Impact of a community-based antiretroviral therapy delivery model on treatment outcomes, mental health, and quality of life among stable people living with HIV in Cambodia: a quasi-experimental study

Impact of a community-based antiretroviral therapy delivery model on treatment outcomes, mental health, and quality of life among stable people living with HIV in Cambodia: a quasi-experimental study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Impact of a community-based antiretroviral therapy delivery model on treatment outcomes, mental health, and quality of life among stable people living with HIV in Cambodia: a quasi-experimental study Siyan Yi, Ziya Tian, Pheak Chhoun, Sovannary Tuot, Esabelle Yam, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6310016/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Nov, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Cambodia’s HIV response successfully met the UNAIDS 90-90-90 targets in 2017; however, ongoing systemic barriers such as clinic congestion, stigma, and mental health disparities pose a threat to this progress. This quasi-experimental study evaluated a community-based antiretroviral (ART) delivery (CAD) model against multi-month dispensing (MMD) for stable people living with HIV from 2021 to 2023 across 20 ART clinics, enrolling a total of 4,089 participants (2,040 in CAD, 2,049 in MMD). The study employed baseline and endline surveys along with clinical data to assess various outcomes, including ART adherence, viral suppression, retention in HIV care, stigma, mental health, and quality of life. Results indicated high retention (97.3%) and viral suppression (> 99%) rates for both models, with CAD showing a significant improvement in ART adherence ( P = 0.002), a smaller decline in participants with no depressive symptoms ( P = 0.001) and enhanced physical health ( P < 0.001). Although CAD resulted in modest decreases in externalised stigma, the effects on internalised stigma remained inconclusive. The findings suggest that CAD is an effective community-based model for sustaining ART adherence and improving health outcomes, supporting the integration of such approaches within Cambodia’s HIV care system while also advocating for the combination of CAD with stigma-reduction strategies. Health sciences/Health care Scientific community and society/Developing world Figures Figure 1 Introduction Cambodia has made significant strides in addressing the HIV epidemic. The prevalence of HIV among adults aged 15 to 49 years decreased from 1.7% in 1998 to 0.5% in 2023. It was also one of three Asia-Pacific countries to meet the UNAIDS 90-90-90 targets in 2017 1,2 . As of 2023, 89% of an estimated 76,000 people living with HIV have been diagnosed, 89% are receiving sustained antiretroviral therapy (ART), and 87% have achieved viral suppression 3 . Nonetheless, further progress is necessary to meet the UNAIDS 95-95-95 targets and eventually eliminate HIV in Cambodia. HIV services are provided through 74 ART clinics managed by government and non-governmental organisations (NGOs) across 25 provinces 4 . These clinics face significant challenges, including congestion and shortages of human resources, which impede high-quality care, especially for unstable individuals who require frequent follow-ups. People living with HIV also experience substantial psychological challenges, including stigma, which is closely associated with poorer mental health outcomes 5 and can negatively affect ART adherence and retention in care 6 – 9 . Additionally, certain sub-populations, particularly those with vulnerable socioeconomic or clinical statuses and inadequate social support, are at risk of being lost to follow-up in ART 10 . Additionally, vulnerable populations with insufficient social support are at risk of losing follow-up care in ART programmes. Other concerns include missed appointments and improper storage of antiretrovirals (ARVs) after dispensing 11 . Since 2015, the World Health Organization (WHO) has advocated for a client-centred approach using differentiated service delivery (DSD) models tailored to the needs of people living with HIV while lessening the burden on health systems 12 . DSD models, such as community-based ART distributions, as seen in Mozambique and Lesotho, have shown promising results in improving ART adherence, alleviating clinic congestion, and enhancing mental health for people living with HIV 13 , 14 . In Cambodia, where community-based services are integral to the national HIV response, the National Centre for HIV/AIDS, Dermatology, and STD (NCHADS) implemented the multi-month dispensing (MMD) model in 2017. This model allows clinically stable individuals to visit ART clinics every three to six months, thereby reducing travel burdens 15 . Building on this, a quasi-experimental study introduced a Community-based ART Delivery (CAD) model, further decentralising care by integrating ARV distributions within peer-led community networks 16 . The CAD model represents an innovative approach to HIV care by leveraging the lived experiences of people living with HIV. Unlike traditional community-based models that rely on trained community health workers (CHWs) without HIV experience, the model empowers people living with HIV to serve as Community Action Workers (CAWs). These CAWs collect pre-packaged ARVs from ART clinics and distribute them during monthly group sessions while also providing health education, monitoring vital signs, and offering peer social support. This peer-led structure fosters a supportive environment that tackles stigma and enhances mental health outcomes through shared experiences, distinguishing the CAD model from other interventions. For instance, while models in Uganda and Zimbabwe prioritise logistical efficiency through CHWs 17 , 18 , the CAD model integrates psychosocial support as a core component, aligning with the WHO’s emphasis on holistic, person-centred care. This quasi-experimental study aims to assess its effectiveness compared to MMD in improving the health and well-being of stable people living with HIV. By positioning people living with HIV as active agents in care delivery, CAD addresses systemic gaps like clinic congestion and mental health disparities while aligning with Cambodia’s broader goals of sustainable, community-driven HIV management. This study will provide essential evidence for the potential scale-up and integration of the CAD model into national HIV programmes. Results Participant characteristics As shown in Fig. 1 , 4,089 people living with HIV were enrolled in the study and completed a baseline survey, with 2,040 (49.9%) in the CAD and 2,049 (50.1%) in the MMD group. By the endline, 3,977 participants (97.3%) were retained in HIV care, and 3,067 (77.1%) completed endline survey. Of those, 1,626 (79.7%) in CAD and 1,441 (70.3%) in MMD completed endline survey. Among 85 participants who did not remain in HIV care, 36 (42.4%) were from CAD, and 49 (57.6%) were from MMD due to death, loss, or transfer. Of those who retained in care but did not complete endline survey (22.9%), a higher percentage of participants were from MMD (61.6%) compared to CAD (35.2%). Table 1 shows that a higher proportion of participants in MMD (75.5%) than the CAD (61.0%) group were recruited from urban areas. Most participants were aged 15–49, predominantly female, married, and had a primary school education. Many were farmers or fishermen, self-employed, or unemployed. MMD participants were nearly four times more likely than CAD participants to identify as lesbian, gay, bisexual, transgender, or queer (LGBTQ+) (4.7% vs. 1.2%). Most had small families, and the median monthly household income was higher in the MMD than in the CAD group (USD 216 vs. USD 192). A more significant proportion of CAD participants (25.9%) reported at least one comorbidity compared to MMD group (17.9%). A significantly higher proportion of MMD participants were newly diagnosed with HIV (1–5 years) and newly on ART (0–5 years) compared to the CAD group ( P < 0.001). Conversely, a higher proportion of CAD participants had lived with HIV and received ART for 11 years or longer. However, most participants in both groups had lived with HIV and received ART for 11–20 years. Approximately half of the participants in both groups travelled less than 30 minutes to ART clinics, and the mean waiting time at the clinics was slightly higher among CAD participants (2.2 hours) than among the MMD group (1.6 hours). Table 1 Summary of sociodemographic, clinical characteristics, care retention, and viral suppression in CAD and MMD arms CAD (N = 1,626) n (%) MMD (N = 1,441) n (%) P -value Study setting Urban 992 (61.0) 1088 (75.5) < 0.001 Rural 634 (39.0) 353 (24.5) .. Age (years) Adults (15–49) 992 (56.7) 842 (58.4) 0.33 Older adults (50+) 704 (43.3) 599 (41.6) .. Gender Male 603 (37.1) 548 (38.0) < 0.001 Female 1004 (61.8) 826 (57.3) .. LGBTQ + 1 19 (1.1) 67 (4.7) .. Marital status Married 984 (60.5) 850 (59.0) 0.03 Widowed 422 (26.0) 348 (24.2) .. Never married or divorced, or others 220 (13.5) 243 (16.9) .. Formal education (years) No, or unknown formal education 295 (18.1) 230 (16.0) <0.001 Primary school (1–6) 831 (51.1) 679 (47.1) .. Secondary school (7–9) 329 (20.2) 311 (21.6) .. Tertiary or university (10 +) 171 (10.5) 221 (15.3) .. Occupation Unemployed 307 (18.9) 267 (18.5) 0.004 Farmer, or fisherman 471 (29.0) 352 (24.4) .. Self-employed business 279 (17.2) 298 (20.7) .. Construction, or factory workers 240 (14.8) 191 (13.3) .. Other (taxi driver, government staff or NGO staff, uniformed officer 2 , or private employee) 329 (20.2) 333 (23.1) .. Family size (number of family members) Small family (1–4) 1021 (70.9) 1230 (75.7) 0.003 Medium to large family (5+) 396 (24.4) 420 (29.2) .. Number of children under 15 years old No children 682 (41.9) 601 (41.7) 0.72 One child 538 (33.1) 463 (32.1) .. Two or more children 406 (25.0) 377 (26.2) .. Monthly household income (USD) Median (interquartile range) 192 (237.6) 216 (240) 0.001 Presence of comorbidity diagnosed Having at least one co-morbidity 3 421 (25.9) 258 (17.9) < 0.001 Duration of living with HIV (years) Newly diagnosed (1–5) 143 (8.8) 258 (17.9) < 0.001 Medium duration (6–10) 263 (16.2) 258 (17.9) .. Long duration (11–15) 541 (33.3) 389 (27.0) .. Very long duration (16+) 679 (41.8) 536 (37.2) .. Duration of receiving ART (years) Newly on ART (0–5) 189 (19.7) 284 (19.7) < 0.001 Medium duration (6–10) 320 (19.7) 303 (21.0) .. Long duration (11–15) 604 (37.2) 462 (32.1) .. Very long duration (16+) 513 (31.6) 392 (27.2) .. Mode of transportation to ART clinic Tuk Tuk, motorcycle, or car 1551 (95.4) 1331 (92.4) < 0.001 On foot or bicycle 69 (4.2) 54 (3.8) .. Boat, ship, or others 6 (0.4) 56 (3.9) .. Traveling time to ART sites (hours) Short travel (< 0.5) 776 (47.7) 621 (43.1) 0.03 Medium travel (0.5-2) 717 (44.1) 702 (48.7) .. Long travel (2+) 133 (8.2) 118 (8.2) .. Waiting time at ART site (hours) Mean ± SD 2.19 ± 1.27 1.55 ± 0.97 <0.001 Retained in HIV care 4 1984 (98.2) 1993 (97.6) 0.17 Viral load suppressed 5 2024 (99.2) 2037 (99.4) < 0.001 Abbreviations: ART, antiretroviral therapy; CAD, community-based antiretroviral therapy delivery model; HIV, human immunodeficiency viruses; IQR, interquartile range; MMD, multi-month dispensing model; NGO, non-governmental organization; SD, standard deviation; USD, United States dollar. 1 LGBTQ+ includes lesbians, gay men, bisexual individuals, transgender people, queers, intersex individuals, asexual individuals, and those who choose not to identify. 2 Uniformed officers include policemen, soldiers, and police military. 3 Co-morbidities include diabetes mellitus, high cholesterol, and hypertension. 4 N = 2,020 in CAD, N = 2,042 in MMD. There were 20 missing values in CAD and 7 in MMD. 5 N = 2,040 in CAD, N = 2,049 in MMD. Treatment outcomes Retention in HIV care was high in both groups, with 98.2% in the CAD and 97.6% in the MMD group, showing no statistically significant difference ( P = 0.17). More than 99.0% of participants maintained suppressed viral loads, with minimal differences between the two arms ( P < 0.001). (Table 1 ) The CAD group demonstrated non-inferiority and superiority over the MMD group across treatment outcomes, as evidenced by descriptive trends (Table 2 ) and robust intervention effects (Tables 3 and 4 ). At baseline, the CAD group had significantly lower self-reported ART adherence than the MMD group (87.0% vs. 90.3%, P = 0.005, Table 2 ). By the endline, ART adherence declined modestly in both groups, but the CAD group maintained a superior trajectory (86.8% vs. 84.4% in MMD, P = 0.05). As shown in Table 3 , the CAD group had 64% higher odds of ART adherence (adjusted odds ratio [AOR] = 1.64, 95% confidence interval [CI] 1.21–2.23, P = 0.002). Table 4 confirms a significant difference-in-difference advantage of 5.49% (95% CI 1.96–9.01). These findings substantiate CAD’s non-inferiority and superiority in maintaining adherence, even with baseline differences between groups. Table 2 ART adherence, mental health, stigma and discrimination, and quality of life of participants at baseline and endline in CAD and MMD arms Baseline Endline CAD 1 ( n = 1,626) n (%) MMD 2 ( n = 1,441) n (%) P -value CAD 1 ( n = 1,626) n (%) MMD 2 ( n = 1,441) n (%) P -value ART adherence Self-reported ART adhered 1415 (87) 1301 (90.3) 0.005 1412 (86.8) 1216 (84.4) 0.05 Stigma (People Living with HIV Stigma Index) Non-stigma experienced 1499 (92.2) 1362 (94.5) 0.01 1503 (92.4) 1315 (91.3) 0.23 Low internal stigma 1122 (69) 914 (63.4) 0.001 1305 (80.3) 1053 (73.1) < 0.001 Not fear of stigma 1445 (88.9) 1234 (85.6) 0.01 1475 (90.7) 1281 (88.9) 0.10 Mental health status (CES-D) No depression symptoms 1263 (77.7) 1208 (83.8) < 0.001 1182 (72.7) 1030 (71.5) 0.45 Quality of life (SF-12) Good mental health 1241 (76.3) 1213 (84.2) < 0.001 1261 (77.6) 1183 (82.1) 0.002 Good physical health 887 (54.6) 1004 (69.7) < 0.001 806 (49.6) 745 (51.7) 0.24 Abbreviations: ART for Antiretroviral therapy; CAD, community-based antiretroviral therapy delivery; CES-D, Centre for Epidemiologic Study Depression Scale; MMD, multi-month dispensing; SF-12, 12-item Short Form survey. Table 3 Intervention effects of CAD among participants with completed baseline and endline surveys over time Intervention effects 1 Crude model Adjusted model 2 OR [95% CI] P-value Model fit (BIC) 3 AOR [95% CI] P -value Model fit (BIC) 3 ART adherence Self-reported adherence 1.69 [1.25,2.29] 0.001 4723.69 1.64 [1.21, 2.23] 0.002 4677.51 Stigma (People Living with HIV Stigma Index) No stigma 1.71 [1.16,2.52] 0.01 3264.96 1.48 [0.99, 2.20] 0.06 3269.99 Low internal stigma 1.17 [0.93,1.46] 0.18 7234.95 1.18 [0.94,1.48] 0.15 7235.89 Not Fear of stigma 0.91 [0.66,1.25] 0.57 4366.84 0.88 [0.63, 1.21] 0.42 4354.12 Mental health status (CES-D) No depressive symptoms 1.58 [1.24,2.02] < 0.001 6666.34 1.54 [1.20, 1.97] 0.001 6521.37 Quality of life (SF-12) Good mental health 1.24 [0.96,1.60] 0.09 6159.54 1.20 [0.92, 1.57] 0.17 6031.94 Good physical health 1.76 [1.43,2.16] < 0.001 8293.89 1.70 [1.37, 2.11] < 0.001 8121.65 Abbreviations: AOR, adjusted odds ratio; ART, antiretroviral therapy; BIC, Bayesian information criterion; CAD, community-based antiretroviral therapy delivery; CES-D, Center for Epidemiologic Study Depression Scale; CI, confidence interval; MMD, multi-month dispensing; OR, odds ratio; SF-12, 12-item Short Form survey. 1 N=1626 in CAD arm; N = 1441 in MMD arm. 2 Outcome-specific covariates used in the adjusted models for each treatment outcome are detailed in Supplementary Table S1 . 