Depression,Medication Adherence,and Beliefs as Determinants of Health-Related Quality of Life among People Living with HIV: A Cross-Sectional Pharmacoepidemiologic Study in Indonesia

Abstract

Objective

To examine the associations of depression, medication adherence, and medication beliefs with HRQoL among people living with HIV (PLWH) in primary healthcare (PHC) settings in Indonesia.

Methods

This cross-sectional study included PLWH attending 6 PHCs in Makassar (July-September 2025). HRQoL was assessed using the EuroQol 5-Dimension 5-Level (EQ-5D-5L); depression using the Patient Health Questionnaire-9 (PHQ-9); adherence using the Medication Adherence Report Scale (MARS); and beliefs using the Beliefs about Medicines Questionnaire (BMQ). Multivariable linear regression examined associations with HRQoL.

Results

Among 400 participants (median age 30 years, interquartile range: 11), mean EQ-5D-5L utility was 0.94 ± 0.10. Higher depression severity was associated with lower HRQoL (β=−0.006; P < .001), while adherence and beliefs were not significant after adjustment.

Conclusion

Depression was the only independent psychosocial predictor of HRQoL, highlighting the need for integrated mental health support in HIV care within PHC settings.

Plain Language Summary Title

How Depression and Taking HIV Medicines Affect Quality of Life for People Living with HIV in Indonesia

Plain Language Summary

People living with HIV are now able to live longer lives because of effective antiretroviral treatment. However, living well with HIV is not only about controlling the virus but also about maintaining a good quality of life. Mental health and daily treatment experiences may play an important role.

This study involved 400 people living with HIV who were receiving care at government primary health centers in Makassar, Indonesia. We looked at how depression, taking HIV medicines regularly, and beliefs about medicines were related to quality of life. Quality of life was measured using standard health questionnaires.

Overall, participants reported good quality of life. However, people with more severe symptoms of depression had a lower quality of life, regardless of how well they took their medicines or how they felt about them. Medication adherence and beliefs about medicines were not strongly linked to quality of life after considering other factors.

These findings show that depression has a major impact on the daily well-being of people living with HIV. Integrating mental health screening and support into routine HIV care at primary health centers may help improve overall quality of life.

Keywords

HIV/AIDS health-related quality of life depression medication adherence beliefs about medicines Good Health and Well Being Reduced Inequalities

Introduction

Human immunodeficiency virus (HIV) infection, which causes acquired immunodeficiency syndrome (AIDS), continue to pose serious global public health challenges, with an estimated 40.8 million people living with HIV (PLWH) in 2024.¹ Although significant progress has been achieved in reducing morbidity and mortality associated with HIV through global prevention and treatment initiatives, the burden of the disease remains substantial, particularly in low- and middle-income countries (LMICs), including Indonesia.² The country continues to experience a concentrated HIV epidemic, with approximately 570,000 PLWH in 2025, predominantly among key populations such as men who have sex with men (MSM), female sex workers, people who inject drugs, and transgender individuals.³ In Indonesia, HIV cases have also been increasingly reported across several provinces, including South Sulawesi. As of August 2025, a total of 1214 cases had been reported in the province, with Makassar representing the city with the highest number of reported cases.⁴

Since the approval of zidovudine in 1987 and the introduction of highly active antiretroviral therapy (HAART) in 1996, antiretroviral therapy (ART) has transformed HIV from a fatal infection to a controllable long-term condition.⁵ ART substantially reduces morbidity and mortality, with viral suppression remaining a central goal of HIV care, while increasing attention is also directed toward improving the overall health-related quality of life (HRQoL) of people living with HIV.⁶ QoL reflects an individual's perceived physical, psychological, and social well-being and is increasingly recognized as a crucial outcome in chronic HIV management.⁷ However, improvements in virological outcomes do not always correspond to enhanced HRQoL, as PLWH continue to face multiple psychosocial and behavioral challenges.^8–10

Among the factors influencing HRQoL, depressive symptoms, medication adherence, and beliefs about medication have emerged as key determinants.¹¹ Depression is one of the most prevalent neuropsychiatric comorbidities among PLWH, affecting up to 50% of this population.¹² Depressive symptoms may influence HIV outcomes through behavioral pathways, particularly reduced adherence to antiretroviral therapy, which may lead to poorer health outcomes and lower HRQoL.¹³ In addition, biological mechanisms such as altered immune responses, increased pro-inflammatory cytokine levels, and declines in CD4 cell counts have also been associated with depression among PLWH.¹⁴ Addressing depression through integrated psychosocial support is thus essential for improving both health outcomes and HRQoL. In Indonesia, psychosocial and mental health support for PLWH is partly integrated into HIV services through the national Care, Support, and Treatment (CST) program delivered mainly in primary healthcare (PHC) facilities. A key component of these services is Voluntary Counseling and Testing (VCT), which provides confidential HIV testing accompanied by pre- and post-test counseling. Through these counseling services, patients receive psychological support, education about HIV, and guidance to improve treatment adherence and coping with stigma. However, despite the availability of these services, the integration of comprehensive mental health care within PHC remains limited, and support is often focused on counseling rather than structured mental health management. In addition to depression, medication adherence also remains central to successful HIV treatment. Optimal adherence ensures viral suppression, immune recovery, and reduced risk of opportunistic infections, translating into improved physical functioning and well-being^15–17 Equally important are patients’ beliefs about ART, which directly influence adherence behavior.¹⁸ Individuals who perceive ART as necessary for maintaining health are more likely to adhere consistently, while those harboring concerns about side effects or dependence may exhibit poor adherence.^18,19 Understanding these beliefs provides valuable insight into patients’ motivation and treatment engagement.

