HIV and AIDS are regarded as global public health threats and pose a considerable challenge to healthcare systems (UNAIDS, 2022); AIDS has gone from being a fatal disease to a chronic condition (Zhou et al, 2020). There are approximately 38.4 million individuals diagnosed with HIV, with 1.5 million new infections occurring in 2021 (UNAIDS, 2022).
In Indonesia, the number of individuals with HIV declined from 640 000 in 2019 (UNAIDS, 2019) to 540 000 in 2022 (UNAIDS, 2022). However, the mortality rate is approximately 4.44% in individuals diagnosed with HIV/AIDS (UNAIDS, 2019). The high prevalence of early mortality in patients with HIV/AIDS means the factors that determine quality of life (QoL) related to disease burden and therefore health need to be better identified (Castro et al, 2019).
QoL assessment has emerged as a critical element of epidemiological and clinical trials related to HIV/AIDS in recent years. Researchers increasingly recognise the importance of QoL on wellbeing, providing good functional capacity in physical health, social relations and psychological QoL domains (Ghiasvand et al, 2019; Vu et al, 2020). Knowing the determinants of QoL and their modifiable factors can be advantageous when drawing up strategies to improve QoL and, ultimately, life satisfaction in HIV/AIDS patients (Ghiasvand et al, 2020).
Notably little research has been undertaken on the determinant factors of QoL in Indonesians diagnosed with HIV/AIDS and the studies that have been done did not investigate adherence to medical treatment and biological markers as determinant factors (Astoro et al, 2007; Lindayani et al, 2018a; Handayani et al, 2019). In addition, evaluations of harmful determinant factors, including non-adherence to therapeutic regimens and poor levels of biological markers that could affect QoL, could be used to help support the personalised healthcare that can gradually improve QoL (Degroote et al, 2014; Castro et al, 2019).
Adherence to antiretroviral therapy (ART) regimens for HIV/AIDS reduces viral proliferation and limits development of HIV infection into AIDS to improve QoL (Dinsa Ayeno et al, 2020). Previous studies have indicated that adherence to ART impacts QoL (Huang et al, 2013; Degroote et al, 2014; Liping et al, 2015; Reis et al, 2020). The World Health Organization (WHO) has reported that ART adherence has improved QoL in European region countries (Popping et al, 2021).
However, ART adherence and its impact on QoL in developing countries are still concerns (Oguntibeju, 2012; Dinsa Ayeno et al, 2020). The Indonesian Ministry of Health (2018) has reported that ART is implemented and fully subsidised at primary healthcare centres but only 41% of those diagnosed with HIV/AIDS have received the therapy.
UNAIDS (2019) has reported that ART is implemented and fully subsidised at primary healthcare centres, but only 16.95% of those diagnosed with HIV/AIDS have received it.
Only one cross-sectional research study has suggested that having a good level of adherence to ART was independently significantly associated with QoL in Indonesians with HIV/AIDS; QoL was 11.06-fold greater than in those who were non-adherent. However, QoL was assessed in only a small sample (Suswani et al, 2018). Adherence to ART may have positive effects on all areas of QoL, including in the environment, physical health, social relations and psychological domains, in individuals with HIV/AIDS in Indonesia. Therefore, these associations require clarification.
Scientific data indicate that viral load (VL) and CD4 cell count are biological markers that are related to QoL in people with HIV/AIDS (Rzeszutek and Gruszczyńska, 2018). Additionally, undetectable VL was not significantly correlated with total QoL compared with detectable VL, but was correlated with a 1.32-fold higher score in the psychological health QoL domain compared with detectable VL. Moreover, undetectable VL was correlated with the environmental, physical health and social relationships domains of QoL (Cho et al, 2020).