3 The model fit had P < 0.001 for all crude and adjusted models. Table 4 Predicted probabilities, difference-in-difference estimates of intervention effects on treatment outcomes over time CAD Intervention (N = 1,626) MMD Control (N = 1,441) DiD Estimate (%) [95% CI] Conclusion Baseline Endline Baseline Endline P (%) [95% CI] P (%) [95% CI] P (%) [95% CI] P (%) [95% CI] ART adherence Self-reported ART adherence 86.83 [85.17, 88.49] 86.10 [84.38, 87.82] 90.69 [89.19, 92.18] 84.92 [83.10, 86.73] 5.03 [1.62, 8.45] Non-inferior and superior Stigma (People Living with HIV Stigma Index) No stigma 92.57 [91.31, 93.84] 91.99 [90.63, 93.36] 94.43 [93.23, 95.63] 91.41 [89.99, 92.84] 2.44 [-0.30, 5.18] Non-inferior Low internal stigma 68.86 [66.60, 71.11] 79.97 [78.00, 81.94] 63.98 [61.48, 66.49] 73.12 [70.84, 75.41] 1.98 [-2.44, 6.39] Non-inferior Not fear of stigma 89.07 [87.54, 90.60] 90.02 [88.50, 91.54] 86.38 [84.62, 88.13] 88.89 [87.27, 90.50] -1.56 [-4.66, 1.55] Non-inferior Mental health status (CES-D) No depressive symptoms 78.21 [76.24, 80.19] 72.85 [70.73, 74.97] 83.38 [81.47, 85.29] 71.21 [68.88, 73.53] 6.81 [2.71, 10.90] Non-inferior and superior Quality of life (SF-12) Good mental health 76.55 [74.47, 78.64] 77.76 [75.78, 79.75] 83.72 [81.82, 85.62] 82.15 [80.18, 84.12] 2.77 [-1.10, 6.65] Non-inferior Good physical health 56.50 [54.01, 58.98] 49.72 [47.31, 52.12] 68.73 [66.34, 71.12] 50.39 [47.75, 53.03] 11.56 [6.62,16.50] Non-inferior and superior Abbreviations: ART for antiretroviral therapy; CAD, community-based antiretroviral therapy delivery; CES-D, Centre for Epidemiologic Study Depression Scale; CI, confidence interval; DiD, difference-in-differences; MMD, multi-month dispensing; P, predicted probability; SF-12, 12-item Short Form survey. Pre-specified non-inferiority margin, risk difference= -10% HIV stigma At baseline, the MMD group reported a significantly higher rate of non-stigma experience (94.5% vs. 92.2% in CAD, P = 0.01; Table 2 ). By the endline, the CAD group showed a marginal improvement (92.4%), while the MMD group experienced a decline (91.3%, P = 0.23). Adjusted models (Table 3 ) suggested a trend toward reduced stigma in the CAD group (AOR = 1.48, P = 0.06), although difference-in-difference estimates were inconclusive (2.4%, 95% CI − 0.30–5.18; Table 4 ). Internal stigma increased sharply in both groups (CAD: 69.0–80.3%, MMD: 63.4–73.1%, P < 0.001), while no significant differences were observed for fear of stigma ( P = 0.10). Depressive symptoms Both the CAD and MMD groups experienced a reduction in the proportion of participants reporting no depressive symptoms over time (CAD: 77.7–72.7%; MMD: 83.8–71.5%; Table 2 ). The decline was more pronounced in the MMD group; however, the between-group difference at the endline was not statistically significant (P = 0.45). Adjusted models (Table 3 ) indicated that CAD participants had 54% higher odds of maintaining no depressive symptoms than those in the MMD group (AOR = 1.54, 95% CI 1.20–1.97, P = 0.001). This advantage was corroborated by a significant difference-in-difference estimate of 6.8% (95% CI 2.71–10.90; Table 4 ), indicating a smaller decline in the proportion of participants without depressive symptoms in the CAD group relative to the MMD group. Quality of life Regarding quality of life, the MMD group reported better physical health (69.7% in MMD vs. 54.6% in CAD, P < 0.001, Table 2 ) at baseline. By the endline, both groups experienced a decline in good physical health (49.6% in the CAD group; 51.7% in the MMD group, P = 0.24), but the CAD group demonstrated striking superiority in the difference-in-difference estimate for good physical health (11.6%, 95% CI 6.62–16.50, Table 4 ), supported by robust intervention effects (AOR = 1.70, 95% CI 1.37–2.11, P < 0.001, Table 3 ). Despite MMD group’s superior baseline mental health (84.2% vs. 76.3% in CAD, P < 0.001), CAD narrowed this gap at endline (77.6% vs. 82.1%, P = 0.002). No significant difference was observed regarding mental health (AOR = 1.20, P = 0.17, Table 3 ). Adjusted models consistently outperformed crude models, reflected in lower Bayesian Information Criterion values (Table 3 ), reinforcing the validity of the estimates. All outcomes met pre-specified non-inferiority margins, with superiority established for ART adherence, mental health, and physical health, where 95% of CIs excluded null effects. Sensitivity analyses The robustness of our findings was rigorously validated through sensitivity analyses that addressed potential biases from missing data (Table 5 ). In all tested scenarios, CAD maintained non-inferiority and demonstrated superiority over MMD, with effect estimates remaining stable or strengthening under conservative assumptions. These findings reinforce the reliability of the primary results (Tables 3 – 4 ) and highlight CAD's resilience to plausible missing data mechanisms. Table 5 Sensitivity analysis on difference-in-difference estimates of intervention effects on treatment outcomes over time Scenario 1 1 Scenario 2 2 Scenario 3 3 DiD estimate (%) [95% CI] DiD estimate (%) [95% CI] DiD estimate (%) [95% CI] ART Adherence Self-Reported ART Adhered 6.55 [5.22, 7.81] 6.40 [5.01, 7.79] 8.14 [6.69, 9.63] Stigma (People Living with HIV Stigma Index) Non-Stigma Experienced 4.92 [3.32, 6.57] 4.56 [2.89, 6.13] 6.33 [4.52, 8.05] Low Internal Stigma -0.82 [-2.18, 0.38] -0.97 [-2.39, 0.30] 1.06 [-0.32, 2.33] Not Fear of Stigma -0.75 [-2.03, 0.46] -1.37 [-2.61, -0.01] 0.57 [-0.66, 1.79] Mental Health Status (CES-D) No Depression Symptoms 6.94 [5.54, 8.50] 6.71 [5.22, 8.28] 8.33 [6.85, 9.95] Quality of Life (SF-12) Good Mental Health 3.47 [2.17, 4.86] 3.92 [2.53, 5.21] 3.47 [2.09, 4.82] Good Physical Health 11.87 [10.55, 13.25] 11.64 [10.10, 13.10] 11.93 [10.50, 13.30] Abbreviations: AOR, adjusted odds ratio; ART, antiretroviral therapy; BIC, Bayesian information criterion; CAD, community-based antiretroviral therapy delivery; CES-D, Centre for Epidemiologic Study Depression Scale; CI, confidence interval; MMD, multi-month dispensing; OR, odds ratio; SF-12, 12-item Short Form survey. 1 Assumptions: i) Missing at random ii) Baseline characteristics remained unchanged at endline. 2 Assumptions: i) Missing at random ii) Some baseline characteristics changed at endline for 50% of participants with incomplete endline surveys. 3 Assumptions: i) Missing not at random, where participants with incomplete endline surveys had worse outcomes (e.g., 5% lower probability of adherence) than observed data at endline. ii) Baseline characteristics remained unchanged at endline. Under the missing-at-random assumption, CAD was associated with a 6.6% improvement in ART adherence (95% CI 5.22–7.81). For mental health outcomes, CAD showed a 6.94 percentage-point advantage (95% CI 5.54–8.50) in maintaining no depressive symptoms compared to MMD and clinically meaningful improvements in physical health (11.9%, 95% CI 10.55–13.25). The consistency between imputed and complete-case estimates underscores the legitimacy of the missing-at-random assumption in this context. There was minimal impact on estimates when accounting for potential differential loss to follow-up by adjusting key sociodemographic variables by 50%. ART adherence remained robust at 6.4% (95% CI 5.01–7.79), as did CAD's advantage in sustaining no depressive symptoms (6.7 percentage points, 95% CI 5.22–8.28) and physical health gains (11.6%, 95% CI 10.10–13.10). Notably, mental health-related quality of life scores increased slightly (3.9%, 95% CI 2.53–5.21 vs. 3.5%, 95% CI 2.17–4.86 in Scenario 1). Under a conservative missing-not-at-random assumption—where the loss to follow-up systematically underperformed—CAD's superiority persisted or even strengthened. ART adherence gains increased to 8.1% (95% CI 6.69–9.63), while the advantage in maintaining no depressive symptoms rose to 8.3% (95% CI 6.85–9.95), and physical health improvements remained stable at 11.9% (95% CI 10.50–13.30). However, stigma-related outcomes exhibited differential patterns. Although CAD continued to improve non-stigma experiences (6.3%, 95% CI 4.52–8.05, compared to 4.9%, 95% CI 3.32–6.57 in Scenario 1), the lower bounds of the 95% CIs for internalised stigma (-0.32) and fear of stigma (-0.66) did not exclude 0, indicating non-inferiority but a lack of superiority in these areas. Discussion Our findings demonstrate the effectiveness of the CAD model in maintaining ART adherence, improving mental health, and enhancing physical health outcomes compared to MMD over the 18-month intervention period. Retention in HIV care was high in both groups, with 98.2% of CAD participants and 97.6% of MMD participants remaining by endline, indicating that the CAD model did not compromise care retention despite differences in service delivery models. Viral suppression rates exceeded 99% in both groups, with minimal differences favouring the CAD model, reinforcing the effectiveness of both models in sustaining virologic control. Self-reported ART adherence declined in both groups over time, though the decline was smaller in the CAD arm. Adjusted models confirmed the CAD model’s superior ART adherence outcomes, with CAD participants showing 64% higher adherence odds than MMD participants. These results align with other studies supporting CAD models in improving HIV care retention and ART adherence in resource-limited settings 19 , 20 . The smaller decline in self-reported adherence within the CAD group suggests that community-based care may buffer against contextual disruptions (e.g., migration, stigma) that disproportionately affect marginalised populations. However, the modest absolute difference in adherence (86.8% vs. 84.4%) underscores the need for cautious interpretation, as self-reported measures may not capture intermittent non-adherence or subtle behavioural patterns. Beyond ART adherence, the CAD model exhibited a protective effect on mental health; while mental health improved in the CAD group, it declined in the MMD arm. Adjusted models indicated that CAD participants had 54% higher odds of maintaining no depressive symptoms, with a significant difference-in-difference improvement of 6.8%. Notably, despite exhibiting poorer baseline mental health, the disparity in outcomes between the CAD and MMD groups narrowed by the endline, suggesting that the CAD model may help mitigate mental health inequities 21 . Physical health outcomes also favoured the CAD model, showing clinically meaningful gains (difference-in-difference: +11.6%, 95% CI 9.75–13.36). However, the impact of the CAD model on mental health-related quality of life remained inconclusive. The CAD model showed promise in reducing externalised stigma, with non-stigma experiences improving in the CAD group but declining in the MMD group. However, internalised stigma increased in both groups, and adjusted models did not confirm the CAD model’s superiority. While all stigma-related outcomes met non-inferiority thresholds, these results align with evidence that CAD models alone cannot address deeply internalised stigma without structural interventions 22 . Integrating peer-led education, community engagement, and policy reforms—guided by frameworks like the Modified Socio-Ecological Model (MSEM)—could enhance the CAD model’s stigma-mitigation potential 23 . Sensitivity analyses confirmed the robustness of the CAD model’s benefits across various missing data assumptions. Under missing-at-random assumptions, the CAD model improved ART adherence by 6.6% (95% CI 5.22–7.81), achieved a 6.94 percentage-point advantage in maintaining no depressive symptoms (95% CI 5.54–8.50), and enhanced physical health by 11.9% (95% CI 10.55–13.25). Adjusting for differential loss to follow-up had minimal impact on these estimates. Under the missing-not-at-random assumption, the benefits of the CAD model persisted or strengthened, further evidencing its resilience to attrition biases. Our study has several strengths, making it particularly significant. This is the first study of its kind in Cambodia and the region, providing critical insights into community-based interventions for stable people living with HIV. With a robust sample size of approximately 2,000 participants in each arm, the study boasts statistical solid power and validity. By encompassing 20 ART clinics across both rural and urban areas, it captures a diverse and representative cross-section of Cambodia’s people living with HIV population, rendering the results highly relevant for shaping national health policy and informing improvements in HIV care delivery. However, it is important to acknowledge several limitations of our study. Though intentional for relevance in Cambodia and similar settings, the purposive selection of ART clinics limits the generalisability of findings to regions with divergent healthcare systems. For example, countries with advanced digital health infrastructures or decentralised HIV care models may exhibit different care retention patterns. Additionally, the definition of retention in care was based solely on whether participants were still receiving HIV care and treatment at the 18-month follow-up, as determined by their clinical records from the routine check-up visits. This definition may overestimate care retention rates compared to those requiring continuous engagement, such as having at least two medical visits at least 90 days apart within the measurement year 24 . The binary metric used for retention in care does not account for transient interruptions in care, which may mask fluctuations in adherence that could be valuable for designing more nuanced interventions. Viral load tests were conducted at participants’ routine clinic visits every six months rather than at standardised study time points determined by the study protocol. While this reflects real-world programmatic data, it limits our ability to attribute suppression directly to the intervention or assess temporal trends. While self-reported ART adherence is widely used in HIV research, it is subject to social desirability and recall biases, which may overestimate actual adherence. Standardised scripts and neutral phrasing were employed during data collection to mitigate interviewer bias. Pill counts or objective measures (e.g., electronic monitoring) were not feasible due to logistical challenges––participants’ pill quantities varied widely depending on their last collection date, and the lack of consistent pill-count data precluded its use as a reliable metric. However, the observed high viral suppression rate (> 99%) is consistent with the self-reported high adherence, providing a validation that the reported adherence levels are sufficient for achieving viral suppression. The COVID-19 pandemic profoundly altered the study’s execution and outcomes. Originally designed as a 24-month quasi-experiment, the intervention was truncated to 18 months due to pandemic-related restrictions. This truncation limited our ability to assess long-term care retention trends. It precluded a planned midline survey, weakening validation of the parallel trend assumption required for robust difference-in-difference analyses. Both study arms experienced declines in ART adherence, mental health outcomes, and non-stigmatising care experiences, likely reflecting systemic pandemic effects such as healthcare access barriers, delayed medication distribution, and reduced in-person services. The CAD model’s adaptation—shifting from group-based activities to individualised delivery and telehealth at times—may have diluted its intended impact. While both CAD and MMD groups faced comparable disruptions (e.g., migration-related delays), the pandemic’s pervasive effects likely obscured differences between arms, reducing observed effect sizes. For instance, reliance on telehealth and fragmented support systems created similar challenges across groups, making it difficult to isolate the intervention’s efficacy under non-pandemic conditions. The absence of midline data and the shortened timeline limit causal interpretations. Had the 24-month endpoint been feasible, dropout patterns might have revealed diverging trends between arms, particularly given the evidence that retention often declines with prolonged follow-ups 24 . Furthermore, while prior studies report mixed pandemic impacts on HIV care (e.g., stable viral suppression despite reduced testing), our findings align with broader evidence of pandemic-driven service disruptions and mental health declines 25 , underscoring the need for context-specific resilience strategies. Despite the limitations, this study demonstrates that the CAD model is a promising strategy for improving ART adherence, mental health, and physical health outcomes among stable people living with HIV in Cambodia. With a 5.5% advantage in ART adherence and an 11.6% improvement in physical health compared to MMD, the CAD model’s benefits align with global evidence on the value of community-based HIV programmes in optimising care resilience. High retention rates in HIV care (98.2%) and viral suppression rates (> 99%) in both arms confirm the robustness of Cambodia’s HIV care system. Moreover, the CAD model's superior capacity to maintain ART adherence, promote mental health, and reduce externalised stigma positions it as a holistic, patient-centred alternative to clinic-based MMD. For policymakers, scaling up the CAD model in Cambodia and similar settings is warranted, particularly given its adaptability to telehealth and the minimal implementation barriers presented during the COVID-19 pandemic. However, to maximise impact, scale-ups should incorporate targeted stigma-reduction interventions and mental health support to address persistent internalised stigma and gaps in mental health quality of life. Future research should prioritise several key directions to address this study's limitations and refine CAD model's implementation. First, extending the follow-up period under non-pandemic conditions would clarify the CAD model's long-term effectiveness and capture potential retention declines over time, using continuous retention metrics (e.g., treatment gaps or visit frequency) aligned with established guidelines 27 . Second, mixed-methods approaches integrating qualitative evaluations are needed to explore contextual barriers—such as migration patterns, telehealth accessibility, and stigma—that influence HIV care delivery in resource-limited settings. Concurrently, health system assessments should evaluate the model’s scalability, including its impact on healthcare worker workload and cost-effectiveness. A formal cost-effectiveness analysis, as outlined in the original protocol, is underway and will inform scalability. Furthermore, adapting the CAD model to include targeted mental health and stigma-reduction components could enhance its holistic impact. At the same time, replication studies in diverse healthcare contexts (e.g., decentralised vs. centralised systems) would validate its generalisability. Finally, findings from these efforts should guide evidence-based guidelines for community-based HIV care, ensuring alignment with pandemic-resilient strategies and global best practices 28 . Methods Study design This quasi-experimental study was conducted between November 2021 and April 2023 in 10 provinces with high HIV burden. Within these provinces, 10 ART clinics were purposefully selected to implement CAD intervention. The selection was based on their similarity to 10 MMD control sites regarding key characteristics