Skip to main content
Download PDF

What are the determinants of antiretroviral therapy adherence among stable people living with HIV? A cross-sectional study in Cambodia

AIDS Research and Therapy volume 20, Article number: 47 (2023) Cite this article

Abstract

Background

Understanding context-specific determinants of antiretroviral therapy (ART) adherence is crucial for developing tailored interventions for improving health outcomes and achieving the UNAIDS’ third 95% target. This cross-sectional study explores factors associated with ART adherence among stable people living with HIV on ART in Cambodia.

Methods

We used baseline survey data from a quasi-experimental study conducted in 2021. The participants were recruited from 20 ART clinics in nine provinces for face-to-face interviews. A structured questionnaire collected information on sociodemographic characteristics, ART adherence, perceived ART self-efficacy, mental health, quality of life, stigma, and discrimination. We conducted bivariate and multiple logistic regression analyses to identify factors associated with ART adherence.

Results

Out of the 4101 participants, 86.5% reported adhering to ART in the past two months. The adjusted odds of ART adherence were significantly higher among participants in older age groups than those aged 15–29, participants with elevated cholesterol than those without it, participants who exhibited strong self-efficacy in health responsibility to maintain life than those with poor self-efficacy in health responsibility, participants who scored < 3 on the stigma and discrimination scale than those who scored ≥ 3, participants who scored ≥ 42 on the mental component of the quality-of-life scale than those who scored < 42. The adjusted odds of ART adherence were significantly lower in participants who earned > 301 USD per month than those who earned ≤ 100 USD per month.

Conclusion

The ART adherence rate among stable people living with HIV in this study was comparable to that of the general people living with HIV in Cambodia. The results suggest the need for innovative interventions to further reduce stigma and discrimination and strategies to improve the self-efficacy and mental health of people living with HIV to improve ART adherence.

Introduction

Significant progress has been made in the battle against the HIV epidemic in the past two decades. Adherence to antiretroviral therapy (ART) has become the key for AIDS to become a manageable chronic disease [1]. Based on these developments, the Joint United Nations Program on HIV/AIDS (UNAIDS) launched a Fast-Track strategy in 2014. The strategy intends to end the global AIDS epidemic by achieving the 95-95-95 targets by 2030 [2] – i.e., to diagnose 95% of all people living with HIV, provide ART for 95% of those diagnosed with HIV, and achieve viral suppression for 95% of people who receive the ART.

Non-adherence to ART is the main reason for treatment failure, resulting in individuals with HIV progressing to AIDS despite being enrolled in the ART program [3]. ART adherence, defined by the patient’s ability to follow the medication regimen and diet restrictions, must be at 70–90% to effectively suppress viral load, thus reducing the risk of transmitting HIV to another person [4]. Poor adherence can also lead to higher hospitalization rates and productivity losses [5]. It may also lead to drug resistance against first-line antiretrovirals (ARVs) [6], raising the demand for second or third-line ARVs that are often more costly and with higher pill burden, which is often associated with poorer health outcomes [7].

Studies from various countries have identified factors associated with ART adherence. For example, being male, being younger, fear of stigma, alcohol and substance use, and lower income have been associated with suboptimal ART adherence [8,9,10,11,12]. These factors can be grouped into four main categories – (i) intrapersonal, (ii) interpersonal, (iii) medication-related, and (iv) healthcare systems-related factors [13]. Intrapersonal factors refer to an individual’s demographics, psychosocial elements, personal beliefs, and health status. Interpersonal-related factors include relationships between patients and their families, caregivers, and healthcare providers. While family and community support positively influence ART initiation and adherence in people living with HIV, lack thereof and stigma in the family and community can result in poor adherence [14, 15]. Similarly, the attitude of healthcare providers can influence the motivation of people living with HIV for ART adherence both positively and negatively [16,17,18]. Medication-related factors, such as patients’ perception of the effectiveness of ART and pill burden, affect treatment adherence and continuation [3]. Health systems-related factors refer to the availability and accessibility to ART, including out-of-pocket ARV costs, distance and transportation costs to reach the services, and health service quality, such as long waiting time [13, 14].

In Cambodia, the estimated number of people living with HIV in 2020 was around 75,000, with an HIV prevalence of 0.6% among the general population aged 15–49 [19]. As of 2020, Cambodia was one of the three countries that have successfully achieved the 90-90-90 HIV targets, with 80% of all people living with HIV having their viral load suppressed. Given this trend, the country now strives to achieve the third UNAIDS target, i.e., further increasing the number of people living with HIV with suppressed viral load. There is an urgent need to understand factors associated with ART non-adherence, even among stable people living with HIV, to develop context-specific interventions to address them. Although the target population was limited to adolescents, a cross-sectional study conducted in 2018 among those aged 15–17 in Cambodia found that the probability of having viral suppression was significantly higher among participants who were older, had been on ART for a more extended period, had a higher CD4 count at the beginning of ART, had a parent as their main daily caregiver, and did not believe that there was a cure for AIDS [20].

