11,813 research outputs found

    Magic mirror on the wall: Selfie-related behavior as mediator of the relationship between narcissism and problematic smartphone use

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    Objective: Recent research has suggested that problematic smartphone use is associated with several psychological factors and that mobile apps and smartphone-related behavior (i.e. selfi e behavior) may encourage the development of problematic smartphone use. However, little is known about how the interplay between dysfunctional personality characteristics and selfi e-related behavior can infl uence problematic smartphone use. The aim of this study was to examine the relationship between narcissism and problematic smartphone use, as well as the mediating role of selfi e-related behavior in this relationship among young men and women. Method: In the current study, a total of 627 undergraduate students (283 males and 344 females) completed a cross-sectional survey. A structural equation model was tested separately for males and females in order to evaluate the associations between narcissism, selfi e-related behavior and problematic smartphone use. Results: The results showed that greater narcissism was related to increased selfi e-related behavior, which in turn were positively associated with problematic smartphone use both for males and females. However, selfi e-related behavior mediated the relationship between narcissism and problematic smartphone use only for females. Conclusions: The study provides fresh insight into our understanding of the psychological mechanisms underlying problematic smartphone use, which may inform prevention and treatment interventions

    The Relationship Between Cell Phone Use And Motivation To Exercise In College Students

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    Past research suggests that high cell phone usage is related to sedentary behavior, poor physical fitness, and poor mental health. College students cell phone usage has increased over previous years while physical activity levels have declined, but due to little research, this relationship is still unclear. The purpose of this study was to examine the relationship between college student\u27s smartphone usage, exercise motivation, and physical activity. College students completed an electronic survey (n=157; female = 135; age = 20.01ยฑ1.49; BMI = 24.39) that assessed exercise motivation, physical activity, smartphone usage, height and weight (to calculate BMI), depression, anxiety, stress and fear of missing out. Data was analyzed with Pearson correlation and independent t-tests using SPSS. Results showed that amotivation (p \u3c 0.01) was positively associated with cell phone usage, while intrinsic motivation (p \u3c 0.01) was negatively associated. High cell phone users (M = 0.75 ยฑ 0.80) showed greater amotivation for exercise than low-users (M = 0.33 ยฑ 0.52), while low-users showed higher levels of intrinsic motivation. This novel study suggests that cell phone usage may interfere with exercise motivation and could be a possible barrier for individuals trying to become more motivated to exercise. Future research should examine ways to limit cell phone use, increase motivation to exercise to improve overall quality of life

    Which affects affect the use of new technologies? Italian adaptation of the Internet Motive Questionnaire for Adolescents (IMQ-A) and criterion validity with problematic use and body dissatisfaction

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    Given the negative role of problematic use of new technological devices (NTD) in behavioral and psychological domains, the aim of the study is the Italian adaptation and validation of the Internet Motive Questionnaire for Adolescents (IMQ-A) in order to understand the motivation for the use of NTD. A total of 769 students 10-19 aged (M = 13.22, SD = 1.56) completed the IMQ-A, the Collins Figures Rating Scale, and two measures regarding the problematic NTD use, focused on overuse during the night and during meals. The IMQ-A showed adequate internal consistency with regard to its four subscales: Coping (ฮฑ = .84), Social (ฮฑ = .80), Enhancement (ฮฑ = .80), and Conformity (ฮฑ = .68) motives. However, with regard to factorial structure, a threefactor model (excluding Conformity subscale) showed slightly better fit indices than the original model. Coping motive was correlated with problematic NTD use and succeeded in predicting higher scores in body dissatisfaction as evidence of criterion-related and external validity. The Italian adaptation of the IMQ-A can be useful in both research and clinical fields, in order to propose alternative strategies for coping to users and to improve emotion regulation facets

    Hedonic use, stress, and life satisfaction as predictors of smartphone addiction

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    This study examined the relationship between hedonic smartphone use (entertainment, social media, games), perceived life stress, and satisfaction with life with smartphone addiction (SA). We tested the connections using structural equation modeling (SEM) on questionnaire data obtained from 410 participants (73.2% women). Results indicated a good overall fit of the model (ฯ‡(2)(36)ย =ย 58.06, pย =ย .011; CFIย =ย 0.970, TLIย =ย 0.954, RMSEA[90% CI]ย =ย 0.039 [0.019, 0.056], SRMRย =ย 0.037). Perceived stress and hedonic use were positive predictors of SA (ฮฒย =ย 0.264, pย =ย .001 and ฮฒย =ย 0.176, pย =ย .002, respectively). Satisfaction with life did not directly predict SA, but an indirect effect, via perceived stress, was statistically significant (ฮฒย =ย โˆ’0.146, pย =ย .001). Women showed greater SA than men, but the effect of age was not significant. Perceived stress was negatively predicted by satisfaction with life, and positively by hedonic use. Based on the compensatory internet use theory, hedonic or non-utilitarian smartphone use might be associated with SA. The study concludes that being female, hedonic smartphone use, and perceived life stress predict SA