to ensure comparability between the two groups, reflecting real-world implementation challenges. The site selection process was conducted in consultation with the Database Management officers of NCHADS and other stakeholders involved in HIV programmes. The CAD intervention arm comprised six clinics in urban areas and four in rural areas across Phnom Penh, Kampong Thom, Kampot, Koh Kong, and Takeo. The MMD arm included seven urban and three rural clinics in Phnom Penh, Kampong Cham, Pailin, Preah Sihanouk, Siem Reap, and Prey Veng. The study protocol details have been published elsewhere 16 . In the CAD arm, 82 CAWs were recruited and trained to collect pre-packaged ARVs from ART clinics and distribute them to community ART groups, each consisting of 20 to 30 members, during monthly meetings. The training provided by ART clinics and implementing partners covered topics such as ART dispensing, drug storage, vital sign assessment and documentation, HIV education, ART adherence measurement, referral systems, and essential issues, including mental health, stigma, discrimination, as well as sexual and reproductive health and rights. In the MMD arm, participants collected and refilled their ARV prescriptions at the ART clinics every three to six months. People living with HIV in both arms visited ART clinics as needed for consultations and routine clinical check-ups every six months. Clinical management was carried out by trained personnel at ART clinics, following national guidelines. Community engagement and co-production The CAD model was developed and implemented with the active involvement of people living with HIV who served as CAWs, drawing on their lived experiences to ensure the intervention’s relevance and effectiveness. CAWs played a vital role in site selection, intervention design, and implementation through a stakeholder participatory approach, ensuring that the model addressed community needs and aligned with national priorities. Furthermore, CAWs directly applied their personal experiences to enhance the delivery of the intervention. This involvement of individuals with lived experiences was crucial in fostering trust, reducing stigma, and tailoring the intervention to the realities faced by people living with HIV in Cambodia. Please refer to the Inclusion and Ethics Statement for additional details on collaboration, stakeholder engagement, and capacity-building efforts. Participants People living with HIV were considered eligible for inclusion based on the following criteria: (1) aged 15 or older, (2) on first-line ART for at least one year, (3) not reporting ART-related adverse reactions or drug interactions requiring regular monitoring, (4) free from tuberculosis and other opportunistic infections at the time of baseline assessment, (5) not receiving prophylactic treatment, (6) having at least two consecutive undetectable viral loads or CD4 counts above 200 cells/mm³, and (7) assessed by their healthcare providers as having a solid understanding of lifelong treatment and medication adherence. Exclusion criteria included pregnant or breastfeeding women. Data collection procedures Quantitative data were collected by trained data collectors at baseline in October 2021, before the CAD intervention was introduced in November, and at the endline in April 2023, following the completion of the 18-month intervention. The questionnaire included sociodemographic and self-reported medical history, including comorbidities. Sex and gender data were self-reported and included options for male, female, and LGBTQ + identities. Viral loads and CD4 counts were captured from clinics’ medical records. Outcome variables The primary outcomes assessed included (i) retention in HIV care, (ii) viral load suppression, and (iii) ART adherence. Retention in HIV care was defined as whether people living with HIV documented in clinical records as actively receiving ART at the 18-month follow-up. Viral load suppression was defined as achieving a viral load of fewer than 1,000 ribonucleic acid (RNA) copies/mL in a most recent measurement during the study period, based on clinical records. ART adherence was defined as a binary outcome based on self-reported responses to five questions assessing medication practices over the prior two months––missed any ARV doses in the past two months, had trouble remembering to take ARVs, stopped taking ARVs when feeling better, missed any doses in the past four days, and stopped taking ARVs when feeling worse. Participants were classified as adherent only if they answered “no” to all five questions, prioritising specificity over sensitivity. This method reduced the risk of misclassifying non-adherent individuals as adherent. While pill counts or pharmacy refill data were considered, they were deemed unreliable due to inconsistencies in participants’ pill quantities during surveys (e.g., some had recently collected ARVs, while others were due for refills). Secondary outcomes included (i) HIV-related stigma and discrimination, (ii) mental health, and (iii) quality of life. Stigma and discrimination were assessed in three dimensions, which included experienced stigma, internal stigma, and fear of stigma, using the People Living with HIV Stigma Index, which had been validated for people living with HIV in Cambodia 29 , 30 Experienced stigma was defined as any exclusion, harassment, or adverse events across social, familial, or institutional settings, with a composite score of less than three indicating the absence of experienced stigma. Internal stigma reflected negative self-perceptions, with a score of less than five indicating low internal stigma. Fear of stigma captured concerns about rejection or discrimination, with a score of less than two indicating no fear of stigma. Composite scores were generated by summing binary variables. Mental health was assessed using the 10-item Centre for Epidemiology Studies Depression Scale (CES-D-10), with scores below 10 indicating no depressive symptoms 31 . Quality of life was measured using the Short-Form-12 (SF-12) survey, which included 12 items across eight health domains––physical function, social function, role limitations due to physical health, role limitations due to emotional problems, mental health, vitality, bodily pain, and general health 32 , 33 A Physical Component Score (PCS) of 50 or higher indicated good physical health, and a Mental Component Score (MCS) of 42 or higher indicated good mental health. The CES-D scale and the SF-12 have been widely used in various Asian populations, including Cambodia, India, Japan, and Singapore 34 – 37 . Statistical analyses Complete case analyses were done for participants who were retained in HIV care and completed baseline and endline surveys. Descriptive analyses summarised the sociodemographic characteristics of participants. The Pearson’s Chi-square test assessed differences between ordinal data, while the Student’s t -test was used for continuous variables when the normality assumption was met; otherwise, the Mann-Whitney U-test was applied. Variables were categorised pragmatically to account for low cell counts. The effects of the intervention on various treatment outcomes were assessed using logistic regression models with robust standard errors to account for potential heteroskedasticity. A comprehensive covariate selection process was employed to identify and adjust for confounders, ensuring the precision and reliability of the estimated treatment effects. This process included four steps: assessing confounding effects, constructing the adjusted model, performing backward selection using the Bayesian information criterion, and validating the final models through bootstrapping. Each candidate covariate was evaluated for its potential confounding effect on the relationship between treatment and outcome using the change-in-estimate criterion. This involved fitting a crude model, including only the primary predictors (timeline, treat, and their interaction term), and an adjusted model incorporating the covariate. The coefficient for treatment was compared between the two models, and the percentage change was calculated as follows: $$\:Percentage\:Change=\left|\frac{{\beta\:}_{crude}-{\beta\:}_{adjusted}}{{\beta\:}_{crude}}\right|*100$$ A covariate was considered a potential confounder if its inclusion caused a more than 10% change in the treatment coefficient. This threshold was applied to both baseline and endline assessments. At baseline, the change in treatment was examined, while at endline, the combined effect of treatment and the interaction term was analysed. Covariates meeting this threshold were included in subsequent models to prevent biased treatment effect estimation. Once potential confounders were identified, an adjusted logistic regression model was created. This model included all significant confounders identified in the previous step and essential demographic variables—age and gender—regardless of their impact on the treatment effect. The inclusion of age and gender was necessary due to their fundamental roles in influencing health outcomes and their ability to enhance model interpretability and generalisability. This step ensured that the treatment effect estimates were not biased by omitted variable confounding, providing a more accurate representation of the intervention’s impact. To refine the model further and achieve parsimony, backward selection using the Bayesian information criterion was performed. The Bayesian information criterion prioritises simpler models while ensuring adequate fit to the data. The procedure began with the fully adjusted model and iteratively removed covariates based on their statistical significance. Covariates with the highest P -values not part of the primary treatment effect were excluded first. For categorical covariates, the overall significance was assessed using the Wald test. A covariate was retained if its P -value was below 0.05 or if its removal caused a change of more than 10% in the treatment effect, indicating its potential role as a confounder. The process continued until only statistically significant or theoretically justified covariates remained, ensuring the model was robust and parsimonious. Once the final covariates were selected, the logistic regression models were specified for each treatment outcome. Predicted probabilities were computed using the margins command to estimate the difference-in-difference effect. To enhance the robustness of these estimates, bootstrapping with 500 replications was employed. Bootstrapping involved repeatedly resampling from the dataset, fitting the logistic regression model each time, and calculating the difference-in-difference estimate for each sample. The distribution of these estimates provided CIs, which were used to assess the non-inferiority and superiority of the intervention, ensuring the observed treatment effects were not driven by sample variability. A pre-specified non-inferiority margin of -10% was applied to assess whether the CAD model was not unacceptably worse than MMD. This margin was selected based on clinical relevance, prior evidence from HIV care studies, and assumptions outlined in the study protocol 16 , 38 . Non-inferiority was concluded if the lower bound of the 95% CI exceeded − 10%, indicating the CAD model was not meaningfully worse than MMD. Superiority was established if the lower bound exceeded 0%, demonstrating a statistically significant benefit of CAD. To rigorously address missing data due to loss to follow-up, a difference-in-difference framework was implemented within a multiple imputation approach using the Multivariate Imputation by Chained Equations (MICE) method. The primary analysis assumed data were missing at random, where missing treatment outcomes were imputed via logistic regression imputation, incorporating outcome-specific covariates. To ensure robustness, 10 imputed datasets were generated. Three sensitivity analyses were conducted to evaluate the potential impact of different missing data mechanisms: (1) Scenario 1 (missing at random, primary analysis), where missing outcomes were imputed based on observed covariates without altering baseline characteristics 39 (2) Scenario 2 (differential missingness in covariates), where the baseline characteristics of 50% of the loss to follow-up individuals were systematically modified before outcome imputation to account for potential differential attrition, adjusting covariates plausibly affected by the intervention; and (3) Scenario 3 (missing-not-at-random adjustment), where missing outcomes were first imputed under missing-at-random assumption and subsequently adjusted to account for unobserved confounding by reducing the predicted probabilities of loss to follow-up individuals by 5%, followed by restimulating their outcomes using a Bernoulli distribution, thereby modelling a scenario in which loss to follow-up individuals systematically exhibited lower probabilities in outcomes. In each scenario, the difference-in-difference estimate was derived from a logistic regression model incorporating an interaction term between treatment and timeline, with final estimates pooled using Rubin’s rules. Nonparametric bootstrapping (500 replications) was applied to quantify uncertainty, computing 95% CIs using the percentile method. Data analyses were conducted using STATA 18 software 40 and R Studio (version 2024.04.1 + 748), using the MICE and boot package 41 . Safety and adverse events An independent Data and Safety Monitoring Board periodically reviewed the study’s progress and safety in consultation with the CAD Project Steering Committee. Interim analyses were conducted to assess potential benefits and harms related to the study’s outcomes. Any adverse events were immediately reported to the study principal investigators, site co-principal investigators, and the National Centre for HIV/AIDS, Dermatology, and STD (NCHADS). The CAD Project Steering Committee held ad-hoc meetings to review and address these events when necessary. Study registration and protocol deviations The quasi-experimental study was registered with ClinicalTrials.gov (NCT04766710) on 23 February 2021, and the first participant was enrolled on 1 April 2021. The ClinicalTrials.gov registration record was prepared before enrolling participants in compliance with the National Institutes of Health (NIH) policy on clinical trial registration. While the study was registered for transparency, it is not a randomized controlled trial in the traditional sense—the registration aimed to ensure adherence to ethical standards and transparency in reporting. The study faced significant protocol deviations due to the COVID-19 pandemic. Initially planned for 24 months, the CAD intervention was shortened to 18 months because of project start-up delays and social restrictions that disrupted the implementation. These unforeseen challenges affected the study timeline, resource availability, and operational capacity, preventing the completion of key assessments. As a result, the midterm quantitative survey and endline qualitative process evaluation could not be conducted, limiting the depth of insights into participant experiences and intervention effectiveness. While adaptations were made, these deviations must be considered when interpreting the study’s findings and conclusions. Inclusion and ethics statement The CAD project is a collaboration between the National University of Singapore (NUS), Khmer HIV/AIDS NGO Alliance (KHANA), and NCHADS, building on over a decade of partnership. KHANA, a key player in Cambodia’s HIV response since 1996, and NCHADS, which leads the national HIV programme, developed a Standard Operating Procedure (SOP) for CAD, endorsed by the Ministry of Health. The project was designed using a stakeholder participatory approach and involved HIV communities, key populations, NGOs, government agencies, and development partners in site selection, intervention design, and implementation. KHANA, NCHADS, and three community-based HIV NGOs, along with representatives of people living with HIV, led the intervention’s development, guided by formative studies and national HIV programme evaluations. Regular stakeholder workshops, community advisory board meetings, and consultations with the National HIV Technical Working Group ensured the intervention was relevant, sustainable, and aligned with national priorities. Clear roles and responsibilities were established before the study, with the study principal investigator (PI) and local PIs serving as co-leaders in all decisions. The project also prioritised capacity building, providing staff training, continuing education, and advanced scholarly training to strengthen local expertise and ensure the long-term sustainability of the CAD model within Cambodia’s HIV response framework. Ethical approval for this study was granted by the National Ethics Committee for Health Research (Ref. 258/NECHR) of the Ministry of Health, Cambodia. All participants, including people living with HIV, community action workers, and healthcare workers, provided written informed consent before data collection. Privacy and confidentiality were strictly upheld, with all personal identifiers removed to ensure anonymity. Participants were offered support resources to mitigate potential risks, such as psychological distress from sensitive questions, and participation remained entirely voluntary. The study's potential benefits, including improvements in HIV care, outweighed any risks, and participants were fully informed of these