Noting that the associated factors of ART adherence can vary among different populations [21], in this present study, we aimed to explore the ART adherence level and identify its associated factors among stable adults living with HIV. To date, no studies have examined ART adherence levels and related factors among this population in Cambodia. Given the scant evidence in low- and middle-income countries, identifying the determinants that hinder their adherence would help provide valuable insights into the underlying factors of ART adherence among stable people living with HIV in Cambodia and other resource-constraint settings.

Methods

Study design and setting

This cross-sectional study used the baseline data from a quasi-experimental study conducted in July 2021 before the intervention began in November of the same year. Implemented by Khmer HIV/AIDS NGO Alliance (KHANA), a leading non-governmental organization working on HIV and AIDS in Cambodia, the parent study aims to assess the feasibility and efficiency of a community-based ART delivery (CAD) model in bringing ART closer to the people living with HIV and improving social support in the community. The medications are distributed during the monthly community meetings, where the members of the community ART group would interact with their peers for medical, social, and emotional support. The model is expected to sustain the treatment outcomes and reduce the economic burden, stigma, and discrimination among stable people living with HIV and the workload of healthcare workers at ART clinics. The intervention study’s protocol has been published elsewhere [22].

We developed a list of participating ART clinics after consulting the Database Management Unit of the National Center for HIV/AIDS, Dermatology, and STD (NCHADS) and other partners involved in the HIV program implementation. We selected 20 ART clinics in 10 provinces (10 clinics for intervention and 10 for the control arm) for the parent study based on the availability of the implementing partners and the number of stable people living with HIV eligible for enrolment.

Participant recruitment

This study included a total sample of 4101 participants . The study team and on-site clinicians assessed and enrolled the participants using the eligibility criteria of stable people living with HIV during their visits to ART clinics. The criteria used to define stable people living with HIV on ART were: (1) ≥ 15 years old, (2) have received first-line ART for at least one year, (3) had not reported any adverse reactions related to ART or drug interactions that require regular monitoring in the past three months, (4) were not having tuberculosis or other opportunistic infections and not taking any prophylactic treatment; (5) were not pregnant or breastfeeding (for women); (6) had a good understanding of lifelong treatment and adherence to medication, evaluated by the ART clinic physicians using two questions on how to remember and plan their daily ARVs; and (7) had achieved treatment success – two consecutive undetectable viral loads or CD4 counts above 200 cells/mm3 [23]. Field workers and coordinators then approached all eligible people to obtain consent to participate in the study and included all consented people. The data collection team double-checked each questionnaire after the interview. The questionnaire would be returned to the interviewer if any information needed to be included or confirmed before the participant left the site.

Variables and measurements

In this analysis, we included the following variables extracted from the baseline survey of the CAD study: ART adherence, sociodemographic characteristics, depressive symptoms, quality of life (QoL), AIDS-related stigma and discrimination, perceived self-efficacy, and social support.

There is no standard method for measuring ART adherence [24]. The World Health Organization (WHO) recommends that a multi-method approach be used to measure adherence levels [25]. In this study, we employed self-reporting adherence questions, the Visual Analogue Scale (VAS), and the knowledge of pill identification test to assess adherence [26]. The self-reporting method has been consistently associated with clinical outcomes and is widely used for its low cost and ease of implementation [27, 28]. Self-reporting adherence questions require participants to answer if they had missed any ART dose in the past week, the reason for missing them, and their perception of their health status after taking them [26]. The questionnaire included seven questions, and the participants would be considered “good adherent” if they answered “no” to all questions and “moderately or poorly adherent” if they answered “yes” to any of the questions. VAS questions asked participants to recall if they had missed any dose over the past four days with a percentage adherence scale. Participants with a result above 95% would be considered adherent, while those who scored 95% and below would be regarded as non-adherent [29].

For the knowledge of pill identification test, participants were asked to show their medication and if they could remember the dosage, the frequency, prescribed timing, and other additional instructions. Only participants who followed the prescription as intended would be considered adherent. We calculated each adherence method separately before combining them to determine the adherence level. Participants would be regarded as ‘adherent to ART’ if they reported that they adhered to ART in the past two months, had a VAS score > 95%, and could correctly answer all questions in the knowledge of the pill identification test.