Despite growing global evidence on factors influencing HRQoL among PLWH, several important gaps remain. Many previous studies have examined individual determinants such as depression, medication adherence, or beliefs about treatment separately^20–22 Evidence examining the combined influence of these psychosocial and behavioral factors on HRQoL in PHC settings in LMICs remains limited. In Indonesia, where most PLWH receive long-term HIV care through PHC facilities, existing studies have generally focused on individual determinants rather than their interrelationships. Understanding how depressive symptoms, medication adherence, and medication beliefs collectively influence HRQoL is important for developing integrated patient-centered interventions in resource-limited healthcare settings.

Therefore, this study aimed to examine the associations between medication adherence, depressive symptoms, and medication beliefs with HRQoL among PLWH attending PHC facilities in Makassar, Indonesia. The findings are expected to provide context-specific evidence to guide patient-centered interventions and inform strategies to enhance HRQoL and long-term treatment outcomes in HIV care within resource-limited settings.

Methods

Study Design and Setting

We employed an analytical cross-sectional design. Data collection was conducted between July and September 2025 at 6 government-run PHCs in Makassar, South Sulawesi, Indonesia i.e. Jumpandang Baru, Kassi-Kassi, Jongayya, Makkasau, Antang, and Sudiang Raya. These PHCs were purposively selected because they provide comprehensive HIV services under the national program and collectively serve 2339 registered PLWH in 2025. Each facility covers a distinct catchment area, ranging from dense urban centers to semi-urban communities, thereby enhancing their representativeness of the population of PLWH in Makassar. The reporting of this study conforms to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement.²³ The completed STROBE checklist is provided as Supplementary File S1.

Participants

The study population comprised adults (≥18 years) with a confirmed HIV diagnosis who were receiving care at one of the participating clinics. We excluded patients with severe or terminal comorbidities or cognitive impairment that could interfere with their ability to provide reliable responses. Cognitive impairment was assessed pragmatically during recruitment based on participants’ ability to understand most of the study information and respond coherently during the consent and questionnaire process. Individuals who were unable to comprehend the study procedures or provide consistent responses were considered ineligible. Questionnaires that were substantially incomplete such as those in which participants discontinued the survey before completing the core study measures (EQ-5D-5L, PHQ-9, MARS-10, and BMQ) were excluded from the analysis. Minor item-level missing responses within otherwise completed questionnaires were retained in the dataset.

Sample Size and Sampling

Using Slovin's formula with a 5% margin of error,²⁴ the minimum required sample size was 342 from the 2339 PLW registered across the 6 PHCs. We applied proportional stratified sampling by PHCs to enhance representativeness. Within each locus, consecutive sampling was employed during routine clinic visits until the required number of participants was achieved. In practice, 400 participants were enrolled: Jumpandang Baru (n = 110), Kassi-Kassi (n = 90), Jongaya (n = 90), Makkasau (n = 50), Antang (n = 30), and Sudiang Raya (n = 30).

Measures

HRQoL was assessed using the EuroQol 5-Dimension 5-Level (EQ-5D-5L) instrument, which evaluates 5 health dimensions: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. Each dimension has 5 response levels ranging from no problems to extreme problems. Responses across the 5 dimensions generate a 5-digit health state, which was converted into a single utility index using the Indonesian EQ-5D-5L value set. Utility scores range from −0.865 to 1.000, with higher values indicating better HRQoL.²⁵ In addition, overall health status was captured using the EQ Visual Analogue Scale (EQ-VAS), where participants rated their perceived health on a vertical scale from 0 (worst imaginable) to 100 (best imaginable).²⁵ Both the EQ-5D-5L utility index and EQ-VAS were included to capture complementary aspects of HRQoL: the utility index provides a standardized, preference-based measure, while the EQ-VAS reflects patients’ subjective perception of their overall health. This combined approach enables a more comprehensive assessment of health status.²⁵

Medication adherence was assessed using the Medication Adherence Rating Scale (MARS-10).²⁶This self-report instrument consists of 10 items reflecting both intentional and unintentional non-adherence, with dichotomous responses of “Yes” (score = 1) and “No” (score = 0). The total score ranges from 0 to 10, where higher scores indicate better adherence. Adherence levels were categorized as high (8-10), moderate (6-7), and low (<6). The MARS-10 has been validated and culturally adapted into Bahasa Indonesia, demonstrating acceptable psychometric properties (Cronbach's α = 0.742).²⁷

Depressive symptoms were measured with the Patient Health Questionnaire-9 (PHQ-9), which assesses the frequency of depressive symptoms over the past 2 weeks based on DSM-IV criteria.²⁸ Scores range from 0 to 27, with categories of none (0-4), mild (5-9), moderate (10-14), moderately severe (15-19), and severe depression (20-27).²⁸ The PHQ-9 has been widely validated in HIV populations^29–31 and is suitable for use in primary care and community settings in Indonesia.^32–34