    ์ฒญ์†Œ๋…„๊ธฐ ์ŠคํŠธ๋ ˆ์Šค์™€ ์Šค๋งˆํŠธํฐ ์ค‘๋…์˜ ๊ด€๊ณ„์—์„œ ๊ทธ๋ฆฟ์˜ ๋งค๊ฐœํšจ๊ณผ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์‚ฌํšŒ๊ณผํ•™๋Œ€ํ•™ ์‹ฌ๋ฆฌํ•™๊ณผ, 2021. 2. ๊ณฝ๊ธˆ์ฃผ.The purpose of this study was to investigate the mediating effect of grit on the relationship between stress and smartphone addiction. With the increased usage of smartphones among adolescents, numerous studies have examined smartphone addiction. However, most studies focused on the negative consequences of smartphone addiction, and relatively few studies investigated how adolescents become addicted to smartphones. In fact, no known studies have reported the association between stress, grit, and smartphone addiction among adolescents. Therefore, the present study aimed to explore the relationship between stress, grit, and smartphone addiction among Korean adolescents from age 12 to 16. Particularly, we focused on the mediating effect of grit on the relationship between daily stress and smartphone addiction. Participants were 605 Korean adolescents (mean age = 13.97 years). They completed questionnaires measuring stress, grit, and smartphone addiction. Stress was assessed using the Daily Hassles Scales for Children in Korea developed by Han and Yoo (1995). Grit was measured by the Korean translated version of the Original Grit Scale (Duckworth et al., 2007; Park et al., 2020). Finally, smartphone addiction was measured by using the Smartphone Addiction Proneness Scale for Youth developed by the National Information Society Agency (2011). We analyzed the association of stress, grit, smartphone addiction through Pearsonโ€™s correlation analysis. The mediating effect was analyzed by using PROCESS macro version 3.5, and bootstrapping was conducted to test the significance of the mediating effect. The main findings were as follows. First, adolescent stress significantly influenced smartphone addiction. Second, grit had a significant influence on smartphone addiction. Finally, grit partially mediated the relationship between stress and smartphone addiction. In other words, high levels of stress reduced grit, which in turn increased the smartphone addiction proneness. In addition, two factors of grit (consistency of interest and perseverance of effort) both mediated the association between stress and smartphone addiction. These results indicate that adolescent's daily stress may be a potential risk factor for smartphone addiction. Furthermore, by demonstrating the mediating effect of grit on