıyla bu araştırmada; öğrencilerin akıllı telefon bağımlılık düzeyleri ve sosyal medya kullanmalarının, Beş Faktör Kişilik özelliği ile ilişkisi incelenmiştir. Araştırma, Bitlis Eren Üniversitesinde öğrenim gören 343 öğrenci üzerinde gerçekleştirilmiştir. Veri toplamak amacıyla anket formu yöntemi kullanılmış olup, örneklem seçiminde basit tesadüfi örneklem yöntemi benimsenmiştir. Araştırma kapsamında, tanımlayıcı istatistiklerin yanı sıra, korelasyon, basit doğrusal regresyon, çoklu regresyon analizleri yapılmıştır. Yapılan analizler sonucunda öğrencilerin kişilik özellikleri ile akıllı telefon bağımlılığı ve sosyal medya kullanımları arasında istatistiki açıdan anlamlı ilişkiler bulunmuş, aynı zamanda sosyal medya kullanımının akıllı telefon bağımlılığını artırdığı tespit edilmiştir.