| Literature DB >> 35619797 |
Lihong Lu1, Mei Liu2, Binchao Ge3, Zijin Bai2, Ziqi Liu2.
Abstract
The adolescent addiction to short video applications is becoming increasingly prominent, which has brought great challenges to the physical and mental health and daily life of the adolescents. This manuscript conducts an empirical study on the contributing factors of the adolescent addiction to short video applications based on the user generated content (UGC). In our study, 96 participants aged 15-25 were surveyed by questionnaire, and then cross-analysis of individual factors and SEM analysis of UGC content factors were carried out. Through the analysis of individual factors of the adolescent addiction from the perspective of gender, age, and family environment, this study reveals that male users are more addicted to the use of applications (APP), and such addiction varies with age, and prolonged family members' use of short video APP can also exacerbate the adolescent addiction degree. Furthermore, through verification of the theoretical model, it indicates that UGC perception and the degree of boredom in daily life have a significant positive effect on the level of addiction to short video applications, and the degree of boredom in daily life plays a significant mediating role between them. Based on the research on the influences of UGC on the adolescent immersive experience, this study proposes a mechanism of the adolescent addiction to the use of short video applications in the mobile Internet age to provide a better service guarantee for the adolescents.Entities:
Keywords: UGC; addiction to short video applications; adolescent; flow theory; immersive experience
Year: 2022 PMID: 35619797 PMCID: PMC9127662 DOI: 10.3389/fpsyg.2022.893599
Source DB: PubMed Journal: Front Psychol ISSN: 1664-1078
FIGURE 1Theoretical model of adolescent addiction to short video apps.
Cross-sectional analysis of gender and addiction degree.
| I spent plenty of time thinking about or planning to use Douyin | Total | ||||
|
| |||||
| Take a positive attitude | Be neutral | Take a negative attitude | |||
| Gender | Male | 3 | 18 | 30 | 51 |
| Female | 9 | 6 | 30 | 45 | |
| Total | 12 | 24 | 60 | 96 | |
Cross-sectional analysis of age group and addiction degree.
| I failed to reduce using Douyin | Total | ||||
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| |||||
| Take a positive attitude | Be neutral | Take a negative attitude | |||
| Age Group | Aged 15–17 | 0 | 12 | 15 | 27 |
| Aged 18–21 | 6 | 6 | 27 | 39 | |
| Aged 22–25 | 6 | 3 | 21 | 30 | |
| Total | 12 | 21 | 63 | 96 | |
Cross-sectional analysis of family environment and addiction degree.
| I failed to reduce using Douyin | Total | ||||
|
| |||||
| Take a positive attitude | Be neutral | Take a negative attitude | |||
| Family Environment (Duration of using short video apps) | Within 1 h | 6 | 9 | 12 | 27 |
| 1–2.5 h | 0 | 6 | 3 | 9 | |
| 2.5–4 h | 3 | 9 | 33 | 45 | |
| More than 4 h | 0 | 3 | 12 | 15 | |
| Total | 9 | 27 | 60 | 96 | |
Setting and source of factor items.
| Constructs | Measurement items | Sources |
| UGC perception | UG1: How much is Douyin in your life? |
|
| UG2: To what extent do you forget your daily worries while swiping Douyin? | ||
| UG3: To what extent do you feel that the content of Douyin’s short videos is something you’re experiencing, rather than just something you’re watching? | ||
| UG4: To what extent do you feel like you’re swiping Douyin on your own terms? | ||
| UG5: When you stop swiping Douyin, to what extent do you want to swipe Douyin again? | ||
| Boredom in daily life | RC1: Everyday life is not going as I planned |
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| RC2: I often lose myself in daily life and feel directionless | ||
| RC3: In my daily life, I often get caught up in something and lose track of time | ||
| Addiction | SY1: I spend a lot of time thinking about Or planning to use Douyin |
|
| SY2: I want to swipe Douyin more and more frequently | ||
| SY3: I use Douyin to escape from reality | ||
| SY4: I fail to reduce the use of Douyin | ||
| SY5: If I was banned from using Douyin, I would get anxious | ||
| SY6: I overuse Douyin in my daily life, which has a negative impact on my work and study |
Total variance interpretation.
| Component | Initial eigenvalues | Extraction sums of squared loading | Rotation sums of loading | ||||||
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| Total | Percentage of variance % | Cumulative % | Total | Percentage of variance % | Cumulative % | Total | Percentage of variance % | Cumulative % | |
| UG | 7.974 | 56.960 | 56.960 | 7.974 | 56.960 | 56.960 | 4.197 | 29.976 | 29.976 |
| SY | 1.526 | 10.902 | 67.862 | 1.526 | 10.902 | 67.862 | 3.681 | 26.291 | 56.267 |
| RC | 1.164 | 8.311 | 76.173 | 1.164 | 8.311 | 76.173 | 2.787 | 19.906 | 76.173 |
Extraction method: principal component analysis.
FIGURE 2Structural model of adolescent addiction to short video apps.
Path analysis.
| Path coefficient | Hypothesis | |||
| RC–>SY | 4.158 | 0.000 | 0.298 | H2 verified |
| UG–>RC | 10.876 | 0.000 | 0.631 | H3 verified |
| UG–>SY | 6.131 | 0.000 | 0.559 | H1 verified |
| UG–>RC–>SY | 3.707 | 0.000 | 0.188 | H4 verified |