Adherence to combined Antiretroviral therapy (cART) among people living with HIV/AIDS in a Tertiary Hospital in Ilorin, Nigeria

Adherence to combined Antiretroviral therapy (cART) among people living with HIV/AIDS in a Tertiary Hospital in Ilorin, Nigeria

Chukwuma Anyaike^1,2, Oladele Ademola Atoyebi³, Omotoso Ibrahim Musa², Oladimeji Akeem Bolarinwa², Kabir Adekunle Durowade^4,5, Adeniyi Ogundiran⁶, Oluwole Adeyemi Babatunde^7,&

 

¹National AIDS/STIs Control Programme, Federal Ministry of Health, Abuja, Nigeria, ²Department of Epidemiology and Community Health, University of Ilorin Teaching Hospital, Ilorin, Nigeria, ³University of British Columbia, 2329 West Mall, Vancouver, BC, Canada, ⁴Department of Community Medicine, Federal Teaching Hospital, PMB 201, Ido-Ekiti, Nigeria, ⁵Department of Community Medicine, Afe Babalola University, Ado-Ekiti, Nigeria, ⁶World Health Organization Country Office, Lagos, Nigeria, ⁷University of South Carolina, Columbia, SC, 20208, USA

 

 

^&Corresponding author
Oluwole Adeyemi Babatunde, University of South Carolina, Columbia, USA

 

 

 

 

Human Immunodeficiency Virus (HIV) infection remains one of the ten leading causes of death in Nigeria [1] and the social stigma associated with this disease compounds the problem. Recent estimates suggest that Africa has about 1.7 million of the global 2.5 million individuals newly infected in 2007 [2]. Antiretroviral therapy is indicated for all patients with obvious AIDS defining illness (WHO stage 4) and those with CD4 count less than 200/mm [3, 4]. However, the current view is that cART should be initiated when the CD4 count is 350/mm³ for effective care [4]. Adherence is the extent to which a person's behavior in taking medications corresponds with the agreed recommendation from a health care provider [5]. Rates of adherence for individual patients are usually reported as percentage of the prescribed doses of medication actually taken by the patient over a specific period [1, 6, 7]. However, there is no consensual standard for what constitutes adequate adherence. Some trials considered rates greater than 80% to be acceptable whereas others regarded rates of 95% and above to be mandatory for adequate adherence, particularly among patients with serious conditions such as infection with human immunodeficiency virus [8]. Adherence to antiretroviral therapy is an essential component of individual and programmatic success and adherence rates exceeding 95% are necessary in order to maximize the benefit of ART as is crucial for the suppression of viral replication, thus avoiding the development of drug resistance and ensuring the prevention of transmission in discordant couples [1, 9-11]. In Nigeria, an estimated 4.4% of adults between the ages of 15-49 years are living with HIV [12]. The disease has overwhelmed the Nigerian health system, increased the cost of achieving developmental goals by decreasing the size of the workforce and increased the number of orphans and vulnerable children due to AIDS [13, 14]. However, recent studies in Africa have revealed a suboptimal medication adherence of about 77% [9, 15]. In Nigeria, ART treatment adherence rates of 54% and 62.6% have been documented at the Aminu Kano Teaching Hospital Kano [16] and Federal Medical Center, Makurdi respectively [17]. This reported suboptimal treatment adherence to ART will pose serious problems to the control of HIV/AIDS in Nigeria. In patients with HIV, the resistance to antiretroviral drugs has been linked to lower levels of adherence [18, 19]. Partial or poor adherence at levels markedly less than 95 percent can lead to the resumption of rapid replication, mutation to treatment resistant strains of HIV and reduced survival rate of the patients [19].