Low scores in physical health, psychological, social relationships and environmental QoL domains are significantly associated with detectable VL (Reis et al, 2020). However, CD4 cell count is not correlated with QoL (Cooper et al, 2017; Reis et al, 2020). Moreover, no study has examined the relationship between VL and CD4 as biological markers affecting Indonesians' QoL. Consequently, the roles of VL and CD4 cell count in QoL among people with HIV/AIDS remain undetermined.
Previous research has found that low or undetected VLs were associated with adherence to ART in HIV/AIDS (Vrijens et al, 2005) and that ART adherence and undetectable VL were independently associated with QoL in people with this condition (Reis et al, 2020).
The authors hypothesised that adherence to ART and an undetectable VL would be significantly synergistic and independently impact QoL. The present study explored the effects of adherence to ART and undetectable VL and CD4 cell count as well as their synergistic effect on QoL, including on the environment, psychological, social relationships and physical health domains, in Indonesians diagnosed with HIV/AIDS.
Methods
Study design and participants
This study had a cross-sectional design and was conducted between 17 December 2020 and 27 February 2021. Participants who attended HIV clinics at two community health centres and branches of a non-governmental AIDS organisation in Yogyakarta Province, Indonesia, were enrolled.
The inclusion criteria were respondents who: were Indonesian nationals aged ≥18 years; had received a diagnosis of HIV/AIDS, verified with medical information and confirmed by a physician; were able to understand spoken and written Bahasa; and agreed to take part in the study and provided signed informed consent. Exclusion criteria included respondents who had psychiatric disorders, were pregnant, were unable to communicate or had disabilities.
Sample size calculation
Sample size calculation requires a medium effect size (f) of 0.15 (Khumsaen et al, 2012), an alpha level of 0.05 and a power value of 0.90. Consequently, the sample size required for the present study needed to be 107. In light of an estimated attrition rate of 20%, the sample size was increased to 129 respondents.
Instruments
The questionnaire survey was conducted by trained nurses. The survey included participants' age, occupation, sex, education level, sexual orientation, marital status and duration of treatment (Astoro et al, 2007; Lindayani et al, 2018a; Handayani et al, 2019).
Assessment of quality of life
The WHOQOL-BREF is a 26-item questionnaire with each item scored on a 1–5 scale. Items are divided into four domains: environment; psychological; physical health; and social relationships (WHO, Division of Mental Health, 1996). The three negatively phrased items are reverse scored.
The WHOQOL-BREF has been widely applied in HIV/AIDS research (Hsiung et al, 2005; Liping et al, 2015; Maleki et al, 2020). It has been translated and validated in the Indonesian population with HIV/AIDS (Martina et al, 2017; Putra et al, 2019). The Cronbach's alpha value for the Bahasa version indicates an excellent index of internal consistency with 0.83, 0.90, 0.79 and 0.89 for the environmental, psychological, social relationships and physical health domains respectively (Martina et al, 2017).
Assessment of adherence to treatment
Adherence to antiretroviral therapy (ART) was evaluated using the Morisky Medication Adherence Scale (MMAS), which consists of eight questions. The score on the MMAS-8 ranges from 0 to 8; lower scores indicate poor or non-adherence. An MMAS-8 score in a range of 0–5 indicates non-adherence and 6–8 indicates adherence (Morisky et al, 2008). A physician validated ART adherence while medicine was being taken, and this was recorded in the patient's medical record and used in the study. The MMAS-8 Indonesian version among patients with HIV has excellent reliability with Cronbach's alpha of 0.89 (Yafi, 2018).
Assessment of biological biomarkers
The most recent VL status was identified using medical records and verified by a physician. Data were interpreted and dichotomised into: VL undetectable or suppressed with <100 viral copies/ml detected); or detectable or unsuppressed with 100–500 viral copies/ml detected (Cho et al, 2020). The categories chosen reflect the CD4 cell count ranges used in a previous study; CD4 cell counts (cell/mm3) were <200 and ≥200 (Lindayani et al, 2018b). CD4 counts were also validated by the physician and medical records.