the relationship between stress and smartphone addiction, the present study revealed that stress leads to smartphone addiction through lowered grit. This suggests that high level of grit is an important personal factor that may prevent the path of stress to smartphone addiction. Our study is meaningful in that it is the first study to empirically investigate adolescent's grit in relation to stress and smartphone addiction. Moreover, this study can provide useful information about prevention and intervention strategies for smartphone addiction. Limitations and directions for future studies are discussed.๋ณธ ์—ฐ๊ตฌ์˜ ๋ชฉ์ ์€ ์ฒญ์†Œ๋…„์˜ ์ŠคํŠธ๋ ˆ์Šค์™€ ์Šค๋งˆํŠธํฐ ์ค‘๋…์˜ ๊ด€๊ณ„์—์„œ ๊ทธ๋ฆฟ์˜ ๋งค๊ฐœํšจ๊ณผ๊ฐ€ ๋‚˜ํƒ€๋‚˜๋Š”์ง€ ์•Œ์•„๋ณด๋Š” ๊ฒƒ์ด๋‹ค. ์ฒญ์†Œ๋…„์˜ ์Šค๋งˆํŠธํฐ ์ด์šฉ์ด ์ฆ๊ฐ€ํ•จ์— ๋”ฐ๋ผ ๋งŽ์€ ์„ ํ–‰ ์—ฐ๊ตฌ๋“ค์€ ์Šค๋งˆํŠธํฐ ์ค‘๋…์˜ ๊ด€๋ จ ์š”์ธ์— ๋Œ€ํ•ด ์—ฐ๊ตฌํ•ด์™”๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋Œ€๋ถ€๋ถ„์˜ ์—ฐ๊ตฌ๋Š” ์Šค๋งˆํŠธํฐ ์ค‘๋…์œผ๋กœ ์ธํ•œ ๋ถ€์ •์  ๊ฒฐ๊ณผ๋ฅผ ์ค‘์‹ฌ์ ์œผ๋กœ ๋‹ค๋ฃจ์—ˆ์œผ๋ฉฐ ์ฒญ์†Œ๋…„๋“ค์ด ์–ด๋–ป๊ฒŒ ์Šค๋งˆํŠธํฐ ์ค‘๋…์— ์ด๋ฅด๊ฒŒ ๋˜๋Š”์ง€ ๊ทธ ๊ฒฝ๋กœ์— ๋Œ€ํ•œ ํƒ์ƒ‰์€ ์ƒ๋Œ€์ ์œผ๋กœ ๋ถ€์กฑํ•œ ์‹ค์ •์ด๋‹ค. ํŠนํžˆ ํ•œ๊ตญ ์ฒญ์†Œ๋…„๋“ค์„ ๋Œ€์ƒ์œผ๋กœ ์ŠคํŠธ๋ ˆ์Šค, ๊ทธ๋ฆฟ, ๊ทธ๋ฆฌ๊ณ  ์Šค๋งˆํŠธํฐ ์ค‘๋…์˜ ๊ด€๊ณ„๋ฅผ ํƒ์ƒ‰ํ•œ ์—ฐ๊ตฌ๋Š” ์ „๋ฌดํ•˜๋‹ค. ๋”ฐ๋ผ์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” 12์„ธ์—์„œ 16์„ธ ํ•œ๊ตญ ์ฒญ์†Œ๋…„๋“ค์„ ๋Œ€์ƒ์œผ๋กœ ์ŠคํŠธ๋ ˆ์Šค, ๊ทธ๋ฆฟ, ์Šค๋งˆํŠธํฐ ์ค‘๋…์˜ ๊ด€๊ณ„๋ฅผ ์•Œ์•„๋ณด์•˜๋‹ค. ๋”๋ถˆ์–ด ์ŠคํŠธ๋ ˆ์Šค์™€ ์Šค๋งˆํŠธํฐ ์ค‘๋…์˜ ๊ด€๊ณ„์—์„œ ๊ทธ๋ฆฟ์˜ ๋งค๊ฐœํšจ๊ณผ๊ฐ€ ๋‚˜ํƒ€๋‚˜๋Š”์ง€ ์•Œ์•„๋ณด์•˜๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—๋Š” 605๋ช…์˜ ํ•œ๊ตญ ์ฒญ์†Œ๋…„๋“ค์ด ์ฐธ์—ฌํ•˜์˜€์œผ๋ฉฐ (ํ‰๊ท  ์—ฐ๋ น = 13.97์„ธ), ์ฐธ์—ฌ์ž๋“ค์€ ์ŠคํŠธ๋ ˆ์Šค, ๊ทธ๋ฆฟ, ์Šค๋งˆํŠธํฐ ์ค‘๋…์„ ์ธก์ •ํ•˜๋Š” ์„ค๋ฌธ์ง€๋ฅผ ์™„๋ฃŒํ•˜์˜€๋‹ค. ์ŠคํŠธ๋ ˆ์Šค๋Š” ํ•œ๊ตญ์•„๋™์˜ ์ผ์ƒ์  ์ŠคํŠธ๋ ˆ์Šค ์ฒ™๋„(Han & Yoo, 1995)๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์ธก์ •ํ•˜์˜€์œผ๋ฉฐ, ๊ทธ๋ฆฟ์€ Original Grit Scale์˜ ๋ฒˆ์•ˆ๋œ ์ฒ™๋„(Duckworth et al., 2007; Park et al., 2020)๋กœ ์ธก์ •ํ•˜์˜€๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ์Šค๋งˆํŠธํฐ ์ค‘๋…์€ ํ•œ๊ตญ์ •๋ณดํ™”์ง„ํฅ์›(2011)์—์„œ ๊ฐœ๋ฐœํ•œ ์ฒญ์†Œ๋…„์šฉ ์Šค๋งˆํŠธํฐ ์ค‘๋… ์ž๊ฐ€์ง„๋‹จ ์ฒ™๋„๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์ธก์ •ํ•˜์˜€๋‹ค. ๋จผ์ € Pearson์˜ ์ƒ๊ด€๋ถ„์„์„ ์‚ฌ์šฉํ•˜์—ฌ ์ŠคํŠธ๋ ˆ์Šค, ๊ทธ๋ฆฟ, ์Šค๋งˆํŠธํฐ ์ค‘๋…์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋˜ํ•œ, ์ŠคํŠธ๋ ˆ์Šค์™€ ์Šค๋งˆํŠธํฐ ์ค‘๋…์˜ ๊ด€๊ณ„์—์„œ ๊ทธ๋ฆฟ์˜ ๋งค๊ฐœํšจ๊ณผ๊ฐ€ ๋‚˜ํƒ€๋‚˜๋Š”์ง€ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•˜์—ฌ Hayes(2017)์˜ PROCESS macro๋ฅผ ์‹ค์‹œํ•˜์˜€๊ณ , ๋งค๊ฐœํšจ๊ณผ์˜ ์œ ์˜์„ฑ์„ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•ด ๋ถ€ํŠธ์ŠคํŠธ๋ž˜ํ•‘(Bootstrapping)์„ ์‹ค์‹œํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ์˜ ์ฃผ์š” ๊ฒฐ๊ณผ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ, ์ฒญ์†Œ๋…„์˜ ์ŠคํŠธ๋ ˆ์Šค๋Š” ์Šค๋งˆํŠธํฐ ์ค‘๋…์— ์œ ์˜๋ฏธํ•œ ์˜ํ–ฅ์„ ๋ฏธ์ณค๋‹ค. ๋‘˜์งธ, ์ฒญ์†Œ๋…„์˜ ๊ทธ๋ฆฟ์€ ์Šค๋งˆํŠธํฐ ์ค‘๋…์— ์œ ์˜๋ฏธํ•œ ์˜ํ–ฅ์„ ๋ฏธ์ณค๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ๊ทธ๋ฆฟ์€ ์ŠคํŠธ๋ ˆ์Šค์™€ ์Šค๋งˆํŠธํฐ ์ค‘๋…์˜ ๊ด€๊ณ„๋ฅผ ๋ถ€๋ถ„ ๋งค๊ฐœํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ฆ‰, ์ŠคํŠธ๋ ˆ์Šค๊ฐ€ ๋†’์„์ˆ˜๋ก, ๊ทธ๋ฆฟ์€ ๋‚ฎ์•„์ง€๊ณ , ์ด๋Š” ์ฒญ์†Œ๋…„์˜ ์Šค๋งˆํŠธํฐ ์ค‘๋… ์„ฑํ–ฅ์„ ๋†’์ด๋Š” ๊ฒฝํ–ฅ์ด ์žˆ์—ˆ๋‹ค. ๊ฒŒ๋‹ค๊ฐ€, ๊ทธ๋ฆฟ์˜ ๋‘ ํ•˜์œ„ ์š”์†Œ (๋…ธ๋ ฅ ์ง€์†๊ณผ ํฅ๋ฏธ ์œ ์ง€) ๋ชจ๋‘ ์ŠคํŠธ๋ ˆ์Šค์™€ ์Šค๋งˆํŠธํฐ ์ค‘๋…์˜ ๊ด€๊ณ„๋ฅผ ๋ถ€๋ถ„ ๋งค๊ฐœํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฐ๊ณผ๋Š” ์ฒญ์†Œ๋…„์˜ ์ผ์ƒ์  ์ŠคํŠธ๋ ˆ์Šค๊ฐ€ ์Šค๋งˆํŠธํฐ ์ค‘๋…์˜ ์ž ์žฌ์  ์œ„ํ—˜ ์š”์ธ์ด ๋  ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ์˜๋ฏธํ•œ๋‹ค. ๋”๋ถˆ์–ด ์ŠคํŠธ๋ ˆ์Šค์™€ ์Šค๋งˆํŠธํฐ ์ค‘๋…์˜ ๊ด€๊ณ„์—์„œ ๊ทธ๋ฆฟ์ด ๋งค๊ฐœ ์—ญํ• ์„ ํ•œ๋‹ค๋Š” ๊ฒƒ์„ ๊ฒ€์ฆํ•จ์œผ๋กœ์จ ๋ณธ ์—ฐ๊ตฌ๋Š” ์ŠคํŠธ๋ ˆ์Šค๊ฐ€ ์Šค๋งˆํŠธํฐ ์ค‘๋…์œผ๋กœ ์ด์–ด์ง€๋Š” ๊ธฐ์ œ๋ฅผ ๋ฐํ˜”์œผ๋ฉฐ ๊ทธ๋ฆฟ์ด ์ฒญ์†Œ๋…„๊ธฐ ์Šค๋งˆํŠธํฐ ์ค‘๋… ์œ„ํ—˜์„ฑ์„ ์™„ํ™”ํ•˜๋Š” ๊ฐœ์ธ์  ์š”์ธ์ด ๋  ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ๋ฐํ˜”๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ฒญ์†Œ๋…„๊ธฐ ๊ทธ๋ฆฟ์„ ์ŠคํŠธ๋ ˆ์Šค, ์Šค๋งˆํŠธํฐ ์ค‘๋…๊ณผ ์—ฐ๊ด€์‹œ์ผœ ํƒ์ƒ‰ํ•œ ์ฒซ๋ฒˆ์งธ ๊ฒฝํ—˜์  ์—ฐ๊ตฌ์ด๋ฉฐ ์Šค๋งˆํŠธํฐ ์ค‘๋…์˜ ์˜ˆ๋ฐฉ๊ณผ ๊ฐœ์ž…์— ๋„์›€์„ ์ค„ ์ˆ˜ ์žˆ๋Š” ์ •๋ณด๋ฅผ ์ œ๊ณตํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์ ์—์„œ ํ•™๋ฌธ์  ์˜์˜๊ฐ€ ์žˆ๋‹ค. ๋…ผ์˜์—๋Š” ์ด ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„์ ๊ณผ ์ถ”ํ›„ ์—ฐ๊ตฌ ๋ฐฉํ–ฅ์— ๋Œ€ํ•œ ์ œ์–ธ์„ ์ œ์‹œํ•˜์˜€๋‹ค.TABLE OF CONTENTS Introduction 1 The Current Study 9 Theoretical Background 12 Stress and Smartphone Addiction 12 Grit and Smartphone Addiction 17 Stress and Grit 25 Research Questions and Hypotheses 28 Method 30 Participants 30 Measures 30 Procedures 32 Results 34 Descriptive Statistics among Stress, Grit, and Smartphone Addiction 35 Correlations between Stress, Grit, and Smartphone Addiction 38 Grit as a Mediator in the Relationship between Stress and Smartphone Addiction 41 Discussion 46 References 54 ๊ตญ๋ฌธ์ดˆ๋ก 78Maste