Sociodemographic characteristics included age group, sex, marital status, employment, monthly income, and formal education level. HIV treatment history and health status information included ART treatment duration, transportation mode, relationship with healthcare providers and satisfaction with healthcare services, and comorbidities of other chronic diseases such as diabetes mellitus, elevated cholesterol, and hypertension. We measured healthcare service satisfaction by asking whether the participants were satisfied with the healthcare services they received at the ART clinic with Likert scale response options (very dissatisfied, dissatisfied, neither satisfied nor dissatisfied, satisfied, and very satisfied). We also asked participants to rate their overall relationship with healthcare providers at the ART clinic on a Likert scale response options (good, fair, poor, and other or no response).

We measured depressive symptoms using the Center for Epidemiologic Studies Depression Scale (CES-D-10), a 10-item four-point Likert scale questionnaire assessing depressive symptoms (Cronbach’s alpha = 0.78). A cut-off score of 10 or higher suggests significant depressive symptoms [30, 31]. We used the 12-item Short Form Survey (SF-12) to assess health-related QoL, generating two 0-100 component scores – physical (PCS, Cronbach’s alpha = 0.69) and mental (MCS, Cronbach’s alpha = 0.59). A score of 50 or less on the PCS indicates a physical condition, and a score of 42 or less on the MCS indicates clinical depression [32,33,34].

We used the People Living with HIV Stigma Index to measure AIDS-related stigma and discrimination experienced over the past 12 months [35,36,37]. The questionnaire has three main sections: [1] experiences of AIDS-related stigma and discrimination in various settings such as home, community, workplace, and religious settings; [2] internal AIDS-related stigma; and [3] fear of AIDS-related stigma and discrimination from family and communities (Cronbach’s alpha = 0.75). The total score was calculated in each section, and the mean score of each section was used to divide the participants into two groups, one with lower and another with higher AIDS-related stigma and discrimination [35].

We measured self-efficacy using the Perceived Self-Efficacy for Receiving Antiretroviral Therapy Scale (PSEARTS), which assesses the participant’s confidence in carrying out health-related behaviors [38, 39]. PSEARTS has five components: [1] self-efficacy in health responsibility to maintain life (Cronbach’s alpha = 0.70), [2] self-efficacy in physical activities for life (Cronbach’s alpha = 0.82), [3] self-efficacy in nutrition for life (Cronbach’s alpha = 0.71), [4] self-efficacy in spiritual growth for life (Cronbach’s alpha = 0.73), and [5] self-efficacy in stress management for life (Cronbach’s alpha = 0.79). The questionnaire is a four-point Likert scale based on confidence levels (no, low, high, and very high confidence). The participants were then categorized into poor (no/low confidence) and strong self-efficacy (high and very high confidence).

Social support was assessed by the Berlin Social Support Scale (BSSS), a 4-point Likert scale questionnaire. The total possible scores were 12–60, with a higher score indicating better perceived social support (Cronbach’s alpha = 0.89). The scores were further categorized into low (12–27 scores), moderate (28–44 scores), and high (45–60 scores) perceived social support [40,41,42].

Data analyses

We stored collected data in REDCap and used Stata 16 (Stata Corp LP, College Station, TX, USA) for analyses. We conducted bivariate analyses using Pearson’s Chi-square test to compare categorical variables and Student’s t-test to examine continuous variables. Bivariable logistic regression analyses were used to identify factors associated with ART adherence. We constructed a multiple logistic model, including variables associated with ART adherence at p-value < 0.1 in bivariate logistic regression analyses in the model. A backward stepwise method was implemented to remove variables with p > 0.05 one by one from the model. Adjusted odds ratios (AOR) with 95% confidence intervals (CI) and two-tailed p-values were reported.

Ethical consideration

Participants were informed about the study’s objectives and the participation risks and benefits before enrolling them in the study. If a participant could not read or write, data collectors would read the information sheet during the consent-taking process. Participants could withdraw from or discontinue the study at any time. Participants’ written, recorded, and transcribed data were stored securely. We assigned codes to participants’ identifiers, and data collection was conducted in a private room. After completing the interview, participants received US$5 for their time and transportation compensation.

Results

Sociodemographic characteristics

Table 1 shows that 41.4% of the participants were male, and 78.7% were ≥ 40 years old. More than half (59.0%) of the participants were married, and 66.0% had only a primary school education or lower. About one in four (26.2%) were farmers or fishermen, and 18.8% were self-employed. Almost half (48.1%) earned less than 100 USD per month, and 50.0% traveled less than an hour to the ART clinic.

