Psychometric evaluations of the Theoretical Framework of Acceptability (TFA) among adolescent girls and young women in a low-resource setting

Psychometric evaluations of the Theoretical Framework of Acceptability (TFA) among adolescent girls and young women in a low-resource setting | 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 Research Article Psychometric evaluations of the Theoretical Framework of Acceptability (TFA) among adolescent girls and young women in a low-resource setting Laban Muteebwa, Patience A. Muwanguzi, Dan Muramuzi, Ivan Ahimbisibwe, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9271781/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 9 You are reading this latest preprint version Abstract Background The Theoretical Framework of Acceptability (TFA) provides a comprehensive lens for assessing acceptability of healthcare interventions. While the TFA has seven constructs, limited literature exists on its psychometric properties in low-resource settings and in the context of HIV prevention. This study assessed the validity and reliability of HIV self-testing (HIVST) acceptability scores measured using the TFA among adolescent girls and young women (AGYW) in Uganda. Methods We enrolled 377 AGYW aged 15–24 years in a cross sectional study and a structured questionnaire was used to collect data. The primary outcome was acceptability of HIVST defined as willingness to accept HIVST services if offered – measured using the seven constructs of the TFA where each was assessed with one 5-level Likert item question. Construct validation of TFA was examined using the exploratory factor analysis (EFA), confirmatory factor analysis (CFA) – through structural equation modelling (SEM), and convergent and divergent validity, while reliability was assessed with the Cronbach’s alpha. Factor extraction was guided by the scree plot, and factor rotation was performed using Oblimin method. Convergent and divergent validity were assessed by correlating the TFA acceptability scores with willingness to use HIVST and perceived HIV risk respectively. Results The median age of participants was 20 years (IQR: 18, 22). Although the scree plot suggested that three factors should be extracted, the rotated solution of the EFA yielded a single dominant factor, with all seven items loading strongly onto one latent factor. In the CFA, both SEM and generalized SEM showed consistent direction and strength of association between the TFA domains and the underlying acceptability construct despite the poor SEM global fit indices (RMSEA = 1.224, CFI = 0.173, TLI= -0.103). The correlation between acceptability scores and willingness to use HIVST, and perceived HIV risk was 0.7 and 0.1 respectively. The overall Cronbach’s alpha for the questionnaire items was 0.889. Conclusions This study provides empirical evidence supporting the construct validity and reliability of the TFA-measured acceptability scores among AGYW. All seven constructs demonstrated strong loadings on a single latent factor, indicating that the TFA operates as a coherent and unidimensional tool for measuring overall acceptability. Acceptability Theoretical Framework of Acceptability construct validity Reliability adolescent girls and young women low-resource setting HIV self-testing Figures Figure 1 Figure 2 Contributions to the literature The Theoretical Framework of Acceptability (TFA) is widely used for measuring acceptability of healthcare interventions, but there is limited evidence showing its psychometric performance among young people in low income countries. We found that the seven item TFA-based questionnaire can be used to measure acceptability of HIV self-testing among adolescent girls and young women in Uganda, and all parts of the questionnaire work together to measure one main idea of overall acceptability as initially theorized. The findings provide evidence that TFA-based measures of acceptability of interventions are reliable and valid among young women in low-resource settings. Background Acceptability is increasingly recognized and considered during the design, evaluation and implementation phases of public health interventions and strategies. Acceptability refers to the extent to which people delivering or receiving a healthcare intervention perceive it as appropriate, based on their cognitive and emotional responses [ 1 ]. Acceptability of an intervention is a reflective outcome, which presents challenges with its measurement. Sekhon and colleagues, (2017) developed a robust Theoretical Framework of Acceptability (TFA) grounded in literature and following acceptable principles of framework development [ 1 ]. The TFA has gained broad acceptance in Implementation Science because it provides a coherent structure for prospective, concurrent and retrospective assessment of user experience of interventions [ 1 ]. It has been applied in diverse settings, including tuberculosis care [ 2 ], maternal health [ 3 – 5 ], and digital health interventions [ 6 , 7 ]. The TFA has also been used in HIV-related research in Uganda [ 6 , 8 ]. Owing to the inconsistent use of TFA measurement, Sekhon and colleagues (2022) developed a generic (adaptable) TFA-informed questionnaire to guide the use of the framework [ 9 ]. Although it provides a well-articulated conceptual structure of assessing intervention acceptability, empirical evidence regarding the validity and reliability of TFA-based measurement tools remain limited particularly in low and middle income countries (LMICs) and among adolescent populations. The TFA conceptualizes acceptability as a multifaceted construct comprising of seven domains; affective attitude, burden, perceived effectiveness, ethicality, intervention coherence, opportunity costs and self-efficacy [ 1 ]. While these domains provide a theoretically grounded structure for understanding how individuals evaluate healthcare interventions, it is necessary to examine whether measurement items derived from the framework accurately capture the underlying construct when applied to different contexts and populations. In the context of HIV prevention, assessing acceptability is particularly important because the success of new interventions such as HIV self-testing (HIVST) depends not only on their clinical effectiveness but also on whether potential users perceive them as appropriate, feasible and worthwhile to adopt [ 1 , 10 ]. Adolescent girls and young women (AGYW) remain disproportionately affected by HIV in the Sub-Saharan African region (SSA), and the interventions targeting this sub-population must be both accessible and acceptable to ensure optimal uptake and sustained use. Although the TFA has increasingly been used to explore acceptability of health interventions in various settings, most studies have applied the framework qualitatively or descriptively, with limited attention to its psychometric performance as a quantitative measurement tool [ 9 ]. Establishing the measurement properties of TFA-based instruments is therefore essential for ensuring that acceptability scores derived from such tools accurately represent the theoretical construct and can be reliably used to guide implementation research and program design. Construct validation is a key step in psychometric evaluation, and refers to the extent to which a measurement tool accurately captures the theoretical concept it is intended to measure [ 11 , 12 ]. For multi-dimensional constructs such as acceptability, exploratory factor analysis (EFA) and the confirmatory factor analysis (CFA) are commonly used to examine whether the observed questionnaire items reflect the underlying latent structure hypothesized by the theoretical framework [ 13 – 15 ]. In this study, EFA was used to assess whether the items derived from the TFA domains collectively represents the latent concept of acceptability of HIVST among AGYW in Uganda. Then the CFA was used to test whether the pre-defined structure fit the observed data. In addition, convergent and divergent validity provide complementary evidence of construct validity. Convergent validity examines whether measures that are theoretically expected to be related are empirically correlated, whereas divergent (discriminant) validity assesses whether measures representing conceptually distinct constructs show weak or negligible correlations [ 16 ]. Reliability is another fundamental property of measurement instruments and refers to the degree to which a tool consistently measures an underlying construct across its component items [ 12 ]. In psychometric research, internal consistency reliability is commonly assessed using the Cronbach’s alpha which evaluates the extent to which the items in the scale measure the same latent concept [ 17 , 18 ]. Establishing reliability is particularly important when applying theoretically derived measurement tools in new populations or settings because variations in context, culture or interpretation of questionnaire items may influence the consistency of the responses. Demonstrating adequate reliability therefore strengthens confidence that an instrument provides coherent measurement of acceptability. This study aimed to assess the construct validity and internal consistent reliability of acceptability scores derived from the TFA when applied to measuring acceptability of HIVST among AGYW in Uganda. Methods Study design and setting This cross sectional study was conducted among AGYW living in the Kampala Metropolitan Area in Uganda. Kampala Metropolitan Area includes the four most populous districts in Central Uganda including Kampala, Wakiso, Mukono and Mpigi according to the 2024 National census [ 19 ]. 