as part of the consent process. Declarations Role of the funding source L' Initiative through Expertise France funded the study. The funder had no roles in the study design, data collection, statistical analyses, finding interpretation, or report writing. Contributors ZT developed the data analysis plan, conducted data analyses, and wrote the initial draft. PC and ST contributed to the study design, supervised project implementation, led data collection efforts, and provided feedback on the draft. ELYY, MN-H, and MZ supported the data analyses and offered input on the draft. SS, BN, and VO provided strategic advice on intervention development, implementation, and evaluation and reviewed the manuscript. AKJT and KP played critical roles in study design, contributed to the data analysis plan, and provided feedback on the draft. SY secured funding, led the study design, and oversaw project implementation, data collection, analyses, and manuscript writing. All authors reviewed and approved the final manuscript and held ultimate responsibility for the decision to publish. Declaration of interests We declare no competing interests. Data availability Data access for the CAD study, which is restricted to non-identifying data underlying the results reported in this article, can be requested from the corresponding author via email at [email protected] . The study protocol, statistical analysis plan, analytic code, consent forms, and clinical report forms will also be available. Data will be accessible immediately following publication with no end date. Access will be granted to investigators whose analyses comply with the restrictions outlined in the study consent forms and whose proposed use of the data has been approved by the appropriate ethical review board. Code availability The underlying code for the results detailed in this article can be requested from the corresponding author. The author will handle all requests for scientific purposes and share the code if the request is deemed scientifically appropriate. Acknowledgements Research reported here was supported by the National Centre for HIV/AIDS, Dermatology, and STD, Khmer HIV/AIDS NGO Alliance, Cambodian People Living with HIV Network, ARV Users Association, Partners in Compassion, and participating ART clinics. We thank community action workers and their community members for supporting this study. References National Center for HIV/AIDS, D.a.S. Strategic Plan for HIV/ AIDS and STI Prevention and Control in the Health Sector 2016–2020. (2016). Authority, N.A. The Fifth National Strategic Plan for a Comprehensive, Multi-Sectoral Response to HIV/AIDS (2019–2023).. (2019). Global AIDS Monitoring. (2022). National Center for HIV/AIDS, D.a.S. 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Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryTableS1Outcome.docx CONSORTChecklist.doc Cite Share Download PDF Status: Published Journal Publication published 25 Nov, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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Singapore","correspondingAuthor":false,"prefix":"","firstName":"Esabelle","middleName":"","lastName":"Yam","suffix":""},{"id":434779551,"identity":"8c2a3729-51db-486d-bd43-c22c41e8c183","order_by":5,"name":"Michiko Michiko Nagashima-Hayashi","email":"","orcid":"","institution":"[email protected]","correspondingAuthor":false,"prefix":"","firstName":"Michiko","middleName":"Michiko","lastName":"Nagashima-Hayashi","suffix":""},{"id":434779552,"identity":"be4b6205-94c8-4b38-98a1-dbdb01fd4148","order_by":6,"name":"Marina Zahari","email":"","orcid":"","institution":"Saw Swee Hock School of Public Health, National University of Singapore and National University Health System","correspondingAuthor":false,"prefix":"","firstName":"Marina","middleName":"","lastName":"Zahari","suffix":""},{"id":434779553,"identity":"e66b2236-6b77-4291-857e-54bef7fcd6b4","order_by":7,"name":"Sok Chamreun Choub","email":"","orcid":"","institution":"KHANA Centre for Population Health Research","correspondingAuthor":false,"prefix":"","firstName":"Sok","middleName":"Chamreun","lastName":"Choub","suffix":""},{"id":434779554,"identity":"06546bc1-d5fc-4440-854d-59ea8a7dca6d","order_by":8,"name":"Sovannarith Sameth","email":"","orcid":"","institution":"National Centre for HIV/AIDS, Dermatology, and STD","correspondingAuthor":false,"prefix":"","firstName":"Sovannarith","middleName":"","lastName":"Sameth","suffix":""},{"id":434779555,"identity":"56c291ec-4d76-4507-a1a7-6bea7ae6fa2c","order_by":9,"name":"Bora Ngauv","email":"","orcid":"","institution":"National Centre for HIV/AIDS, Dermatology, and STD","correspondingAuthor":false,"prefix":"","firstName":"Bora","middleName":"","lastName":"Ngauv","suffix":""},{"id":434779556,"identity":"08da84aa-7a7f-45e2-9af4-9b312e3f2b66","order_by":10,"name":"Vichea Ouk","email":"","orcid":"","institution":"National Centre for HIV/AIDS, Dermatology, and STD","correspondingAuthor":false,"prefix":"","firstName":"Vichea","middleName":"","lastName":"Ouk","suffix":""},{"id":434779557,"identity":"c190ad45-5ecb-4c99-a07b-b6b9dd667113","order_by":11,"name":"Alvin Teo","email":"","orcid":"","institution":"University of Sydney","correspondingAuthor":false,"prefix":"","firstName":"Alvin","middleName":"","lastName":"Teo","suffix":""},{"id":434779558,"identity":"990be6cf-3945-48ae-89fa-ce4fa5271403","order_by":12,"name":"Kiesha Prem","email":"","orcid":"","institution":"National University of Singapore","correspondingAuthor":false,"prefix":"","firstName":"Kiesha","middleName":"","lastName":"Prem","suffix":""}],"badges":[],"createdAt":"2025-03-26 08:05:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6310016/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6310016/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41467-025-66606-x","type":"published","date":"2025-11-25T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79580703,"identity":"52ed193d-93d6-487a-9c0b-fb51bd980cda","added_by":"auto","created_at":"2025-03-31 11:49:30","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":44078,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlowchart of participants from 20 ART clinics across Cambodia\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAbbreviations:\u003cstrong\u003e \u003c/strong\u003eCAD, community-based antiretroviral therapy delivery; MMD, multi-month dispensing.\u003c/p\u003e","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6310016/v1/e3c85bbfe5a4097695b45c19.png"},{"id":99211909,"identity":"b0b2a3bd-2265-41a0-a39d-8fc8c3505972","added_by":"auto","created_at":"2025-12-30 08:19:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1663544,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6310016/v1/e43ab3e8-6ced-48b5-a986-6f87b4a2f17a.pdf"},{"id":79579531,"identity":"bac766c9-f7a5-4891-975b-4ab3cb62b357","added_by":"auto","created_at":"2025-03-31 11:41:30","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16195,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableS1Outcome.docx","url":"https://assets-eu.researchsquare.com/files/rs-6310016/v1/63f1ef75163478ae158f6335.docx"},{"id":79581640,"identity":"8fcae7d8-769f-4dfe-aa38-6c6094c5c92d","added_by":"auto","created_at":"2025-03-31 11:57:31","extension":"doc","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":223232,"visible":true,"origin":"","legend":"","description":"","filename":"CONSORTChecklist.doc","url":"https://assets-eu.researchsquare.com/files/rs-6310016/v1/9a14c8ac97f0b7884dad8fb5.doc"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Impact of a community-based antiretroviral therapy delivery model on treatment outcomes, mental health, and quality of life among stable people living with HIV in Cambodia: a quasi-experimental study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCambodia has made significant strides in addressing the HIV epidemic. The prevalence of HIV among adults aged 15 to 49 years decreased from 1.7% in 1998 to 0.5% in 2023. It was also one of three Asia-Pacific countries to meet the UNAIDS 90-90-90 targets in 2017\u003csup\u003e1,2\u003c/sup\u003e. As of 2023, 89% of an estimated 76,000 people living with HIV have been diagnosed, 89% are receiving sustained antiretroviral therapy (ART), and 87% have achieved viral suppression\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Nonetheless, further progress is necessary to meet the UNAIDS 95-95-95 targets and eventually eliminate HIV in Cambodia.\u003c/p\u003e \u003cp\u003eHIV services are provided through 74 ART clinics managed by government and non-governmental organisations (NGOs) across 25 provinces\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. These clinics face significant challenges, including congestion and shortages of human resources, which impede high-quality care, especially for unstable individuals who require frequent follow-ups. People living with HIV also experience substantial psychological challenges, including stigma, which is closely associated with poorer mental health outcomes\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e and can negatively affect ART adherence and retention in care\u003csup\u003e\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Additionally, certain sub-populations, particularly those with vulnerable socioeconomic or clinical statuses and inadequate social support, are at risk of being lost to follow-up in ART\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Additionally, vulnerable populations with insufficient social support are at risk of losing follow-up care in ART programmes. Other concerns include missed appointments and improper storage of antiretrovirals (ARVs) after dispensing\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSince 2015, the World Health Organization (WHO) has advocated for a client-centred approach using differentiated service delivery (DSD) models tailored to the needs of people living with HIV while lessening the burden on health systems\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. DSD models, such as community-based ART distributions, as seen in Mozambique and Lesotho, have shown promising results in improving ART adherence, alleviating clinic congestion, and enhancing mental health for people living with HIV\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn Cambodia, where community-based services are integral to the national HIV response, the National Centre for HIV/AIDS, Dermatology, and STD (NCHADS) implemented the multi-month dispensing (MMD) model in 2017. This model allows clinically stable individuals to visit ART clinics every three to six months, thereby reducing travel burdens\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Building on this, a quasi-experimental study introduced a Community-based ART Delivery (CAD) model, further decentralising care by integrating ARV distributions within peer-led community networks\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe CAD model represents an innovative approach to HIV care by leveraging the lived experiences of people living with HIV. Unlike traditional community-based models that rely on trained community health workers (CHWs) without HIV experience, the model empowers people living with HIV to serve as Community Action Workers (CAWs). These CAWs collect pre-packaged ARVs from ART clinics and distribute them during monthly group sessions while also providing health education, monitoring vital signs, and offering peer social support. This peer-led structure fosters a supportive environment that tackles stigma and enhances mental health outcomes through shared experiences, distinguishing the CAD model from other interventions. For instance, while models in Uganda and Zimbabwe prioritise logistical efficiency through CHWs\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, the CAD model integrates psychosocial support as a core component, aligning with the WHO\u0026rsquo;s emphasis on holistic, person-centred care.\u003c/p\u003e \u003cp\u003eThis quasi-experimental study aims to assess its effectiveness compared to MMD in improving the health and well-being of stable people living with HIV. By positioning people living with HIV as active agents in care delivery, CAD addresses systemic gaps like clinic congestion and mental health disparities while aligning with Cambodia\u0026rsquo;s broader goals of sustainable, community-driven HIV management. This study will provide essential evidence for the potential scale-up and integration of the CAD model into national HIV programmes.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipant characteristics\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, 4,089 people living with HIV were enrolled in the study and completed a baseline survey, with 2,040 (49.9%) in the CAD and 2,049 (50.1%) in the MMD group. By the endline, 3,977 participants (97.3%) were retained in HIV care, and 3,067 (77.1%) completed endline survey. Of those, 1,626 (79.7%) in CAD and 1,441 (70.3%) in MMD completed endline survey. Among 85 participants who did not remain in HIV care, 36 (42.4%) were from CAD, and 49 (57.6%) were from MMD due to death, loss, or transfer. Of those who retained in care but did not complete endline survey (22.9%), a higher percentage of participants were from MMD (61.6%) compared to CAD (35.2%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows that a higher proportion of participants in MMD (75.5%) than the CAD (61.0%) group were recruited from urban areas. Most participants were aged 15\u0026ndash;49, predominantly female, married, and had a primary school education. Many were farmers or fishermen, self-employed, or unemployed. MMD participants were nearly four times more likely than CAD participants to identify as lesbian, gay, bisexual, transgender, or queer (LGBTQ+) (4.7% vs. 1.2%). Most had small families, and the median monthly household income was higher in the MMD than in the CAD group (USD 216 vs. USD 192). A more significant proportion of CAD participants (25.9%) reported at least one comorbidity compared to MMD group (17.9%). A significantly higher proportion of MMD participants were newly diagnosed with HIV (1\u0026ndash;5 years) and newly on ART (0\u0026ndash;5 years) compared to the CAD group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Conversely, a higher proportion of CAD participants had lived with HIV and received ART for 11 years or longer. However, most participants in both groups had lived with HIV and received ART for 11\u0026ndash;20 years. Approximately half of the participants in both groups travelled less than 30 minutes to ART clinics, and the mean waiting time at the clinics was slightly higher among CAD participants (2.2 hours) than among the MMD group (1.6 hours).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of sociodemographic, clinical characteristics, care retention, and viral suppression in CAD and MMD arms\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCAD (N\u0026thinsp;=\u0026thinsp;1,626)\u003c/p\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMMD (N\u0026thinsp;=\u0026thinsp;1,441)\u003c/p\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eStudy setting\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e992 (61.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1088 (75.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e634 (39.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e353 (24.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdults (15\u0026ndash;49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e992 (56.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e842 (58.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOlder adults (50+)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e704 (43.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e599 (41.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e603 (37.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e548 (38.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1004 (61.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e826 (57.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLGBTQ\u0026thinsp;+\u0026thinsp;\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e984 (60.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e850 (59.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e422 (26.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e348 (24.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever married or divorced, or others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e220 (13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e243 (16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFormal education (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo, or unknown formal education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e295 (18.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e230 (16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary school (1\u0026ndash;6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e831 (51.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e679 (47.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary school (7\u0026ndash;9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e329 (20.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e311 (21.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTertiary or university (10 +)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e171 (10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e221 (15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOccupation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e307 (18.