Background: Breast cancer is a major life-threatening global public health problem. It is the most common form of cancer in females in many developing countries including Ethiopia. Social networks could change the course of cancer and can influence the quality of life among breast cancer patients. Therefore, the purpose of this study was to assess social networks and quality of life among female breast cancer patients attending in Tikur Anbassa Specialized Hospital, Addis Ababa, Ethiopia 2019. Methods: An institutional-based cross-sectional study was conducted in Tikur Anbessa Specialized Hospital Addis Ababa, Ethiopia from March 1 to April 30/2019. A total of 214 female breast cancer patients were included Binary and multiple logistic regression was used to show the association of social networks and quality of life. Result: A total of 214 females with breast cancer were recruited with a mean age of 41.85. Participants who had children (AOR = 5, 95%CL: 1.3,21 COR = 6), and other relatives (AOR = 6, 95%CI: 1.2,30, COR = 7), were more likely to have good social networks. Participants who were not married (AOR = 0.02, 95%CI: 0.03, 0.28), had no parents living (AOR = 0.1, 95%CI: 0.02, 0.4), no close friends (AOR = 0.06, 95%CI: 0.01, 0.4), and no neighbors (AOR = 0.09, 95%CI: 0.03, 0.5) had poor social networks. Conclusion: The quality of life was relatively low and social support were found to be poor in women with breast cancer. Health-care providers in oncology departments need to focus on addressing the side effects of therapy and social networks which may help to improve the quality of life of females with breast cancer.
Background Breast cancer is a major life-threatening public health problem worlwide. It is the most common form of cancer among women in many developing countries including Ethiopia. Social support could change the course of cancer and can influence the quality of life among breast cancer patients. Therefore, purpose of this study was to assess social support and quality of life among female breast cancer patients attending in Tikur Anbassa Specialized Hospital, Addis Ababa, Ethiopia 2019.Methods A Hospital-based cross-sectional study was conducted in Tikur Anbessa Specialized Hospital, Ethiopia from March to April 2019. A total of 214 female breast cancer patients were included and a systematic sampling method was used. A structured and pre-tested questionnaire was used. Data entry was done using epi data manager version 4.2. Data analysis was done using Statistical Package for Social Sciences version 25. Binary and multiple logistic regression was used to show the association of social support and quality of life. Variables significantly associated were declared at P-value <0.05 and 95%CI was used.Result A total of 214 women with breast cancer were recruited. Of the total participants, 124(58%) had good social support. It was found that participants who were college graduated (AOR=3, 95%CI: 1.5, 5.9 COR=3.2) and who had high monthly income(AOR=2.3, 95% CI: 1.2,8.5, COR= 5.39) were more likely to have good social support. It was also found that participants who were illiterate (AOR=3, 95%CI: 1.3,6.9, COR=4.8, p-value=0.008), who had systematic therapy side effects(AOR=3.8, 95%CI: 1.1,13, COR=4, p-value=0.035)and participants who had problem of appetite loss(AOR=3.5, 95%CI: 1.02,12COR=4, p-value= 0.047) were more likely to have affected QoL. Conclusion In this study finding, social support and, quality of life in breast cancer patients was low. Healthcare providers should enhance social support which may help to improve the quality of life of women with breast cancer.
Background: Breast cancer is a major life-threatening global public health problem. It is the most common form of cancer in females in many developing countries including Ethiopia. Social networks could change the course of cancer and can influence the quality of life among breast cancer patients. Therefore, the purpose of this study was to assess social networks and quality of life among female breast cancer patients attending in Tikur Anbassa Specialized Hospital, Addis Ababa, Ethiopia 2019. Methods: An institutional-based cross-sectional study was conducted in Tikur Anbessa Specialized Hospital Addis Ababa, Ethiopia from March 1 to April 30/2019. A total of 214 female breast cancer patients were included Binary and multiple logistic regression was used to show the association of social networks and quality of life. Result: A total of 214 females with breast cancer were recruited with a mean age of 41.85. Participants who had children (AOR=5, 95%CL: 1.3,21 COR=6), and other relatives (AOR=6, 95%CI: 1.2,30, COR=7), were more likely to have good social networks. Participants who were not married (AOR=0.02, 95%CI: 0.03, 0.28), had no parents living (AOR=0.1, 95%CI: 0.02, 0.4), no close friends (AOR=0.06, 95%CI: 0.01, 0.4), and no neighbors (AOR=0.09, 95%CI: 0.03, 0.5) had poor social networks. Conclusion: The quality of life was relatively low and social networks were found to be poor in women with breast cancer. Health-care providers in oncology departments need to focus on addressing the side effects of therapy and social networks which may help to improve the quality of life of females with breast cancer.