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 [ 20 ]. This region has one of the highest burden of HIV and consistently reports high numbers of new HIV infections [ 21 ]. 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 average (2023) of 5.1% [ 21 ]. Additionally, Kampala Metropolitan Area also accounted for the largest number of new HIV cases in 2023 (8,805) which threatens the gains on HIV epidemic control [ 21 ]. Study population and sampling procedure We enrolled 377 AGYW aged 15 to 24 years who had lived in the study area for at least six months, being sexually active (at least one sexual intercourse in the past six months) with an HIV risk score of ≥ 2 (high-risk), using and HIV risk assessment tool used by Ministry of Health and previously used among AGYW in Kampala, Uganda [ 22 , 23 ], and gave written informed consent (for adults and emancipated minors) or assent for minors in addition to their guardian’s consent. A multistage sampling design was used to select participants, where in the first stage two out of four districts (Kampala and Wakiso) were selected purposively because they had the highest HIV incident cases [ 21 ]. At the second stage, two divisions in Kampala city (Makindye and Rubaga divisions) and two municipalities in Wakiso (Entebbe and Nansana) were selected by simple random sampling. At the third stage, the study participants were selected from communities by consecutive sampling technique, but the number selected from each of the study divisions/municipalities were proportionately allocated based on 2024 population projections of AGYW [ 24 ]. Theoretical Framework of Acceptability (TFA) The TFA was developed by Skehon and colleagues (2017) after a comprehensive literature review and then applied principles of inductive and deductive reasoning to theorize the concept of acceptability [ 1 ]. The authors contend that acceptability of an intervention can be assessed prospectively (pre-intervention phase), concurrently (during implementation phase) or retrospectively (after the implementation phase). Particularly for the prospective acceptability, the authors contend that prior to experiencing an intervention, both recipients and providers can form judgements about whether they expect the intervention to be acceptable or unacceptable. Such judgements may be based on the information provided about the intervention. The framework specifies seven distinct constructs of acceptability: affective attitude, burden, perceived effectiveness, ethicality, intervention coherence, opportunity cost, and self-efficacy. A theoretically informed generic questionnaire was proposed to assess these constructs across healthcare settings [ 9 ]. It comprises seven five-level Likert item questions with each measuring one construct of the TFA. Sample size estimation This study was nested in a larger study that aimed to determine the acceptability of HIV self-testing services and preference of models for delivering HIVST testing services among AGYW. The parent study enrolled 377 participants between December 2024 and May 2025 [ 22 , 25 ]. However, recommendations based on number of questionnaire items show that at least 5–10 participants per item for EFA and 5–20 participants per item for CFA is sufficient [ 26 , 27 ]. With TFA-based questionnaire of seven items the sample size is at least 35–140 participants to cover both analyses. In this study we used all the 377 participants. Data collection tools and procedures The data was collected using a pre-tested structured questionnaire that captured the socio-demographic and behavioral characteristics of the AGYW as well as the measurement of acceptability of HIVST using the TFA [ 22 ]. The generic questionnaire developed by Sekhon and colleagues (2022) [ 28 ], was used to develop customized questions to measure acceptability of HIVST, with a guiding statement like “ How much do you agree or disagree that… ” to help the participant in using the Likert scale. Each of the seven constructs of the TFA was assessed using one 5-level Likert item question weighted 1 to 5 where a higher score represents high acceptability (supplementary file1). However the construct of ethicality was not reverse coded and a question on overall acceptability was not considered, as recommended in the original questionnaire [ 28 ]. The questionnaire was administered by trained research assistants from 1st December 2024 to 31st May 2025, and the responses captured in the Kobo collect toolkit ( https://www.kobotoolbox.org/ ). To assess willingness to use HIVST, participants were asked “If the HIVST services were available to you, on a scale of 0 to 10, where 0 means you can never use them and 10 means you will most definitely use them, how likely would you plan or be willing to use HIVST services?”. To assess the perceived HIV risk, participants were asked “On a scale of 0 to 10, where 0 means “no risk of getting HIV” and 10 means “a very high risk of getting HIV”, how would you grade your risk of getting HIV in the past 6 months?”. Data analysis The data analysis was conducted in STATA version 17.0 (Texas, USA). The descriptive statistics were used to summarize the data. Continuous variables were summarized using the median and interquartile range (IQR), while the categorical variables were summarized using frequencies and percentages. The validation of acceptability scores measured using the TFA was assessed using three approaches, that is, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), convergent validity and divergent validity. To conduct the exploratory factor analysis, the data was first assessed for suitability of factor analysis using the correlation matrix, the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and the Bartlett’s test of Sphericity. For the correlation matrix, the threshold was to observe correlation coefficients ≥ 0.3 in the matrix. For the KMO, the cutoff was set at 0.6 and the significance of the Bartlett’s test was set at P value < 0.05. All the TFA-based questionnaire items for measuring acceptability of HIVST were in the same direction and there was no missing data. The number of factors to extract was guided by the scree plot – a plot of Eigen values, where the point of inflection indicates the number of factors to extract. Principal factor extraction was used and the pattern matrix was rotated using the Oblimin orthogonal method, and the rotated pattern matrix was reported. Following EFA, CFA was performed within a structural equation modelling (SEM) framework to test the hypothesized factor structure (generated by EFA) using the maximum likelihood estimator (MLE). A unidimensional model was specified in which seven items were modeled as indicators of a single latent acceptability construct. Standardized factor loadings and their 95% confidence intervals (CIs) were examined to assess the strength of the relationship between each item and the latent construct. Model fit was evaluated using multiple indices, including the root mean square error of approximation (RMSEA), comparative fit index (CFI), Tucker-Lewis index (TLI), and standardized root mean square residual (SRMR). Given that the indicator items were measured using ordinal