Ethical considerations
The institutional review board of Sekolah Tinggi Ilmu Kesehatan Ngudia Husada Madura evaluated and approved the study protocol (IRB: 709/KEPK/STIKES-NHM-/EC/IX/2020), which complied with the Declaration of Helsinki. Each participant gave written informed consent after receiving both verbal and written information about the research.
Statistical analysis
The distribution of demographic data and determinant factors between groups were assessed using frequency (n) and percentage. The continuous variables are shown as means with standard deviations (SDs) and were analysed using a t-test, Pearson's correlation or Spearman's rank correlation as appropriate. Multicollinearity was examined using a variance inflation factor (VIF) of <10 (García et al, 2015). The data had a low impact on multicollinearity; it had a maximum VIF of 2.49.
The adjusted coefficients and 95% confidence intervals (CIs) for QoL were obtained by conducting a multiple linear regression after adjusting for potential confounding variables such as age, occupation, sex, education, sexual orientation, marital status and time of treatment.
In addition, the synergistic interaction effect between ART adherence with undetectable VL on the four QoL domains was verified after forming four dummy variables for the accompanying four (2 x 2) conditions: detectable VL and ART non-adherence (the reference condition or β00); detectable VL and ART adherence (β10); undetectable VL and ART non-adherence (β01); and undetectable VL and ART adherence (β11). The authors computed the additive interaction or synergistic effect utilising the following categories:
- If β11=β01+β10, no interaction
- If β11>β01+β10, positive interaction
- If β11<β01+β10, negative interaction (Knol et al, 2007; Rias et al, 2020).
In the synergistic effect analysis, to calculate the 95% CI, the authors also controlled for the confounding variables of age, occupation, sex, education, sexual orientation, marital status, duration of treatment and CD4 cell counts.
Statistical analyses were performed using SPSS version 25.0 with P<0.05 considered statistically significant.
Results
Table 1 presents the respondents' demographic characteristics. The 129 patients with HIV/AIDS who participated in this research showed no significant differences regarding age, occupation, sex, education, sexual orientation and marital status in all domains of QoL. The authors did find a significant difference regarding duration of treatment in all domains of QoL, whereby the means (SD) of all domains of QoL were significantly higher in respondents with an undetected VL than those with a detected VL (P<0.001). Moreover, the means (SD) of all domains of QoL were significantly higher (P<0.001) in respondents who adhered to ART (Table 1).
Table 1. Relationships demographic characteristic and determinant factors with quality of life score from the WHOQOL-BREF in participants living with HIV/AIDS (n=129)
| Variables | Total participants | Physical health | Psychological | Social relationships | Environmental | ||||
|---|---|---|---|---|---|---|---|---|---|
| n (%) | Mean (SD)/r | P | Mean (SD)/r | P value | Mean (SD)/r | P value | Mean (SD)/r | P value | |
| Age (years)a | 129 (100) | 0.14 | 0.108 | 0.14 | 0.116 | 0.07 | 0.475 | 0.03 | 0.749 |
