1.Mayahara, M., Self-regulation of pain management by hospice patients. 2009: University of Illinois at Chicago, Health Sciences Center.
2.Smith, A.D., et al., Men who have sex with men and HIV/AIDS in sub-Saharan Africa. The Lancet, 2009. 374(9687): p. 416–422.
3.Pettifor, A. E., et al., Young people’s sexual health in South Africa: HIV prevalence and sexual behaviors from a nationally representative household survey. Aids, 2005. 19(14): p. 1525–1534.
4.Demographic, E., Health Survey 2011 Central Statistical Agency Addis Ababa. Ethiopia ICF International Calverton, Maryland, USA, 2012.
5.Aynalem Tesfay, F. and T. Dejenie Habtewold, Assessment of prevalence and determinants of occupational exposure to HIV infection among healthcare workers in selected health institutions in Debre Berhan town, North Shoa Zone, Amhara Region, Ethiopia, 2014. AIDS research and treatment, 2014. 2014.
6.Gelaw, B. and Y. Mengitsu, The prevalence of HBV, HCV and malaria parasites among blood donor in Amhara and Tigray regional states. Ethiopian Journal of Health Development, 2008. 22(1): p. 3–7.
7.Abebe, Y., et al., HIV prevalence in 72 000 urban and rural male army recruits, Ethiopia. Aids, 2003. 17(12): p. 1835–1840.
8.Beach, M. C., J. Keruly, and R. D. Moore, Is the quality of the patient-provider relationship associated with better adherence and health outcomes for patients with HIV? Journal of general internal medicine, 2006. 21(6): p. 661.
9.Lawn, S. D., et al., CD4 cell count recovery among HIV-infected patients with very advanced immunodeficiency commencing antiretroviral treatment in sub-Saharan Africa. BMC infectious diseases, 2006. 6(1): p. 1.
10.Kurth, A. E., et al., Combination HIV prevention: significance, challenges, and opportunities. Current HIV/AIDS Reports, 2011. 8(1): p. 62–72.
11.Kharsany, A. B. and Q. A. Karim, HIV infection and AIDS in Sub-Saharan Africa: current status, challenges and opportunities. The open AIDS journal, 2016. 10: p. 34.
12.Seyoum, A., P. Ndlovu, and T. Zewotir, Quasi-Poisson versus negative binomial regression models in identifying factors affecting initial CD4 cell count change due to antiretroviral therapy administered to HIV-positive adults in North–West Ethiopia (Amhara region). AIDS research and therapy, 2016. 13(1): p. 36.
13.Gezie, L. D., Predictors of CD4 count over time among HIV patients initiated ART in Felege Hiwot Referral Hospital, northwest Ethiopia: multilevel analysis. BMC research notes, 2016. 9(1): p. 377.
14.Amberbir, A., et al., Predictors of adherence to antiretroviral therapy among HIV-infected persons: a prospective study in Southwest Ethiopia. BMC Public Health, 2008. 8(1): p. 1.
15.Muyingo, S. K., et al., Patterns of individual and population-level adherence to antiretroviral therapy and risk factors for poor adherence in the first year of the DART trial in Uganda and Zimbabwe. JAIDS Journal of Acquired Immune Deficiency Syndromes, 2008. 48(4): p. 468–475.
16.Edwards, L. J., Modern statistical techniques for the analysis of longitudinal data in biomedical research. Pediatric pulmonology, 2000. 30(4): p. 330–344.
17.Byrne, B. M., Structural equation modeling with Mplus: Basic concepts, applications, and programming. 2013: Routledge.
18.Langebeek, N., et al., Predictors and correlates of adherence to combination antiretroviral therapy (ART) for chronic HIV infection: a meta-analysis. BMC medicine, 2014. 12(1): p. 142.
19.Do, N. T., et al., Psychosocial factors affecting medication adherence among HIV–1 infected adults receiving combination antiretroviral therapy (cART) in Botswana. AIDS research and human retroviruses, 2010. 26(6): p. 685–691.
20.Nosyk, B., et al., Characterizing retention in HAART as a recurrent event process: insights into ‘cascade churn’. AIDS (London, England), 2015. 29(13): p. 1681.
21.Howard, A. A., et al., A prospective study of adherence and viral load in a large multi-center cohort of HIV-infected women. Aids, 2002. 16(16): p. 2175–2182.
22.Belle, D., Poverty and women’s mental health. American psychologist, 1990. 45(3): p. 385.
23.Alok, R., et al., Problem-focused coping and self-efficacy as correlates of quality of life and severity of fibromyalgia in primary fibromyalgia patients. JCR: Journal of Clinical Rheumatology, 2014. 20(6): p. 314–316.
24.Okonji, J. A., et al., CD4, viral load response, and adherence among antiretroviral-naive breast-feeding women receiving triple antiretroviral prophylaxis for prevention of mother-to-child transmission of HIV in Kisumu, Kenya. JAIDS Journal of Acquired Immune Deficiency Syndromes, 2012. 61(2): p. 249–257.