    Types of smartphone usage and problematic smartphone use among adolescents: A review of literature

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    This review aimed to provide an overview of the influence of social and process smartphone use on problematic smartphone use (PSU) among adolescents aged between 10-24 years old. Social smartphone use comprises three types of smartphone features: social networking sites, chatting/texting/instant messaging, and video/phone calls. On the other hand, categories of process smartphone use include watching videos/television/movies, web surfing, playing games, listening to music/podcasts/radio, and educational learning. There were 42 studies with a total of 139,389 adolescents met the criteria for inclusion after a thorough search of academic databases. Overall, the evidence from the studies included in this review revealed that chatting/texting, video/phone calls, watching videos/television/movies and music/podcasts/radio were positively and significantly linked to and predicted problematic smartphone use. Social networking sites use, instant messaging, gaming, web surfing and educational learning yielded inconsistent results. They could have a positive or negative relationship with PSU and play a role in predicting PSU. More research is needed for music/podcasts/radio and video/phone calls because the results are still scarce

    Internet and Smartphone Use-Related Addiction Health Problems: Treatment, Education and Research

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    This Special Issue presents some of the main emerging research on technological topics of health and education approaches to Internet use-related problems, before and during the beginning of coronavirus disease 2019 (COVID-19). The objective is to provide an overview to facilitate a comprehensive and practical approach to these new trends to promote research, interventions, education, and prevention. It contains 40 papers, four reviews and thirty-five empirical papers and an editorial introducing everything in a rapid review format. Overall, the empirical ones are of a relational type, associating specific behavioral addictive problems with individual factors, and a few with contextual factors, generally in adult populations. Many have adapted scales to measure these problems, and a few cover experiments and mixed methods studies. The reviews tend to be about the concepts and measures of these problems, intervention options, and prevention. In summary, it seems that these are a global culture trend impacting health and educational domains. Internet use-related addiction problems have emerged in almost all societies, and strategies to cope with them are under development to offer solutions to these contemporary challenges, especially during the pandemic situation that has highlighted the global health problems that we have, and how to holistically tackle them
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