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e267 (18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFarmer, or fisherman\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e471 (29.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e352 (24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-employed business\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e279 (17.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e298 (20.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruction, or factory workers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e240 (14.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e191 (13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther (taxi driver, government staff or NGO staff, uniformed officer\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, or private employee)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e329 (20.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e333 (23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily size (number of family members)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmall family (1\u0026ndash;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1021 (70.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1230 (75.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium to large family (5+)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e396 (24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e420 (29.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of children under 15 years old\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e682 (41.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e601 (41.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOne child\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e538 (33.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e463 (32.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTwo or more children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e406 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e377 (26.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMonthly household income (USD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (interquartile range)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e192 (237.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e216 (240)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePresence of comorbidity diagnosed\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHaving at least one co-morbidity\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e421 (25.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e258 (17.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDuration of living with HIV (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNewly diagnosed (1\u0026ndash;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e143 (8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e258 (17.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium duration (6\u0026ndash;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e263 (16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e258 (17.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLong duration (11\u0026ndash;15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e541 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e389 (27.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery long duration (16+)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e679 (41.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e536 (37.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDuration of receiving ART (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNewly on ART (0\u0026ndash;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e189 (19.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e284 (19.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium duration (6\u0026ndash;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e320 (19.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e303 (21.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLong duration (11\u0026ndash;15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e604 (37.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e462 (32.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVery long duration (16+)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e513 (31.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e392 (27.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMode of transportation to ART clinic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTuk Tuk, motorcycle, or car\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1551 (95.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1331 (92.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOn foot or bicycle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69 (4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoat, ship, or others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTraveling time to ART sites (hours)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShort travel (\u0026lt;\u0026thinsp;0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e776 (47.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e621 (43.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium travel (0.5-2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e717 (44.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e702 (48.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLong travel (2+)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e133 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e118 (8.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e..\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWaiting time at ART site (hours)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.19\u0026thinsp;\u0026plusmn;\u0026thinsp;1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRetained in HIV care\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1984 (98.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1993 (97.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eViral load suppressed\u003c/b\u003e\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2024 (99.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2037 (99.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eAbbreviations: ART, antiretroviral therapy; CAD, community-based antiretroviral therapy delivery model; HIV, human immunodeficiency viruses; IQR, interquartile range; MMD, multi-month dispensing model; NGO, non-governmental organization; SD, standard deviation; USD, United States dollar.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e1\u003c/sup\u003eLGBTQ+ includes lesbians, gay men, bisexual individuals, transgender people, queers, intersex individuals, asexual individuals, and those who choose not to identify.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Uniformed officers include policemen, soldiers, and police military.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Co-morbidities include diabetes mellitus, high cholesterol, and hypertension.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e N\u0026thinsp;=\u0026thinsp;2,020 in CAD, N\u0026thinsp;=\u0026thinsp;2,042 in MMD. There were 20 missing values in CAD and 7 in MMD.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e N\u0026thinsp;=\u0026thinsp;2,040 in CAD, N\u0026thinsp;=\u0026thinsp;2,049 in MMD.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTreatment outcomes\u003c/h3\u003e\n\u003cp\u003eRetention in HIV care was high in both groups, with 98.2% in the CAD and 97.6% in the MMD group, showing no statistically significant difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.17). More than 99.0% of participants maintained suppressed viral loads, with minimal differences between the two arms (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe CAD group demonstrated non-inferiority and superiority over the MMD group across treatment outcomes, as evidenced by descriptive trends (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) and robust intervention effects (Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). At baseline, the CAD group had significantly lower self-reported ART adherence than the MMD group (87.0% vs. 90.3%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). By the endline, ART adherence declined modestly in both groups, but the CAD group maintained a superior trajectory (86.8% vs. 84.4% in MMD, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05). As shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the CAD group had 64% higher odds of ART adherence (adjusted odds ratio [AOR]\u0026thinsp;=\u0026thinsp;1.64, 95% confidence interval [CI] 1.21\u0026ndash;2.23, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002). Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e confirms a significant difference-in-difference advantage of 5.49% (95% CI 1.96\u0026ndash;9.01). These findings substantiate CAD\u0026rsquo;s non-inferiority and superiority in maintaining adherence, even with baseline differences between groups.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eART adherence, mental health, stigma and discrimination, and quality of life of participants at baseline and endline in CAD and MMD arms\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eEndline\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCAD\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1,626)\u003c/p\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMMD\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1,441)\u003c/p\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCAD\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1,626)\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMMD\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1,441)\u003c/p\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eART adherence\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-reported ART adhered\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1415 (87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1301 (90.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1412 (86.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1216 (84.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStigma (People Living with HIV Stigma Index)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-stigma experienced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1499 (92.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1362 (94.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1503 (92.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1315 (91.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow internal stigma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1122 (69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e914 (63.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1305 (80.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1053 (73.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot fear of stigma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1445 (88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1234 (85.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1475 (90.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1281 (88.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMental health status (CES-D)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo depression symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1263 (77.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1208 (83.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1182 (72.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1030 (71.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eQuality of life (SF-12)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood mental health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1241 (76.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1213 (84.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1261 (77.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1183 (82.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood physical health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e887 (54.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1004 (69.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e806 (49.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e745 (51.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAbbreviations: ART for Antiretroviral therapy; CAD, community-based antiretroviral therapy delivery; CES-D, Centre for Epidemiologic Study Depression Scale; MMD, multi-month dispensing; SF-12, 12-item Short Form survey.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIntervention effects of CAD among participants with completed baseline and endline surveys over time\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eIntervention effects\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eCrude model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eAdjusted model\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR [95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel fit (BIC)\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAOR [95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eModel fit (BIC)\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eART adherence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-reported adherence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.69 [1.25,2.29]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4723.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.64 [1.21, 2.23]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4677.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStigma (People Living with HIV Stigma Index)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo stigma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.71 [1.16,2.52]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3264.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.48 [0.99, 2.20]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3269.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow internal stigma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.17 [0.93,1.46]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7234.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.18 [0.94,1.48]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7235.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot Fear of stigma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.91 [0.66,1.25]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4366.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.88 [0.63, 1.21]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4354.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMental health status (CES-D)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo depressive symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.58 [1.24,2.02]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6666.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.54 [1.20, 1.97]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6521.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eQuality of life (SF-12)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood mental health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.24 [0.96,1.60]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6159.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.20 [0.92, 1.57]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6031.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood physical health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.76 [1.43,2.16]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8293.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.70 [1.37, 2.11]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8121.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAbbreviations: AOR, adjusted odds ratio; ART, antiretroviral therapy; BIC, Bayesian information criterion; CAD, community-based antiretroviral therapy delivery; CES-D, Center for Epidemiologic Study Depression Scale; CI, confidence interval; MMD, multi-month dispensing; OR, odds ratio; SF-12, 12-item Short Form survey.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e1\u003c/sup\u003eN=1626 in CAD arm; N\u0026thinsp;=\u0026thinsp;1441 in MMD arm.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e \u003csup\u003e \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e \u003c/sup\u003eOutcome-specific covariates used in the adjusted models for each treatment outcome are detailed in Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003eThe model fit had \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for all crude and adjusted models.