Beliefs about medicines were assessed using the Beliefs about Medicines Questionnaire (BMQ), which consists of 2 components: BMQ General and BMQ Specific.^35,36 The BMQ General measures overall beliefs about medicines through 2 subscales, General Harm (GH) and General Overuse (GO), each containing 4 items rated on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree), yielding scores ranging from 4 to 20.^35,36 Higher GH scores indicate stronger beliefs that medicines are harmful, addictive, or generally detrimental to health, while higher GO scores reflect stronger perceptions that medicines are overprescribed or overused by healthcare providers. The BMQ Specific includes 2 subscales, Specific Necessity (SN) and Specific Concerns (SC), each comprising 5 items with total scores ranging from 5 to 25.^35,36 A higher SN score indicates a stronger belief in the necessity of medication, whereas a higher SC score reflects greater concern about potential side effects and negative consequences of medication use. The BMQ has been translated, culturally adapted, and validated for use among the PLWH, demonstrating good reliability and validity (Cronbach's α = 0.80.^20,37

We also collected sociodemographic and clinical covariates, including age, sex, education, employment status, income, marital status, living arrangement, presence of a treatment supporter, HIV clinical stage, ART regimen and duration, hospitalization history, smoking status, alcohol use, herbal medicine use, and distance to the health center. Comorbidities were assessed using a self-reported checklist in which participants were asked whether they had ever been diagnosed with selected chronic or infectious conditions. The listed conditions included cancer, acute respiratory infections, diabetes, pneumonia, heart disease, pulmonary tuberculosis, hypertension, hepatitis, stroke, asthma, kidney failure, gout, and hypercholesterolemia. Participants could also report other comorbid conditions not included in the predefined list. All questionnaires can be found in Supplemental File S2.

Data Collection

Trained research assistants facilitated interviewer-assisted self-administered questionnaires in a private setting within the participating PHCs to ensure participants’ comfort and confidentiality. Written informed consent was secured from all participants before study participation. Participants completed the questionnaire independently, while research assistants were available to clarify questions when necessary. Each questionnaire was completed in a single sitting without follow-up and typically required approximately 15-20 min to complete. The study instruments were pretested among 30 participants to assess clarity and cultural appropriateness. To protect confidentiality, no personal identifiers were recorded, and all responses were coded and securely stored with access restricted to the research team.

Statistical Analysis

All analyses were conducted using IBM SPSS Statistics version 29 (IBM Corp., Armonk, NY, USA). Descriptive statistics were used to summarize participants’ sociodemographic characteristics, clinical variables, and questionnaire scores. Categorical variables were presented as frequencies and percentages, while continuous variables were summarized as mean ± standard deviation (SD) for approximately normally distributed data or median with interquartile range (IQR) for skewed distributions.

Item-level missing data within otherwise eligible questionnaires were addressed using multiple imputation (MI) with fully conditional specification, equivalent to multiple imputation by chained equations.³⁸ A total of 20 imputed datasets were generated, and all study variables were included in the imputation model with plausible bounds applied.³⁹ Estimates across imputations were pooled with Rubin's rules.⁴⁰ The overall missingness in the dataset was minimal (<1%), with no variable exhibiting more than 3% missing values.

Given the cross-sectional design of the study, the regression analyses were intended to examine associations between study variables and HRQoL rather than to establish causal relationships. Linear regression models were applied with the EQ-5D-5L utility index as the dependent variable. Univariable models were first used to examine crude associations between each independent variable (sociodemographic, clinical, adherence, depression, and medication beliefs) and HRQoL. Variables with P < .05 in the univariable analysis were considered candidates for the multivariable regression model. In addition, selected variables with established clinical relevance to HIV care and HRQoL were included regardless of their statistical significance in the univariable analysis (treatment supporter and duration of ART treatment). Total scores from the MARS-10 (adherence), PHQ-9 (depression), and BMQ subscales (medication beliefs) were treated as independent variables. Results are presented as unstandardized coefficients (B) with 95% confidence intervals (CI) and with statistical significance set at P < .05.

Assumptions of linear regression were assessed prior to model interpretation. The normality of residuals was evaluated using histograms and normal probability (P-P) plots, while linearity and homoscedasticity were examined through scatterplots of standardized residuals against predicted values. Visual inspection indicated that the assumptions of normality and homoscedasticity were reasonably satisfied. Variance inflation factors (VIF) were used to assess multicollinearity, with values <10 considered indicative of no significant multicollinearity.

Results

We collected data from 400 PLWHA attending 6 PHCs in Makassar City (Table 1). The median age of participants was 30 years (IQR: 11), and the majority were male (88%). More than half of the participants (64.8%) had 12 years of education or less, and 69.3% were employed at the time of data collection. Most respondents were unmarried (80%) and reported a monthly income below 3.5 million Indonesian Rupiah (IDR) (62.5%). A total of 24.5% lived alone, while 68% reported having a treatment supporter, defined as a family member, partner, or peer who assists the patient in maintaining adherence to antiretroviral therapy.

Table 1.

Participant Characteristics (N = 400).