25.Schwimmer, J. B., T. M. Burwinkle, and J. W. Varni, Health-related quality of life of severely obese children and adolescents. Jama, 2003. 289(14): p. 1813–1819.
26.Sagarduy, J. L. Y., et al., Psychological model of ART adherence behaviors in persons living with HIV/AIDS in Mexico: a structural equation analysis. Revista de saude publica, 2017. 51: p. 81.
27.Rao, D., et al., A structural equation model of HIV-related stigma, depressive symptoms, and medication adherence. AIDS and Behavior, 2012. 16(3): p. 711–716.
28.Shmueli, A., Socio-economic and demographic variation in health and in its measures: the issue of reporting heterogeneity. Social Science & Medicine, 2003. 57(1): p. 125–134.
29.Guerrero, M., J. Rialp, and D. Urbano, The impact of desirability and feasibility on entrepreneurial intentions: A structural equation model. International Entrepreneurship and Management Journal, 2008. 4(1): p. 35–50.
30.Marsh, H. W. and D. Hocevar, Application of confirmatory factor analysis to the study of self-concept: First-and higher order factor models and their invariance across groups. Psychological bulletin, 1985. 97(3): p. 562.
31.MacCallum, R. C. and J. T. Austin, Applications of structural equation modeling in psychological research. Annual review of psychology, 2000. 51(1): p. 201–226.
32.Adams, M. and A. Luguterah, Longitudinal analysis of change in CD4+ cell counts of HIV–1 patients on antiretroviral therapy (ART) in the Builsa district hospital. European Scientific Journal, 2013. 9(33).
33.Berg, K. M., et al., Gender differences in factors associated with adherence to antiretroviral therapy. Journal of general internal medicine, 2004. 19(11): p. 1111–1117.
34.Asfaw, A., et al., CD4 cell count trends after commencement of antiretroviral therapy among HIV-infected patients in Tigray, Northern Ethiopia: a retrospective cross-sectional study. PloS one, 2015. 10(3): p. e0122583.
35.Skhosana, N. L., et al., HIV disclosure and other factors that impact on adherence to antiretroviral therapy: the case of Soweto, South Africa. African Journal of AIDS Research, 2006. 5(1): p. 17–26.
36.Lima, V. D., et al., Association between HIV–1 RNA level and CD4 cell count among untreated HIV-infected individuals. American journal of public health, 2009. 99(S1): p. S193-S196.
37.Kulkarni, H., et al., Early Postseroconversion CD4 Cell Counts Independently Predict CD4 Cell Count Recovery in HIV–1–Postive Subjects Receiving Antiretroviral Therapy. Journal of acquired immune deficiency syndromes (1999), 2011. 57(5): p. 387.
38.Montarroyos, U. R., et al., Factors related to changes in CD4+ T-cell counts over time in patients living with HIV/AIDS: a multilevel analysis. PloS one, 2014. 9(2): p. e84276.
39.Mair, C., et al., Factors associated with CD4 lymphocyte counts in HIV‐negative Senegalese individuals. Clinical & Experimental Immunology, 2008. 151(3): p. 432–440.
40.Maqutu, D. and T. Zewotir, Optimal HAART adherence over time and time interval between successive visits: their association and determinants. AIDS care, 2011. 23(11): p. 1417–1424.
41.Kaufmann, G. R., et al., CD4 T-lymphocyte recovery in individuals with advanced HIV–1 infection receiving potent antiretroviral therapy for 4 years: the Swiss HIV Cohort Study. Archives of internal medicine, 2003. 163(18): p. 2187–2195.
42.Kipp, A.M., et al., Socio-demographic and AIDS-related factors associated with tuberculosis stigma in southern Thailand: a quantitative, cross-sectional study of stigma among patients with TB and healthy community members. BMC Public Health, 2011. 11(1): p. 675.
43.Maqutu, D., et al., Determinants of optimal adherence over time to antiretroviral therapy amongst HIV positive adults in South Africa: a longitudinal study. AIDS and Behavior, 2011. 15(7): p. 1465–1474.
44.Florence, E., et al., Factors associated with a reduced CD4 lymphocyte count response to HAART despite full viral suppression in the EuroSIDA study. HIV medicine, 2003. 4(3): p. 255–262.
45.Amberbir, A., et al., Predictors of adherence to antiretroviral therapy among HIV-infected persons: a prospective study in Southwest Ethiopia. BMC public health, 2008. 8(1): p. 265.
46.Ebonyi, A. O., et al., Factors associated with a low CD4 count among HIV–1 infected patients at enrolment into HAART in Jos, Nigeria. British Journal of Medicine and Medical Research, 2014. 4(13): p. 2536.
47.Smith, C. J., et al., Factors influencing increases in CD4 cell counts of HIV-positive persons receiving long-term highly active antiretroviral therapy. Journal of Infectious Diseases, 2004. 190(10): p. 1860–1868.