Likert scale responses, additional analyses were conducted using generalized SEM (GSEM) to account for the ordinal nature of the data. GSEM models were estimated using both the probit and ordinal logit link functions, with the observed indicator items specified as ordinal outcomes of the latent acceptability construct. Model comparison using Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) was used to identify the best fitting specification. The ordinal logit model was retained for final interpretation based on improved model fit. In building the GSEM ordinal logit model, the loading of “affective attitude” (anchor indicator) was fixed to “1” to scale the latent construct, and the log-odds coefficients and their 95% CIs were presented. For convergent validity, the participants were asked how willing they were to accept HIV self-testing services if offered on a scale of 0–10, where a higher score represented more willingness. This score was compared with the acceptability scores arising from the sum of weights of the seven questions used to assess the constructs of the TFA using the Pearson correlation. The assumption was that the two scores should be highly correlated with Pearson correlation coefficient value of ≥ 0.7. For divergent validity, the participants were asked to rate their perceived risk of acquiring HIV on a scale of 0–10, where a higher score represented a high HIV risk. This score was compared with the acceptability scores arising from the sum of weights of the seven questions used to assess the constructs of the TFA using the Pearson correlation. The assumption was that perceived HIV risk is a totally different construct from the acceptability of HIV self-testing, and therefore they shouldn’t be correlated. A Pearson correlation coefficient of < 0.3 demonstrated divergent validity. The reliability of the TFA questionnaire was assessed using the reliability coefficient (Cronbach’s alpha) to evaluate the extent to which the seven items consistently measured acceptability of HIVST. An alpha coefficient of ≥ 0.7 was considered acceptable. The item-total correlations and alpha values if an item was deleted were examined to assess the contribution of individual items. Results Socio-demographic characteristics of study participants The median age of the participants was 20 years (IQR; 18, 22), and about a third were still in school (34.5%). Majority of the AGYW (70.8%) were Christians, and about a quarter lived with their primary partners (27.3%). Close to half of AGYW (47.8%) were in sexual relationship with a partner older than them by ten or more years, 41.6% were employed and the median monthly income was US dollars $ 42.9 (IQR: 28.6–57.4) (Table 1 ). Table 1 Socio-demographic characteristics of AGYW enrolled in the study Variable Categories Frequency (N = 377) Percentage (%) Age (years) Median (IQR) 20 (18, 22) Schooling status In School 130 34.5 Not in school 247 65.5 Religion Christians 267 70.8 Moslems 107 28.4 No religion 3 0.8 Age difference with any partner < 10 years 197 52.2 ≥ 10 years 180 47.8 Live with primary partner Yes 103 27.3 No 274 72.7 Employment status Employed 157 41.6 Not Employed 220 56.4 Monthly income (USD)* Median (IQR) 42.9 (28.6–57.4) *Exchange rate at the time of writing: 1 USD ≈ 3500 Uganda Shillings (UGX). Behavioral characteristics Among the 377 participants, 82.8% had ever tested for HIV, 73.7% had tested within the past 12 months, and 43.2% had ever been pregnant. In the six months preceding the study, 13.3% had consistently used condoms, 29.2% reported to have multiple sexual partners and more than half (55.2%) reported to have had a sexually transmitted infection (STI). In the six months preceding the study, 11.7% of participants reported anal sex, 4.5% reported sharing injections, and 30.0% reported engaging in sexual intercourse in exchange for money or gifts. Additionally, 15.4% reported using illicit drugs before sexual intercourse. Use of HIV prevention methods was low, with only 6.6% and 5.7% of participants reporting the use of post-exposure prophylaxis (PEP) and pre-exposure prophylaxis (PrEP), respectively (Table 2 ). Table 2 Behavioral characteristics of AGYW enrolled in the study Variable Category Frequency (N = 377) Percentage (%) Ever tested for HIV Yes 312 82.8 No 65 17.2 Had HIV test in past 12 months* Yes 230 73.7 No 82 26.3 Ever pregnant Yes 163 43.2 No 214 56.8 Consistent condom use in past six months Yes 50 13.3 No 327 86.7 Had more than one sexual partner Yes 110 29.2 No 267 70.8 Had STI in past six months Yes 208 55.2 No 169 44.8 Shared injections in past six months Yes 17 4.5 No 360 95.5 Had anal sex in past six months Yes 44 (11.7) No 333 (88.3) Had sex in exchange of money/gifts in past six months Yes 113 30.0 No 264 70.0 Used illicit drugs before sex in past six months Yes 58 15.4 No 319 84.6 Used PEP in past six months Yes 25 6.6 No 352 93.4 Used PrEP in past six months Yes 20 5.7 No 357 94.7 *N = 312 Exploratory factor analysis (EFA) The data had a KMO of 0.88 and the Bartlett’s test of Sphericity was statistically significant (P value < 0.001). The scree plot showed three factors to be extracted (Fig. 1 ). Extraction of factors (rotated factor solution) On rotation of the factor loadings, all the variables load significantly on one factor (factor 1) with the loadings ranging from 0.64 to 0.82 (Table 3 ) Table 3 Rotated solution of factor loadings (pattern matrix) and unique variances Indicator item Factor 1 Factor 2* Uniqueness Affective attitude 0.75 0.43 Burden 0.64 0.49 0.35 Self-efficacy 0.64 0.48 0.35 Ethicality 0.69 0.51 Opportunity cost 0.74 0.45 Effectiveness 0.82 0.33 Coherence 0.82 0.32 *Factor loadings of < 0.3 were suppressed Confirmatory factor analysis (CFA) Structural equation modelling (SEM) The global model fit indices for the SEM were; RMSEA of 1.224, CFI of 0.173, TLI of -0.103, SRMR of 0.078 and the coefficient of determination (CD) was 0.917. The standardized factor loadings ranged from 0.72 to 0.807, of which the highest were observed for perceived effectiveness (0.81), intervention coherence (0.80) and affective attitude (0.80), while ethicality showed the lowest (0.72). All the factor loadings were significant with P values < 0.001 (Table 4 ) Table 4 The standardized factor loadings of the indicator items estimated by Structural Equation Modelling model Indicator item Standardized factor loading (95% CI) P value Residual variance (95% CI) Affective attitude 0.80 (0.76, 0.83) < 0.001 0.37 (0.32, 0.42) Burden 0.77 (0.73, 0.80) < 0.001 0.41 (0.36, 0.47) Self-efficacy 0.77 (0.73, 0.80) < 0.001 0.41 (0.36, 0.47) Ethicality 0.72 (0.68,0.76) < 0.001 0.48 (0.43, 0.55) Opportunity cost 0.79 (0.76, 0.82) < 0.001 0.38 (0.33, 0.43) Effectiveness 0.81 (0.78, 0.84) < 0.001 0.35 (0.31, 0.40) Coherence 0.80 (0.77, 0.83) < 0.001 0.36 (0.31, 0.41) Generalized structural equation modelling with ordinal logit model The GSEM yielded positive and significant log-odds coefficients for all domains. The strongest associations were observed for coherence (1.15) and perceived effectiveness (1.08), followed by opportunity cost (0.88) and ethicality (0.74). slightly lower associations were observed for burden (0.67) and self-efficacy (0.65). All estimated coefficients were significant with P values < 0.001 (Table 5 ) Table 5 The log-odds coefficients for the indicator items in a GSEM model Indicator item Log-odds coefficients (95% CI) P value Affective attitude 1 < 0.001 Burden 0.67 (0.49, 0.84) < 0.001 Self-efficacy 0.65 (0.48, 0.83) < 0.001 Ethicality 0.74 (0.53, 0.96) < 0.001 Opportunity cost 0.88 (0.65, 1.12) < 0.001 Effectiveness 1.08 (0.76, 1.39) < 0.001 Coherence 1.15 (0.82, 1.48) < 0.001 Convergent and divergent validity The Pearson correlation coefficient between the acceptability score from the seven constructs of TFA and the perceived willingness to accept HIV self-testing was 0.7 (Fig. 2 a). The Pearson correlation coefficient between the acceptability score from the seven constructs of TFA and perceived HIV risk was 0.1 (Fig. 2 b) Reliability of the TFA questionnaire The seven item TFA acceptability scale had an overall internal consistency (Cronbach’s alpha) of 0.889. The item-test and item-rest correlations were all > 0.3 (recommended threshold). The removal of any individual item did not result in a higher alpha value (Table 6 ). Table 6 Internal consistency reliability of the TFA acceptability scale Item Item-test