| Sexb | 0.802 | 0.652 | 0.700 | 0.381 | |||||
| Male | 86 (66.7) | 12.74 (3.12) | 12.69 (2.96) | 13.47 (2.66) | 14.17 (2.17) | ||||
| Female | 43 (33.3) | 12.60 (2.90) | 12.93 (2.85) | 13.65 (2.53) | 13.79 (2.41) | ||||
| Marital statusb | 0.127 | 0.178 | 0.091 | 0.101 | |||||
| Not married | 94 (72.9) | 12.95 (3.13) | 12.97 (3.00) | 13.74 (2.72) | 14.24 (2.33) | ||||
| Married | 35 (27.1) | 12.03 (2.71) | 12.23 (2.65) | 12.94 (2.22) | 13.51 (1.95) | ||||
| Occupationb | 0.965 | 0.484 | 0.639 | 0.564 | |||||
| Not working | 32 (24.8) | 12.72 (3.10) | 12.44 (3.11) | 13.72 (2.67) | 14.25 (2.30) | ||||
| Employed | 97 (75.2) | 12.69 (3.03) | 12.88 (2.86) | 13.46 (2.60) | 13.98 (2.24) | ||||
| Educationb | 0.646 | 0.920 | 0.905 | 0.663 | |||||
| ISCED <3 | 88 (68.2) | 12.78 (2.98) | 12.78 (3.07) | 13.55 (2.68) | 13.99 (2.30) | ||||
| ISCED ≥3 | 41 (31.8) | 12.51 (3.18) | 12.73 (2.59) | 13.49 (2.49) | 14.17 (2.16) | ||||
| Sexual orientationb | 0.119 | 0.054 | 0.075 | 0.100 | |||||
| Heterosexual | 52 (40.3) | 13.21 (3.11) | 13.37 (2.83) | 14.02 (2.49) | 14.44 (2.21) | ||||
| Non-heterosexual | 77 (59.7) | 12.35 (2.96) | 12.36 (2.92) | 13.19 (2.66) | 13.78 (2.25) | ||||
| Length of ART (years)b | 0.003 | <0.001 | 0.019 | 0.015 | |||||
| ≥1 | 64 (49.6) | 11.91 (2.53) | 11.80 (2.58) | 12.98 (2.31) | 13.56 (1.89) | ||||
| <1 | 65 (50.4) | 13.48 (3.30) | 13.72 (2.93) | 14.06 (2.79) | 14.52 (2.48) | ||||
| Viral load | <0.001 | <0.001 | <0.001 | <0.001 | |||||
| Detectable | 83 (64.3) | 10.89 (1.96) | 11.04 (1.75) | 12.14 (1.89) | 12.72 (1.42) | ||||
| Undetectable | 46 (35.7) | 15.96 (1.53) | 15.89 (1.77) | 16.02 (1.73) | 16.43 (1.29) | ||||
| CD4 cell count (cell/mm3) | <0.001 | 0.002 | 0.008 | 0.002 | |||||
| <200 | 89 (69.0) | 12.01 (2.85) | 12.25 (2.83) | 13.11 (2.51) | 13.62 (2.10) | ||||
| ≥200 | 40 (31.0) | 14.23 (2.90) | 13.93 (2.80) | 14.45 (2.62) | 15.00 (2.30) | ||||
| Adherence tp ART | <0.001 | <0.001 | <0.001 | <0.001 | |||||
| Non-adherence | 77 (59.7) | 10.91 (1.93) | 11.04 (1.75) | 12.09 (1.84) | 12.69 (1.29) | ||||
| Adherence | 52 (40.3) | 15.35 (2.37) | 15.33 (2.37) | 15.65 (2.08) | 16.06 (1.82) | ||||
ART: antiretroviral therapy; ISCED: International Standard Classification of Education; Non-heterosexual: bisexual, homosexual, something else, don't know.
aPearson's correlation,
bIndependent t test
Table 2 presents the adjusted β coefficients and 95% CIs of ART adherence, undetectable VL and CD4 cell counts for QoL. Patients who adhered to ART exhibited significantly higher physical health (β=2.00; 95% CI (1.15–2.85)), psychological (β=1.96; 95% CI (1.15–2.78)), social relationships (β=1.94; 95% CI (1.05–2.84)) and environmental (β=1.79; 95% CI (1.14–2.43)) scores than those who did not. Patients with undetectable VL had significantly higher (β=3.07; 95% CI (2.13–4.00)), psychological (β=3.02; 95% CI (2.13–3.92)), social relationships (β=2.28; 95% CI (1.29–3.27)) and environmental (β=2.24; 95% CI (1.53–2.95)) scores than those with detectable VL. The authors also found no significant association between CD4 cell count and physiological, social relationships and environment QoL domains after controlling for confounding factors, but there were significant differences regarding the physical health domain (Table 2).
