| Literature DB >> 35329369 |
Soon-Aun Tan1,2, Yee Shan Goh1, Norzarina Mohd Zaharim2, Su Wan Gan1, Chin Choo Yap3, Sarvarubini Nainee1, Ling Khai Lee4.
Abstract
Internet pornography use (IPU) refers to Internet-based sexually explicit materials that are ultimately used to elicit sexual feelings or thoughts. The accessibility of Internet pornography could lead to excessive exposure to pornographic messages, posing a risk to heavy users' psychological health. This paper offers a preliminary understanding of the relationship between Internet pornography use and psychological distress among emerging adults and the moderating role of gender in the association. This cross-sectional study has taken a purposive sampling approach to recruit 144 emerging adult pornography users via the online survey method. The results indicated that males reported having more problematic Internet pornography use, and there were no gender differences in psychological distress. Meanwhile, gender is a significant moderator between Internet pornography use and psychological distress. The females were found to be more psychologically affected by their problematic Internet pornography use than the males. Overall, this study has provided a novel finding of the moderating role of gender in problematic Internet pornography use and psychological distress in the Malaysian context. This study also calls for a gender-focused sexual health programme for Malaysian emerging adults. Furthermore, the scores of problematic IPU in this study raise a concern over the effectiveness of current sex education in Malaysia. The scores may highlight the need to provide education targeting Internet pornography use.Entities:
Keywords: Malaysia; emerging adults; gender; internet pornography; psychological distress
Mesh:
Year: 2022 PMID: 35329369 PMCID: PMC8951151 DOI: 10.3390/ijerph19063682
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Demographic information of the participants (n = 144).
|
| % | Mean | SD | Min. | Max. | |
|---|---|---|---|---|---|---|
| Age | 21.41 | 3.49 | 18 | 29 | ||
| Gender | ||||||
| Male | 91 | 63.2 | ||||
| Female | 53 | 36.8 | ||||
| Ethnicity | ||||||
| Malays | 28 | 19.4 | ||||
| Chinese | 98 | 68.1 | ||||
| Indians | 16 | 11.1 | ||||
| Others | 2 | 1.4 | ||||
| Employment Status | ||||||
| Students | 98 | 68.1 | ||||
| Full-time employed | 34 | 23.6 | ||||
| Unemployed | 12 | 8.3 | ||||
| Relationship Status | ||||||
| Single | 84 | 58.7 | ||||
| In-relationship | 43 | 30.1 | ||||
| Married | 16 | 11.2 |
Note: SD = Standard deviation.
Gender differences in problematic IPU (n = 144).
| Variable | Total | Male | Female |
|
| |||
|---|---|---|---|---|---|---|---|---|
| Mean | SD | Mean | SD | Mean | SD | |||
| Salience | 2.96 | 1.51 | 3.30 | 1.54 | 2.38 | 1.27 | 3.83 | <0.001 |
| Mood Modification | 3.10 | 1.68 | 3.42 | 1.67 | 2.54 | 1.55 | 3.16 | 0.002 |
| Conflict | 2.31 | 1.35 | 2.55 | 1.42 | 1.91 | 1.15 | 2.93 | 0.004 |
| Tolerance | 2.50 | 1.47 | 2.69 | 1.50 | 2.19 | 1.36 | 2.05 | 0.043 |
| Relapse | 2.86 | 1.57 | 3.23 | 1.54 | 2.21 | 1.42 | 4.01 | <0.001 |
| Withdrawal | 2.24 | 1.42 | 2.40 | 1.45 | 1.96 | 1.35 | 1.81 | 0.073 |
| Problematic Pornography Use | 2.66 | 1.28 | 2.93 | 1.25 | 2.20 | 1.22 | 3.42 | 0.001 |
Note: SD = Standard Deviation.
Matric correlation between variables (n = 144).
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | |
|---|---|---|---|---|---|---|---|---|
| 1. Salience | 1 | |||||||
| 2. Mood modification | 0.81 *** | 1 | ||||||
| 3. Conflict | 0.44 *** | 0.47 *** | 1 | |||||
| 4. Tolerance | 0.73 *** | 0.72 *** | 0.60 *** | 1 | ||||
| 5. Relapse | 0.78 *** | 0.71 *** | 0.53 *** | 0.77 *** | 1 | |||
| 6. Withdrawal | 0.78 *** | 0.75 *** | 0.51 *** | 0.78 *** | 0.75 *** | 1 | ||
| 7. Problematic IPU | 0.89 *** | 0.88 *** | 0.68 *** | 0.89 *** | 0.89 *** | 0.89 *** | 1 | |
| 8. Psychological distress | 0.13 | 0.17 * | 0.28 *** | 0.12 | 0.17 * | 0.19 * | 0.20 ** | 1 |
Note: *** p < 0.001; ** p < 0.01; * p < 0.05.
Figure 1Interaction between problematic internet pornography use and gender in predicting psychological distress (n = 144). Note: *** p < 0.001.