Characteristics	Values
Sociodemographic
Age, years—Median (IQR)	30.00 (11)
Male sex—n (%)	352 (88)
Education ≤12 years—n (%)	259 (64.8)
Employed—n (%)	277 (69.3)
Unmarried—n (%)	320 (80)
Monthly income ≥3.5 million IDR—n (%)	150 (37.5)
Living alone—n (%)	98 (24.5)
Treatment supporter—n (%)	272 (68)
Sample Distribution by PHC—n (%)
─ Jumpandang Baru	110 (27.5)
─ Kassi-Kassi	90 (22.5)
─ Jongayya	90 (22.5)
─ Makkasau	50 (12.5)
─ Antang	30 (7.5)
─ Sudiang Raya	30 (7.5)
Clinical characteristics
Duration of HIV infection, years—Median (IQR)	4 (5)
Duration of ART, years—Median (IQR)	4 (5)
FDC ART regimen type—n (%)	327 (81.8)
HIV stage—n (%)
─ Asymptomatic	280 (70)
─ Symptomatic	66 (16.5)
─ AIDS	6 (1.5)
─ Unknown	48 (12)
Route of HIV transmission—n (%)
─ Heterosexual	74 (18.5)
─ Homosexual	230 (57.5)
─ Intravenous drug use	21 (5.2)
─ Unknown	75 (18.8)
Comorbidity—n (%)	81 (20.2)
History of hospitalization—n (%)	99 (24.8)
Smoking—n (%)	132 (33)
Alcohol consumption—n (%)	316 (79)
Herbal medicine use—n (%)	73 (18.2)
Distance to health center, km—Median (IQR)	5 (5)
Questionnaires and scores
EQ-5D-5L Utility index—Median (IQR)	1 (0.1)
EQ-5D-5L Utility index—Mean (±SD)	0.94 (±0.10)
EQ-VAS (0-100)—Median (IQR)	90 (13)
EQ-VAS (0-100)—Mean (±SD)	89.43 (±13.7)
MARS-10 adherence category—n (%)
─ Low	20 (5)
─ Medium	100 (25)
─ High	280 (70)
PHQ-9 depression category—n (%)
─ None	200 (50)
─ Mild	117 (29.3)
─ Moderate	54 (13.5)
─ Moderately severe	20 (5)
─ Severe	9 (2.3)
BMQ-specific necessity—n (%)
─ Low	257 (64.3)
─ High	143 (35.7)
BMQ-specific concerns—n (%)
─ Low	208 (52)
─ High	192 (48)
BMQ-general H aarm—n (%)
─ Low	246 (61.5)
─ High	154 (38.5)
BMQ-general overuse—n (%)
─ Low	239 (59.8)
─ High	161 (40.2)

Note: IDR: Indonesian Rupiah; EQ-5D-5L: EuroQol 5-Dimension 5-level; EQ-VAS: EuroQol Visual Analogue Scale; PHQ-9: Patient Health Questionnaire-9; MARS-10: Medication Adherence Report Scale-10; BMQ: Beliefs about Medicines Questionnaire; IQR: Interquartile Range; SD: Standard Deviation

The median duration of HIV infection was 4 years (IQR: 5), with a similar median duration for ART use (4 years, IQR: 5). Most participants (81.8%) were on a fixed-dose combination (FDC) regimen. The majority were in the asymptomatic stage (70%), while 16.5% were symptomatic, and 1.5% were in the AIDS stage. The main reported route of HIV transmission was homosexual contact (57.5%), followed by heterosexual contact (18.5%), intravenous drug use (5.2%), and unknown routes (18.8%). Comorbidities were present in 20.2% of participants, and nearly one-fourth (24.8%) had a history of hospitalization. Approximately one-third (33%) were smokers, 79% reported alcohol consumption, and 18.2% used herbal medicines. The median distance from participants’ residence to the primary healthcare center was 5 km (IQR: 5).

The mean EQ-5D-5L utility index was 0.94 (±0.1) and the mean VAS score for self-rated health was 89.43 (±13.7). Most participants (70%) had high adherence (score 8-10), 25% had medium adherence (score 6-7), and 5% had low adherence (score <6). Half of the participants (50%) had no depression, while 29.3% had mild, 13.5% moderate, 5% moderately severe, and 2.3% severe depression. For medication beliefs, 64.3% of participants had low scores on the specific necessity subscale, and 48% had high specific concerns. On the general beliefs domain, 38.5% expressed high perceptions of harm and 40.2% reported high beliefs in overuse of medicines.

Bivariate linear regression identified several potential factors associated with EQ-5D-5L utility index. Participants who were employed (β = 0.025, 95% CI: 0.002-0.048; P = .032), had higher monthly income (β = 0.038, 95% CI: 0.016-0.059; P < .001), and lived alone (β = 0.035, 95% CI: 0.010-0.059; P = .005) were found to have positive association with the utility index. Clinical factors negatively associated with the utility index included being in the symptomatic (β = –0.071, 95% CI: −0.098 to −0.043; P < .001) or AIDS stage (β = −0.150, −95% CI: −0.234 to −0.066; P < .001), having comorbidities (β = −0.066, 95% CI: −0.092 to −0.040; P < .001), a history of hospitalization (β = −0.056, 95% CI: −0.080 to −0.032; P < .001), and herbal medicine use (β = −0.034, 95% CI: −0.061 to −0.007; P = .014). Participants with an unknown route of transmission also had significantly positive association with the utility scores (β = 0.041, 95% CI: 0.006-0.076; p = 0.020).