 

Stigmatization has been documented as one of many factors related to varying ART adherence [20]. Between 3.5% and 14.6% of women in Africa have reported experiencing a violent reaction from a partner after HIV disclosure [20, 21]. Reports have also revealed the extents to which people are stigmatized and discriminated against by the health workers and the health system [4, 22, 23]. Stigmatization as a factor against optimal treatment adherence has been documented severally [24-27]. Also, the regular availability of the antiretroviral drugs and their accessibility are important factors that affect adherence. The antiretroviral drugs are very expensive, although their cost has been subsidized in the developing countries by the governments and International Organizations. Moreover, stock out of drugs has been identified as a barrier to treatment adherence especially in the developing countries [16, 17, 28, 29]. The health system can create barriers to adherence by limiting access to health care using a restricted formulary, switching to different formulary and having prohibitory high cost for drugs [30, 31]. The success of adherence strategy depends on the education of the patients before initiation of therapy, and co-operation between the patient and the health care provider [32-34]. Factors that strengthen the relationship between the patient and provider include perception of provider's competence, quality and clarity of communication, compassion and involving the patient as an active participant in the treatment decision of the regimen [20]. Having a trusting relationship with a health care provider has also been reported as a facilitator of adherence [32, 35, 36]. Possible side effects of drugs, patient's forgetfulness, depression, being too busy and being away from home have been identified as barriers to adherence [28, 37]. Also, active substances have been documented as one of the strong predictors of non-adherence [38, 39]. Nevertheless, even active substance abusers can have good adherence if the provider takes time to address the patient's concerns about medication, including anticipation of and management of side effects [40]. In the developing countries, financial constraints hampers transportation to the health facility and purchase of food have been found to be great barriers to cART adherence [27, 41, 42]. Other barriers affecting drug adherence include fear of disclosure, trouble incorporating work and family responsibilities with cART, travelling long distances to receive treatment and complicated regimen [30, 40, 41]. With the ART medication adherence in Africa estimated at 77% [15] and Nigeria being the 3rd in the burden of HIV infection in Sub-Saharan Africa [4], there is a challenge in ensuring an optimal level of treatment adherence to prevent the development and spread of resistant strain of the Human Immunodeficiency Virus. Effective treatment is the only option to prevent this complication and prolong life; which can only be achieved with optimal treatment adherence rate of 95% and above, required for the effective suppression of viral replication and prevention of drug resistance [9]. Optimal management of PLWHA can be ensured if clients with indicators of poor adherence can be identified and closely monitored. The objective of this study was to assess the treatment adherence rate and the factors affecting adherence among PLWHA.

 

 

This study was conducted at the HIV clinic of University of Ilorin Teaching Hospital (UITH), Kwara State, a tertiary health care centre in middle-belt, Nigeria in 2012. It was a descriptive survey with analysis of the observed variables in PLWHA aged 18 years and above who are accessing treatment at the clinic. Self-reported treatment adherence rate was assessed among the respondents over the preceding 7 days to minimize recall bias. Respondents were asked to indicate how many pills they missed during each of the previous 7 days. The mean percent adherence was calculated based on the total number of pills taken divided by the total number of pills respondents reported being expected to take or prescribed by the doctor. In this study treatment adherence was defined as at least 95% of the prescribed dose of cART taken by the patient [8]. Non-adherence to treatment was those patients who score below 95%. Consenting PLWHA who have been on antiretroviral therapy for at least 3 months and not on admission were included in the study while PLWHA with co-morbidities such as tuberculosis, Diabetes Mellitus, Hypertension, mental disorders, hepatitis or any other medical conditions whose medications may interact with the antiretroviral drugs were excluded. The minimum sample size of 550 was determined using the Fishers' formula

 

 

where: z² is the abscissa of the normal curve that cuts off an area α at the tails (the value for z is found in statistical tables which contain the area under the normal curve and z = 1.96 for 95 % level of confidence); p is the estimated proportion of an attribute that is present in the population (proportion of patients that never returned for further visits after the first clinic visit when cARTs were dispensed in Nigeria was put at 43.4% [43]); q is 1-p (56.6%); and d is the acceptable margin of error for proportion being estimated (0.5). Therefore, sample size

 

 

= 1.962 X 4.3 X 5.7/0.52 = 3.842x24.51/0.25 =94.167/0.25 =377 Due to the high rate of attrition in HIV/AIDS programmes and research, we have increased our calculated sample size by 45%, yielding a total of 550 The HIV clinic of the UITH had about 2200 adults in its record who were accessing antiretroviral drugs. The survey was carried out during the clinic visits and systematic random sampling method was used to select the sample of 550 participants. Data were collected by a modification of adherence survey instrument developed by the AIDS Clinical Trial (ACTG Adherence Instrument) [40]. Data were analysed using the Statistical Package for Social Sciences (SPSS) version 16. The observed similarities and differences were tested using the Chi-Square Test while cross tabulation of necessary factors with observed variables were done. P-value of less than 0.05 was considered significant at 95% confidence level. Informed consent was sought from selected respondents after careful explanation of the purpose of the study and intended respect for confidentiality had been stated. Ethical approval was obtained from the Research and Ethical Committee of the University of Ilorin Teaching Hospital Ilorin, Nigeria. Limitations of the study include the problem of recall bias on the number and periods of missed doses.

