Impact of Socioeconomic and Structural Determinants on Sustained Treatment Discontinuation among Chronic Disease Patients in Ghazni Province
DOI:
https://doi.org/10.65486/0n4az772Keywords:
Treatment, Sustained-treatment, chronically ill patients, DiscontinuationAbstract
Purpose: This study delves into the role of Socioeconomic and structural determinants on sustained treatment discontinuation within the context of Ghazni province.
Method: This study employed a quantitative, survey-based descriptive research design, utilizing a structured questionnaire for data collection. A statistically significant sample of 385 participants was selected using the Cochran sampling method.
The collected data were analyzed using SPSS statistical software, applying Pearson’s correlation coefficient to assess the strength and direction of relationships between variables. Additionally, multiple regression analysis was conducted to determine the predictive influence of socioeconomic and structural determinants on discontinuation of sustained treatment.
Result: The study included a sample of 385 participants from Ghazni Province, selected via the Cochran Sampling method. The findings of the research and data analysis, by revealing a significant positive correlation between socioeconomic & structural determinants and sustained treatment discontinuation, prove that socioeconomic situation plays a crucial role in the continuous treatment of the chronically ill patients. Specifically, the correlation coefficient of 0.821 indicates a strong direct relationship.
Practical Implications: These findings hold the potential to guide administrators and policymakers to support the public general hospitals, control the costs, thereby playing a pivotal role in supporting the performance and operational efficiency.
Originality/Novelty: The findings of the research and data analysis by revealing a significant positive correlation between socioeconomic & structural determinants and sustained treatment discontinuation, prove that socioeconomic situation plays a crucial role in the continuous treatment of the chronically ill patients.
Downloads
References
Akseer, N., Kandru, G., Keats, E., & Bhutta, Z. (2020). COVID-19 and the impact on health systems, service delivery, and maternal and child health in Afghanistan. BMJ Global Health, 5(6), 1- 13. doi:https://doi.org/10.1136/bmjgh-2020-002306
An, S., Meier, K., Ladenburg, J., & Westergård-Nielsen, N. (2020). Leadership and job satisfaction: Addressing endogeneity with panel data from a field experiment. Review of Public Personnel Administration, 40*(4), 589-612. doi:https://doi.org/10.1177/0734371X19839180
Bhatia, M., & Sinha, D. (2023). The economic cost of rising non-communicable diseases in India: A macro and micro perspective. PharmacoEconomics - Open, 7(3), 345–359. doi:https://doi.org/10.1007/s40258-023-00822-8
Blonde, L., McLaughlin, M., Qiu, Y., Augustin, K., Kern, D., Evans, K., & Korrer, K. (2022). Increased Healthcare Resource Use and Costs After Discontinuation of Liraglutide in Adults with Type 2 Diabetes. Diabetes Therapy, 1201–1215. doi:https://doi.org/10.1007/s13300-022-01322-z
BMC Women’s Health. (2023). Socio-economic variations of breast cancer treatment and discontinuation. BMC: BMC Women’s Health.
Bodenheimer, T., & Berry-Millett, R. (2009). Chronic Disease Prevention and Management: The Role of Primary Care. The Future of Primary Care: Transforming Practice, 1-30. Retrieved from https://www.ncbi.nlm.nih.gov/books/NBK43749/
Brown, M., Trevino, L., & Harrison, D. (2005). Ethical leadership: A social learning perspective for construct development and testing. . Organizational Behavior & Human Decision Processes, 97(2), 117-134.
Cronbach, L. (1951). coefficient alpha and the internal structure of tests. psychometrika springer science and business media LLC, 297-334. Retrieved from https://psycnet.apa.org/record/1952-03137-001
Das, K., Banerjee, M., Mondal, G., Devi, L., Singh, O., & Mukherjee, B. (2007). Evaluation of socio- economic factors causing discontinuation of epilepsy treatment resulting in seizure recurrence: A study in an urban epilepsy clinic in India. Seizure, 601–607. doi:10.1016/j.seizure.2007.05.009
Dodd, R., Palagyi, A., Guild, L., Jha, V., & Jan, S. (2018). The impact of out-of-pocket costs on treatment commencement and adherence in chronic kidney disease: a systematic review. Health Policy and Planning, 33, 1047–1054. doi:10.1093/heapol/czy081
Dodd, R., Palagyi, A., Jan, S., & Peiris, D. (2018). Economic impact of non-communicable disease on households in low- and middle-income countries: A systematic review. Health Policy and Planning, 33(5), 675–690. doi:https://doi.org/10.1093/heapol/czy021
Essue, B., Laba, T., & Jan, S. (2017). Economic burden of chronic diseases: Multimorbidity and implications for health policy. . Health Policy, 121(1), 1–7.