For the EQ-VAS score, significant associations were observed with comorbidity (β = −6.001, 95% CI: −9.342 to −2.660; P < .001) and history of hospitalization (β = −3.542, 95% CI: −6.664 to −0.419; P = .026). Other sociodemographic and clinical factors, including age, sex, education, treatment supporter, duration of HIV and ART, smoking, alcohol use and distance to health center, were not significantly related to either the EQ-5D-5L utility or VAS scores (Table 2).

Table 2.

Association Between Characteristics of Participants and Quality of Life.

Variable	EQ-5D-5L Utility Index		EQ-VAS
Variable	(Unstd.) β (95% CI)	P-value	(Unstd.) β (95% CI)	P-value
Sociodemographic factors
Age (years)	0.001 (−0.001 to 0.002)	0.297	0.036 (−0.119 to 0.191)	0.647
Sex (Ref: male)	−0.01 (−0.043 to 0.022)	0.528	−0.547 (−4.723 to 3.628)	0.797
Duration of education (Ref: ≤12 years)	0.018 (−0.004 to 0.040)	0.114	0.871 (−1.977 to 3.719)	0.549
Employment status (Ref: not employed)	0.025 (0.002 to 0.048)	0.032	1.232 (−1.702 to 4.167)	0.410
Marital status (Ref: not married)	0.009 (−0.018 to 0.035)	0.513	0.170 (−3.212 to 3.552)	0.921
Monthly income (Ref: <3.5 million)	0.038 (0.016 to 0.059)	<0.001	2.415 (−0.372 to 5.203)	0.089
Living alone (Ref: no)	0.035 (0.010 to 0.059)	0.005	2.279 (−0.884 to 5.443)	0.158
Treatment supporter (Ref: no)	0.009 (−0.014 to 0.032)	0.435	0.971 (−1.943 to 3.885)	0.514
Clinical factors
Duration of HIV (years)	0.001 (−0.001 to 0.003)	0.422	0.044 (−0.272 to 0.361)	0.783
Duration on ART (years)	0.001 (−0.001 to 0.004)	0.413	0.067 (−0.259 to 0.393)	0.686
ART type (Ref: FDC)	0.009 (−0.018 to 0.036)	0.515	2.978 (−0.517 to 6.474)	0.095
HIV stage (Ref: asymptomatic)
• Symptomatic	−0.071 (−0.098 to −0.043)	<0.001	−1.313 (−5.015 to 2.389)	0.487
• AIDS	−0.150 (−0.234 to −0.066)	<0.001	−7.450 (−18.595 to 3.695)	0.190
• Do not know	-0.022 (−0.054 to 0.010)	0.180	−0.234 (−4.475 to 4.007)	0.914
Route of HIV transmission (Ref: heterosexual)
─ Homosexual	0.019 (−0.009 to 0.047)	0.185	1.264 (−2.351 to 4.879)	0.493
─ Intravenous drug use	0.025 (−0.027 to 0.078)	0.339	5.669 (−1.002 to 12.339)	0.096
─ Unknown	0.041 (0.006 to 0.076)	0.020	0.630 (−3.799 to 5.058)	0.781
Comorbidity (Ref: no)	−0.066 (−0.092 to −0.040)	<0.001	−6.001 (−9.342 to −2.660)	<0.001
History of hospitalization (Ref: No)	-0.056 (−0.080 to −0.032)	<0.001	−3.542 (−6.664 to −0.419)	0.026
Smoking status (Ref: No)	0.001 (−0.022 to 0.023)	0.942	0.120 (−2.771 to 3.011)	0.935
Alcohol consumption (Ref: no)	0.010 (−0.016 to 0.035)	0.470	1.428 (−1.885 to 4.740)	0.398
Herbal medicine use (Ref: no)	−0.034 (−0.061 to −0.007)	0.014	−1.254 (−4.752 to 2.243)	0.482
Distance to health center	0,0003 (−0.001 to 0.002)	0.706	−0.104 (−0.271 to 0.062)	0.219

Multivariate linear regression was performed to identify the independent determinants of quality of life after adjusting for relevant sociodemographic and clinical covariates (Table 3). For the EQ-5D-5L utility index, depression severity was the only independent predictor among the psychosocial variables examined (β = −0.006, 95% CI: −0.008 to −0.004; P < .001). This indicates a negative association, whereby higher levels of depression were associated with lower quality-of-life scores. Medication adherence was positively associated with utility scores in the crude model (β = 0.013, 95% CI: 0.007-0.020; P < .001); however, this association became nonsignificant after adjustment for covariates (β = 0.003, 95% CI: −0.003-0.010; P = .303). All medication belief subscales (specific necessity, specific concerns, general harm, and general overuse) showed no significant association with the EQ-5D-5L utility index.

Table 3.

Multivariate analysis between Psychosocial factors and Quality of Life: a. EQ-5D-5L Utility index b. EQ-VAS.