correlation Item-rest correlation Average inter-item covariance Alpha Affective attitude 0.795 0.706 0.522 0.870 Burden 0.768 0.657 0.518 0.877 Ethicality 0.720 0.627 0.519 0.880 Intervention coherence 0.803 0.729 0.539 0.868 Opportunity cost 0.787 0.702 0.533 0.870 Perceived effectiveness 0.807 0.734 0.537 0.867 Self-efficacy 0.768 0.659 0.519 0.877 Overall scale 0.534 0.889 Discussion This study assessed the construct validity and internal consistency reliability of the TFA-measured acceptability scores among AGYW. The findings demonstrate that the seven TFA items function as a coherent and reliable measure of acceptability in this sub-population. EFA revealed a dominant single latent factor, which supports a unidimensional TFA-theorized acceptability. Furthermore, the CFA findings provided mixed evidence on construct validity where on one had the very strong and significant factor loadings in the SEM model indicate that each construct is highly correlated with the underlying acceptability construct while on the other hand, the poor global fit indices indicate that the hypothesized one-factor model does not adequately reproduce the observed covariance structure. However, the GSEM model that accounts for the ordinal nature of the TFA domain variables showed that the latent acceptability scores were positively and significantly associated with all the seven TFA domains which indicates that higher acceptability corresponds to higher levels across each domain. The direction and magnitude of the associations were consistent with the SEM findings, thus demonstrating strong and coherent relationships between the latent acceptability construct and observed indicator items Evidence of construct validity was further observed through strong convergent validity with willingness to use HIVST and weak divergent validity with perceived HIV risk. Internal consistency reliability was excellent and all items contributed meaningfully to the scale. Collectively, these findings support the validity and reliability of the TFA- measured acceptability scores among AGYW. Validity of the TFA- measured acceptability scores Although the TFA is conceptually organized into seven sub-domains, the EFA in this study identified a single dominant latent factor. This aligns with the theoretical underpinning of the TFA that all the seven constructs collectively measure one overarching domain of acceptability. Evidence from previous validation studies shows that in some settings fewer factors are extracted as compared to the theorized seven sub-domains. For instance, in the development of a digital health acceptability tool, Haydon and colleagues (2023) found that while the TFA informed the item generation, the responses primarily clustered into two broad dimensions (attitude and perceived capacity dimensions) rather than the seven sub-domains [ 28 ]. Similarly, another study on a telephone-facilitated health coaching intervention in Sweden identified fewer factors than the theoretical seven with items clustering under three main factors (affective attitude, coherence and burden) [ 29 ]. These two studies deviate from the theory behind the TFA by Sekhon and colleagues [ 1 ]. In our study, much as we report poor global fit indices of RMSEA, CFI and TLI that don’t meet the established SME fit criteria of acceptable model fit of < 0.06, ≥ 0.95 and ≥ 0.95 respectively [ 30 ], we note that the use of continuous SEM with ordinal Likert scale data may have violated distribution assumptions thus leasing to inflated misfit indices as previously reported [ 31 ]. Nonetheless, the SRMR value (0.078) falls within the acceptable limits based on recommended threshold of ≤ 0.08 [ 30 ], suggesting that absolute residual differences are relatively small. This pattern has been reported in literature particularly in large samples or when analyzing ordinal data [ 31 ]. The use of an ordinal logit link in the GSEM provide better representation of the Likert scale responses, addressing the limitations of treating ordinal variables as continuous. The GSEM findings in our study showed that all the latent acceptability scores were positively and significantly associated with all the seven TFA domains, which reinforces the construct validity of the TFA-measured acceptability scores. The consistency in direction and strength of these associations suggests that the domains operate as coherent indicators of acceptability, even when modeled using an ordinal framework. The consistency between the SEM and GSEM findings suggest that the poor global fit in the SEM may be partly attributable to modelling assumptions rather than true construct validity. Taken together, the findings from the EFA, SEM and the GSEM support the construct validity of the TFA-measured acceptability scores. Further validity testing showed evidence of convergent validity with the acceptability score strongly correlated with the participants’ willingness to use HIVST. Methodological standards suggest that a correlation coefficient of ≥ 0.7 is considered evidence of strong convergence between constructs that should in theory be related [ 32 , 33 ]. Thus, the observed correlation in our study supports the assertion that the TFA is indeed capturing the underlying construct of acceptability. In contrast divergent validity was also supported by the weak correlation between the acceptability score and perceived HIV risk. The weak correlation in this study therefore, demonstrates that the TFA measure is not merely reflecting general perceptions but specifically capturing the intervention acceptability. Findings from other TFA validation studies further support this interpretation. For example, the higher acceptability scores were significantly associated with participants’ willingness to engage in health coaching [ 29 ]. Similarly, in a study aimed at developing a digital health tool, the acceptability scores were strongly related to self-reported intension to use telehealth service, while showing weak correlation with unrelated psychological constructs [ 28 ]. This supports both convergent and divergent validity. The observed convergent and divergent validity in our study further confirm that the TFA scale is conceptually coherent and provides empirical evidence of its construct validity of acceptability scores. This strengthens confidence in the TFA’s applicability for assessing the acceptability of health interventions like HIVST among AGYW in low-resource settings. Internal consistency reliability of the TFA The TFA acceptability scale demonstrated good internal consistency reliability in measuring acceptability scores with a strong Cronbach’s alpha. All items exhibited strong item-test and item-rest correlations, suggesting that each construct contributed meaningfully to the overall scale without redundancy. Importantly, removal of any individual item did not improve the Cronbach’s alpha thus supporting retention of all seven TFA sub-domains in the final TFA-based measurement of acceptability. According to psychometric standards, Cronbach’s alpha of > 0.8 reflects strong internal coherence of multi-item scales assessing latent constructs [ 12 , 17 , 34 ]. Similar levels of internal consistency have been reported in other studies applying TFA-informed measures of acceptability across health interventions [ 6 , 29 ]. This further supports the reliability of the framework when operationalized quantitatively. Therefore, these findings provide evidence that the TFA-based measurement of acceptability is reliable for measuring health intervention acceptability among AGYW in low-resource settings. Limitations This study has some limitations that should be considered when interpreting the findings. First, the data were cross sectional, which limits the ability to assess how acceptability may change over time. Secondly, all the measures relied on self-reported data which may be subject to recall and social desirability bias, particularly given the sensitivity of HIV-related behaviors, however, the period of recall was limited to six months apart from the period of past HIV testing (12 months). Thirdly, the study participants were selected using a non-probability sampling technique which may have introduced selection bias. The study focused on AGYW in urban settings, and while this is a key population for HIV prevention, the results may have limited generalizability to other age groups, gender or settings. Nonetheless, the