pg. 17
Arghand Journal of Social Science (AJSS) | XXXXXXX | Volume No. XX | Issue No. XX | p. XX - XX | E-ISSN:
Freedman, D., Pisani, R., & Purves, R. (2007). Statistics (international student edition). Pisani: R. Purves. Retrieved from https://www.amazon.com/Statistics-4th-David- Freedman/dp/0393929728
Habibi, S. (2024). The Role of Smart Technologies in the Relationship Between Volatile, Uncertain, Complex, and Ambiguous Business Environment (VUCA) and Organizational Agility. Industrial Enterprises Research [Ph.D]: Selçuk University.
Julie, M., & Khera, N. (2015). Financial Hardship: An Unwanted Consequence of Cancer Treatment. Current Hematologic Malignancy Reports, 202–210. doi:https://doi.org/10.1007/s11899-015- 0266-1
Khan, N., Patel, D., Trivedi, C., & Yang, Y. (2023). Economic impact of biologic discontinuation in inflammatory bowel disease: A real-world analysis. Inflammatory Bowel Diseases, 29(2), 215–223. doi:https://doi.org/10.1093/ibd/izac198
Kwak, S., & Kim, J. (2017). Central limit theorem: The cornerstone of modern statistics. Korean Journal of Anesthesiology, 70(2), 144-158. doi:https://doi.org/10.4097/kjEA.2017.70.2.144
Lee, S., Koo, J., Kim, Y., & Park, D. (2021). Long-term outcomes after discontinuation of anti-TNF therapy in patients with inflammatory bowel disease: A multicenter cohort study. Journal of Crohn's and Colitis, 15(4), 678–686. doi:https://doi.org/10.1093/ecco-jcc/jjaa222
May, C., Eton, D., Boehmer, K., Gallacher, K., Hunt, K., MacDonald, S., & Montori, V. (2014). Assessing the burden of treatment. Journal of General Internal Medicine, 29(3), 477–485. doi:https://doi.org/10.1007/s11606-017-4117-8
Muka, T., Imo, D., & Franco, O. (2015). The global impact of non-communicable diseases on healthcare spending and national income: A systematic review. European Journal of Epidemiology, 30(4), 251–277. doi:https://doi.org/10.1007/s10654-014-9984-2
Naghavi, M. (2017). Global mortality from chronic diseases. The Lancet, 390(10100), 1151–1210.
Nele, K., Norbert, D.-B., Ina, S., Nina, G., Annette, B., & Annika, V. (2025). Trials evaluating drug discontinuation:a scoping review sub-analysis focusing on outcomes and research questions. BMC Medical Research Methodology, 1-14. doi:https://doi.org/10.1186/s12874- 025-02597-z
Patel, M., Volpp, K., & Asch, D. (2019). Behavioral Economic Insights to Improve Medication Adherence in Adults with Chronic Conditions. Drugs & Therapy Perspectives, 35(10), 491– 497. doi:https://doi.org/10.1007/s40271-019-00377-8
Pedro, J., Brandão, T., Schmidt, L., Costa, M., & Martins, M. (2022). Why do patients discontinue fertility treatment? A systematic review of reasons and predictors of discontinuation in fertility treatment. Human Reproduction Update, 28(1), 1–20. doi:https://doi.org/10.1093/humupd/dmaa045
Rashid, M. (2020). Management by Social Media: Impact of Online Comments on Business Management [Ph.D]. Selçuk University.
Razali, N., & Wah, Y. (2011). Power comparisons of the Shapiro-Wilk, Kolmogorov-Smirnov, Lilliefors, and Anderson-Darling tests. Journal of Statistical Modeling and Analytics, 2(1), 21–33.