Background Breast cancer is a major life-threatening public health problem in the world. It is the most common form of cancer among women in many developing countries including Ethiopia. Social networks could change the course of cancer and can influence the quality of life among breast cancer patients. Therefore, the purpose of this study was to assess social networks and quality of life among female breast cancer patients attending in Tikur Anbassa Specialized Hospital, Addis Ababa, Ethiopia 2019. Methods An institutional based cross-sectional study was conducted in Tikur Anbessa Specialized Hospital Addis Ababa, Ethiopia from March to April 2019. A total of 214 female breast cancer patients were included and systematic sampling method was used. A structured and pre-tested questionnaire was used. Data entry was done using epi data-manager version 4.2. Data analysis was done using Statistical Package for the Social Sciences version 25. Binary and multiple logistic regression was used to show the association of social networks and quality of life. The strength of association was declared P-value <0.05 and 95%CI was used. Result A total of 214 women with breast cancer were recruited. The mean age was 41.85. Among total participants, 13(6%), 65(30%) and 136(64%) had limited, medium and diverse social networks respectively. Whereas, 198(92.52%) of them had affected quality of life. Participants who were illiterate were more likely to have affected quality of life by 3 times than who were more educated (AOR=3, 95%CI: 1.3,6.9, COR=4.8) and who had systematic therapy side effects were more likely to have affected QoL by 3.8 times than who had no systemic therapy side effect (AOR=3.8, 95%CI: 1.1,13, COR=4). Conclusion and recommendation In this study finding quality of life in breast cancer was low. Healthcare providers especially working at oncology department need to focus on addressing side effects of therapy and social networks which may help to improve quality of life of women with breast cancer.
Background : Breast cancer is a major life-threatening public health problem in the world. It is the most common form of cancer on females in many developing countries including Ethiopia. Social networks could change the course of cancer and can influence the quality of life among breast cancer patients. Therefore, the purpose of this study was to assess social networks and quality of life among female breast cancer patients attending in Tikur Anbassa Specialized Hospital, Addis Ababa, Ethiopia 2019. Methods : An institutional-based cross-sectional study was conducted in Tikur Anbessa Specialized Hospital Addis Ababa, Ethiopia from March to April 2019. A total of 214 female breast cancer patients were included and a systematic sampling method was used. A structured and pre-tested questionnaire was used. Data entry was done using epi data version 4.2. Data analysis was done using Statistical Package for the Social Sciences version 25. Binary and multiple logistic regression was used to show the association of social networks and quality of life. The strength of association was declared P-value <0.05 and 95%CI was used. Result: A total of 214 female with breast cancer were recruited with a mean age of 41.85. From participants, 13(6%), 65(30%) and 136(64%) had limited, medium and diverse social networks respectively. However, 198(92.52%) of them had affected the quality of life. It was found that participants who had children (AOR=5, 95%CL:1.3,21 COR=6), and other relatives(AOR=6, 95%CI: 1.2,30, COR=7), were more likely to have good social networks. In addition, it was found that participants who had systematic therapy side effects(AOR=3.8, 95%CI: 1.1,13, COR=4, p value=0.035), problem of appetite loss(AOR=3.5, 95%CI: 1.02,12 COR=4, p-value= 0.047) were more likely to have affected Quality of life. Conclusion: In this study finding, the quality of life and social networks on breast cancer females was relatively low. Healthcare providers especially working at the oncology department need to focus on addressing the side effects of therapy and social networks which may help to improve the quality of life of females with breast cancer.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.