systematic biases highlighted may have had minimal influence on the findings. Conclusions This study provides empirical evidence supporting the construct validity and reliability of acceptability scores measured using the TFA among AGYW in Uganda. The seven TFA-informed items collectively formed a single latent acceptability construct and demonstrate strong convergent validity with willingness to use HIVST, weak divergent validity with perceived HIV risk, and strong internal consistency reliability. The scale may serve as a useful quantitative tool for measuring intervention acceptability among AGYW in similar low-resource settings. Declarations Ethical considerations The study was approved by the Makerere University School of Medicine Research Ethics Committee under the reference number Mak-SOMREC-2023-843. Further clearance was obtained from the Uganda National Council for Science and Technology (UNCST) under the reference number HS5167ES. The administrative clearance to conduct the study was obtained from the Kampala Capital City Authority (KCCA), and the Municipal Health Offices of Entebbe and Nansana Municipalities. The adult and emancipated minors provided written informed consent, while the other minors (<18 years) gave written informed assent in addition to their guardian’s written informed consent following the UNCST guidelines (25). Acknowledgements We acknowledge the study participants for creating time to participate in this study. We acknowledge the Village Health Teams of Kampala and Wakiso districts for their support in participant mobilization Funding The findings and data reported in this publication were supported by the Fogarty International Center and the National Institute of Mental Health of the National Institutes of Health under Award Number D43 TW010037 (to FCS). The contents are solely the responsibility of the authors and do not necessarily represent the official views of the National Institutes of Health. The funders had no role in the study conceptualization, design, data collection and analysis, decision to publish or preparation of the Manuscript. Clinical trial number Not applicable Consent for publication Not applicable Competing interests The authors declare no competing interests Author contribution LM, PAM, JN and FCS conceived and conceptualized the research idea. LM, PAM, IA, SN, DM and CT were instrumental in refining the research idea and methodology. LM, DM, IA, EA, CT and SN were instrumental in data collection and management. LM, IA, CT, PAM and SN conducted the initial data analysis. LM, PAM and JN drafted the initial manuscript. All co-authors reviewed and approved the final version of the manuscript. Availability of datasets and materials The datasets analyzed during the current study are available from the corresponding author on reasonable request References Sekhon M, Cartwright M, Francis JJ. Acceptability of healthcare interventions: an overview of reviews and development of a theoretical framework. BMC Health Serv Res. 2017;17:1–13. Mukora R, Ahumah B, Maraba N, Orrell C, Jennings L, Naidoo P, et al. Acceptability of using the medication monitor and experience of a differentiated care approach for TB treatment adherence among people living with TB in South Africa. PLOS Glob public Heal. 2023;3:e0001885. Chen A, Väyrynen K, Leskelä R, Torkki P, Heinonen S, Tekay A, et al. The acceptability of implementing patient‐reported measures in routine maternity care: A systematic review. Acta Obstet Gynecol Scand. 2023;102:406–19. Nyumwa P, Bula AK, Nyondo-Mipando AL. Perceptions on acceptability of the 2016 WHO ANC model among the pregnant women in Phalombe District, Malawi–a qualitative study using Theoretical Framework of Acceptability. BMC Pregnancy Childbirth. 2023;23:166. Meades R, Moran PM, Hutton U, Khan R, Maxwell M, Cheyne H, et al. Acceptability of identification and management of perinatal anxiety: a qualitative interview study with postnatal women. Front Public Heal. 2024;12:1466150. Laban M, Nakku EJ, Nangendo J, Muramuzi D, Akello F, Bakeera SK, et al. Acceptability of short message service reminders as the support tool for PrEP adherence among young women in Mukono district, Uganda. PLOS Glob public Heal. 2024;4:e0002492. Mtenga AE, Maro RA, Dillip A, Msoka P, Emmanuel N, Ngowi K, et al. Acceptability of a Digital Adherence Tool Among Patients With Tuberculosis and Tuberculosis Care Providers in Kilimanjaro Region, Tanzania: Mixed Methods Study. Online J Public Health Inform. 2024;16:e51662. Matovu JKB, Bogart LM, Nakabugo J, Kagaayi J, Serwadda D, Wanyenze RK, et al. Feasibility and acceptability of a pilot, peer-led HIV self-testing intervention in a hyperendemic fishing community in rural Uganda. PLoS One. 2020;15:e0236141. Sekhon M, Cartwright M, Francis JJ. Development of a theory-informed questionnaire to assess the acceptability of healthcare interventions. BMC Health Serv Res. 2022;22:279. Proctor E, Silmere H, Raghavan R, Hovmand P, Aarons G, Bunger A, et al. Outcomes for implementation research: conceptual distinctions, measurement challenges, and research agenda. Adm policy Ment Heal Ment Heal Serv Res. 2011;38:65–76. Smith GT. On construct validity: issues of method and measurement. Psychol Assess. 2005;17:396. DeVellis RF, Thorpe CT. Scale development: Theory and applications. Sage publications; 2021. Hu Z, Li J. The integration of EFA and CFA: One method of evaluating the construct validity. Glob J Hum Soc Sci. 2015;15:15–9. Hair JF, Black WC, Babin BJ, Anderson RE, Tatham RL. Multivariate data analysis (Vol. 6). 2006; Alavi M, Biros E, Cleary M. Notes to factor analysis techniques for construct validity. Can J Nurs Res. 2024;56:164–70. Campbell DT, Fiske DW. Convergent and discriminant validation by the multitrait-multimethod matrix. Psychol Bull. 1959;56:81. Tavakol M, Dennick R. Making sense of Cronbach’s alpha. Int J Med Educ. 2011;2:53. Kline RB. Nunnally, jc, & bernstein, ih (1994). Psychometric Theory. J Psychoeduc Assess. 1999;17:275–80. UBOS. National Population and Housing Census 2024, Final Report. Kampala; 2024. Mukwaya PI, Mbabazi J, Ernstson H. Kampala: city report. Kampala; 2025. Uganda AIDS Commission. 2024 Uganda HIV and AIDS Factsheet [Internet]. 2024 [cited 2025 Aug 8]. Available from: https://uac.go.ug/index.php/easy-customization/custom-404-page-and-offline-page Muteebwa L, Nangendo J, Muramuzi D, Nuwasiima S, Ahimbisibwe I, Atwine E, et al. Acceptability of HIV self-testing among HIV high-risk Adolescent Girls and Young Women (AGYW) in urban settings in Uganda. PLOS Glob Public Heal. 2026;6:e0005857. Mayanja Y, Kamacooko O, Lunkuse JF, Muturi‐Kioi V, Buzibye A, Omali D, et al. Oral pre‐exposure prophylaxis preference, uptake, adherence and continuation among adolescent girls and young women in Kampala, Uganda: a prospective cohort study. J Int AIDS Soc. 2022;25:e25909. Uganda Breau of Statistics (UBOS). Gender statistics portal; one-stop center for gender statistics in Uganda [Internet]. 2026 [cited 2025 Nov 24]. Available from: http://gender.ubos.org:8080/ Muteebwa L, Muwanguzi PA, Nuwasiima S, Ahimbisibwe I, Atwine E, Muramuzi D, et al. HIV self-testing preferences among HIV high-risk Adolescent Girls and Young Women (AGYW) in urban settings in Uganda: A Discrete Choice Experiment. medRxiv. 2025;2010–25. Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate data analysis. 2019; Costello AB, Osborne J. Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Pract assessment, Res Eval. 2005;10. Haydon HM, Major T, Kelly JT, Catapan S de C, Caffery LJ, Smith AC, et al. Development and validation of the digital health acceptability questionnaire. J Telemed Telecare. 2023;29:8S-15S. Timm L, Annerstedt KS, Ahlgren JÁ, Absetz P, Alvesson HM, Forsberg BC, et al. Application of the Theoretical Framework of Acceptability to assess a telephone-facilitated health coaching intervention for the prevention and management of type 2 diabetes. PLoS One. 2022;17:e0275576. Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct Equ Model a Multidiscip J. 1999;6:1–55. Kline RB. Principles and practice of structural equation modeling. Guilford publications; 2023. Hair JF. Multivariate data analysis. 2009; Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Mark Res. 1981;18:39–50. Nunnally J, Bernstein I. Psychometric Theory 3rd edition (MacGraw-Hill, New York). 