Table 2. Adjusted β coefficients and 95% confidence intervals (CIs) of adherence ART status, VL, CD4 cell counts, and QoL in participants living with HIV/AIDS (n=129)
| Variables | Physical health | Psychological | Social relationships | Environmental | ||||
|---|---|---|---|---|---|---|---|---|
| Unadjusted coefficients β (95% CI) | Adjusted coefficients β (95% CI) | Unadjusted coefficients β (95% CI) | Adjusted coefficients β (95% CI) | Unadjusted coefficients β (95% CI) | Adjusted coefficients β (95% CI) | Unadjusted coefficients β (95% CI) | Adjusted coefficients β (95% CI) | |
| Adherence to ART | ||||||||
| Non-adherent | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref |
| Adherent | 4.34 [3.69–5.19]** | 2.00 [1.15–2.85]** | 4.29 [3.57–5.01]** | 1.96 [1.15–2.78]** | 3.56 [2.87–4.25]* | 1.94 [1.05–2.84]** | 3.37 [2.83–3.91]** | 1.79 [1.14–2.43]** |
| Viral load | ||||||||
| Detectable | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref |
| Undetectable | 5.07 [4.40–5.73]** | 3.07 [2.13–4.00]** | 4.86 [4.22–5.49]** | 3.02 [2.13–3.92]** | 3.88 [3.21–4.54]** | 2.28 [1.29–3.27]** | 3.71 [3.21–4.21]** | 2.24 [1.53–2.95]** |
| CD4 cell counts (cell/mm3) | ||||||||
| <200 | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref |
| ≥200 | 1.11 [0.57–1.65]** | 0.52 [0.17–0.87]* | 0.84 [0.31–1.37]** | 0.19 [−0.15, 0.53] | 0.67 [0.19–1.15]** | 0.14 [−0.24, 0.51] | 0.69 [0.28–1.10]** | 0.15 [−0.12, 0.42] |
Note: Adjusted β coefficients and 95% CI were estimated using multiple linear regression after adjusting for age, occupation, gender, education, sex orientation, marital status, and time of treatment.
ART: antiretroviral therapy; CI: confidence interval; QoL: quality of life; VL: viral load
*P<0.05;
**P<0.001
The synergistic effects between ART adherence and the HIV/AIDS-related predictor of VL on QoL are shown in Table 3. The adjusted β coefficients of physical health, physiological, social and environment domains were 5.16 (95% CI (4.48–5.84)), 5.11 (95% CI (4.47–5.75)), 4.29 (95% CI (3.57–5.01)) and 4.11 (95% CI (3.59–4.62)) respectively in patients who had undetectable VL and adhered to ART, and were higher than in patients who had both detectable VL and non-adherence to ART. Furthermore, the findings indicate there was a positive synergistic effect of undetectable VL and ART adherence on the physical health (5.16>2.03+1.47), physiological (5.11>1.69+1.28), social relationships (4.29>1.58+1.58) and environment domains (4.11 1.36+1.34) (Table 3).
