| Literature DB >> 35967602 |
Winnie W Y Tso1,2, Frank Reichert3, Nancy Law3, King Wa Fu4, Jimmy de la Torre3, Nirmala Rao3, Lok Kan Leung1, Yu-Liang Wang1, Wilfred H S Wong1, Patrick Ip1.
Abstract
Background: Digital competence can help children and adolescents engage with technology for acquiring new knowledge and for broadening social contact and support, while reducing the risk of inappropriate media use. This study investigated the effects of digital competence on the risk of gaming addiction among children and adolescents. We explored whether students with good digital competence were protected from the adverse effects of media use and the risk of gaming addiction.Entities:
Keywords: Cyberbullying; Digital competence; Digital device; Digital literacy; Gaming addiction; Mental health
Year: 2022 PMID: 35967602 PMCID: PMC9366955 DOI: 10.1016/j.lanwpc.2022.100382
Source DB: PubMed Journal: Lancet Reg Health West Pac ISSN: 2666-6065
Subject characteristics
| Primary | Secondary | Overall | |
|---|---|---|---|
| (n=690) | (n=1266) | (n=1956) | |
| n (%) / Mean (SD) | n (%) / Mean (SD) | n (%) / Mean (SD) | |
| Basic Demographics | |||
| Gender | |||
| Male | 348 (50.4) | 596 (47.1) | 944 (48.3) |
| Female | 326 (47.2) | 661 (52.2) | 987 (50.5) |
| Not stated | 16 (2.3) | 9 (0.7) | 25 (1.5) |
| Digital Competence | |||
| Unidimensional Digital Competence | -0.759 (0.68) | 0.437 (0.78) | 0.016 (0.94) |
| Gaming addiction | |||
| Internet Gaming Disorder Scale | 18.683 (8.57) | 17.775(8.06) | 18.097 (8.25) |
| Time using electronic devices for leisure | (n=667) | (n=1213) | (n=1880) |
| Less than 1 hour per day | 300 (45.0) | 262 (21.6) | 562 (29.9) |
| 1-2 hours per day | 233 (34.9) | 379 (31.2) | 612 (32.6) |
| 2-3 hours per day | 79 (11.8) | 264 (21.8) | 343 (18.2) |
| More than 3 hours per day | 55 (8.2) | 308 (25.4) | 363 (19.3) |
| General Health Questionnaire (GHQ-12) | ⏤ | 0.95 (0.48) | ⏤ |
| Collaborative Problem Solving (CPS) | |||
| Cognitive | ⏤ | -0.25483 (1.04) | ⏤ |
| Social | ⏤ | 0.65621 (0.84) | ⏤ |
| Cyberbullying experience | (n=643) | (n=1198) | (n=1841) |
| As perpetrator only | 39 (6.1) | 87 (7.3) | 126 (6.8) |
| As victim only | 43 (6.7) | 160 (13.4) | 203 (11.0) |
| As both perpetrator and victim | 118 (18.4) | 191 (15.9) | 309 (16.8) |
| Not involved | 443 (68.9) | 760 (63.4) | 1203 (65.3) |
| Parents’ Education Level | |||
| Father | (n=278) | (n=749) | (n=1027) |
| Below secondary | 38 (13.7) | 118 (15.8) | 156 (15.2) |
| Secondary | 76 (27.3) | 378 (50.5) | 454 (44.2) |
| Associate degree | 30 (10.8) | 38 (5.1) | 68 (6.6) |
| Bachelor's degree | 134 (48.2) | 215 (28.7) | 349 (34.0) |
| Mother | (n=267) | (n=791) | (n=1058) |
| Below secondary | 65 (24.3) | 160 (20.2) | 225 (21.3) |
| Secondary | 84 (31.5) | 425 (53.7) | 509 (48.1) |
| Associate degree | 16 (6.0) | 23 (2.9) | 39 (3.7) |
| Bachelor's degree | 102 (38.2) | 183 (23.1) | 285 (26.9) |
Prevalence of gaming addiction according to digital device usage time
| Time Using Digital Devices for Leisure. | Prevalence of gaming addiction | ||
|---|---|---|---|
| Secondary school student | Primary School student | Total | |
| Less than 1 hour per day | 6.9% | 5.7% | 6.3% |
| 1-2 hours per day | 4% | 8.4% | 5.6% |
| 2-3 hours per day | 4.2% | 9.0% | 5.3% |
| More than 3 hours per day | 11.7% | 16.4% | 12.4% |
P < .01. Chi-square test was used to Compare digital device usage time in the same age group.
Partial Correlation between variables after controlling for gender and socioeconomic status (SES) index
| Variables | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
|---|---|---|---|---|---|---|---|
| 1. Digital Competence | — | ||||||
| 2. Gaming Addiction | -0.148 | — | |||||
| 3. GHQ score | 0.027 | 0.248 | — | ||||
| 4. Cybervictimization | -0.119 | 0.278 | 0.245 | — | |||
| 5. Cyberbullying | -0.164 | 0.319 | 0.180 | 0.631 | — | ||
| 6. Cognitive CPS | 0.400 | -0.083 | -0.012 | 0.029 | -0.012 | — | |
| 7. Social CPS | 0.259 | -0.095 | -0.043 | 0.025 | -0.006 | 0.609 | — |
| 8. Time using electronic devices for leisure | 0.236 | 0.172 | 0.088 | 0.091 | 0.063 | -0.021 | -0.036 |
p < 0.01
p < 0.001.
Note. Missing values were excluded pairwise. Only secondary school students filled in the GHQ and participated in the CPS assessments (variables 3, 6, and 7).
Figure 1Game addiction as a function of digital competence in primary and secondary school children after controlling for gender and SES.
Figure 2Relationship between digital device usage time, gaming addiction, digital competence, and mental health status after controlling for gender and SES. Mental health status was measured by the GHQ scale (reverse coded). Standardized regression coefficient (beta) was used as the path coefficient. TE: total effect. DE: direct effect. ** p < 0.01, ***p < 0.001, ns: not significant.
Figure 3Cyberbullying as a function of digital competence at different levels of game addiction after controlling for gender and SES. Low, medium, and high levels of game addiction defined as 1 S.D. below, equal to, and 1 S.D. above the mean level of game addiction, respectively.
Figure 4Cybervictimization as a function of digital competence at different levels of game addiction after controlling for gender and SES. Low, medium, and high levels of game addiction defined as 1 S.D. below, equal to, and 1 S.D. above the mean level of game addiction, respectively.