HIV self-testing preferences among HIV high-risk Adolescent Girls and Young Women (AGYW) in urban settings in Uganda: A Discrete Choice Experiment

HIV self-testing preferences among HIV high-risk Adolescent Girls and Young Women (AGYW) in urban settings in Uganda: A Discrete Choice Experiment | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (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];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search HIV self-testing preferences among HIV high-risk Adolescent Girls and Young Women (AGYW) in urban settings in Uganda: A Discrete Choice Experiment View ORCID Profile Laban Muteebwa , Patience A. Muwanguzi , Shivan Nuwasiima , View ORCID Profile Ivan Ahimbisibwe , Edson Atwine , View ORCID Profile Dan Muramuzi , View ORCID Profile Cathbert Tumusiime , Fred C. Semitala , Joanita Nangendo doi: https://doi.org/10.1101/2025.10.22.25338604 Laban Muteebwa 1 Department of Medicine, School of Medicine, College of Health Sciences, Makerere University Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Laban Muteebwa For correspondence: mutlabans{at}gmail.com Patience A. Muwanguzi 2 Department of Nursing, School of Health Sciences, College of Health Sciences, Makerere University Find this author on Google Scholar Find this author on PubMed Search for this author on this site Shivan Nuwasiima 3 Clinical Epidemiology Unit, School of Medicine, College of health Sciences, Makerere University Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ivan Ahimbisibwe 3 Clinical Epidemiology Unit, School of Medicine, College of health Sciences, Makerere University Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Ivan Ahimbisibwe Edson Atwine 4 Faculty of Graduate Studies, Makerere University Business School, Makerere University Find this author on Google Scholar Find this author on PubMed Search for this author on this site Dan Muramuzi 5 Department of Pharmacy, School of Health Sciences, College of Health Sciences, Makerere University 6 Department of Health Policy Planning and Management, School of Public Health, College of Health Sciences, Makerere University Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Dan Muramuzi Cathbert Tumusiime 7 Directorate of Research, Baylor College of Medicine Children’s Foundation-Uganda , Kampala, Uganda Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Cathbert Tumusiime Fred C. Semitala 1 Department of Medicine, School of Medicine, College of Health Sciences, Makerere University 8 Makerere University Joint AIDS Program , Kampala, Uganda 9 Infectious Disease Research Collaboration , Kampala, Uganda Find this author on Google Scholar Find this author on PubMed Search for this author on this site Joanita Nangendo 1 Department of Medicine, School of Medicine, College of Health Sciences, Makerere University 9 Infectious Disease Research Collaboration , Kampala, Uganda Find this author on Google Scholar Find this author on PubMed Search for this author on this site Abstract Full Text Info/History Metrics Data/Code Preview PDF Abstract HIV self-testing (HIVST) represents a crucial innovation for improving testing coverage, particularly among high-risk adolescent girls and young women (AGYW) inadequately reached through standard provider-assisted HIV testing approaches. Understanding user preferences for HIVST services is essential for designing models that optimize uptake. We assessed the HIVST preferences among high-risk AGYW living in urban Uganda. We enrolled high-risk AGYW consecutively in a discrete choice experiment (DCE). Each participant completed eight choice sets, each comprising of two hypothetical HIVST service alternatives and an opt-out option. The four attributes included level of assistance (assisted versus unassisted), distribution model (facility-based versus community-based), delivery channel (primary versus secondary) and sample type (oral swab versus blood). A mixed logit model was used to estimate the utility, relative importance (RI) and trade-offs. Between December 2024 and May 2025, a total of 340 participants were enrolled with mean age 19.8 years (SD: 2.6), and 65.9% of them were not in school. The distribution model, delivery channel and level of assistance significantly influenced participants’ choices to use HIVST services with coefficients of 0.14 (95%CI: 0.06, 0.23), 0.09 (95%CI: 0.00, 0.17) and 0.46 (95%CI: 0.37, 0.54) respectively. The sample type didn’t significantly influence the choice of participants to use HIVST (coefficient, 0.05 (95%CI: -0.04, 0.13). The level of assistance emerged as the most important attribute (RI: 60%), followed by facility-based distribution model (RI: 18.9%) and primary delivery channel (RI: 12.2%). AGYW were willing to sacrifice 9.2 units of utility of the test kit type to get unassisted HIVST. AGYW living in urban settings preferred unassisted HIVST delivered through the health facility. Regardless of the type of kit, the level of autonomy and convenience attained during unassisted testing greatly influenced the users’ choice of the HIVST service. Background Global HIV infections have declined by 40% since 2010 – from 2.2 million to 1.3 million in 2024, yet progress remains inadequate [ 1 ]. The continued shortfall from the 2025 target of fewer than 370,000 new infections, highlighting persistent weaknesses in prevention and control efforts[ 1 ]. Women and girls continued to bear a disproportionate burden, accounting for 63% of new infections in Sub-Saharan Africa (SSA) in 2024. Within this group, adolescent girls and young women (AGYW) aged 15 – 24 years are the most severely affected: in 2024 alone, more than 4,000 AGYW were infected with HIV every week globally, with over 82.5% of these infections occurring in SSA [ 1 ]. In Uganda, the gendered impact is even more pronounced. In 2024, approximately 80% of all new HIV infections among young people aged 15 – 24 years occurred in AGYW [ 2 ]. A recent analysis of HIV testing data (November 2019 – November 2021) further revealed that, among 2,672 new infections in AGYW, at least 13.4% were recently acquired (acquired within the previous 12 months) [ 3 ]. This suggests that the majority of AGYW were living with long-standing, undiagnosed HIV infection, and therefore, not accessing timely treatment. Furthermore, one in three AGYW with recent HIV infection were first-time testers [ 3 ], underscoring the critical need to expand routine and accessible HIV testing, particularly for HIV high-risk AGYW. HIV testing is the gateway to HIV prevention, care, and treatment, and constitutes the first pillar of the UNAIDS 95-95-95 targets: 95% of people living with HIV knowing their status, 95% of those diagnosed receiving treatment, and 95% of those on treatment achieving viral suppression [ 4 ]. In Uganda, the Ministry of Health (MoH) has expanded provider-assisted HIV testing through various approaches, including facility-based (provider-initiated and client-initiated), community outreach, home-based, and index testing [ 5 ]. Despite these efforts, conventional strategies have not optimally reached high risk populations, particularly AGYW, female sex workers, men, and men who have sex with men (MSM) [ 6 ]. Among AGYW, low HIV testing uptake are attributed to developmental factors intertwined with interpersonal, cultural, structural, and health system barriers, including stigma, limited privacy, long waiting times, negative provider attitudes, and inadequate youth-friendly services[ 7 ]. HIV self-testing (HIVST) offers a promising convenient, confidential, and youth-responsive alternative to address these challenges [ 8 – 10 ]. HIVST is a “test-for-triage” approach in which individuals collect their own specimen (oral fluid or blood), perform the test, and interpret the results independently or with a trusted person [ 11 ]. Evidence from randomized controlled trials and implementation studies demonstrates that HIVST significantly increases testing uptake compared with provider-delivered testing and is highly acceptable across diverse populations, including AGYW [ 12 , 13 ]. In Uganda, HIVST was incorporated into national HIV guidelines in 2018 [ 6 ], and is being scaled up in public and private sectors through various differentiated service delivery (DSD) models [ 5 ]. However, the heterogeneity of DSD models complicates efforts to tailor HIVST interventions to high-risk subpopulations such as AGYW and contributes to increased implementation costs [ 14 , 15 ]. Understanding which HIVST service delivery attributes are most valued by AGYW is therefore critical for designing AGYW-centered, cost-efficient models that optimize uptake. Prioritizing delivery models aligned with AGYW preferences has potential to enhance testing coverage and HIV positivity yield while improving resource efficiency. This study aimed to assess HIVST service preferences and key attributes associated with improved testing uptake among high-risk AGYW in urban Uganda. Methods Discrete choice experiments This study utilized a discrete choice experiment, grounded in the Lancaster’s theory of consumer demand [ 16 ], and the Random Utility Theory (RUT) [ 17 ] that underpins modelling of choice data. Under the RUT, when an individual is presented with two or more alternatives, they will choose an alternative that maximizes utility (benefit). This latent utility is a function of; (1) a systematic (observable) component which is determined by the measurable attributes of the alternatives and the characteristics of the individual; and (2) a random (unobserved) component which captures the factors not included in the model or randomness in decision making. The utility (U ij ) for an individual (i) choosing alternative (j) is expressed as; U ij = V ij + π ij , Where; V ij is the observable (deterministic) component –a linear combination of attributes and π ij is the unobserved (random) component. Discrete Choice Experiments (DCE) provide a structured and evidence-based method for eliciting stated preferences about health service delivery attributes [ 18 ]. By presenting