A
Variable	Crude (Unstd.) β (95% CI)	P-Value	Adjusted (Unstd.) β (95% CI)*	P-Value
Medication adherence (MARS-10)	0.013 (0.007 to 0.020)	<0.001	0.003 (−0.003 to 0.010)	0.303
Depression severity (PHQ-9)	−0.008 (−0.010 to −0.006)	<0.001	−0.006 (−0.008 to −0.004)	<0.001
Beliefs about medicines—specific necessity (BMQ-SN)	−0.003 (−0.006 to 0.0003)	0.080	-	-
Beliefs about medicines—specific concerns (BMQ-SC)	−0.004 (−0.007 to (−0.001)	0.005	−0.001 (−0.003 to 0.002)	0.694
Beliefs about medicines—general harm (BMQ-GH)	−0.003 (−0.007 to 0.0003)	0.076	-	-
Beliefs about medicines—general overuse (BMQ-GO)	−0.003 (−0.007 to 0.001)	0.113	-	-
B
Variable	Crude (Unstd.) β (95% CI)	P-value	Adjusted (Unstd.) β (95% CI)*	P-value
Medication adherence (MARS-10)	1.535 (0.663 to 2.408)	<0.001	0.643 (−0327 to 1.613)	0.194
Depression severity (PHQ-9)	−0.523 (−0.789 to −0.258)	<0.001	−0.360 (−0.652 to −0.067)	0.016
Beliefs about medicines—Specific necessity (BMQ-SN)	−0.233 (−0.644 to 0.177)	0.265	-	-
Beliefs about medicines—Specific concerns (BMQ-SC)	−0.518 (−0.873 to −0.163)	0.004	−0.079 (−0.505 to 0.347)	0.717
Beliefs about medicines—General harm (BMQ-GH)	−0.875 (−0.1361 to −0.389)	<0.001	−0.594 (−1.269 to 0.082)	0.085
Beliefs about medicines—General overuse (BMQ-GO)	−0.588 (−1.051 to −0.125)	0.013	−0.031 (−0.646 to 0.584)	0.921

*Adjusted for employment status, monthly income, living alone, HIV stage, route of transmission, comorbidity, history of hospitalization, herbal medicine use, duration of ARV therapy, and treatment supporter.

For the EQ-VAS, depression severity remained significantly and inversely associated with perceived health status (β = −0.360, 95% CI: −0.652 to −0.067; P = .016), even after adjustment for comorbidity and hospitalization history. Although medication adherence and the 3 aspects of medication beliefs (specific concerns, general harm, and general overuse) were significantly associated with EQ-VAS scores in the crude model, these associations were no longer statistically significant after adjustment.

In addition to depression, several sociodemographic and clinical variables were also associated with HRQoL in the adjusted models. For the EQ-5D-5L utility index, higher income and living arrangement were associated with higher HRQoL scores, while symptomatic HIV stage, AIDS stage, the presence of comorbidities, and a history of hospitalization were associated with lower utility scores. Additionally, participants with an unclear route of HIV transmission showed slightly higher utility scores. For the EQ-VAS outcome, comorbidity remained significantly associated with lower self-rated health status. Other variables included in the adjustment model showed no statistically significant association with EQ-VAS after multivariable adjustment. The complete regression results for all adjustment covariates are presented in Supplementary File S3.

Discussion

Our study aimed to examine the associations between depression severity, medication adherence, and medication beliefs with HRQoL among PLWH receiving care in PHC settings located in a high-prevalence area of a developing country, namely Makassar, Indonesia. By simultaneously evaluating these psychosocial and behavioral factors within a PHC context, this study provides additional evidence from an LMIC setting where most PLWH receive long-term HIV care. The EQ-5D-5L mean utility score among PLWH was 0.94 (SD = 0.10), indicating generally good HRQoL in this population. Comparable values have been reported in other Asian settings using the same instrument, such as Philippines (0.95 ± 0.06),⁴¹ Thailand (0.912 ± 0.149),⁴² and India (0.976 ± 0.0519).⁴³ Among the investigated determinants, depression severity emerged as the only independent psychosocial determinant of HRQoL. Depression severity showed a negative association with HRQoL, indicating that higher levels of depression were associated with lower HRQoL index scores.

The negative relationship between depression and HRQoL found in this study is consistent with emerging evidence from Indonesia. A recent Indonesian study by Stefanovic et al reported a significant relationship between ‘quality of life, perceived stigma, and depression among PLWH’.²² In their analysis, poorer QoL was associated with higher levels of depression, suggesting that QoL may serve as a protective factor against depressive symptoms. Although their study used different instruments, including the WHOQOL-BREF and the Hamilton Depression Rating Scale, the findings similarly highlight the close interrelationship between psychological well-being and quality of life among PLWH. Our findings are also consistent with studies conducted among PLWH in other low- and middle-income countries, including Ethiopia,¹³ Nigeria,⁴⁴ Brazil,⁴⁵ and India¹² which similarly reported a negative association between depressive symptoms and HRQoL. Depression may influence HIV outcomes through both biological and behavioral mechanisms. The direct biological pathway involves dysregulation of the hypothalamic-pituitary-adrenal axis, resulting in elevated cortisol levels that suppress immune function, decrease CD4 T-cell counts, and enhance viral replication^46–48 Indirectly, depression may accelerate disease progression through behavioral (ex: substance use), social (ex: poor social support), and psychological (ex: hopelessness) pathways that collectively alter immune responses and worsen clinical outcomes, therefore, diminished HRQoL among PLWH.^46–48