Table 1 Sociodemographic characteristics, comorbidities, health service satisfaction, mental health, and quality of life of stable people living with HIV (n = 4101)
Full size table

Table 1 also shows that 61.6% of the study participants had been on ART for ≥ 11 years. The majority (94.1%) were either satisfied or very satisfied with the healthcare services, with 88.5% reporting having good relationships with their healthcare providers. Regarding comorbidities, 7.8% reported having diabetes mellitus, 16.9% having hypertension, and 6.6% having elevated cholesterol. About two-thirds (65.1%) had poor self-efficacy, and 19.5% had a possible risk of clinical depression. The majority (92.4%) expressed high perceived social support. About one-third (33.6%) had experienced high AIDS-related stigma and discrimination, 6.8% had a high internal AIDS-related stigma, and 13% feared AIDS-related stigma and discrimination over the past 12 months. Over one-third (37.5%) had poor physical QoL, and 20.2% had poor mental QoL.

Antiretroviral therapy (ART) adherence

As shown in Tables 2, 88.2% of the participants reported adhering to ART, 97.1% had a VAS score > 95%, and 98.1% reported being able to take the medication as prescribed. The multi-method approach combining all three methods showed that 86.5% of the participants adhered to ART.

Table 2 Adherence to ART among stable people living with HIV (n = 4101)
Full size table

Bivariate logistic regression

Table 3 shows that older participants were significantly more likely to adhere to ART than those younger than 30. Married participants were significantly more likely to adhere to ART than those who never married. Participants with a monthly income of ≤ 100 USD were significantly more likely to adhere to ART than those who earned ≥ 301 USD. Participants on ART for > 5 years were significantly more likely to adhere to ART than those on ART for ≤ 5 years. Participants with diabetes or elevated cholesterol were significantly more likely to adhere to ART than those who did not have these chronic comorbidities.

Table 3 Bivariable logistic regression analysis of factors associated with ART adherence among stable people living with HIV (n = 4101)
Full size table

As shown in Table 3, participants with good relationships with their healthcare providers were significantly more likely to adhere to ART than those with fair or poor relationships. Participants with strong self-efficacies in health responsibility to maintain life, nutrition, spiritual growth, and stress management were more likely to adhere to ART than those with poor self-efficacy.

Participants without depressive symptoms were significantly more likely to adhere to ART than those with depressive symptoms. Participants with high perceived social support were significantly more likely to adhere to ART than those with low perceived social support. Participants who reported lower AIDS-related stigma and discrimination scores, lower internal AIDS-related stigma scores, and lower fears of AIDS-related stigma and discrimination were significantly more likely to adhere to ART than those who reported higher AIDS-related stigma and discrimination scores, higher internal AIDS-related stigma scores, and higher fears of AIDS-related stigma and discrimination, respectively. Participants with higher PCS and MCS scores were significantly more likely to adhere to ART than those who had lower PCS and MCS scores, respectively.

Multiple logistic regression model

Table 4 shows that the adjusted odds of ART adherence were significantly higher among participants in older age groups than those aged 15–29, participants with elevated cholesterol than those without it, participants who exhibited strong self-efficacy in health responsibility to maintain life than those with poor self-efficacy in health responsibility to maintain life, participants who scored < 3 on the AIDS-related stigma and discrimination scale than those who scored ≥ 3, participants who scored ≥ 42 on the mental component of the QoL scale than those who scored < 42. The adjusted odds of ART adherence were significantly lower in participants who earned > 301 USD per month than those who earned ≤ 100 USD per month.

Table 4 Final model of the multiple logistic regression analysis of factors associated with ART adherence among stable people living with HIV (n = 4101)
Full size table

Discussion

This study examined ART adherence and its associated factors among stable people living with HIV as part of a CAD implementation program in Cambodia. The ART adherence rate among stable people living with HIV in this study is comparable to that of the general people living with HIV in Cambodia, where 80% of all people living with HIV have viral suppression [19]. Age, monthly income, cholesterol level, self-efficacy in health responsibility to maintain life, AIDS-related stigma and discrimination, and mental health were significantly associated with ART adherence.

Participants aged 40 and older were more likely to adhere to ART than those younger than 30. This finding is similar to our previous study, where older adolescents were more likely to have viral suppression than the younger groups [20]. This result supports other studies where better adherence rates have been observed in older people living with HIV [8, 9]. It indicates the need for tailored interventions to promote adherence among adolescents and young adults living with HIV. Regarding income, participants with a monthly income of US$300 or more were less likely to adhere to ART than those earning $100 and less. One of the possible explanations could be that, in Cambodia, ART is provided free of charge for everyone [40], and the government and NGOs target poorer and more vulnerable groups for non-clinical interventions. Hence, the higher income group might have fallen through the gap. This finding contradicts previous studies where poverty was associated with non-adherence [43]. It calls for further research to understand the underlying factors.