participants with hypothetical service options composed of varying features (attributes), DCEs allow researchers to estimate the relative importance of each attribute, simulate uptake under different scenarios and identify trade-offs that users are willing to make [ 19 ]. Study design and setting This cross-sectional study was conducted among HIV high-risk AGYW living in the Kampala Metropolitan Area in Uganda from 1 st December 2024 to 31 st May 2025. This study setting was selected because prior assessment in Sub-Saharan Africa reported that adolescents and young people living in urban settings have a 1.5 to 2 times HIV prevalence compared to their counterparts in rural settings [ 20 ]. Kampala Metropolitan Area includes the four most populous districts in Central Uganda, that is, Kampala, Wakiso, Mukono and Mpigi according to the 2024 National census [ 21 ]. This is the most urbanized and commercial area in Uganda and includes its Capital City, Kampala, hosting an estimated daytime population of about five million people [ 22 ]. Moreover, this study setting accounted for the largest number of new HIV cases among AGYW of which Wakiso had the highest (4,900) followed by Kampala (2,800), Mukono (700) and Mpigi (405) [ 4 ]. Additionally, the HIV prevalence among adults aged 15-49 years (2023) in Kampala, Wakiso, Mpigi and Mukono is 7.4%, 7.2%, 8.2% and 5.3% respectively, all above the national prevalence (2023) of 5.1% [ 4 ]. Study population The study population included AGYW aged 15 to 24 years who had lived in the study area for at least six months, with an HIV risk score of ≥2 (high-risk), were willing to accept HIVST if it was provided (willingness score >21) and gave written informed consent (for adults and emancipated minors) or assent for minors in addition to their guardian’s consent. The HIV risk was assessed using the HIV risk assessment tool previously used among AGYW in Kampala, Uganda [ 24 ] and follows the criteria set by the MoH. The willingness to accept HIVST if it was provided was measured using the theoretical framework of acceptability [ 23 ]. This framework has seven constructs for which each construct was assessed using a one 5-level Likert item question weighted 1 – 5 for which a higher score indicated a higher level of acceptability. The sum of weights from all seven constructs was computed and a score above the 50 th percentile of the possible scores (21) ranging from 7 – 35 was used as a threshold of willingness to accept HIVST. Participants who couldn’t read or comprehend basic English or Luganda were excluded from the study. Sample size estimation and sampling procedure The sample size was estimated using the Orme and Johnson formula [ 24 ] where, “N” is the estimated sample size, “c” is the number of levels per each attribute (2), “t” is the number of tasks (8) and “a” is the number of alternatives per task excluding the null alternative (opt-out) (2). Adjusting for 10% non-response and design effect of two, the estimated sample size was 140. However, this DCE study was nested in a larger study that assessed the willingness to use HIVST among HIV high-risk AGYW. All participants that demonstrated willingness to use HIVST were enrolled into the DCE study, thus a total 340 AGYW were included. The sampling was done on three levels – firstly, two (Kampala and Wakiso) out of four districts were selected purposively because they had the highest number of new HIV infections among AGYW. Secondly, two (Makindye and Rubaga) out of five divisions in Kampala district and two (Entebbe and Nansana) out of four divisions in Wakiso district were selected using simple random sampling. Lastly, the study participants were selected using consecutive sampling technique, and the number of participants from each district was proportionate to the 2023 projected number of AGYW [ 25 ]. Experimental design for a DCE The attributes of HIVST service were derived from the MoH consolidated guidelines for prevention and treatment of HIV (2022)[ 5 ] to conform with the existing DSD models that are currently being implemented for HIVST. However, the distribution model of the HIVST services delivery through the private sector was not considered. Therefore, only four attributes of the HIVST service were considered, of which all had two levels. These include; distribution model (Facility-based versus community-based), delivery channel (primary delivery source versus secondary delivery source), sample/kit type (oral swab versus blood), and level of assistance (assisted versus unassisted) ( Table 1 ). With the four attributes of the HIVST services considered, each with two levels, a full factorial experimental design would give rise to 16 choice sets (2 4 ). However, only eight choice sets (fractional factorial) were considered as it has been reported to be optimal to elicit the desired utility measures while preventing cognitive overload of study participants [ 26 , 27 ]. To select the choice sets to be considered, the D-efficient design in STATA version 17.0 (Texas USA) was used and the assumption that no prior coefficient estimates of the attributes in the target population exist (no priors’ matrix) including the alternative specific constant). Given attribute level matrix of 2, 2, 2, 2 (each has two levels) and two alternatives plus the opt-out (opt-out matrix of 1, 1, 1, 1), the modified Fedorov algorithm [ 28 – 30 ], which maximizes the D-efficiency of the design based on covariance matrix of a conditional logit model, was used to generate eight choice sets. The generated choice sets were used to design the DCE questionnaire. View this table: View inline View popup Table 1: HIVST service attributes and levels adapted from the Consolidated guidelines for prevention and treatment of HIV in Uganda Data collection tool and procedure A structured questionnaire was used to collect the data on the socio-demographic, and behavioral characteristics, as well as the discrete choices that describe the DSD models for HIVST service. The choice sets of the HIVST service attributes and levels assessed in this study are attached as supplementary file1. The DCE questionnaire was further enhanced with images describing the attributes of HIVST services which were obtained from a public database of images (noun project) [ 31 ]. The questionnaire was pretested among 20 HIV high-risk AGYW in Kawempe division in Kampala city, and these participants were excluded in the analysis. A “think-aloud” approach was used in the pretest to assess the participants’ understanding and thought process as they made choices about the tasks presented. Targeted mobilization was carried out in the study areas to identify AGYW who are at an elevated risk of acquiring HIV. The information about HIVST was given and practical demonstrations of how the HIVST kits are used were done before screening the study participants. Both the oral (OraQuick, OraSure Technologies, Inc. Bethlehem, PA, USA) and blood-based (GOLDEN TIME, Gaobeidian PRISES Biotechnology Co., Ltd, Hebei Province, China) HIVST kits were used in the demonstrations. Trained research assistants administered the questionnaire to AGYW who were eligible for the study. Study outcomes The primary outcome was the choice of preferred alternative of the tasks that offered the highest utility (benefit) to individual participants. The marginal utility gained from each of the attributes was computed as the primary measure. The Relative Importance (RI) was defined as the measure of influence each attribute had on participant’s decision to choose an alternative relative to other attributes in the model. Furthermore, the attribute tradeoffs – defined as the utility of one attribute level a participant is willing to give up (or accept less of) in order to gain a more preferred level of another attribute while still choosing the same alternative was also reported. Statistical analysis The data analysis was done in STATA version 17.0 (Texas, USA). The participant characteristics were summarized using descriptive statistics. For continuous variables, the mean and the standard deviation (SD) or the median and interquartile range (IQR). The categorical variables were summarized using the frequencies and percentages. The mixed logit model was used to fit a model with the outcome of choice, and attributes of HIVST services as the alternative-specific variables. The relative importance of an HIVST service attribute was computed as a proportion of the range of coefficients of an attribute out of the total sum of the ranges of coefficients of other attributes in the final model [ 32 ]. The Trade-offs between one attribute levels to another were computed as a ratio of coefficient of the preferred level to the sacrificed level [ 33 ]. Ethical considerations The study was approved by the Makerere University School of Medicine Research Ethics Committee (Reference: Mak-SOMREC-2023-843), and further clearance was obtained from the Uganda National Council for Science and Technology (UNCST) (Reference: HS5167ES). Administrative approvals to conduct the study were secured from the Kampala Capital City Authority (KCCA) and the Municipal Health Offices of Entebbe and Nansana in Wakiso District. Written informed consent was obtained from all adult participants and emancipated minors. For other participants below 18 years, written informed assent was obtained alongside written informed consent from their guardians, in accordance with UNCST guidelines [ 34 ]. Results Socio-demographic characteristics of study participants The mean age of the participants was 19.8 years (SD: 2.6), about two-thirds (65.9%) were out of school and 71.8 didn’t live with their primary partner. The participants had a median monthly income of about United Stated Dollars $42.1 (IQR: 28.1, 56.1). Slightly more than half of participants (56.8%) had ever been pregnant and about a similar proportion (55.9%) were using a modern contraceptive method. Half of the participants (50.5%) had primary partners who were older by >5 years. 