 

 

A total number of 550 HIV patients who met the criteria for the study were surveyed. The age distribution of the respondents ranged from 18 to 65 years with the mean age of 39.9 years±10.0 (Table 1). A high proportion (68.7%) of the respondents were below the age of 45 years and 59.8% were females. Also, 67.8% of respondents were married, 13.1% divorced or separated while 12.0% were single. The highest proportions of respondents have formal education (86.7%), were Muslims (49.3%), were self-employed (46.4%), earned less than Twenty Thousand naira monthly (65.5%) and had secondary education as highest level of education (35.8%). Many (37.5%) of the respondents have been on treatment between 1-2 years with mean duration of 1.2 years, (SD=0.5) and most (99.8%) received pretreatment adherence instruction. More than three quarter (86.9%) of the patients did not miss their drugs in the last 3 months while majority (89.8%) of the patients did not miss their drugs in the last 7 days (Table 2). However, there was a drop on the acceptance of missing their drugs (3.1%) when compared with the responses 3 months ago. Adherence rate for HIV patients is 92.6% (Table 3). Close to half (44.4%) of the respondents missed their drugs because they travelled outside their station, 25% because they felt sick and depressed, 33.3% because they ran out of drugs at home, 5.6 % because they felt better and discontinued treatment, 50% due to lack of money for transportation, 37.5% because they wanted to avoid side effects of the drugs, 41.7% simply forgot to take their drugs, 30.5% because they did not want to be seen in the clinic while collecting drugs and 19.8% because they could not refill their drugs in the clinic because of unscheduled public holidays by the government (Table 4). The respondents with no formal education (21.9%) were the highest proportion that missed their drugs. This was closely followed by those with primary education (12.2%) and secondary education (8.1%) respectively. Those with tertiary education were the least proportion (4.5%) that missed their drugs. There was statistically significant association between the level of education and missing of drugs (Not shown in tables). There was statistically significant association between support from friends and family and treatment adherence among patients. About three quarters (68.8%) of the patients missed their drugs because they travelled outside town and there was statistically significant association between travelling outside home and treatment adherence among patients (Table 5). Among the patients that lack money for transportation, 75% of them missed their drugs. Lack of money for transportation was statistically associated with treatment adherence among the patients. Above half (66.7%) of the patients that wanted to avoid side effects of drugs missed their drugs. There was statistically significant association between avoiding side effects of drugs and treatment adherence. A higher proportion (66.7%) of the patients that was forgetful missed their drug. Also 25% of the patients who felt better and needed to discontinue their drugs missed their medication. However, there was no statistically significant association between feeling better and need not continue treatment and missing of drugs. The proportion of patients who missed drug because they felt better and needed to discontinue treatment was 25% while 78.9% of those that feel sick and depressed missed their drugs. There was statistically significant association between feeling sick and depressed and missing of drugs. Three quarters of the patients that ran out of drug at home missed their drugs and there was statistical significant association between running out of drugs at home and missing drugs. Above half (63.6%) of the patients that wanted to avoid being seen in the clinic missed their drugs. There was statistically significant association between avoiding being seen in the clinic and treatment adherence.

 

 