Participants with a normal cholesterol level as comorbidity were more likely to adhere to ART than those with elevated cholesterol. A possible reason for this finding might be the pill burden, as participants with high cholesterol might experience more side effects due to the increased number of pills, thus making them less adherent or inclined to skip ART entirely. This finding is supported by another cross-sectional study in West Ethiopia, where participants with other chronic comorbidities were less adherent to ART than those without due to increased side effects and pill burden [44]. Similarly, a cross-sectional study in Ghana showed that participants with elevated cholesterol and diabetes mellitus had significantly reduced ART adherence [45].

Confidence in their self-efficacy in maintaining life was positively associated with ART adherence in this study. Self-efficacy refers to people’s confidence and beliefs in their ability to take the medication and adhere to the treatment plan [46]. In this study, self-efficacy refers explicitly to participants’ confidence in participating in healthy behaviors based on the perception that they are responsible for their own lives. This finding is consistent with other studies, demonstrating that participants with poor confidence are less likely to adhere to ART [38].

AIDS-related stigma and discrimination were negatively associated with ART adherence among stable people living with HIV in this study. Stigma, discrimination, and internal stigma were determinants of treatment adherence among cancer patients in Thailand [47]. With such experiences, people living with HIV may feel demoralized and emotionally distressed, resulting in diminished self-efficacy. Similarly, participants with poor mental health were more likely to be non-adherent than those without it. Depression has also been shown in other studies to be a determinant of ART non-adherence [31, 48]. As a result of depression, people living with HIV may feel less motivated and optimistic and perceive HIV infection as a terminal disease rather than a manageable chronic condition, thus making them unlikely to adhere to ART.

This study has several limitations. First, the study’s findings may not be generalized to all people living with HIV in Cambodia as it included only stable people living with HIV on ART. Second, we could not confirm causality due to the cross-sectional design, and reverse relationships might exist. Since this survey was part of an intervention study, future work can include exploring the changes in associated factors of ART adherence from different phases of the intervention. Such longitudinal analyses will allow us to assess the causal relationship between the factors and ART adherence over the next two years. Third, the self-reporting measures can be prone to social desirability and recall biases and possibly inflate the estimates. Forth, the lengthy questionnaire may result in a cognitive burden on the participants, leading to the use of heuristics. Lastly, we could not verify if the high level of adherence observed had corresponded to viral suppression as the viral load results were unavailable at the time of the analyses.

Despite the above limitations, we believe the study findings will provide valuable insights into the possible factors associated with ART adherence among people with HIV in Cambodia. While stable adults living with HIV are often considered to have higher ART adherence, the factors that hinder their adherence, such as low self-efficacy and high AIDS-related stigma and discrimination, could apply to those not in stable conditions to a similar extent, if not more. Further studies to explore ART adherence and its factors longitudinally during different intervention phases will address the limitation of the causal relationships between the variables in this study.

Conclusion

This study underscores the ongoing need for comprehensive and tailored interventions that address the multifaceted challenges faced by individuals living with HIV. The factors associated with ART adherence in this study highlight the importance of public education to combat AIDS-related stigma and discrimination and community-based strategies to enhance self-efficacy and mental well-being among people living with HIV. Additionally, targeted efforts are needed to promote ART adherence among adolescents, young adults, and those with chronic comorbidities.

Cambodia has made significant strides in ensuring universal access to HIV and AIDS services, including ART. However, it remains crucial to maintain treatment adherence and provide continuous support to individuals living with HIV to achieve the ambitious third UNAIDS’ 95% target by 2030. By implementing effective strategies and collaborating with key stakeholders, we can continue to make substantial advancements in HIV treatment and care, ultimately improving the health outcomes and quality of life for those affected by the virus.

Data availability

The data supporting this study’s findings are available from the corresponding author (siyan@doctor.com) upon reasonable request.

References

  1. Deeks SG, Lewin SR, Havlir DV. The end of AIDS: HIV infection as a chronic disease. Lancet. 2013;382(9903):1525–33.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Joint United Nations Programme on HIV/AIDS (UNAIDS). Understanding Fast-Track: Accelerating Action to End the AIDS Epidemic by 2030. Geneva: UNAIDS. ; 2015. Accessed May 23, 2022. https://www.unaids.org/sites/default/files/media_asset/201506_JC2743_Understanding_FastTrack_en.pdf.