In addition to depression, adherence to ART is also considered an important factor influencing HRQoL. In our study, better medication adherence was linked to higher HRQoL in the univariate analysis; however, this relationship was no longer statistically significant after adjustment for other variables. This finding should be interpreted alongside prior Indonesian evidence. Wardojo et al, in a study conducted among HIV clinic attendees in Malang, Indonesia, found that adherence was associated with better QoL, together with social support, lower stigma, and better access to healthcare services.²¹ However, their study was conducted in a single setting and employed different measurement instruments, using the WHOQOL-HIV BREF to assess QoL and the AIDS Clinical Trial Group (ACTG) questionnaire to measure adherence, whereas our study used the EQ-5D-5L and MARS-10 instruments. Differences in measurement tools, study settings, and analytical approaches may partly explain the variation in findings. Our results suggest that the influence of adherence on HRQoL may not be direct but may instead be mediated by psychosocial factors, particularly depression. This interpretation is supported by previous studies showing that depressive symptoms can reduce medication adherence, which in turn contributes to poorer treatment outcomes and lower HRQoL.^49,50 The presence of particular depressive symptoms, such as low motivation, poor concentration, hopelessness, worthlessness, and fatigue, may elucidate the mechanisms underlying nonadherence to medication among individuals with depression.⁵¹ Thus, managing depressive symptoms may enhance adherence behaviors and indirectly improve HRQoL among PLWH.⁵²

A similar trend was observed in medication beliefs. In the univariate analysis, higher scores on specific concerns, general harm, and general overuse of ART were associated with lower HRQoL among PLWH, but these associations did not remain significant after multivariate adjustment. This finding can be better understood in light of previous Indonesian work by Sianturi et al, who examined the relationship between stigma, beliefs about medicines, and adherence among PLWH in rural Indonesia.²⁰ That study found that beliefs about medicines were not significantly associated with adherence, despite participants generally reporting a high perceived necessity of ART alongside substantial concerns about overuse and harmful effects. Their findings suggest that decisions regarding ART use may not be determined solely by perceived risks and benefits of medication, but also by broader psychosocial factors such as stigma. In our study, medication beliefs may likewise have had a more indirect role, potentially operating through depression or adherence rather than acting as an independent determinant of HRQoL. This interpretation is also consistent with evidence from other chronic disease settings showing that medication beliefs may partly explain the pathway linking emotional distress and adherence behavior.⁵³ Beliefs that medications are generally harmful have been found to be negatively associated with adherence.⁵⁴ Therefore, interventions aimed at improving HRQoL among PLWH may need to address not only medication beliefs, but also the broader psychosocial context in which such beliefs are forme.

In addition to the psychosocial variables examined in this study, several socioeconomic and clinical characteristics were also associated with HRQoL, highlighting the multifactorial nature of quality of life among PLWH in Makassar. In the adjusted models, higher income and living arrangements were associated with better HRQoL, whereas symptomatic or advanced HIV stage, the presence of comorbidities, and a history of hospitalization were associated with lower HRQoL. These findings suggest that HRQoL among PLWH is influenced not only by psychological well-being but also by broader socioeconomic conditions and disease-related factors. Addressing quality of life therefore requires a comprehensive approach that integrates clinical management, social support, and mental health care within HIV services.

Some limitations are worth underlining. First, we did not have information on immunological and virological markers, such as CD4 count and viral load, which could have provided a more comprehensive understanding of the clinical status and its association with HRQoL. Second, the study was conducted in urban PHCs in Makassar, where most participants were in the asymptomatic stage of HIV infection and only a small proportion were in the AIDS stage. This distribution likely reflects the PHC-based recruitment setting, where individuals with stable clinical conditions typically receive routine care. Consequently, the findings may not be fully generalizable to PLWH with more advanced HIV infection who are more likely to receive care in hospital settings. This limited clinical spectrum may also partly explain the relatively high EQ-5D-5L utility scores observed in this study. Third, the majority of participants were male. This distribution likely reflects the epidemiological pattern of HIV infection in Indonesia, where a substantial proportion of cases occur among men, particularly among particular cohorts such as men who have sex with men (MSM). This pattern is consistent with previously published evidence. A literature review of 15 studies examining HIV/AIDS patient characteristics in Indonesian healthcare facilities reported that HIV/AIDS cases were predominantly male across all included studies (>50%).⁵⁵ Similarly, a prospective cohort study examining the HIV care cascade among key populations in Indonesia found that most participants were male (82%), with MSM representing the largest key population (77%).⁵⁶ Nevertheless, the relatively small proportion of female participants may limit the generalizability of the findings to women living with HIV and restrict the ability to explore potential gender differences in HRQoL. Fourth, depression, medication adherence, and medication beliefs were assessed using self-reported instruments, which may be subject to social desirability and recall bias. Although validated questionnaires were used, these measures rely on participants’ subjective perceptions and may not fully reflect objective clinical or behavioral outcomes. Fifth, although information on ART regimen type (FDC vs non-FDC) was collected, the study did not examine potential differences in HRQoL according to specific ART regimens or treatment-related side effects. Variations in antiretroviral therapy and treatment tolerability may influence patients’ perceived quality of life and therefore warrant further investigation in future studies. Sixth, we did not measure perceived stigma, which has been identified as an important determinant of quality of life among PLWH. Finally, unmeasured confounders, such as coping mechanisms, might have influenced the observed associations, but information on these variables was not available.