This study found out that 89.8% of the patients did not miss their drugs. Of those who missed their drugs only 27.3% of the prescribed antiretroviral drugs were taken by them. The mean adherence rate of all the respondents was 92.6%. Although this was below the optimal level of greater than 95% [1, 8, 9-11], there was an improvement in the treatment adherence level of 70.8% reported by Salami et al [44] in the same hospital about ten years ago. This improvement could be associated with the increased access to antiretroviral drugs in the hospital, regular training of the treatment adherence counselors and the shift from multiple pills therapy to combined pills therapy. However, there was an observed variation in favour of improved adherence levels in respondents when compared with their responses if they missed taking any drugs three months ago. This variation could be explained as recall bias on the part of the respondents. It could also be that the respondents wanted to impress the doctor by their responses. This has been demonstrated in many studies concerning therapy for other diseases where patients often say what they think the doctor would want to hear [45]. This study also found that level of education was significantly associated with treatment adherence among the patients. Those with no formal education were the highest proportion (21.9%) that missed their drugs compared to 4.5% of those with tertiary education. This was consistent with the finding by Christensen et al. [46] in which they found that patients with higher educational level have higher treatment adherence because they could have better knowledge of the disease and therapy. Employment status was not found to be significantly associated treatment adherence among the patients. However, the unemployed respondents were found to have higher treatment adherence than the employed. Among the patients, the unemployed were the least proportion (5.3%) that missed their drugs compared to 12.9% of the self-employed and privately employed patients (10%) respectively. There was no statistically significant association between level of income and treatment adherence among the patients. This study found out that treatment adherence was higher with shorter duration of therapy. Among the patients, a higher proportion (11.1%) of those that missed their drugs was from the patients that have been on treatment for more than one year compared to 8.5% of those who have been on treatment for less than one year. Longer duration of therapy was not significantly associated with treatment adherence among patients, (p=0.5365). Disclosure of illness to friends and family was found to be significantly associated with treatment adherence. Higher proportion (26.7%) of those that missed their drugs did not disclose their illness to their friends and families compared to 9.7% that did. This finding was consistent with the findings by Mills et al. [47] and Chesney et al. [20] in which they identified that not disclosing of illness to friends and families could affect treatment adherence. Disclosure of illness to friends and families will help reduce stigmatization and improve support from friends and families.

 

This study found that support from friend and family could improve treatment adherence. Higher proportion (27%) of patients that missed their drugs did not have support from friends and family. Support from friends and families could reduce psychological stress and financial burden especially in our environment where extended family system is practiced. Lack of money for transportation was also identified as a significant factor affecting treatment adherence. Seventy five percent of the patients who did not have money for transportation to keep hospital appointment missed their drugs. Lack of money for transportation has been reported in a similar study at Enugu, Nigeria by Uzochukwu et al. [29] and in Malawi by Yu et al. [48]. Possible reasons could be because above half of the patients live below one Dollar per day. Also, it could be that some of the patients travel a long distance outside where they live to access their drugs to avoid being seen by those who may know them. Patients avoiding side effects of drugs was significantly associated with treatment adherence among the patients. Two-thirds (66.7%) of patients who wanted to avoid side effects of the antiretroviral drugs missed their drugs. This finding is consistent with result of a similar studies by Uzochukwu et al. [30] in a tertiary hospital in Enugu, Nigeria and among HIV patients by Chesney et al. [38] Forgetfulness was found to be significantly associated with treatment adherence among HIV patients. Above half (66.7%) of the patients that were always forgetful missed their drugs. Forgetfulness as a barrier to treatment adherence have also been documented from a study by Ilyasu et al. [16] at the Aminu Kano Teaching Hospital Kano, Nigeria and also by Olowokere et al [28] among HIV patients in Ibadan, Nigeria. The reason for forgetfulness could be that they were getting better or that they have busy schedules. Running out of drugs at home was significantly associated with treatment adherence. This finding is consistent with the result of the study by Weiser et al. [41] in Botswana. Probable reason for running out of drugs at home could be not keeping clinic appointment for follow-up care and drug refill. Patients avoiding being seen at the clinic was also found to be a significant barrier to treatment adherence among the patients. The treatment adherence rate of the patients was 92.6% and there was an improvement in the treatment levels when compared with previous studies. Although this commends the efforts of the government and the development partners, more needs to be done to attain the optimal treatment adherence rate of at least 95%. The current study has some limitations. Being a descriptive approach to determine associations between factors affecting adherence to cART and the adherence rate, causality could coud not be established. In addition, there could be confounding factors that are difficult to ascertain usin a descriptive approach. For example, other comorbidities unrelated to HIV could affect patients' health such that they become sicker and skip their cART on certain days. The self-reporting of the amount of drug taken in the 7 days preceding the data collection is also not free from bias. A person living with HIV/AIDS might have been poor in adhering to treatment in the past month and give a false or misleading account on adherence to please the researchers. These shortcomings notwithstanding, this research has shown the significant associations between the factors affecting adherence and adherence rate. This information about the associations can help guide future research on adherence to cART.