  3. Langebeek N, Gisolf EH, Reiss P, et al. Predictors and correlates of adherence to combination antiretroviral therapy (ART) for chronic HIV infection: a meta-analysis. BMC Med. 2014;12(1):142.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Ortego C, Huedo-Medina TB, Vejo J, et al. Adherence to highly active antiretroviral therapy in Spain. A meta-analysis. Gac Sanit. 2011;25(4):282–9.

    Article  PubMed  Google Scholar 

  5. Nachega JB, Uthman OA, Peltzer K, et al. Association between antiretroviral therapy adherence and employment status: systematic review and meta-analysis. Bull World Health Organ. 2015;93(1):29–41.

    Article  PubMed  Google Scholar 

  6. Haberer JE, Musinguzi N, Boum Y, et al. Duration of antiretroviral therapy adherence interruption is Associated with risk of Virologic Rebound as determined by real-time adherence monitoring in rural Uganda. J Acquir Immune Defic Syndr. 2015;70(4):386–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Snedecor SJ, Khachatryan A, Nedrow K, et al. The prevalence of transmitted resistance to first-generation non-nucleoside reverse transcriptase inhibitors and its potential economic impact in HIV-infected patients. PLoS ONE. 2013;8(8):e72784.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Alemu H, Mariam DH, Tsui AO, et al. Correlates of highly active antiretroviral therapy adherence among urban ethiopian clients. Afr J AIDS Res. 2011;10(3):263–70.

    Article  PubMed  Google Scholar 

  9. Elul B, Basinga P, Nuwagaba-Biribonwoha H, et al. High levels of adherence and viral suppression in a nationally representative sample of HIV-infected adults on antiretroviral therapy for 6, 12 and 18 months in Rwanda. PLoS ONE. 2013;8(1):e53586.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Negash T, Ehlers V. Personal factors influencing patients’ adherence to ART in Addis Ababa, Ethiopia. J Assoc Nurses AIDS Care. 2013;24(6):530–8.

    Article  PubMed  Google Scholar 

  11. Vyankandondera J, Mitchell K, Asiimwe-Kateera, et al. Antiretroviral therapy drug adherence in Rwanda: perspectives from patients and healthcare workers using a mixed-methods approach. AIDS Care. 2013;25(12):1504–12.

    Article  PubMed  Google Scholar 

  12. Moosa A, Gengiah TN, Lewis L, et al. Long-term adherence to antiretroviral therapy in a south african adult patient cohort: a retrospective study. BMC Infect Dis. 2019;19(1):775.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Reda AA, Biadgilign S. Determinants of adherence to antiretroviral therapy among HIV-Infected patients in Africa. AIDS Res Treat. 2012;2012:574656.

    PubMed  PubMed Central  Google Scholar 

  14. Skovdal M, Campbell C, Nhongo C, et al. Contextual and psychosocial influences on antiretroviral therapy adherence in rural Zimbabwe: towards a systematic framework for programme planners. Int J Health Plann Manage. 2011;26(3):296–318.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Kip E, Ehlers VJ, van Der Wal DM. Patients’ adherence to anti-retroviral therapy in Botswana. J Nurs Scholarsh. 2009;41(2):149–57.

    Article  PubMed  Google Scholar 

  16. Watt MH, Maman S, Earp JA, et al. It’s all the time in my mind”: facilitators of adherence to antiretroviral therapy in a Tanzanian setting. Soc Sci Med. 2009;68(10):1793–800.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Musumari PM, Feldman MD, Techasrivichien T, et al. If I have nothing to eat, I get angry and push the pills bottle away from me’’: a qualitative study of patient determinants of adherence to antiretroviral therapy in the Democratic Republic of Congo. AIDS Care. 2013;25(10):1271–7.

    Article  PubMed  Google Scholar 

  18. Wolfe WR, Weiser SD, Bansberg DR, et al. Effects of HIV-related stigma among an early sample of patients receiving antiretroviral therapy in Botswana. AIDS Care. 2006;18(8):931–3.

    Article  CAS  PubMed  Google Scholar 

  19. Joint United Nations Programme on HIV/AIDS (UNAIDS). UNAIDS Data 2020. Geneva: UNAIDS. ; 2020. Accessed May 23, 2022. https://www.unaids.org/en/resources/documents/2020/unaids-data.

  20. Chhim K, Mburu G, Tuot S, et al. Factors associated with viral non-suppression among adolescents living with HIV in Cambodia: a cross-sectional study. AIDS Res Ther. 2018;15(1):20.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Ware NC, Idoko J, Kaaya S, et al. Explaining adherence success in sub-saharan Africa: an ethnographic study. PLoS Med. 2009;6(1):e11.