Table 3. Synergistic effect of ART adherence and viral load for quality of life in participants living with HIV/AIDS (n=129)
| Variables | Physical health | Psychological | Social relationships | Environmental | ||||
|---|---|---|---|---|---|---|---|---|
| Unadjusted coefficients β (95% CI) | Adjusted coefficients β (95% CI) | Unadjusted coefficients β (95% CI) | Adjusted coefficients β (95% CI) | Unadjusted coefficients β (95% CI) | Adjusted coefficients β (95% CI) | Unadjusted coefficients β (95% CI) | Adjusted coefficients β (95% CI) | |
| Both detectable VL and non-adherence to ART | Ref | Ref | Ref | Ref | Ref | Ref | Ref | Ref |
| Both detectable VL and adherence to ART | 1.20 (0.19–2.21)* | 1.47 (0.50–2.43)* | 1.03 (0.72–1.99)* | 1.28 (0.36–2.19)* | 1.29 (0.25–2.33)* | 1.58 (0.56–2.61)* | 1.20 (0.45–1.95)* | 1.34 (0.60–2.07)** |
| Both undetectable VL and non-adherence to ART | 2.45 (1.07–3.83)** | 2.03 (0.64–3.42)* | 1.95 (0.64–3.25)* | 1.69 (0.38–3.00)* | 1.71 (0.29–3.12)* | 1.58 (0.11–3.05)* | 1.78 (0.76–2.81)** | 1.36 (0.31–2.42)* |
| Both undetectable VL and adherence to ART | 5.66 (5.02–6.30)** | 5.16 (4.48–5.84)** | 5.46 (4.86–6.07)** | 5.11 (4.47–5.71)** | 4.42 (3.76–5.08)** | 4.29 (3.57–5.01)** | 4.20 (3.73–4.68)** | 4.11 (3.59–4.62)** |
Note: Adjusted β coefficients and 95% CI were estimated using multiple linear regression after adjusting for age, occupation, sex, education, sexual orientation, marital status, time of treatment, and CD4 cell counts.
ART: antiretroviral therapy; CI: confidence interval; VL: viral load
*P<0.05;
**P<0.001
Discussion
This is the first study to explore the relationship between VL and QoL among Indonesians with HIV/AIDS. ART adherence and undetectable VL synergistically increased QoL in environment, social relationships, psychological and physical health domains.
Previous research has shown that ART adherence is correlated with a high QoL score (Dinsa Ayeno et al, 2020; Reis et al, 2020). Our findings indicate adherence to ART was significantly associated with higher scores in all domains of QoL. This result is in line with a previous study (Liping et al, 2015), which found that people who adhered to ART had a higher prediction score in the QoL physical health domain (β=1.23; CI (0.35–2.11)). Moreover, ART adherence was the strongest predictor for better scores for social relationships (β=1.18; 95% CI (0.26–2.10)) and environment (β=1.10; 95% CI (0.30–1.86)) domains but not for the psychological domain (Liping et al, 2015). However, in another study, ART adherence was most strongly correlated with the psychological domain (Reis et al, 2020).
In the present study, the significant relationship between ART adherence and higher physical health, social relations and environmental but not psychological scores might be explained by various reasons, such as the secondary effects of drugs and the therapeutic schema (Parienti et al, 2009).
Another crucial finding in this research was that an undetectable VL was correlated with higher physical health, psychological, social relations and environmental QoL scores, but no significant relationship was identified between CD4 cell and the QoL domains except for the physical health domain after controlling for confounding factors.
In line with these results, a cohort study has reported that a higher CD4 cell count (≥200–499 cell/mm3) was positively predictive in the QoL domain of physical function but there was no significant difference in the psychological component score (Emuren et al, 2020). Moreover, CD4 cell count did not influence psychological, social relations and environmental QoL domains (Reis et al, 2020). Among the HIV/AIDS biological biomarkers, only CD4 cell counts were independently linked with the physical health QoL domain (Emuren et al, 2020).
This is in line with previous research that has indicated a low CD4 cell count is a more strongly prognostic of HIV/AIDS progression than HIV ribonucleic acid level while on highly active ART, so is among the most accurate predictors of elevated physical health (Tarwater et al, 2004; Emuren et al, 2020).
Furthermore, the finding in the present study that undetectable VL is significantly correlated with high scores in the physical health, psychological, social relationships and environmental QoL domains was consistent with previous studies, in which a high or detectable VL was shown to be significantly associated with a low score in all domains of QoL (Reis et al, 2020).