18.8% reported to have experienced intimate partner violence with 10.6% experiencing sexual violence from their intimate partners in the past six months ( Table 2 ). View this table: View inline View popup Table 2: Socio-demographic characteristics of AGYW who participated in the study Behavioral characteristics of the study participants In the six months preceding the study, 55.6% of participants reported a sexually transmitted infection, 30.3% had multiple sexual partners, and 14.1% reported consistent condom use. Transactional sex was reported by 29.7%, anal sex by 11.2%, and intravenous drug use by 15.6%. Only 6.2% and 4.7% reported using PEP and PrEP, respectively. Overall, 83.2% had ever tested for HIV, and 75.6% of these had done so within the past 12 months. While 71.2% had heard of HIV self-testing (HIVST), only 50.4% had ever used an HIVST kit, and 58.8% reported being unable to obtain one when needed. ( Table 3 ) View this table: View inline View popup Table 3: Behavioral characteristics of AGYW who participated in the study Preference of the HIVST service attributes Participants preferred HIVST services with a facility-based distribution model (coefficient: 0.14; [95% CI: 0.06 - 0.23]), primary delivery (coefficient: 0.09; [95% CI: 0.00 - 0.17]), and unassisted testing (coefficient: 0.46; [95% CI: 0.37 - 0.54]). The type of test kit/sample did not significantly influence participants’ choices. The level of assistance was the most important attribute that influenced the choice of an alternative (RI: 62.2%), followed by distribution model (RI: 18.9%), delivery channel (RI: 12.2%) and sample/test kit type. ( Table 4 ) View this table: View inline View popup Download powerpoint Table 4: HIV self-testing service preferences of 340 AGYW who participated in the study Willingness to trade-off for a more preferred HIVST attribute Participants were willing to sacrifice 9.2 units of utility for sample type, 5.1 units for delivery channel, and 3.4 units for distribution model in order to access unassisted HIVST, without any loss in overall utility. However, they were not willing to sacrifice any HIVST attributes in order to obtain a preferred test kit (sample type) ( Figure 1 ). Download figure Open in new tab Figure 1: HIV self-testing attribute trade-offs for AGYW Discussion This DCE explored HIVST preferences among high-risk AGYW in urban Uganda to identify optimal service delivery models. Findings show a strong preference for unassisted HIVST, facility-based distribution, and primary-level delivery channels, while the type of test kit (oral vs. blood) had no significant influence on choice of the alternative tasks. These results provide actionable evidence to guide HIVST models that are responsive to the needs and realities of AGYW. The level of assistance emerged as the most influential attribute, contributing over 60% of the relative importance in choice decisions. For HIV high-risk AGYW, the ability to self-test without assistance was by far the most important factor in deciding whether to use HIVST service model. It was three times more important than the source of the kit, five times more important than the delivery channel, and nine times more important than the type of test kit. This indicates that even if kit type or distribution method is not ideal, AGYW are still more likely to use HIVST if they can do it without assistance. This finding aligns with global evidence that autonomy and privacy are key facilitators of HIVST uptake [ 35 , 36 ]. Unassisted testing offers control over the testing process while minimizing stigma from health workers, peers, or partners – barriers to which AGYW are particularly vulnerable [ 37 , 38 ]. It also reduces practical obstacles such as scheduling, travel, and waiting times, while allowing immediate testing at moments of perceived risk. HIVST models targeting AGYW should therefore, prioritize unassisted testing to maximize acceptability and uptake. The distribution model provided participants with significant utility and ranked second in relative importance. While unassisted testing was the dominant driver of choice, the location from which test kits are obtained also played a key role in decision-making. Health facilities are often viewed as reliable sources of high-quality HIVST kits, with studies in SSA reporting strong trust in facility-based quality assurance [ 39 – 41 ], even when individuals prefer to test privately [ 41 ]. In addition, some young women may perceive facility staff as bound by confidentiality rules, which helps reduce fears of unwanted disclosure. Integrating unassisted HIVST access within trusted health facilities – particularly at primary care level – may therefore, maximize uptake. Furthermore, the efforts to further strengthen trust in these facilities among AGYW could enhance both HIVST use and broader service engagement. In this study, delivering HIVST kits through primary delivery channels provided greater utility than secondary distribution. AGYW preferred to collect test kits themselves rather than relying