Resilience as a predictor of internet addictive behaviours: a study among Ghanaian and Saudi samples using structural equation modelling approach
Abstract This study aimed to examine the relationship between resilience and internet addictive behaviours, focusing on cross-cultural contexts involving tertiary education students in Ghana and Saudi Arabia. Using a cross-sectional survey design, data were collected from 738 students across selecte...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-01-01
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| Series: | BMC Psychology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40359-025-02383-y |
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| Summary: | Abstract This study aimed to examine the relationship between resilience and internet addictive behaviours, focusing on cross-cultural contexts involving tertiary education students in Ghana and Saudi Arabia. Using a cross-sectional survey design, data were collected from 738 students across selected universities in both countries. Structural equation modeling (SEM) techniques were employed to analyse the data. The findings indicated that most respondents exhibited low resilience levels alongside a high prevalence of internet addictive behaviours. A significant positive relationship was identified between resilience levels and various dimensions of internet addiction, as well as the overall composite of internet addictive behaviours. Interestingly, while low resilience levels were found to increase the risk of internet addiction, higher resilience levels also appeared to heighten susceptibility to addictive behaviours. These results suggest the need for targeted interventions to address internet addiction. Programs should focus on enhancing resilience through resilience-building initiatives, promoting digital well-being, and integrating mental health support services. These approaches can help mitigate the risks associated with internet addiction while fostering healthier coping mechanisms in students across diverse cultural settings. |
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| ISSN: | 2050-7283 |