Damage to the hippocampus has been linked not only to a variety of neurological and psychiatric illnesses but also to some physical diseases, which indicates its condition impacts bodily functions and memory (Lu et al, 2018). There were consistent connections between the hippocampal response and CD4 cell count and VL measurements (Nir et al, 2021). Moreover, the high volume of grey matter in the hippocampus mediates the link between self-esteem and physical health, indicating a critical role in the brain circuitry that links self-esteem to physical health (Lu et al, 2018). Higher VLs are associated with smaller amygdala volumes, which might account for their correlation with the domains of attention, verbal fluency and motor functioning (Nir et al, 2021), social adversity and cognitive performance (Thames et al, 2018). This mechanism might provide new insight into the pathways that affect QoL among patients with HIV/AIDS.
A major finding of the present study concerns the relationship where the combination of an undetectable VL and ART adherence synergistically increases all domains of QoL compared with detectable VL and ART non-adherence. The potential mechanism for this synergistic effect on QoL, including on the physical health, psychological, social relations and environmental domains, might be explained by the relationship between undetectable VL and ART adherence. ART adherence is positively associated with undetectable VL (Vrijens et al, 2005). Additional research has shown that, independently of undetectable VL (Reis et al, 2020), ART adherence (Liping et al, 2015) is linked to better QoL. These earlier results are comparable with our finding that patients with HIV/AIDS with an undetectable VL and ART adherence had a higher QoL score than those who met only one of these parameters.
Self-reported ART non-adherence is: associated with higher levels of inflammatory biological markers in VL that are suppressed by ART; and significantly reduces at least one biomarker of immune activation – CD4 cell counts (Castillo-Mancilla et al, 2018; 2019). One reason for the findings of the present study is that ART non-adherence may result in low-level viral replication, with VL undetectable in the majority of clinically accessible assays, but with bursts of inflammation and immunological activation (Castillo-Mancilla et al, 2018; 2019). This study provides additional information, showing that both maintaining ART adherence and avoiding detectable VL are likely to be helpful strategies for optimising QoL.
Limitations
A limitation of this research is that the QoL might have been overestimated because participants were recruited from ART clinics and NGOs. Patients provided with ART therapies generally have a better QoL than those not receiving them.
Therefore, although the authors adjusted for many potential confounding variables, they cannot eliminate the possibility that VL and CD4 cells count are affected by factors other than HIV/AIDS. Instead, they established that ART adherence and undetectable VL have a synergistic effect on boosting QoL in patients with HIV/AIDS and that this is potentially valuable and may help promote programmes for regulating and improving QoL in patients with HIV/AIDS.
Ultimately, a large, cluster-randomised, multi-site investigation would provide more substantial evidence on the individual and combined effects of ART adherence and undetectable VL and other biological markers on QoL, thereby guiding future nursing research and practice.
Conclusion
ART adherence is independently related to a better QoL. Patients with undetectable VL had significantly higher scores in physical health, psychological, social relationships and environmental QoL domains.
Adherence to ART and an undetectable VL have a positive, synergistic effect of promoting QoL, including in the physical, psychological, social relationships and environmental domains, among patients with HIV/AIDS in Indonesia.
In line with these findings, nurse educators and health providers should promote specific strategies, including aiming to increase the proportion of patients whose VL levels are undetectable and encouraging adherence to ART among patients with HIV/AIDS.
KEY POINTS
- Adherence to antiretroviral therapy (ART) is independently associated with a better quality of life in the physical health, psychological, social relations and environmental quality-of-life domains
- Patients with an undetectable viral load had a significantly higher quality of life in the physical health, psychological, social relations and environmental quality-of-life domains
- Adherence to ART and an undetectable viral load together had a positive synergistic effect on improving all domains of quality of life − physical health, psychological, social relations and environmental − among patients with HIV/AIDS in Indonesia
CPD reflective questions
- What impact might good adherence to antiretroviral therapy (ART) have on the quality of life of patients with HIV/AIDS?
- Why is a good quality of life essential in people with HIV/AIDS?
- Why should adherence to ART and maintaining an undetectable viral load be encouraged among people with HIV/AIDS?