| Literature DB >> 36078377 |
Chung-Ying Yang1, Fong-Ching Chang2, Ru Rutherford2, Wen-Yu Chen2, Chiung-Hui Chiu3, Ping-Hung Chen4, Jeng-Tung Chiang5, Nae-Fang Miao6, Hung-Yi Chuang7, Chie-Chien Tseng2.
Abstract
In this study, we examined excessive online gaming by adolescents and the resultant effects of their exposure to the online marketing of energy drinks and alcohol, and whether marketing literacy could serve as a mitigating factor. This cross-sectional study was conducted in 2020. Data were obtained from a sample of 2613 seventh-grade students from 30 middle schools in Taiwan. A self-administered questionnaire was conducted. The results showed that nearly 18% of the adolescent respondents had used energy drinks, while 75% reported seeing energy-drink advertisements on the internet in the past year. Multiple regression results indicated that factors such as being male, reporting excessive gaming, being exposed to higher levels of online energy-drink marketing, and reporting alcohol use were positively associated with energy-drink consumption. A higher level of online energy-drink marketing-affective literacy, however, was negatively associated with energy-drink consumption. In conclusion, factors that predicted energy-drink consumption among adolescents included excessive gaming and exposure to online energy-drink marketing, but marketing-affective literacy tended to lessen the impact of such advertising.Entities:
Keywords: energy drinks; excessive gaming; literacy; online marketing exposure
Mesh:
Year: 2022 PMID: 36078377 PMCID: PMC9518090 DOI: 10.3390/ijerph191710661
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 4.614
Gender differences in energy-drink consumption and related factors.
| Overall | Girls | Boys | |||||
|---|---|---|---|---|---|---|---|
| Mean | SD | Mean | SD | Mean | SD | ||
| Online energy-drink marketing exposure | 2.53 | 1.23 | 2.55 | 1.21 | 2.51 | 1.26 | 0.433 |
| Energy-drink advertising effect | 1.51 | 0.64 | 1.44 | 0.57 | 1.58 | 0.70 | <0.001 |
| Energy-drink digital marketing cognitive literacy | 2.83 | 0.60 | 2.87 | 0.52 | 2.78 | 0.67 | 0.001 |
| Energy-drink digital marketing affective literacy | 2.78 | 0.67 | 2.80 | 0.61 | 2.77 | 0.73 | 0.281 |
| Energy-drink consumption | 1.55 | 1.03 | 1.41 | 0.88 | 1.71 | 1.14 | <0.001 |
| Alcohol use | 1.28 | 0.70 | 1.35 | 0.77 | 1.21 | 0.60 | <0.001 |
| Gaming addiction | 3.06 | 2.52 | 2.43 | 2.36 | 3.78 | 2.50 | <0.001 |
N = 2613. T-tests conducted.
Factors related to energy-drink consumption.
| Β | SE |
| VIF | |
|---|---|---|---|---|
| Gender (Female = 0, Male = 1) | 0.24 | 0.04 | <0.001 | 1.11 |
| Area (Urban = 0, Rural = 1) | 0.02 | 0.04 | 0.563 | 1.04 |
| Online energy-drink marketing exposure | 0.09 | 0.02 | <0.001 | 1.07 |
| Energy-drink advertising effect | 0.51 | 0.03 | <0.001 | 1.13 |
| Energy-drink digital marketing cognitive literacy | 0.01 | 0.03 | 0.696 | 1.19 |
| Energy-drink digital marketing affective literacy | −0.06 | 0.03 | 0.033 | 1.18 |
| Alcohol use | 0.27 | 0.03 | <0.001 | 1.04 |
| Excessive gaming | 0.02 | 0.01 | 0.002 | 1.14 |
N = 2613. Multiple regression conducted.