In addition to the clinical implications, the findings of this study also highlight important equity considerations in HIV care. PLWH frequently experience stigma and discrimination within healthcare and community settings, which may create disparities in access to comprehensive care, including mental health services.^57,58 Evidence from previous studies in antiretroviral treatment settings indicates that stigma among healthcare providers remains prevalent.^59,60 Such stigma may negatively influence the quality of care, treatment adherence, and broader HIV prevention efforts. In this context, mental health conditions such as depression may remain under-recognized or insufficiently addressed among PLWH. The identification of depression as a key determinant of HRQoL in this study therefore underscores the importance of integrating stigma-sensitive mental health support within HIV care services at the primary healthcare level. Strengthening such integrated care may help reduce health disparities experienced by PLWH and aligns with the broader goal of the Sustainable Development Goals to reduce health inequalities.

Conclusion

Our study identified depression severity as the only independent psychosocial predictor of HRQoL among PLWH in primary healthcare settings in Makassar, Indonesia. While medication adherence and medication beliefs were associated with HRQoL in unadjusted analyses, their effects were attenuated after controlling for confounders, suggesting that depression may play a central mediating role. These findings underscore the need to integrate regular mental health assessment and psychosocial support into HIV primary care programs to improve patients’ overall well-being. Future research should explore implementation strategies for integrating mental health services within HIV care, as well as investigate potential barriers to accessing mental health support among people living with HIV in primary healthcare settings.

Supplemental Material

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Supplemental material, sj-docx-1-jia-10.1177_23259582261452316 for Depression, Medication Adherence, and Beliefs as Determinants of Health-Related Quality of Life among People Living with HIV: A Cross-Sectional Pharmacoepidemiologic Study in Indonesia by Muh. Akbar Bahar, Hardiyanti Syarif, Neily Zakiyah and Najmiatul Fitria in Journal of the International Association of Providers of AIDS Care (JIAPAC)

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Supplemental material, sj-docx-2-jia-10.1177_23259582261452316 for Depression, Medication Adherence, and Beliefs as Determinants of Health-Related Quality of Life among People Living with HIV: A Cross-Sectional Pharmacoepidemiologic Study in Indonesia by Muh. Akbar Bahar, Hardiyanti Syarif, Neily Zakiyah and Najmiatul Fitria in Journal of the International Association of Providers of AIDS Care (JIAPAC)

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Supplemental material, sj-docx-3-jia-10.1177_23259582261452316 for Depression, Medication Adherence, and Beliefs as Determinants of Health-Related Quality of Life among People Living with HIV: A Cross-Sectional Pharmacoepidemiologic Study in Indonesia by Muh. Akbar Bahar, Hardiyanti Syarif, Neily Zakiyah and Najmiatul Fitria in Journal of the International Association of Providers of AIDS Care (JIAPAC)

Footnotes

Acknowledgments

The authors extend their sincere appreciation to Riset Kolaborasi Indonesia and Universitas Hasanuddin for the research grant and support in conducting this study. Special thanks are given to the Makassar City Health Office (Dinas Kesehatan Kota Makassar) and the staff of participating primary health care centers for their assistance during data collection. We also gratefully acknowledge Universitas Padjadjaran and Universitas Andalas for their collaboration and academic support. The authors further thank Zulhijrah, Nurliana, and Raslona Arman for their excellent assistance in data collection arrangements.

ORCID iDs

Muh. Akbar Bahar

Hardiyanti Syarif

Najmiatul Fitria

Ethical Statement and Informed Consent

The study protocol was reviewed and approved by the Ethics Committee of the Faculty of Pharmacy, Universitas Hasanuddin (ethics approval number: 2252/UN4.1.23/KP.06.05/2025; 18 July 2025). All participants were adults aged 18 years or older and provided written informed consent prior to participation; therefore, consent from a legally authorized representative was not required. Participation was voluntary, confidentiality was strictly maintained, and participants were informed of their right to withdraw from the study at any time without affecting their access to care. The study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki.

Author Contributions

Conceptualization and methodology: M.A.B., H.S., N.Z., and N.F.; Formal analysis and software: M.A.B. and H.S.; Ethics approval and data collection: M.A.B. and H.S.; Project administration: M.A.B. and H.S.; Resources: M.A.B., N.Z., and N.F.; Investigation: M.A.B. and H.S.; Data curation and validation: M.A.B. and H.S.; Data interpretation: M.A.B., N.Z., and N.F.; Writing—original draft preparation: M.A.B.; Writing—review and editing: H.S., N.Z., and N.F.; Funding acquisition: M.A.B., N.Z., and N.F.

All authors have read and approved the final version of the manuscript.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by the Riset Kolaborasi Indonesia (RKI) program under Contract Number 01319/UN4.22/PT.01.03/RKI/2025, funded by the Institute for Research and Community Service (Lembaga Penelitian dan Pengabdian kepada Masyarakat) of Universitas Hasanuddin for the fiscal year 2025.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request. Due to privacy and ethical restrictions, some data cannot be made publicly available.

Declaration of Generative AI and AI-Assisted Technologies in the Writing Process

The authors used ChatGPT to assist in improving the English language of this manuscript. After using the tool, the authors carefully reviewed, revised, and edited the text, and take full responsibility for the final content of the publication.

Supplemental Material

Supplemental material for this article is available online.

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