This study aimed to explore the relationships between internet addiction on Depression, Anxiety and Stress of 154 students from various universities in the Chittagong regions. The primary data was collected through Google Forms and Cronbach's Alpha was used to evaluate the reliability of four key constructs: internet addiction, depression, anxiety, and stress. The results showed a positive relationship between the severity of internet addiction and elevated levels of depression, anxiety, and stress. The study also revealed deviations from normality in anxiety scores across different groups, particularly within those with complete control over their internet usage. Further investigation is to understand the complexities contributing to this non-normal distribution. Anxiety scores were analyzed using the Kruskal-Walli’s test, but no significant differences were found in subcategories A2 and A19. The study also used the Kruskal-Wallis H statistic to analyze depression, anxiety, and stress scores across different categories of Internet Addiction Test (IAT) scores. A Structural Equation Modeling (SEM) analysis was used to assess the model's fit, revealing an outstanding CFI and commendable NFI, GFI, and AGFI indices. The model effectively explained a substantial portion of the variation in anxiety, stress, and depression, indicating the underlying relationships. The study provides valuable insights into the profound relationship between internet addiction and psychological constraints, emphasizing the need for targeted interventions to mitigate the detrimental impact of internet addiction on mental health. According to study findings, it's significant to inform students about the harmful effects of the internet and encourage responsible internet use, even though it's impossible to entirely prevent it.
| Published in | Research & Development (Volume 4, Issue 4) |
| DOI | 10.11648/j.rd.20230404.18 |
| Page(s) | 177-186 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2023. Published by Science Publishing Group |
Internet Addiction, Depression, Anxiety and Stress
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APA Style
Akter Keya, J., Ashraful Islam, M. (2023). Internet Addiction's Impact on Depression, Anxiety and Stress: A Comprehensive Statistical Analysis. Research & Development, 4(4), 177-186. https://doi.org/10.11648/j.rd.20230404.18
ACS Style
Akter Keya, J.; Ashraful Islam, M. Internet Addiction's Impact on Depression, Anxiety and Stress: A Comprehensive Statistical Analysis. Res. Dev. 2023, 4(4), 177-186. doi: 10.11648/j.rd.20230404.18
AMA Style
Akter Keya J, Ashraful Islam M. Internet Addiction's Impact on Depression, Anxiety and Stress: A Comprehensive Statistical Analysis. Res Dev. 2023;4(4):177-186. doi: 10.11648/j.rd.20230404.18
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Download@article{10.11648/j.rd.20230404.18,
author = {Jahanara Akter Keya and Md. Ashraful Islam},
title = {Internet Addiction's Impact on Depression, Anxiety and Stress: A Comprehensive Statistical Analysis},
journal = {Research & Development},
volume = {4},
number = {4},
pages = {177-186},
doi = {10.11648/j.rd.20230404.18},
url = {https://doi.org/10.11648/j.rd.20230404.18},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.rd.20230404.18},
abstract = {This study aimed to explore the relationships between internet addiction on Depression, Anxiety and Stress of 154 students from various universities in the Chittagong regions. The primary data was collected through Google Forms and Cronbach's Alpha was used to evaluate the reliability of four key constructs: internet addiction, depression, anxiety, and stress. The results showed a positive relationship between the severity of internet addiction and elevated levels of depression, anxiety, and stress. The study also revealed deviations from normality in anxiety scores across different groups, particularly within those with complete control over their internet usage. Further investigation is to understand the complexities contributing to this non-normal distribution. Anxiety scores were analyzed using the Kruskal-Walli’s test, but no significant differences were found in subcategories A2 and A19. The study also used the Kruskal-Wallis H statistic to analyze depression, anxiety, and stress scores across different categories of Internet Addiction Test (IAT) scores. A Structural Equation Modeling (SEM) analysis was used to assess the model's fit, revealing an outstanding CFI and commendable NFI, GFI, and AGFI indices. The model effectively explained a substantial portion of the variation in anxiety, stress, and depression, indicating the underlying relationships. The study provides valuable insights into the profound relationship between internet addiction and psychological constraints, emphasizing the need for targeted interventions to mitigate the detrimental impact of internet addiction on mental health. According to study findings, it's significant to inform students about the harmful effects of the internet and encourage responsible internet use, even though it's impossible to entirely prevent it.
},
year = {2023}
}
TY - JOUR T1 - Internet Addiction's Impact on Depression, Anxiety and Stress: A Comprehensive Statistical Analysis AU - Jahanara Akter Keya AU - Md. Ashraful Islam Y1 - 2023/12/28 PY - 2023 N1 - https://doi.org/10.11648/j.rd.20230404.18 DO - 10.11648/j.rd.20230404.18 T2 - Research & Development JF - Research & Development JO - Research & Development SP - 177 EP - 186 PB - Science Publishing Group SN - 2994-7057 UR - https://doi.org/10.11648/j.rd.20230404.18 AB - This study aimed to explore the relationships between internet addiction on Depression, Anxiety and Stress of 154 students from various universities in the Chittagong regions. The primary data was collected through Google Forms and Cronbach's Alpha was used to evaluate the reliability of four key constructs: internet addiction, depression, anxiety, and stress. The results showed a positive relationship between the severity of internet addiction and elevated levels of depression, anxiety, and stress. The study also revealed deviations from normality in anxiety scores across different groups, particularly within those with complete control over their internet usage. Further investigation is to understand the complexities contributing to this non-normal distribution. Anxiety scores were analyzed using the Kruskal-Walli’s test, but no significant differences were found in subcategories A2 and A19. The study also used the Kruskal-Wallis H statistic to analyze depression, anxiety, and stress scores across different categories of Internet Addiction Test (IAT) scores. A Structural Equation Modeling (SEM) analysis was used to assess the model's fit, revealing an outstanding CFI and commendable NFI, GFI, and AGFI indices. The model effectively explained a substantial portion of the variation in anxiety, stress, and depression, indicating the underlying relationships. The study provides valuable insights into the profound relationship between internet addiction and psychological constraints, emphasizing the need for targeted interventions to mitigate the detrimental impact of internet addiction on mental health. According to study findings, it's significant to inform students about the harmful effects of the internet and encourage responsible internet use, even though it's impossible to entirely prevent it. VL - 4 IS - 4 ER -
Department of Statistics, University of Chittagong, Chattogram, Bangladesh
Department of Natural Science, Port City International University, Chattogram, Bangladesh
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