 

 

In conclusion, we were able to demonstrate a mean adherence rate of 92.6% among all the respondents which was below the optimal level of greater than 95% but higher than the treatment adherence level of 70.8% reported [44] in the same hospital about ten years ago. This study has been able to also identify some factors affecting adherence such as lack of money for transportation, forgetfulness, frequent travelling outside home, feeling sick and depressed, running out of drugs at home, wanting to avoid side effects of drugs, and no access to drugs due to unscheduled public holidays. The establishment of initiatives by the government, non-governmental organizations or the communities to address these problems would help patients to keep clinic appointments. A system of financial enhancement to defray transportation cost for every clinic visit could be considered and patients should be given a week appointment before the exhaustion of the prescribed drugs. This could address the problem of running out of drugs during unscheduled public holidays. The findings of this study could also inform other future studies to determine the causal factors related to adherence. Knowing the causes of poor adherence would help to design more targeted and effective solutions.

 

 

The authors declare competing interests.

 

 

Chukwuma Anyaike, Oladimeji Akeem Bolarinwa, Oluwole Adeyemi Babatunde & Omotoso Ibrahim Musa originated the idea. Chukwuma Anyaike, Omotoso Ibrahim Musa, Oluwole Adeyemi Babatunde, Oladele Ademola Atoyebi & Adeniyi Ogundiran contributed in data collection that was used for the analyses of this paper. Chukwuma Anyaike, Oladimeji Akeem Bolarinwa, Oluwole Adeyemi Babatunde, Kabir Adekunle Durowade, Oladele Ademola Atoyebi & Adeniyi Ogundiran carried out the statistical analyses. Chukwuma Anyaike & Omotoso Ibrahim Musa wrote the first draft of the manuscript. Chukwuma Anyaike, Oladimeji Akeem Bolarinwa, OIM, Oluwole Adeyemi Babatunde, Kabir Adekunle Durowade, Oladele Ademola Atoyebi & Adeniyi Ogundiran contributed to interpreting the results and writing the final article. All authors approved of this version of the manuscript.

 

 

Table 1: sociodemographic characteristics of respondents

Table 2: treatment adherence among respondents

Table 3: treatment adherence rate among HIV patients based on 7 days recall

Table 4: distribution of the factors affecting adherence among the respondents

Table 5: relationship between the factors affecting adherence and treatment adherence among respondents

 

 

1. Federal Ministry of Health. National Tuberculosis and Leprosy Control Programme; Department of Public Health. Worker's Manual. 2008; 5^th Edition: 42.


2. World Health Organization. Global HIV prevalence has levelled off. 2007. Accessed 20 January 2010.


3. Obionu CN. Primary Health Care for developing countries. Institute for Developmental Studies, University of Nigeria, Enugu Campus, Enugu. Second Edition 2007; 139-150.


4. Federal Ministry of Health. National Guidelines for HIV and AIDS Treatment and Care in Adolescents and Adults. Federal Ministry of Health Abuja, Nigeria. 2007; 1-4.


5. World Health Organization. Adherence to long-term therapies: evidence for action. WHO. 2003; P3. Google Scholar


6. Claxton AJ, Cramer J, Pierce CA. Systematic review of the associations between dose regimens and medication compliance. Clinical Therapy. 2001; 23(8): 1296-310. PubMed | Google Scholar


7. Rudd P, Byyny RI, Zachary V. Pill count measures of compliance in a drug trial: variability and suitability. Am J Hypertens. 1988 Jul; 1(3 Pt 1): 309-12. PubMed | Google Scholar


8. Osterberg L, Blaschke T. Adherence to medication. N Engl J Med. 2005; 353(5): 487-97. PubMed | Google Scholar


9. Bangsberg DR. Adherence to protease inhibitors, HIV-1 viral load and development of drug resistance in an indigent population. AIDS. 2000; 14(4): 357-366. PubMed | Google Scholar


10. Montaner JSG. A randomized, double-blind trial comparing combinations of navirapine, didanosine and zidovudine for HIV-infected patients: the INCAS Trial. JAMA. 1998; 279(12): 930-937. PubMed | Google Scholar


11. Paterson DL. Adherence to protease inhibitors therapy and outcome in patients with HIV infection. Annals of Internal Medicine. 2000; 133(1): 21-30. PubMed | Google Scholar