1994. Additional Declarations No competing interests reported. Supplementary Files Supplementaryfile1.pdf Supplementary file1 – TFA-based questionnaire used in the study Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 19 May, 2026 Reviews received at journal 12 May, 2026 Reviewers agreed at journal 01 May, 2026 Reviews received at journal 26 Apr, 2026 Reviewers agreed at journal 15 Apr, 2026 Reviewers invited by journal 14 Apr, 2026 Editor assigned by journal 13 Apr, 2026 Submission checks completed at journal 31 Mar, 2026 First submitted to journal 30 Mar, 2026 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9271781","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":623551675,"identity":"dd7f9f0b-2218-4175-bf69-7574130d1167","order_by":0,"name":"Laban Muteebwa","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0ElEQVRIiWNgGAWjYHACxgOMDUCKHUQYWBCjg5kBooXnAEiLBClaJBJAPCK06M7IP3Dg5w67PPmZz69u+FEgwcDf3p2AV4vZjWSGg71nkosNbueU3ewBOkzizNkNBLUc4G1jTtwgnZN2gweoxUAil7CWg3/b6hPnzzyTdvMPsVoO87YdTmy4wX7sNnG2nHlscFj2zPHEDWdy2G7LGEjwEPbL8cSHD9/uqE6c33782c03f2zk+Nt78WtBAjwGYJJY5SDA/oAU1aNgFIyCUTCCAAAXs09/eBLfrQAAAABJRU5ErkJggg==","orcid":"","institution":"Makerere University","correspondingAuthor":true,"prefix":"","firstName":"Laban","middleName":"","lastName":"Muteebwa","suffix":""},{"id":623551677,"identity":"af66bb43-4d54-4143-ac86-bc4298479af8","order_by":1,"name":"Patience A. Muwanguzi","email":"","orcid":"","institution":"Makerere University","correspondingAuthor":false,"prefix":"","firstName":"Patience","middleName":"A.","lastName":"Muwanguzi","suffix":""},{"id":623551680,"identity":"ad9f315d-f2bb-4790-8186-ea3b627ea3a3","order_by":2,"name":"Dan Muramuzi","email":"","orcid":"","institution":"Makerere University","correspondingAuthor":false,"prefix":"","firstName":"Dan","middleName":"","lastName":"Muramuzi","suffix":""},{"id":623551683,"identity":"7cf6c689-8525-4d2b-87e9-06225b51c592","order_by":3,"name":"Ivan Ahimbisibwe","email":"","orcid":"","institution":"Makerere University","correspondingAuthor":false,"prefix":"","firstName":"Ivan","middleName":"","lastName":"Ahimbisibwe","suffix":""},{"id":623551684,"identity":"2f568196-1cfe-41ed-986a-bb013ddae144","order_by":4,"name":"Shivan Nuwasiima","email":"","orcid":"","institution":"Makerere University","correspondingAuthor":false,"prefix":"","firstName":"Shivan","middleName":"","lastName":"Nuwasiima","suffix":""},{"id":623551685,"identity":"481486ee-ab71-403e-b3a0-0078ef31808a","order_by":5,"name":"Cathbert Tumusiime","email":"","orcid":"","institution":"Baylor College of Medicine Children’s Foundation-Uganda","correspondingAuthor":false,"prefix":"","firstName":"Cathbert","middleName":"","lastName":"Tumusiime","suffix":""},{"id":623551687,"identity":"03bf9cfc-6773-467c-967d-8f19760ea70a","order_by":6,"name":"Edson Atwine","email":"","orcid":"","institution":"Makerere University Business School, Makerere University","correspondingAuthor":false,"prefix":"","firstName":"Edson","middleName":"","lastName":"Atwine","suffix":""},{"id":623551689,"identity":"b44f8f9a-9a9e-407b-9697-472b54764c24","order_by":7,"name":"Fred C. Semitala","email":"","orcid":"","institution":"Makerere University","correspondingAuthor":false,"prefix":"","firstName":"Fred","middleName":"C.","lastName":"Semitala","suffix":""},{"id":623551691,"identity":"37186dc4-fa79-46f8-a04f-481b8bfe02db","order_by":8,"name":"Joanita Nangendo","email":"","orcid":"","institution":"Makerere University","correspondingAuthor":false,"prefix":"","firstName":"Joanita","middleName":"","lastName":"Nangendo","suffix":""}],"badges":[],"createdAt":"2026-03-30 20:38:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9271781/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9271781/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107616834,"identity":"adbe9fa2-2353-4412-a4fb-3f86bc930ae3","added_by":"auto","created_at":"2026-04-23 09:16:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":16816,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eScree plot of Eigen values\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9271781/v1/630550b18c93f8dd886b2820.png"},{"id":107616835,"identity":"188f738c-bd88-4fa2-bf43-6d500d0bb75e","added_by":"auto","created_at":"2026-04-23 09:16:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":232701,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ea: Scatter plot for acceptability score from TFA and willingness to use HIVST\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb: Scatter plot for acceptability score from TFA and perceived HIV risk\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9271781/v1/5c26802fc9a43a25534f8e5e.png"},{"id":107707059,"identity":"ec59e57f-ad95-4892-b5df-d5a20ff718cc","added_by":"auto","created_at":"2026-04-24 09:19:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":626622,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9271781/v1/8a7ebcfc-0345-4b54-b16a-1c8fc2fe3b62.pdf"},{"id":107616836,"identity":"0335cc9e-16b9-4c93-899c-73e0c6cc3c34","added_by":"auto","created_at":"2026-04-23 09:16:11","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":96311,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary file1 \u003c/strong\u003e– TFA-based questionnaire used in the study\u003c/p\u003e","description":"","filename":"Supplementaryfile1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9271781/v1/fd59572a098cc0ee76b6165b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Psychometric evaluations of the Theoretical Framework of Acceptability (TFA) among adolescent girls and young women in a low-resource setting","fulltext":[{"header":"Contributions to the literature","content":"\u003cul\u003e\n \u003cli\u003eThe Theoretical Framework of Acceptability (TFA) is widely used for measuring acceptability of healthcare interventions, but there is limited evidence showing its psychometric performance among young people in low income countries.\u003c/li\u003e\n \u003cli\u003eWe found that the seven item TFA-based questionnaire can be used to measure acceptability of HIV self-testing among adolescent girls and young women in Uganda, and all parts of the questionnaire work together to measure one main idea of overall acceptability as initially theorized.\u003c/li\u003e\n \u003cli\u003eThe findings provide evidence that TFA-based measures of acceptability of interventions are reliable and valid among young women in low-resource settings.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Background","content":"\u003cp\u003eAcceptability is increasingly recognized and considered during the design, evaluation and implementation phases of public health interventions and strategies. Acceptability refers to the extent to which people delivering or receiving a healthcare intervention perceive it as appropriate, based on their cognitive and emotional responses [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Acceptability of an intervention is a reflective outcome, which presents challenges with its measurement. Sekhon and colleagues, (2017) developed a robust Theoretical Framework of Acceptability (TFA) grounded in literature and following acceptable principles of framework development [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The TFA has gained broad acceptance in Implementation Science because it provides a coherent structure for prospective, concurrent and retrospective assessment of user experience of interventions [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. It has been applied in diverse settings, including tuberculosis care [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], maternal health [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], and digital health interventions [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The TFA has also been used in HIV-related research in Uganda [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Owing to the inconsistent use of TFA measurement, Sekhon and colleagues (2022) developed a generic (adaptable) TFA-informed questionnaire to guide the use of the framework [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Although it provides a well-articulated conceptual structure of assessing intervention acceptability, empirical evidence regarding the validity and reliability of TFA-based measurement tools remain limited particularly in low and middle income countries (LMICs) and among adolescent populations. The TFA conceptualizes acceptability as a multifaceted construct comprising of seven domains; affective attitude, burden, perceived effectiveness, ethicality, intervention coherence, opportunity costs and self-efficacy [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. While these domains provide a theoretically grounded structure for understanding how individuals evaluate healthcare interventions, it is necessary to examine whether measurement items derived from the framework accurately capture the underlying construct when applied to different contexts and populations.