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePredicted probabilities, difference-in-difference estimates of intervention effects on treatment outcomes over time\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCAD Intervention (N\u0026thinsp;=\u0026thinsp;1,626)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMMD Control (N\u0026thinsp;=\u0026thinsp;1,441)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDiD Estimate (%) [95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eConclusion\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEndline\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEndline\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP (%) [95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP (%) [95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP (%) [95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP (%) [95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eART adherence\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-reported ART adherence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86.83 [85.17, 88.49]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86.10 [84.38, 87.82]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90.69 [89.19, 92.18]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e84.92 [83.10, 86.73]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.03 [1.62, 8.45]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNon-inferior and superior\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eStigma (People Living with HIV Stigma Index)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo stigma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92.57 [91.31, 93.84]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91.99 [90.63, 93.36]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94.43 [93.23, 95.63]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e91.41 [89.99, 92.84]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.44 [-0.30, 5.18]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNon-inferior\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow internal stigma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68.86 [66.60, 71.11]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.97 [78.00, 81.94]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.98 [61.48, 66.49]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e73.12 [70.84, 75.41]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.98 [-2.44, 6.39]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNon-inferior\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot fear of stigma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89.07 [87.54, 90.60]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90.02 [88.50, 91.54]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86.38 [84.62, 88.13]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88.89 [87.27, 90.50]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.56 [-4.66, 1.55]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNon-inferior\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eMental health status (CES-D)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo depressive symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78.21 [76.24, 80.19]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.85 [70.73, 74.97]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83.38 [81.47, 85.29]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71.21 [68.88, 73.53]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.81 [2.71, 10.90]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNon-inferior and superior\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eQuality of life (SF-12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood mental health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76.55 [74.47, 78.64]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.76 [75.78, 79.75]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83.72 [81.82, 85.62]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82.15 [80.18, 84.12]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.77 [-1.10, 6.65]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNon-inferior\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood physical health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.50 [54.01, 58.98]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.72 [47.31, 52.12]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68.73 [66.34, 71.12]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.39 [47.75, 53.03]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.56 [6.62,16.50]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNon-inferior and superior\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAbbreviations: ART for antiretroviral therapy; CAD, community-based antiretroviral therapy delivery; CES-D, Centre for Epidemiologic Study Depression Scale; CI, confidence interval; DiD, difference-in-differences; MMD, multi-month dispensing; P, predicted probability; SF-12, 12-item Short Form survey.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003ePre-specified non-inferiority margin, risk difference= -10%\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eHIV stigma\u003c/h3\u003e\n\u003cp\u003eAt baseline, the MMD group reported a significantly higher rate of non-stigma experience (94.5% vs. 92.2% in CAD, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). By the endline, the CAD group showed a marginal improvement (92.4%), while the MMD group experienced a decline (91.3%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.23). Adjusted models (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) suggested a trend toward reduced stigma in the CAD group (AOR\u0026thinsp;=\u0026thinsp;1.48, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.06), although difference-in-difference estimates were inconclusive (2.4%, 95% CI \u0026minus;\u0026thinsp;0.30\u0026ndash;5.18; Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Internal stigma increased sharply in both groups (CAD: 69.0\u0026ndash;80.3%, MMD: 63.4\u0026ndash;73.1%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while no significant differences were observed for fear of stigma (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.10).\u003c/p\u003e\n\u003ch3\u003eDepressive symptoms\u003c/h3\u003e\n\u003cp\u003eBoth the CAD and MMD groups experienced a reduction in the proportion of participants reporting no depressive symptoms over time (CAD: 77.7\u0026ndash;72.7%; MMD: 83.8\u0026ndash;71.5%; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The decline was more pronounced in the MMD group; however, the between-group difference at the endline was not statistically significant (P\u0026thinsp;=\u0026thinsp;0.45). Adjusted models (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) indicated that CAD participants had 54% higher odds of maintaining no depressive symptoms than those in the MMD group (AOR\u0026thinsp;=\u0026thinsp;1.54, 95% CI 1.20\u0026ndash;1.97, P\u0026thinsp;=\u0026thinsp;0.001). This advantage was corroborated by a significant difference-in-difference estimate of 6.8% (95% CI 2.71\u0026ndash;10.90; Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), indicating a smaller decline in the proportion of participants without depressive symptoms in the CAD group relative to the MMD group.\u003c/p\u003e\n\u003ch3\u003eQuality of life\u003c/h3\u003e\n\u003cp\u003eRegarding quality of life, the MMD group reported better physical health (69.7% in MMD vs. 54.6% in CAD, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) at baseline. By the endline, both groups experienced a decline in good physical health (49.6% in the CAD group; 51.7% in the MMD group, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.24), but the CAD group demonstrated striking superiority in the difference-in-difference estimate for good physical health (11.6%, 95% CI 6.62\u0026ndash;16.50, Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), supported by robust intervention effects (AOR\u0026thinsp;=\u0026thinsp;1.70, 95% CI 1.37\u0026ndash;2.11, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Despite MMD group\u0026rsquo;s superior baseline mental health (84.2% vs. 76.3% in CAD, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), CAD narrowed this gap at endline (77.6% vs. 82.1%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002). No significant difference was observed regarding mental health (AOR\u0026thinsp;=\u0026thinsp;1.20, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.17, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAdjusted models consistently outperformed crude models, reflected in lower Bayesian Information Criterion values (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), reinforcing the validity of the estimates. All outcomes met pre-specified non-inferiority margins, with superiority established for ART adherence, mental health, and physical health, where 95% of CIs excluded null effects.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSensitivity analyses\u003c/h2\u003e \u003cp\u003eThe robustness of our findings was rigorously validated through sensitivity analyses that addressed potential biases from missing data (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). In all tested scenarios, CAD maintained non-inferiority and demonstrated superiority over MMD, with effect estimates remaining stable or strengthening under conservative assumptions. These findings reinforce the reliability of the primary results (Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) and highlight CAD's resilience to plausible missing data mechanisms.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSensitivity analysis on difference-in-difference estimates of intervention effects on treatment outcomes over time\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eScenario 1\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eScenario 2\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eScenario 3\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiD estimate (%) [95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDiD estimate (%) [95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDiD estimate (%) [95% CI]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eART Adherence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-Reported ART Adhered\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.55 [5.22, 7.81]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.40 [5.01, 7.79]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.14 [6.69, 9.63]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStigma (People Living with HIV Stigma Index)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Stigma Experienced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.92 [3.32, 6.57]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.56 [2.89, 6.13]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.33 [4.52, 8.05]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow Internal Stigma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.82 [-2.18, 0.38]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.97 [-2.39, 0.30]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.06 [-0.32, 2.33]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot Fear of Stigma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.75 [-2.03, 0.46]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.37 [-2.61, -0.01]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.57 [-0.66, 1.79]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMental Health Status (CES-D)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo Depression Symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.94 [5.54, 8.50]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.71 [5.22, 8.28]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.33 [6.85, 9.95]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eQuality of Life (SF-12)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood Mental Health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.47 [2.17, 4.86]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.92 [2.53, 5.21]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.47 [2.09, 4.82]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood Physical Health\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.87 [10.55, 13.25]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.64 [10.10, 13.10]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.93 [10.50, 13.30]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eAbbreviations: AOR, adjusted odds ratio; ART, antiretroviral therapy; BIC, Bayesian information criterion; CAD, community-based antiretroviral therapy delivery; CES-D, Centre for Epidemiologic Study Depression Scale; CI, confidence interval; MMD, multi-month dispensing; OR, odds ratio; SF-12, 12-item Short Form survey.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003eAssumptions: i) Missing at random ii) Baseline characteristics remained unchanged at endline.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003eAssumptions: i) Missing at random ii) Some baseline characteristics changed at endline for 50% of participants with incomplete endline surveys.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003eAssumptions: i) Missing not at random, where participants with incomplete endline surveys had worse outcomes (e.g., 5% lower probability of adherence) than observed data at endline. ii) Baseline characteristics remained unchanged at endline.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eUnder the missing-at-random assumption, CAD was associated with a 6.6% improvement in ART adherence (95% CI 5.22\u0026ndash;7.81). For mental health outcomes, CAD showed a 6.94 percentage-point advantage (95% CI 5.54\u0026ndash;8.50) in maintaining no depressive symptoms compared to MMD and clinically meaningful improvements in physical health (11.9%, 95% CI 10.55\u0026ndash;13.25). The consistency between imputed and complete-case estimates underscores the legitimacy of the missing-at-random assumption in this context.\u003c/p\u003e \u003cp\u003eThere was minimal impact on estimates when accounting for potential differential loss to follow-up by adjusting key sociodemographic variables by 50%. ART adherence remained robust at 6.4% (95% CI 5.01\u0026ndash;7.79), as did CAD's advantage in sustaining no depressive symptoms (6.7 percentage points, 95% CI 5.22\u0026ndash;8.28) and physical health gains (11.6%, 95% CI 10.10\u0026ndash;13.10). Notably, mental health-related quality of life scores increased slightly (3.9%, 95% CI 2.53\u0026ndash;5.21 vs. 3.5%, 95% CI 2.17\u0026ndash;4.86 in Scenario 1).\u003c/p\u003e \u003cp\u003eUnder a conservative missing-not-at-random assumption\u0026mdash;where the loss to follow-up systematically underperformed\u0026mdash;CAD's superiority persisted or even strengthened. ART adherence gains increased to 8.1% (95% CI 6.69\u0026ndash;9.63), while the advantage in maintaining no depressive symptoms rose to 8.3% (95% CI 6.85\u0026ndash;9.95), and physical health improvements remained stable at 11.9% (95% CI 10.50\u0026ndash;13.30). However, stigma-related outcomes exhibited differential patterns. Although CAD continued to improve non-stigma experiences (6.3%, 95% CI 4.52\u0026ndash;8.05, compared to 4.9%, 95% CI 3.32\u0026ndash;6.57 in Scenario 1), the lower bounds of the 95% CIs for internalised stigma (-0.32) and fear of stigma (-0.66) did not exclude 0, indicating non-inferiority but a lack of superiority in these areas.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur findings demonstrate the effectiveness of the CAD model in maintaining ART adherence, improving mental health, and enhancing physical health outcomes compared to MMD over the 18-month intervention period. Retention in HIV care was high in both groups, with 98.2% of CAD participants and 97.6% of MMD participants remaining by endline, indicating that the CAD model did not compromise care retention despite differences in service delivery models. Viral suppression rates exceeded 99% in both groups, with minimal differences favouring the CAD model, reinforcing the effectiveness of both models in sustaining virologic control.\u003c/p\u003e \u003cp\u003eSelf-reported ART adherence declined in both groups over time, though the decline was smaller in the CAD arm. Adjusted models confirmed the CAD model\u0026rsquo;s superior ART adherence outcomes, with CAD participants showing 64% higher adherence odds than MMD participants. These results align with other studies supporting CAD models in improving HIV care retention and ART adherence in resource-limited settings\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The smaller decline in self-reported adherence within the CAD group suggests that community-based care may buffer against contextual disruptions (e.g., migration, stigma) that disproportionately affect marginalised populations. However, the modest absolute difference in adherence (86.8% vs. 84.4%) underscores the need for cautious interpretation, as self-reported measures may not capture intermittent non-adherence or subtle behavioural patterns.\u003c/p\u003e \u003cp\u003eBeyond ART adherence, the CAD model exhibited a protective effect on mental health; while mental health improved in the CAD group, it declined in the MMD arm. Adjusted models indicated that CAD participants had 54% higher odds of maintaining no depressive symptoms, with a significant difference-in-difference improvement of 6.8%. Notably, despite exhibiting poorer baseline mental health, the disparity in outcomes between the CAD and MMD groups narrowed by the endline, suggesting that the CAD model may help mitigate mental health inequities\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Physical health outcomes also favoured the CAD model, showing clinically meaningful gains (difference-in-difference: +11.6%, 95% CI 9.75\u0026ndash;13.36). However, the impact of the CAD model on mental health-related quality of life remained inconclusive.