12. Federal Ministry of Health. National HIV Seroprevalence Sentinel Survey. Abuja: Federal Ministry of Health. 2005.


13. World Health Organization. WHO African Region: Nigeria. 2008.


14. Avert. HIV and AIDS in Africa. Accessed 20 January 2010.


15. Dlamini PS, Wantland D, Makoae LN et al. HIV stigma and missed medication in HIV- positive people in five African countries. AIDS Patient Care STDs. 2009; 23(5): 377-389. PubMed | Google Scholar


16. Iliyasu Z, Kabir M, Abubakar IS et al. Compliance to antiretroviral therapy among AIDS patients in Aminu Kano Teaching Hospital, Kano Nigeria. Niger J Med. 2005; 14(3): 290-4. PubMed | Google Scholar


17. Shaahu VN, Lawoyin TO, Sangowawa AO. Adherence to highly active antiretroviral therapy (cART) at a Federal Medical Centre. Afr J Med Sci. 2008; 37(1): 29-36. PubMed


18. Van Leeumen R, Katlama C, Murphy RL. A randomized trial to study first line combination therapy with or without a protease inhibitor in HIV-1 infected patients. AIDS. 2003 May 2; 17(7): 987-99. PubMed | Google Scholar


19. Parienti JJ, Das-Douglas M, Massari V, Guzman D, Deeks SG, Verdon R, Bangsberg DR. Not all missed doses are the same: sustained NNRTI treatment interruptions predict HIV rebound at low-to-moderate adherence levels. PloS one. 2008; 3(7): e2783. PubMed | Google Scholar


20. Chesney MA. Factors affecting adherence to antiretroviral therapy. Clinical Infection Diseases. 2000; 30: S171-S176. PubMed | Google Scholar


21. Medley A, Garcia-Moreno C, McGill S et al. Rates, barriers and outcomes of HIV serostatus disclosure among women in developing countries: implication for prevention of mother-to-child transmission programmes. Bull World Health organ. 2004; 82(4): 299-307. PubMed | Google Scholar


22. Rao D, Kekwaletswe TC, Hoseks S, Martinez J, Rodriguez F. Stigma and social barriers to medication adherence with urban youths living with HIV. AIDS Care. 2007; 19(1): 28-33. Google Scholar


23. Adelekan NL, Olayemi EJ, Ndom J. Caring for people with AIDS in Nigeria Teaching Hospitals. Staff attitude and knowledge. AIDS Care. 1995; 7 Suppl 1: S63-72. PubMed | Google Scholar


24. Wolfe WR, Weisser SD, Bangsberg DR. Effects of HIV related stigma among an early sample of patients receiving antiretroviral therapy in Botswana. AIDS Care. 2006; 18(8): 931-933. PubMed | Google Scholar


25. Nachega JB, Stain DM, Lehman D. Adherence to Antiretroviral Therapy in HIV-Infected Adults in Soweto, South Africa. 2004; 20(10): 1053-1056. PubMed | Google Scholar


26. Oloowokere SA, Fatiregun AA, Akinyemi JO et al. Prevalence and determinants of non-adherence to highly active antiretroviral therapy among people living with HIV/AIDS in Ibadan, Nigeria. J Infect Dev Cties. 2008; 2(5): 369-72. PubMed | Google Scholar


27. Erah PO, Arute JE. Adherence of HIV/AIDS patients to antiretroviral in a tertiary health facility in Benin City. African Journal of pharmacy and pharmacology. 2008; 2(7): 142-152. Google Scholar


28. Talam NC, Gatongi P, Rotich J, Kimaiyo S. Factors affecting antiretroviral drug adherence among HIV/AIDS adult patients attending HIV/AIDS clinic at Moi Teaching and Referral Hospital Eldoret, Kenya. East Afr J Public Health. 2008; 5(2): 74-8. PubMed | Google Scholar


29. Uzochukwu BS, Onwujekwe OE, Onoka AC, Okoli C, Uguru NP, Chukwuogo OI. Determinants of non-adherence to subsidized anti-retroviral treatment in southeast Nigeria. Health policy and planning. 2009; 24(3): 189-96. PubMed | Google Scholar