    Article  PubMed  Google Scholar 

  22. Tuot S, Teo AKJ, Prem K, et al. Community-based model for the delivery of antiretroviral therapy in Cambodia: a quasi-experimental study protocol. BMC Infect Dis. 2021;21(1):763.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Waldrop G, Doherty M, Vitoria M, Fort N. Stable patients and patients with advanced disease: consensus definitions to support sustained scale up of antiretroviral therapy. Trop Med Int Health. 2016;21(9):1124–30.

    Article  PubMed  Google Scholar 

  24. Garrison LE, Haberer JE. Technological methods to measure adherence to antiretroviral therapy and preexposure prophylaxis. Curr Opin HIV AIDS. 2017;12(5):467–74.

    Article  PubMed  Google Scholar 

  25. Steel G, Nwokike J, Joshi MP. Development of a multi-method tool to measure ART adherence in resource-constrained settings: the South Africa experience. Arlington, VA: Management Science for Health; 2007. Accessed June 24, 2021. https://pdf.usaid.gov/pdf_docs/Pnadk153.pdf.

  26. Lam WY, Fresco P. Medication adherence measures: an overview. Biomed Res Int. 2015;2015:217047.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Chesney MA. The Elusive Gold Standard: future perspectives for HIV Adherence Assessment and intervention. J Acquir Immune Defic Syndr. 2006;43(Suppl 1):149–55.

    Article  Google Scholar 

  28. Da W, Li X, Qiao S, et al. Evaluation of self-report adherence measures and their associations with detectable viral load among people living with HIV (PLHIV) in China. PLoS ONE. 2018;13(8):e0203032.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Mai HT, Le GM, Tran BX, et al. Adherence to antiretroviral therapy among HIV/AIDS patients in the context of early treatment initiation in Vietnam. Patient Prefer Adherence. 2022;12:2131–7.

    Google Scholar 

  30. Zhang W, O’Brien N, Forrest JI, et al. Validating a shortened depression scale (10 item CES-D) among HIV-positive people in British Columbia, Canada. PLoS ONE. 2012;7(7):e40793.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Uthman OA, Magidson JF, Safren SA, et al. Depression and adherence to antiretroviral therapy in low-, middle- and high-income countries: a systematic review and meta-analysis. Curr HIV/AIDS Rep. 2014;11(3):291–307.

    Article  PubMed  PubMed Central  Google Scholar 

  32. da Silva J, Bunn K, Bertoni RF, et al. Quality of life of people living with HIV. AIDS Care. 2013;25(1):71–6.

    Article  PubMed  Google Scholar 

  33. González-Chica DA, Grande ED, Bowden J, et al. Are we reducing the risk of cardiovascular disease and improving the quality of life through preventive health care? Results of a population-based study in South Australia. Prev Med. 2017;99:164–70.

    Article  PubMed  Google Scholar 

  34. Osei-Yeboah J, Owiredu WKBA, Norgbe GK, et al. Quality of life of people living with HIV/AIDS in the Ho Municipality, Ghana: a cross-sectional study. AIDS Res Treat. 2017;2017:6806951.

    PubMed  PubMed Central  Google Scholar 

  35. Yi S, Chhoun P, Suong S, et al. AIDS-related stigma and mental disorders among people living with HIV: a cross-sectional study in Cambodia. PLoS ONE. 2015;10(3):e0121461.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Friedland BA, Gottert A, Hows J, et al. The people living with HIV Stigma Index 2.0: generating critical evidence for change worldwide. AIDS. 2020;34(Suppl 1):5–S18.

    Article  Google Scholar 

  37. Friedland BA, Sprague L, Nyblade L, et al. Measuring intersecting stigma among key populations living with HIV: implementing the people living with HIV Stigma Index 2.0. J Int AIDS Soc. 2018;21(Suppl 5):e25131.

    PubMed  PubMed Central  Google Scholar 

  38. Johnson MO, Neilands TB, Dilworth SE, et al. The role of self-efficacy in HIV Treatment Adherence: validation of the HIV Treatment Adherence Self-Efficacy Scale (HIV-ASES). J Behav Med. 2007;30(5):359–70.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Erlen JA, Cha ES, Kim KH, et al. The HIV Medication taking self-efficacy scale: psychometric evaluation. J Adv Nurs. 2010;66(11):2560–72.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Rzeszutek M, Gruszczyńska E. Paradoxical effect of social support among people living with HIV: a diary study investigating the buffering hypothesis. J Psychosom Res. 2018;109:25–31.