on others, partly because direct pick-up minimizes risks of unintended disclosure, reduces anxiety, and allows them autonomy to decide when to collect and use the HIVST kit. Evidence from Zimbabwe and Malawi similarly shows that youth prefer collecting kits from health facilities or pharmacies because of trust, confidentiality, and independence. While secondary distribution – particularly partner-delivered kits – has proven effective [ 42 ][ 43 ], it may be less suitable for unmarried youth or those facing high stigma, as it can compromise privacy. Importantly, the willingness of AGYW to pick up HIVST kits directly from trusted facilities creates opportunities to integrate kit distribution with other health services such as sexual and reproductive health counselling, family planning, STI clinics, and HIV prevention platforms including PrEP and PEP delivery – strengthening both reach and utility of other prevention commodities. The sample type (oral versus blood-based kits) was not a significant driver of choice and carried the lowest relative importance. For AGYW, the biological sample collection method was less influential compared to other features such as level of assistance, distribution model, and delivery channel. Similar to our findings, other studies have also ranked sample type lower than factors such as cost, access point, and level of assistance [ 44 ]. While some contexts suggest that oral swabs may be more acceptable due to their non-invasive nature [ 45 , 46 ], our results indicate that among AGYW, other HIVST features outweigh the sample collection method. Although blood-based kits are sometimes perceived as more accurate [ 47 ], oral kits are often viewed as easier and less painful. In Uganda, both types are approved for use, though oral HIVST kits remain more expensive. This creates an opportunity for implementers to expand access by making affordable blood-based HIVST kits available to young women, thereby supporting broader HIV testing uptake. Limitations This study employed a DCE to elicit stated preferences using hypothetical scenarios, which may not fully reflect actual behavior when AGYW are offered HIVST options. This could result in either over- or under-estimation of preferences. Furthermore, as HIVST becomes normalized, AGYW’s preferences may evolve over time; however, the cross-sectional design of this study did not allow assessment of such temporal trends. Although the attributes and levels were guided by MoH-recommended DSD models, the potential influence of cost, an important determinant of HIVST uptake, was not assessed. Some data were collected retrospectively and are subject to recall bias, though this was minimized by restricting the recall period to six months (except for HIV testing history, which extended to 12 months). Consecutive sampling, a non-probability technique, may have introduced selection bias by not giving every eligible participant an equal chance of inclusion. Similarly, the exclusion of participants who did not speak English or Luganda could have introduced bias; however, Luganda is widely spoken in the study setting. Finally, the study focused on HIV high-risk AGYW in urban settings, which may limit the generalizability of findings to rural or lower-risk populations. Despite these limitations, the potential biases are unlikely to have substantially affected the validity of the findings. Conclusions HIV high-risk AGYW living in urban settings showed a clear preference for unassisted HIVST, delivered through a facility-based distribution model and a primary-level delivery channel. While the type of test kit was less influential, the autonomy and convenience afforded by unassisted testing emerged as the strongest driver of HIVST service choice. Recommendations From the findings, we recommend that Ministries of Health and HIV program implementing partners to integrate unassisted HIVST into scale-up strategies for AGYW, ensuring that test kits are packaged with clear, youth-friendly instructions. This should be coupled with strengthening facility-based distribution, particularly through youth-friendly facilities, pharmacies, and drug shops with extended hours, to maximize accessibility. Such approaches will expand opportunities for AGYW to conveniently and confidentially obtain HIVST kits from trusted sources. Integration of HIVST into existing health-facility platforms – including sexual and reproductive health counselling, family planning, STI clinics, and HIV prevention services such as PrEP delivery sites – can further enhance distribution to HIV high-risk AGYW. Given that test kit type was not a significant driver of choice, Ministries of Health should focus on ensuring the availability and affordability of multiple kit options, rather than restricting scale-up to a single type. Future research should explore the influence of additional attributes not measured in this study, such as cost and willingness to pay, which may directly affect uptake. 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