30. Mannheimer SB, Matts J, Telzak E et al. Quality of life in HIV-infected individuals receiving antiretroviral therapy is related to adherence. AIDS Care. 2005; 17(1): 10-22. PubMed | Google Scholar


31. Murphy DA, Sarr M, Durako SJ. Barriers to HAART among Human Immunodeficiency Virus infected adolescents. Arch Paediatr Adolesc Med. 2003; 157(3): 249-55. PubMed | Google Scholar


32. Abel E, Painter L. Factors that influence adherence to HIV medications: perception of women and health care providers. J Association Nurses. AIDS Care. 2003; 14(4): 61-67. PubMed | Google Scholar


33. Murphy D, Johnson RK, Martin DJ. Barriers to antiretroviral adherence among HIV infected adults. AIDS Patient Care STDs. 2000; (14)1: 47-58. PubMed | Google Scholar


34. Malcom S, Ng JJ, Rosen RK et al. An examination of HIV/AIDS patients who have excellent adherence to HAART. AIDS Care. 2003; (15)2: 251-261. PubMed | Google Scholar


35. Golin C, Isasi F, Bontempi JB et al. Secret pills: HIV-positive patients' expenses taking antiretroviral therapy in North Carolina. AIDS Educ Prev. 2002; 14(4): 318-329. Google Scholar


36. Adam B, Maticka-Tyndale E, Cohen JJ. Adherence practices among people living with AIDS. AIDS Care. 2003; 15(2): 263-274. PubMed | Google Scholar


37. Van Servellen G, Brown JS, Lombardi E et al. Health literacy in low-income Latino men and women receiving antiretroviral therapy in community based treatment centre. AIDS patient Care STDs. 2003; 17(6):283-98. PubMed | Google Scholar


38. Chesney MA. Self-reported adherence to antiretroviral medications among participants in HIV clinical trials: the AACTG adherence instruments. AIDS Care. 2000; 12(3): 255-266. PubMed | Google Scholar


39. Gordillo V. Socio-demographic and psychological variables influencing adherence to antiretroviral therapy. AIDS. 1999; 13(13): 1763-1769. PubMed | Google Scholar


40. Macroft A. A comparison of exposure groups in the Eurosida Study: Starting highly active antiretroviral therapy HAART), response to HAART and survival. Journal of Acquired Immunodeficiency Syndrome. 1999; 22(4): 369-378. PubMed | Google Scholar


41. Weiser S, Wolfe W, Bangsberg D et al. Barriers to antiretroviral adherence for patients living with HIV/AIDS in Botswana. J Acquir Immunodeficiency Syndrome. 2003; 34(3): 281-288. PubMed | Google Scholar


42. Brigido L, Rodrigues R, Cassels J et al. Impact of adherence to antiretroviral therapy in HIV-1 infected patients at a University Public Service in Brazil. AIDS patient Care STDs. 2001; 15(11): 587-593. PubMed | Google Scholar


43. Salami AK, Fadeyi A, Ogunmodede JA et al. Factors influencing adherence to antiretroviral medication in Ilorin, Nigeria. Journal of International Association of Physicians in AIDS Care. 2010; 9(3): 191-195. PubMed | Google Scholar


44. Charurat M, Oyegunle M, Benjamin R, Habib A, Eze E, Ele P, Ibanga I, Ajayi S, Eng M, Mondal P, Gebi U. Patient retention and adherence to antiretrovirals in a large antiretroviral therapy program in Nigeria: a longitudinal analysis for risk factors. PloS one. 2010; 5(5): e10584. PubMed | Google Scholar


45. Bond W, Hussar DA. Detection of methods and strategies for improving medication compliance. American journal of public health. 1991; 48(9): 1978-88. PubMed | Google Scholar


46. Christensen AJ, Smith TW. Personality and patience adherence correlates of the five factor model in renal dialysis. J Behav Med. 1995; 18(3): 305-13. PubMed | Google Scholar


47. Mills EJ, Nachega JB, Buchan I. Adherence to antiretroviral therapy in Sub-Saharan Africa and North America: A meta-analysis. JAMA. 2006; 296(6): 679-690. PubMed | Google Scholar


48. Yu JK, Chen SC, Wang KY. True outcomes for patients on antiretroviral therapy who are "lost to follow up" in Malawi. Bulletin of world Health Organization. 2007; 85(7): 550-554. PubMed | Google Scholar