    Article  PubMed  Google Scholar 

  41. Wallace DD, Pack A, Castonguay BU, et al. Validity of Social Support Scales utilized among HIV-Infected and HIV-Affected populations: a systematic review. AIDS Behav. 2019;23(8):2155–75.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Warapornmongkholkul A, Howteerakul N, Suwannapong N, et al. Self-efficacy, social support, and quality of life among primary family-member caregivers of patients with cancer in Thailand. J Health Res. 2018;32(2):111–22.

    Article  Google Scholar 

  43. Sasaki Y, Kakimoto K, Dube C, et al. Adherence to antiretroviral therapy (ART) during the early months of treatment in rural Zambia: influence of demographic characteristics and social surroundings of patients. Ann Clin Microbiol Antimicrob. 2012;11(1):34.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Abadiga M, Hasen T, Mosisa G, et al. Adherence to antiretroviral therapy and associated factors among human immunodeficiency virus positive patients accessing treatment at Nekemte referral hospital, west Ethiopia, 2019. PLoS ONE. 2020;15(5):e0232703.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Obirikorang C, Selleh PK, Abledu JK, et al. Predictors of adherence to antiretroviral therapy among HIV/AIDS patients in the Upper West Region of Ghana. ISRN AIDS. 2013;2013:873939.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Lee WK, Milloy MJS, Nosova E, et al. Predictors of antiretroviral adherence self-efficacy among people living with HIV/AIDS in a canadian setting. J Acquir Immune Defic Syndr. 2019;80(1):103–9.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Li MJ, Murray JK, Suwanteerangkul J, Wiwatanadate P, et al. Stigma, social support, and treatment adherence among HIV-positive patients in Chiang Mai, Thailand. AIDS Educ Prev. 2014;26(5):471–83.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Wagner GJ, Ghosh-Dastidar B, Robinson E, et al. Effects of Depression Alleviation on ART Adherence and HIV Clinic Attendance in Uganda, and the Mediating Roles of Self-Efficacy and Motivation. AIDS Behav. 2017;21(6):1655–64.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank the National Center for HIV/AIDS, Dermatology, and STD, the municipality and provincial health departments, ART clinics, and implementing partners for supporting the study design, implementation, and evaluation. Special thanks go to representatives of people living with HIV communities and participants for contributing to the study.

Funding

L’ Initiative of the French Government funded the parent study (Grant No. 19-SB0765) through Expertise France. This study was also partly funded by the Singapore Ministry of Education Academic Research Fund Tier 1 (Start-Up Grant) and the UHS-SSHSPH Integrated Research Programme, Saw Swee Hock School of Public Health, National University of Singapore. The funders had no role in the study design, project implementation and evaluation, and manuscript writing.

Author information

Authors and Affiliations

  1. KHANA Center for Population Health Research, Phnom Penh, Cambodia

    Sovannary Tuot, Pheak Chhoun & Siyan Yi

  2. Department of Community and Global Health, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan

    Sovannary Tuot

  3. Faculty of Social Sciences and Humanity, Royal University of Phnom Penh, Phnom Penh, Cambodia

    Sovannary Tuot

  4. Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, 12 Science Drive 2, #10- 01, 117549, Singapore, Singapore

    Jian Wei Sim, Michiko Nagashima-Hayashi, Alvin Kuo Jing Teo, Kiesha Prem & Siyan Yi

  5. Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia

    Alvin Kuo Jing Teo

  6. Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK

    Kiesha Prem

  7. Center for Global Health Research, Public Health Program, Touro University California, Vallejo, CA, USA

    Siyan Yi

Authors
  1. Sovannary Tuot
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jian Wei Sim
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Michiko Nagashima-Hayashi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Pheak Chhoun
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Alvin Kuo Jing Teo
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Kiesha Prem
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Siyan Yi
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

S.Y. and S.T. conceived the parent study and obtained the funding. S.Y., A.K.J.T., and K.P. supervised the study and designed the survey. P.C. and S.T. led the project implementation and data collection. J.W.S. and M.N-H. analyzed the data, interpreted the results, and drafted the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Siyan Yi.

Ethics declarations

Ethics approval and consent to participate

The National Ethics Committee approved this study for Health Research, Ministry of Health, Cambodia (Reference: 258/NECHR). Participants provided written informed consent before data collection started.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tuot, S., Sim, J.W., Nagashima-Hayashi, M. et al. What are the determinants of antiretroviral therapy adherence among stable people living with HIV? A cross-sectional study in Cambodia. AIDS Res Ther 20, 47 (2023). https://0-doi-org.brum.beds.ac.uk/10.1186/s12981-023-00544-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://0-doi-org.brum.beds.ac.uk/10.1186/s12981-023-00544-w

Keywords

AIDS Research and Therapy

ISSN: 1742-6405

Contact us