\u003c/p\u003e \u003cp\u003eIn the context of HIV prevention, assessing acceptability is particularly important because the success of new interventions such as HIV self-testing (HIVST) depends not only on their clinical effectiveness but also on whether potential users perceive them as appropriate, feasible and worthwhile to adopt [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Adolescent girls and young women (AGYW) remain disproportionately affected by HIV in the Sub-Saharan African region (SSA), and the interventions targeting this sub-population must be both accessible and acceptable to ensure optimal uptake and sustained use. Although the TFA has increasingly been used to explore acceptability of health interventions in various settings, most studies have applied the framework qualitatively or descriptively, with limited attention to its psychometric performance as a quantitative measurement tool [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Establishing the measurement properties of TFA-based instruments is therefore essential for ensuring that acceptability scores derived from such tools accurately represent the theoretical construct and can be reliably used to guide implementation research and program design.\u003c/p\u003e \u003cp\u003eConstruct validation is a key step in psychometric evaluation, and refers to the extent to which a measurement tool accurately captures the theoretical concept it is intended to measure [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. For multi-dimensional constructs such as acceptability, exploratory factor analysis (EFA) and the confirmatory factor analysis (CFA) are commonly used to examine whether the observed questionnaire items reflect the underlying latent structure hypothesized by the theoretical framework [\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In this study, EFA was used to assess whether the items derived from the TFA domains collectively represents the latent concept of acceptability of HIVST among AGYW in Uganda. Then the CFA was used to test whether the pre-defined structure fit the observed data. In addition, convergent and divergent validity provide complementary evidence of construct validity. Convergent validity examines whether measures that are theoretically expected to be related are empirically correlated, whereas divergent (discriminant) validity assesses whether measures representing conceptually distinct constructs show weak or negligible correlations [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eReliability is another fundamental property of measurement instruments and refers to the degree to which a tool consistently measures an underlying construct across its component items [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. In psychometric research, internal consistency reliability is commonly assessed using the Cronbach\u0026rsquo;s alpha which evaluates the extent to which the items in the scale measure the same latent concept [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Establishing reliability is particularly important when applying theoretically derived measurement tools in new populations or settings because variations in context, culture or interpretation of questionnaire items may influence the consistency of the responses. Demonstrating adequate reliability therefore strengthens confidence that an instrument provides coherent measurement of acceptability. This study aimed to assess the construct validity and internal consistent reliability of acceptability scores derived from the TFA when applied to measuring acceptability of HIVST among AGYW in Uganda.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003eThis cross sectional study was conducted among AGYW living in the Kampala Metropolitan Area in Uganda. Kampala Metropolitan Area includes the four most populous districts in Central Uganda including Kampala, Wakiso, Mukono and Mpigi according to the 2024 National census [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. 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 [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. This region has one of the highest burden of HIV and consistently reports high numbers of new HIV infections [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The HIV prevalence among adults aged 15\u0026ndash;49 years (2023) in Kampala, Wakiso, Mpigi and Mukono is 7.4%, 7.2%, 8.2% and 5.3% respectively, all above the national average (2023) of 5.1% [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Additionally, Kampala Metropolitan Area also accounted for the largest number of new HIV cases in 2023 (8,805) which threatens the gains on HIV epidemic control [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy population and sampling procedure\u003c/h3\u003e\n\u003cp\u003eWe enrolled 377 AGYW aged 15 to 24 years who had lived in the study area for at least six months, being sexually active (at least one sexual intercourse in the past six months) with an HIV risk score of \u0026ge;\u0026thinsp;2 (high-risk), using and HIV risk assessment tool used by Ministry of Health and previously used among AGYW in Kampala, Uganda [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], and gave written informed consent (for adults and emancipated minors) or assent for minors in addition to their guardian\u0026rsquo;s consent. A multistage sampling design was used to select participants, where in the first stage two out of four districts (Kampala and Wakiso) were selected purposively because they had the highest HIV incident cases [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. At the second stage, two divisions in Kampala city (Makindye and Rubaga divisions) and two municipalities in Wakiso (Entebbe and Nansana) were selected by simple random sampling. At the third stage, the study participants were selected from communities by consecutive sampling technique, but the number selected from each of the study divisions/municipalities were proportionately allocated based on 2024 population projections of AGYW [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eTheoretical Framework of Acceptability (TFA)\u003c/h3\u003e\n\u003cp\u003eThe TFA was developed by Skehon and colleagues (2017) after a comprehensive literature review and then applied principles of inductive and deductive reasoning to theorize the concept of acceptability [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The authors contend that acceptability of an intervention can be assessed prospectively (pre-intervention phase), concurrently (during implementation phase) or retrospectively (after the implementation phase). Particularly for the prospective acceptability, the authors contend that prior to experiencing an intervention, both recipients and providers can form judgements about whether they expect the intervention to be acceptable or unacceptable. Such judgements may be based on the information provided about the intervention. The framework specifies seven distinct constructs of acceptability: affective attitude, burden, perceived effectiveness, ethicality, intervention coherence, opportunity cost, and self-efficacy. A theoretically informed generic questionnaire was proposed to assess these constructs across healthcare settings [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. It comprises seven five-level Likert item questions with each measuring one construct of the TFA.\u003c/p\u003e\n\u003ch3\u003eSample size estimation\u003c/h3\u003e\n\u003cp\u003eThis study was nested in a larger study that aimed to determine the acceptability of HIV self-testing services and preference of models for delivering HIVST testing services among AGYW. The parent study enrolled 377 participants between December 2024 and May 2025 [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, recommendations based on number of questionnaire items show that at least 5\u0026ndash;10 participants per item for EFA and 5\u0026ndash;20 participants per item for CFA is sufficient [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. With TFA-based questionnaire of seven items the sample size is at least 35\u0026ndash;140 participants to cover both analyses. In this study we used all the 377 participants.