\u003c/p\u003e \u003cp\u003eThe CAD model showed promise in reducing externalised stigma, with non-stigma experiences improving in the CAD group but declining in the MMD group. However, internalised stigma increased in both groups, and adjusted models did not confirm the CAD model\u0026rsquo;s superiority. While all stigma-related outcomes met non-inferiority thresholds, these results align with evidence that CAD models alone cannot address deeply internalised stigma without structural interventions\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Integrating peer-led education, community engagement, and policy reforms\u0026mdash;guided by frameworks like the Modified Socio-Ecological Model (MSEM)\u0026mdash;could enhance the CAD model\u0026rsquo;s stigma-mitigation potential\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSensitivity analyses confirmed the robustness of the CAD model\u0026rsquo;s benefits across various missing data assumptions. Under missing-at-random assumptions, the CAD model improved ART adherence by 6.6% (95% CI 5.22\u0026ndash;7.81), achieved a 6.94 percentage-point advantage in maintaining no depressive symptoms (95% CI 5.54\u0026ndash;8.50), and enhanced physical health by 11.9% (95% CI 10.55\u0026ndash;13.25). Adjusting for differential loss to follow-up had minimal impact on these estimates. Under the missing-not-at-random assumption, the benefits of the CAD model persisted or strengthened, further evidencing its resilience to attrition biases.\u003c/p\u003e \u003cp\u003eOur study has several strengths, making it particularly significant. This is the first study of its kind in Cambodia and the region, providing critical insights into community-based interventions for stable people living with HIV. With a robust sample size of approximately 2,000 participants in each arm, the study boasts statistical solid power and validity. By encompassing 20 ART clinics across both rural and urban areas, it captures a diverse and representative cross-section of Cambodia\u0026rsquo;s people living with HIV population, rendering the results highly relevant for shaping national health policy and informing improvements in HIV care delivery.\u003c/p\u003e \u003cp\u003eHowever, it is important to acknowledge several limitations of our study. Though intentional for relevance in Cambodia and similar settings, the purposive selection of ART clinics limits the generalisability of findings to regions with divergent healthcare systems. For example, countries with advanced digital health infrastructures or decentralised HIV care models may exhibit different care retention patterns. Additionally, the definition of retention in care was based solely on whether participants were still receiving HIV care and treatment at the 18-month follow-up, as determined by their clinical records from the routine check-up visits. This definition may overestimate care retention rates compared to those requiring continuous engagement, such as having at least two medical visits at least 90 days apart within the measurement year\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. The binary metric used for retention in care does not account for transient interruptions in care, which may mask fluctuations in adherence that could be valuable for designing more nuanced interventions.\u003c/p\u003e \u003cp\u003eViral load tests were conducted at participants\u0026rsquo; routine clinic visits every six months rather than at standardised study time points determined by the study protocol. While this reflects real-world programmatic data, it limits our ability to attribute suppression directly to the intervention or assess temporal trends. While self-reported ART adherence is widely used in HIV research, it is subject to social desirability and recall biases, which may overestimate actual adherence. Standardised scripts and neutral phrasing were employed during data collection to mitigate interviewer bias. Pill counts or objective measures (e.g., electronic monitoring) were not feasible due to logistical challenges\u0026ndash;\u0026ndash;participants\u0026rsquo; pill quantities varied widely depending on their last collection date, and the lack of consistent pill-count data precluded its use as a reliable metric. However, the observed high viral suppression rate (\u0026gt;\u0026thinsp;99%) is consistent with the self-reported high adherence, providing a validation that the reported adherence levels are sufficient for achieving viral suppression.\u003c/p\u003e \u003cp\u003eThe COVID-19 pandemic profoundly altered the study\u0026rsquo;s execution and outcomes. Originally designed as a 24-month quasi-experiment, the intervention was truncated to 18 months due to pandemic-related restrictions. This truncation limited our ability to assess long-term care retention trends. It precluded a planned midline survey, weakening validation of the parallel trend assumption required for robust difference-in-difference analyses. Both study arms experienced declines in ART adherence, mental health outcomes, and non-stigmatising care experiences, likely reflecting systemic pandemic effects such as healthcare access barriers, delayed medication distribution, and reduced in-person services. The CAD model\u0026rsquo;s adaptation\u0026mdash;shifting from group-based activities to individualised delivery and telehealth at times\u0026mdash;may have diluted its intended impact. While both CAD and MMD groups faced comparable disruptions (e.g., migration-related delays), the pandemic\u0026rsquo;s pervasive effects likely obscured differences between arms, reducing observed effect sizes. For instance, reliance on telehealth and fragmented support systems created similar challenges across groups, making it difficult to isolate the intervention\u0026rsquo;s efficacy under non-pandemic conditions. The absence of midline data and the shortened timeline limit causal interpretations. Had the 24-month endpoint been feasible, dropout patterns might have revealed diverging trends between arms, particularly given the evidence that retention often declines with prolonged follow-ups\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Furthermore, while prior studies report mixed pandemic impacts on HIV care (e.g., stable viral suppression despite reduced testing), our findings align with broader evidence of pandemic-driven service disruptions and mental health declines\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, underscoring the need for context-specific resilience strategies.\u003c/p\u003e \u003cp\u003eDespite the limitations, this study demonstrates that the CAD model is a promising strategy for improving ART adherence, mental health, and physical health outcomes among stable people living with HIV in Cambodia. With a 5.5% advantage in ART adherence and an 11.6% improvement in physical health compared to MMD, the CAD model\u0026rsquo;s benefits align with global evidence on the value of community-based HIV programmes in optimising care resilience. High retention rates in HIV care (98.2%) and viral suppression rates (\u0026gt;\u0026thinsp;99%) in both arms confirm the robustness of Cambodia\u0026rsquo;s HIV care system. Moreover, the CAD model's superior capacity to maintain ART adherence, promote mental health, and reduce externalised stigma positions it as a holistic, patient-centred alternative to clinic-based MMD. For policymakers, scaling up the CAD model in Cambodia and similar settings is warranted, particularly given its adaptability to telehealth and the minimal implementation barriers presented during the COVID-19 pandemic. However, to maximise impact, scale-ups should incorporate targeted stigma-reduction interventions and mental health support to address persistent internalised stigma and gaps in mental health quality of life.\u003c/p\u003e \u003cp\u003eFuture research should prioritise several key directions to address this study's limitations and refine CAD model's implementation. First, extending the follow-up period under non-pandemic conditions would clarify the CAD model's long-term effectiveness and capture potential retention declines over time, using continuous retention metrics (e.g., treatment gaps or visit frequency) aligned with established guidelines\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Second, mixed-methods approaches integrating qualitative evaluations are needed to explore contextual barriers\u0026mdash;such as migration patterns, telehealth accessibility, and stigma\u0026mdash;that influence HIV care delivery in resource-limited settings. Concurrently, health system assessments should evaluate the model\u0026rsquo;s scalability, including its impact on healthcare worker workload and cost-effectiveness. A formal cost-effectiveness analysis, as outlined in the original protocol, is underway and will inform scalability. Furthermore, adapting the CAD model to include targeted mental health and stigma-reduction components could enhance its holistic impact. At the same time, replication studies in diverse healthcare contexts (e.g., decentralised vs. centralised systems) would validate its generalisability. Finally, findings from these efforts should guide evidence-based guidelines for community-based HIV care, ensuring alignment with pandemic-resilient strategies and global best practices\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eThis quasi-experimental study was conducted between November 2021 and April 2023 in 10 provinces with high HIV burden. Within these provinces, 10 ART clinics were purposefully selected to implement CAD intervention. The selection was based on their similarity to 10 MMD control sites regarding key characteristics to ensure comparability between the two groups, reflecting real-world implementation challenges. The site selection process was conducted in consultation with the Database Management officers of NCHADS and other stakeholders involved in HIV programmes. The CAD intervention arm comprised six clinics in urban areas and four in rural areas across Phnom Penh, Kampong Thom, Kampot, Koh Kong, and Takeo. The MMD arm included seven urban and three rural clinics in Phnom Penh, Kampong Cham, Pailin, Preah Sihanouk, Siem Reap, and Prey Veng. The study protocol details have been published elsewhere\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn the CAD arm, 82 CAWs were recruited and trained to collect pre-packaged ARVs from ART clinics and distribute them to community ART groups, each consisting of 20 to 30 members, during monthly meetings. The training provided by ART clinics and implementing partners covered topics such as ART dispensing, drug storage, vital sign assessment and documentation, HIV education, ART adherence measurement, referral systems, and essential issues, including mental health, stigma, discrimination, as well as sexual and reproductive health and rights. In the MMD arm, participants collected and refilled their ARV prescriptions at the ART clinics every three to six months. People living with HIV in both arms visited ART clinics as needed for consultations and routine clinical check-ups every six months. Clinical management was carried out by trained personnel at ART clinics, following national guidelines.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eCommunity engagement and co-production\u003c/h2\u003e \u003cp\u003eThe CAD model was developed and implemented with the active involvement of people living with HIV who served as CAWs, drawing on their lived experiences to ensure the intervention\u0026rsquo;s relevance and effectiveness. CAWs played a vital role in site selection, intervention design, and implementation through a stakeholder participatory approach, ensuring that the model addressed community needs and aligned with national priorities. Furthermore, CAWs directly applied their personal experiences to enhance the delivery of the intervention. This involvement of individuals with lived experiences was crucial in fostering trust, reducing stigma, and tailoring the intervention to the realities faced by people living with HIV in Cambodia. Please refer to the Inclusion and Ethics Statement for additional details on collaboration, stakeholder engagement, and capacity-building efforts.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003ePeople living with HIV were considered eligible for inclusion based on the following criteria: (1) aged 15 or older, (2) on first-line ART for at least one year, (3) not reporting ART-related adverse reactions or drug interactions requiring regular monitoring, (4) free from tuberculosis and other opportunistic infections at the time of baseline assessment, (5) not receiving prophylactic treatment, (6) having at least two consecutive undetectable viral loads or CD4 counts above 200 cells/mm\u0026sup3;, and (7) assessed by their healthcare providers as having a solid understanding of lifelong treatment and medication adherence. Exclusion criteria included pregnant or breastfeeding women.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eData collection procedures\u003c/h2\u003e \u003cp\u003eQuantitative data were collected by trained data collectors at baseline in October 2021, before the CAD intervention was introduced in November, and at the endline in April 2023, following the completion of the 18-month intervention. The questionnaire included sociodemographic and self-reported medical history, including comorbidities. Sex and gender data were self-reported and included options for male, female, and LGBTQ\u0026thinsp;+\u0026thinsp;identities. Viral loads and CD4 counts were captured from clinics\u0026rsquo; medical records.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eOutcome variables\u003c/h2\u003e \u003cp\u003eThe primary outcomes assessed included (i) retention in HIV care, (ii) viral load suppression, and (iii) ART adherence. Retention in HIV care was defined as whether people living with HIV documented in clinical records as actively receiving ART at the 18-month follow-up. Viral load suppression was defined as achieving a viral load of fewer than 1,000 ribonucleic acid (RNA) copies/mL in a most recent measurement during the study period, based on clinical records.\u003c/p\u003e \u003cp\u003eART adherence was defined as a binary outcome based on self-reported responses to five questions assessing medication practices over the prior two months\u0026ndash;\u0026ndash;missed any ARV doses in the past two months, had trouble remembering to take ARVs, stopped taking ARVs when feeling better, missed any doses in the past four days, and stopped taking ARVs when feeling worse. Participants were classified as adherent only if they answered \u0026ldquo;no\u0026rdquo; to all five questions, prioritising specificity over sensitivity. This method reduced the risk of misclassifying non-adherent individuals as adherent. While pill counts or pharmacy refill data were considered, they were deemed unreliable due to inconsistencies in participants\u0026rsquo; pill quantities during surveys (e.g., some had recently collected ARVs, while others were due for refills).\u003c/p\u003e \u003cp\u003eSecondary outcomes included (i) HIV-related stigma and discrimination, (ii) mental health, and (iii) quality of life. Stigma and discrimination were assessed in three dimensions, which included experienced stigma, internal stigma, and fear of stigma, using the People Living with HIV Stigma Index, which had been validated for people living with HIV in Cambodia\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e Experienced stigma was defined as any exclusion, harassment, or adverse events across social, familial, or institutional settings, with a composite score of less than three indicating the absence of experienced stigma. Internal stigma reflected negative self-perceptions, with a score of less than five indicating low internal stigma. Fear of stigma captured concerns about rejection or discrimination, with a score of less than two indicating no fear of stigma. Composite scores were generated by summing binary variables.\u003c/p\u003e \u003cp\u003eMental health was assessed using the 10-item Centre for Epidemiology Studies Depression Scale (CES-D-10), with scores below 10 indicating no depressive symptoms\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Quality of life was measured using the Short-Form-12 (SF-12) survey, which included 12 items across eight health domains\u0026ndash;\u0026ndash;physical function, social function, role limitations due to physical health, role limitations due to emotional problems, mental health, vitality, bodily pain, and general health\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e A Physical Component Score (PCS) of 50 or higher indicated good physical health, and a Mental Component Score (MCS) of 42 or higher indicated good mental health. The CES-D scale and the SF-12 have been widely used in various Asian populations, including Cambodia, India, Japan, and Singapore\u003csup\u003e\u003cspan additionalcitationids=\"CR35 CR36\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eComplete case analyses were done for participants who were retained in HIV care and completed baseline and endline surveys. Descriptive analyses summarised the sociodemographic characteristics of participants. The Pearson\u0026rsquo;s Chi-square test assessed differences between ordinal data, while the Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test was used for continuous variables when the normality assumption was met; otherwise, the Mann-Whitney U-test was applied. Variables were categorised pragmatically to account for low cell counts.