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. 2019 Apr 2;21(4):e11485.
doi: 10.2196/11485.

To Each Stress Its Own Screen: A Cross-Sectional Survey of the Patterns of Stress and Various Screen Uses in Relation to Self-Admitted Screen Addiction

Affiliations

To Each Stress Its Own Screen: A Cross-Sectional Survey of the Patterns of Stress and Various Screen Uses in Relation to Self-Admitted Screen Addiction

Najmeh Khalili-Mahani et al. J Med Internet Res. .

Abstract

Background: The relationship between stress and screen addiction is often studied by exploring a single aspect of screen-related behavior in terms of maladaptive dependency or the risks associated with the content. Generally, little attention is given to the pattern of using different screens for different types of stressors, and variations arising from the subjective perception of stress and screen addiction are often neglected. Given that both addiction and stress are complex and multidimensional factors, we performed a multivariate analysis of the link between individual's subjective perceptions of screen addiction, various types of stress, and the pattern of screen usage.

Objective: Using the media-repertoires framework to study usage patterns, we explored (1) the relation between subjective and quantitative assessments of stress and screen addiction; and (2) differences in stress types in relation to subjective screen addiction and different types of needs for screens. We hypothesized that interindividual heterogeneity in screen-related behavior would reflect coping differences in dealing with different stressors.

Methods: A multifactorial Web-based survey was conducted to gather data about screen-related behaviors (such as screen time, internet addiction, and salience of different types of screens and related activities), and different sources of stress (emotional states, perceptual risks, health problems, and general life domain satisfaction). We performed group comparisons based on whether participants reported themselves as addicted to internet and games (A1) or not (A0), and whether they had experienced a major life stress (S1) or not (S0).

Results: Complete responses were obtained in 459 out of 654 survey responders, with the majority in the S1A0 (44.6%, 205/459) group, followed by S0A0 (25.9%, 119/459), S1A1 (19.8%, 91/459), and S0A1 (9.5%, 44/459). The S1A1 group was significantly different from S0A0 in all types of stress, internet overuse, and screen time (P<.001). Groups did not differ in rating screens important for short message service (SMS) or mail, searching information, shopping, and following the news, but a greater majority of A1 depended on screens for entertainment (χ23=20.5; P<.001), gaming (χ23=35.6; P<.001), and social networking (χ23=26.5; P<.001). Those who depended on screens for entertainment and social networking had up to 19% more emotional stress and up to 14% more perceptual stress. In contrast, those who relied on screens for work and professional networking had up to 10% higher levels of life satisfaction. Regression models including age, gender, and 4 stress types explained less than 30% of variation in internet use and less than 24% of the likelihood of being screen addicted.

Conclusions: We showed a robust but heterogeneous link between screen dependency and emotional and perceptual stressors that shift the pattern of screen usage toward entertainment and social networking. Our findings underline the potential of using ludic and interactive apps for intervention against stress.

Keywords: addictive behavior; communications; coping behavior; eHealth; gaming, internet; psychological stress; social network; telemedicine.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
(A) Distribution of the sample based on self-rated screen addiction and recent stress; (B) Group differences in age; (C) Group differences in internet overuse; (D) Group differences in daily screen time; (E) Group differences in emotional stress; (F) Group differences in perceptual stress; (G) Group differences in health stress; (H) Group differences in life dissatisfaction; (I) Posthoc estimated mean differences of stress based on Screen x Addiction categories. The largest differences are observed in comparison of S0A0 (neither addicted nor stressed) versus S1A1 (both addicted and stressed).
Figure 2
Figure 2
Radar diagram of the ratio of individuals within each group who rated various aspects of the screen repertoires highly; (A) How important are these activities to your daily life? (B) What is the degree of daily dependence on screens for these activities? (C) How essential is it to access these screens on a holiday or during the weekend.

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