\u003c/p\u003e \u003cp\u003eThe effects of the intervention on various treatment outcomes were assessed using logistic regression models with robust standard errors to account for potential heteroskedasticity. A comprehensive covariate selection process was employed to identify and adjust for confounders, ensuring the precision and reliability of the estimated treatment effects. This process included four steps: assessing confounding effects, constructing the adjusted model, performing backward selection using the Bayesian information criterion, and validating the final models through bootstrapping.\u003c/p\u003e \u003cp\u003eEach candidate covariate was evaluated for its potential confounding effect on the relationship between treatment and outcome using the change-in-estimate criterion. This involved fitting a crude model, including only the primary predictors (timeline, treat, and their interaction term), and an adjusted model incorporating the covariate. The coefficient for treatment was compared between the two models, and the percentage change was calculated as follows:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:Percentage\\:Change=\\left|\\frac{{\\beta\\:}_{crude}-{\\beta\\:}_{adjusted}}{{\\beta\\:}_{crude}}\\right|*100$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eA covariate was considered a potential confounder if its inclusion caused a more than 10% change in the treatment coefficient. This threshold was applied to both baseline and endline assessments. At baseline, the change in treatment was examined, while at endline, the combined effect of treatment and the interaction term was analysed. Covariates meeting this threshold were included in subsequent models to prevent biased treatment effect estimation.\u003c/p\u003e \u003cp\u003eOnce potential confounders were identified, an adjusted logistic regression model was created. This model included all significant confounders identified in the previous step and essential demographic variables\u0026mdash;age and gender\u0026mdash;regardless of their impact on the treatment effect. The inclusion of age and gender was necessary due to their fundamental roles in influencing health outcomes and their ability to enhance model interpretability and generalisability. This step ensured that the treatment effect estimates were not biased by omitted variable confounding, providing a more accurate representation of the intervention\u0026rsquo;s impact.\u003c/p\u003e \u003cp\u003eTo refine the model further and achieve parsimony, backward selection using the Bayesian information criterion was performed. The Bayesian information criterion prioritises simpler models while ensuring adequate fit to the data. The procedure began with the fully adjusted model and iteratively removed covariates based on their statistical significance. Covariates with the highest \u003cem\u003eP\u003c/em\u003e-values not part of the primary treatment effect were excluded first. For categorical covariates, the overall significance was assessed using the Wald test. A covariate was retained if its \u003cem\u003eP\u003c/em\u003e-value was below 0.05 or if its removal caused a change of more than 10% in the treatment effect, indicating its potential role as a confounder. The process continued until only statistically significant or theoretically justified covariates remained, ensuring the model was robust and parsimonious.\u003c/p\u003e \u003cp\u003eOnce the final covariates were selected, the logistic regression models were specified for each treatment outcome. Predicted probabilities were computed using the margins command to estimate the difference-in-difference effect. To enhance the robustness of these estimates, bootstrapping with 500 replications was employed. Bootstrapping involved repeatedly resampling from the dataset, fitting the logistic regression model each time, and calculating the difference-in-difference estimate for each sample. The distribution of these estimates provided CIs, which were used to assess the non-inferiority and superiority of the intervention, ensuring the observed treatment effects were not driven by sample variability. A pre-specified non-inferiority margin of -10% was applied to assess whether the CAD model was not unacceptably worse than MMD. This margin was selected based on clinical relevance, prior evidence from HIV care studies, and assumptions outlined in the study protocol\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Non-inferiority was concluded if the lower bound of the 95% CI exceeded \u0026minus;\u0026thinsp;10%, indicating the CAD model was not meaningfully worse than MMD. Superiority was established if the lower bound exceeded 0%, demonstrating a statistically significant benefit of CAD.\u003c/p\u003e \u003cp\u003eTo rigorously address missing data due to loss to follow-up, a difference-in-difference framework was implemented within a multiple imputation approach using the Multivariate Imputation by Chained Equations (MICE) method. The primary analysis assumed data were missing at random, where missing treatment outcomes were imputed via logistic regression imputation, incorporating outcome-specific covariates. To ensure robustness, 10 imputed datasets were generated. Three sensitivity analyses were conducted to evaluate the potential impact of different missing data mechanisms: (1) Scenario 1 (missing at random, primary analysis), where missing outcomes were imputed based on observed covariates without altering baseline characteristics\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e (2) Scenario 2 (differential missingness in covariates), where the baseline characteristics of 50% of the loss to follow-up individuals were systematically modified before outcome imputation to account for potential differential attrition, adjusting covariates plausibly affected by the intervention; and (3) Scenario 3 (missing-not-at-random adjustment), where missing outcomes were first imputed under missing-at-random assumption and subsequently adjusted to account for unobserved confounding by reducing the predicted probabilities of loss to follow-up individuals by 5%, followed by restimulating their outcomes using a Bernoulli distribution, thereby modelling a scenario in which loss to follow-up individuals systematically exhibited lower probabilities in outcomes. In each scenario, the difference-in-difference estimate was derived from a logistic regression model incorporating an interaction term between treatment and timeline, with final estimates pooled using Rubin\u0026rsquo;s rules. Nonparametric bootstrapping (500 replications) was applied to quantify uncertainty, computing 95% CIs using the percentile method.\u003c/p\u003e \u003cp\u003eData analyses were conducted using STATA 18 software\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e and R Studio (version 2024.04.1\u0026thinsp;+\u0026thinsp;748), using the MICE and boot package\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eSafety and adverse events\u003c/h2\u003e \u003cp\u003eAn independent Data and Safety Monitoring Board periodically reviewed the study\u0026rsquo;s progress and safety in consultation with the CAD Project Steering Committee. Interim analyses were conducted to assess potential benefits and harms related to the study\u0026rsquo;s outcomes. Any adverse events were immediately reported to the study principal investigators, site co-principal investigators, and the National Centre for HIV/AIDS, Dermatology, and STD (NCHADS). The CAD Project Steering Committee held ad-hoc meetings to review and address these events when necessary.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eStudy registration and protocol deviations\u003c/h2\u003e \u003cp\u003eThe quasi-experimental study was registered with ClinicalTrials.gov (NCT04766710) on 23 February 2021, and the first participant was enrolled on 1 April 2021. The ClinicalTrials.gov registration record was prepared before enrolling participants in compliance with the National Institutes of Health (NIH) policy on clinical trial registration. While the study was registered for transparency, it is not a randomized controlled trial in the traditional sense\u0026mdash;the registration aimed to ensure adherence to ethical standards and transparency in reporting.\u003c/p\u003e \u003cp\u003eThe study faced significant protocol deviations due to the COVID-19 pandemic. Initially planned for 24 months, the CAD intervention was shortened to 18 months because of project start-up delays and social restrictions that disrupted the implementation. These unforeseen challenges affected the study timeline, resource availability, and operational capacity, preventing the completion of key assessments. As a result, the midterm quantitative survey and endline qualitative process evaluation could not be conducted, limiting the depth of insights into participant experiences and intervention effectiveness. While adaptations were made, these deviations must be considered when interpreting the study\u0026rsquo;s findings and conclusions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eInclusion and ethics statement\u003c/h2\u003e \u003cp\u003eThe CAD project is a collaboration between the National University of Singapore (NUS), Khmer HIV/AIDS NGO Alliance (KHANA), and NCHADS, building on over a decade of partnership. KHANA, a key player in Cambodia\u0026rsquo;s HIV response since 1996, and NCHADS, which leads the national HIV programme, developed a Standard Operating Procedure (SOP) for CAD, endorsed by the Ministry of Health. The project was designed using a stakeholder participatory approach and involved HIV communities, key populations, NGOs, government agencies, and development partners in site selection, intervention design, and implementation. KHANA, NCHADS, and three community-based HIV NGOs, along with representatives of people living with HIV, led the intervention\u0026rsquo;s development, guided by formative studies and national HIV programme evaluations. Regular stakeholder workshops, community advisory board meetings, and consultations with the National HIV Technical Working Group ensured the intervention was relevant, sustainable, and aligned with national priorities. Clear roles and responsibilities were established before the study, with the study principal investigator (PI) and local PIs serving as co-leaders in all decisions. The project also prioritised capacity building, providing staff training, continuing education, and advanced scholarly training to strengthen local expertise and ensure the long-term sustainability of the CAD model within Cambodia\u0026rsquo;s HIV response framework.\u003c/p\u003e \u003cp\u003eEthical approval\u003c/strong\u003e for this study was granted by the National Ethics Committee for Health Research (Ref. 258/NECHR) of the Ministry of Health, Cambodia. All participants, including people living with HIV, community action workers, and healthcare workers, provided written informed consent before data collection. Privacy and confidentiality were strictly upheld, with all personal identifiers removed to ensure anonymity. Participants were offered support resources to mitigate potential risks, such as psychological distress from sensitive questions, and participation remained entirely voluntary. The study's potential benefits, including improvements in HIV care, outweighed any risks, and participants were fully informed of these as part of the consent process.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eRole of the funding source\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eL\u0026apos; Initiative through Expertise France funded the study. The funder had no roles in the study design, data collection, statistical analyses, finding interpretation, or report writing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributors\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZT developed the data analysis plan, conducted data analyses, and wrote the initial draft. PC and ST contributed to the study design, supervised project implementation, led data collection efforts, and provided feedback on the draft. ELYY, MN-H, and MZ supported the data analyses and offered input on the draft. SS, BN, and VO provided strategic advice on intervention development, implementation, and evaluation and reviewed the manuscript. AKJT and KP played critical roles in study design, contributed to the data analysis plan, and provided feedback on the draft. SY secured funding, led the study design, and oversaw project implementation, data collection, analyses, and manuscript writing. All authors reviewed and approved the final manuscript and held ultimate responsibility for the decision to publish.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData access for the CAD study, which is restricted to non-identifying data underlying the results reported in this article, can be requested from the corresponding author via email at [email protected]. The study protocol, statistical analysis plan, analytic code, consent forms, and clinical report forms will also be available. Data will be accessible immediately following publication with no end date. Access will be granted to investigators whose analyses comply with the restrictions outlined in the study consent forms and whose proposed use of the data has been approved by the appropriate ethical review board.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe underlying code for the results detailed in this article can be requested from the corresponding author. The author will handle all requests for scientific purposes and share the code if the request is deemed scientifically appropriate.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResearch reported here was supported by the National Centre for HIV/AIDS, Dermatology, and STD, Khmer HIV/AIDS NGO Alliance, Cambodian People Living with HIV Network, ARV Users Association, Partners in Compassion, and participating ART clinics. We thank community action workers and their community members for supporting this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNational Center for HIV/AIDS, D.a.S. Strategic Plan for HIV/ AIDS and STI Prevention and Control in the Health Sector 2016\u0026ndash;2020. (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAuthority, N.A. 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Comparison of intent-to-treat analysis strategies for pre-post studies with loss to follow-up. Contemp Clin Trials Commun 11, 20\u0026ndash;29 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStataCorp. 2023. Stata Statistical Software: Release 18. College Station, TX: StataCorp LLC.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Buuren, S. \u0026amp; Groothuis-Oudshoorn, K. mice: Multivariate Imputation by Chained Equations in R. Journal of Statistical Software 45, 1\u0026ndash;67 (2011).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6310016/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6310016/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCambodia\u0026rsquo;s HIV response successfully met the UNAIDS 90-90-90 targets in 2017; however, ongoing systemic barriers such as clinic congestion, stigma, and mental health disparities pose a threat to this progress. This quasi-experimental study evaluated a community-based antiretroviral (ART) delivery (CAD) model against multi-month dispensing (MMD) for stable people living with HIV from 2021 to 2023 across 20 ART clinics, enrolling a total of 4,089 participants (2,040 in CAD, 2,049 in MMD). The study employed baseline and endline surveys along with clinical data to assess various outcomes, including ART adherence, viral suppression, retention in HIV care, stigma, mental health, and quality of life. Results indicated high retention (97.3%) and viral suppression (\u0026gt;\u0026thinsp;99%) rates for both models, with CAD showing a significant improvement in ART adherence (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002), a smaller decline in participants with no depressive symptoms (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) and enhanced physical health (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Although CAD resulted in modest decreases in externalised stigma, the effects on internalised stigma remained inconclusive. The findings suggest that CAD is an effective community-based model for sustaining ART adherence and improving health outcomes, supporting the integration of such approaches within Cambodia\u0026rsquo;s HIV care system while also advocating for the combination of CAD with stigma-reduction strategies.\u003c/p\u003e","manuscriptTitle":"Impact of a community-based antiretroviral therapy delivery model on treatment outcomes, mental health, and quality of life among stable people living with HIV in Cambodia: a quasi-experimental study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-31 11:41:26","doi":"10.21203/rs.3.rs-6310016/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"4ae53967-0472-438a-8a63-952bccc72e4a","owner":[],"postedDate":"March 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":46294999,"name":"Health sciences/Health care"},{"id":46295000,"name":"Scientific community and society/Developing world"}],"tags":[],"updatedAt":"2025-12-30T08:19:01+00:00","versionOfRecord":{"articleIdentity":"rs-6310016","link":"https://doi.org/10.1038/s41467-025-66606-x","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2025-11-25 05:00:00","publishedOnDateReadable":"November 25th, 2025"},"versionCreatedAt":"2025-03-31 11:41:26","video":"","vorDoi":"10.1038/s41467-025-66606-x","vorDoiUrl":"https://doi.org/10.1038/s41467-025-66606-x","workflowStages":[]},"version":"v1","identity":"rs-6310016","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6310016","identity":"rs-6310016","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}