\u003c/p\u003e\n\u003ch3\u003eData collection tools and procedures\u003c/h3\u003e\n\u003cp\u003eThe data was collected using a pre-tested structured questionnaire that captured the socio-demographic and behavioral characteristics of the AGYW as well as the measurement of acceptability of HIVST using the TFA [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The generic questionnaire developed by Sekhon and colleagues (2022) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], was used to develop customized questions to measure acceptability of HIVST, with a guiding statement like \u0026ldquo;\u003cem\u003eHow much do you agree or disagree that\u0026hellip;\u003c/em\u003e\u0026rdquo; to help the participant in using the Likert scale. Each of the seven constructs of the TFA was assessed using one 5-level Likert item question weighted 1 to 5 where a higher score represents high acceptability (supplementary file1). However the construct of ethicality was not reverse coded and a question on overall acceptability was not considered, as recommended in the original questionnaire [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The questionnaire was administered by trained research assistants from 1st December 2024 to 31st May 2025, and the responses captured in the Kobo collect toolkit (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.kobotoolbox.org/\u003c/span\u003e\u003cspan address=\"https://www.kobotoolbox.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). To assess willingness to use HIVST, participants were asked \u0026ldquo;If the HIVST services were available to you, on a scale of 0 to 10, where 0 means you can never use them and 10 means you will most definitely use them, how likely would you plan or be willing to use HIVST services?\u0026rdquo;. To assess the perceived HIV risk, participants were asked \u0026ldquo;On a scale of 0 to 10, where 0 means \u0026ldquo;no risk of getting HIV\u0026rdquo; and 10 means \u0026ldquo;a very high risk of getting HIV\u0026rdquo;, how would you grade your risk of getting HIV in the past 6 months?\u0026rdquo;.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eThe data analysis was conducted in STATA version 17.0 (Texas, USA). The descriptive statistics were used to summarize the data. Continuous variables were summarized using the median and interquartile range (IQR), while the categorical variables were summarized using frequencies and percentages. The validation of acceptability scores measured using the TFA was assessed using three approaches, that is, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), convergent validity and divergent validity. To conduct the exploratory factor analysis, the data was first assessed for suitability of factor analysis using the correlation matrix, the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and the Bartlett\u0026rsquo;s test of Sphericity. For the correlation matrix, the threshold was to observe correlation coefficients\u0026thinsp;\u0026ge;\u0026thinsp;0.3 in the matrix. For the KMO, the cutoff was set at 0.6 and the significance of the Bartlett\u0026rsquo;s test was set at P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. All the TFA-based questionnaire items for measuring acceptability of HIVST were in the same direction and there was no missing data. The number of factors to extract was guided by the scree plot \u0026ndash; a plot of Eigen values, where the point of inflection indicates the number of factors to extract. Principal factor extraction was used and the pattern matrix was rotated using the Oblimin orthogonal method, and the rotated pattern matrix was reported. Following EFA, CFA was performed within a structural equation modelling (SEM) framework to test the hypothesized factor structure (generated by EFA) using the maximum likelihood estimator (MLE). A unidimensional model was specified in which seven items were modeled as indicators of a single latent acceptability construct. Standardized factor loadings and their 95% confidence intervals (CIs) were examined to assess the strength of the relationship between each item and the latent construct. Model fit was evaluated using multiple indices, including the root mean square error of approximation (RMSEA), comparative fit index (CFI), Tucker-Lewis index (TLI), and standardized root mean square residual (SRMR). Given that the indicator items were measured using ordinal Likert scale responses, additional analyses were conducted using generalized SEM (GSEM) to account for the ordinal nature of the data. GSEM models were estimated using both the probit and ordinal logit link functions, with the observed indicator items specified as ordinal outcomes of the latent acceptability construct. Model comparison using Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) was used to identify the best fitting specification. The ordinal logit model was retained for final interpretation based on improved model fit. In building the GSEM ordinal logit model, the loading of \u0026ldquo;affective attitude\u0026rdquo; (anchor indicator) was fixed to \u0026ldquo;1\u0026rdquo; to scale the latent construct, and the log-odds coefficients and their 95% CIs were presented. For convergent validity, the participants were asked how willing they were to accept HIV self-testing services if offered on a scale of 0\u0026ndash;10, where a higher score represented more willingness. This score was compared with the acceptability scores arising from the sum of weights of the seven questions used to assess the constructs of the TFA using the Pearson correlation. The assumption was that the two scores should be highly correlated with Pearson correlation coefficient value of \u0026ge;\u0026thinsp;0.7. For divergent validity, the participants were asked to rate their perceived risk of acquiring HIV on a scale of 0\u0026ndash;10, where a higher score represented a high HIV risk. This score was compared with the acceptability scores arising from the sum of weights of the seven questions used to assess the constructs of the TFA using the Pearson correlation. The assumption was that perceived HIV risk is a totally different construct from the acceptability of HIV self-testing, and therefore they shouldn\u0026rsquo;t be correlated. A Pearson correlation coefficient of \u0026lt;\u0026thinsp;0.3 demonstrated divergent validity. The reliability of the TFA questionnaire was assessed using the reliability coefficient (Cronbach\u0026rsquo;s alpha) to evaluate the extent to which the seven items consistently measured acceptability of HIVST. An alpha coefficient of \u0026ge;\u0026thinsp;0.7 was considered acceptable. The item-total correlations and alpha values if an item was deleted were examined to assess the contribution of individual items.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003eSocio-demographic characteristics of study participants\u003c/h2\u003e\n \u003cp\u003eThe median age of the participants was 20 years (IQR; 18, 22), and about a third were still in school (34.5%). Majority of the AGYW (70.8%) were Christians, and about a quarter lived with their primary partners (27.3%). Close to half of AGYW (47.8%) were in sexual relationship with a partner older than them by ten or more years, 41.6% were employed and the median monthly income was US dollars \u003cspan\u003e$\u003c/span\u003e42.9 (IQR: 28.6\u0026ndash;57.4) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSocio-demographic characteristics of AGYW enrolled in the study\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCategories\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eFrequency (N\u0026thinsp;=\u0026thinsp;377)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003ePercentage (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e20 (18, 22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSchooling status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eIn School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e34.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNot in school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e247\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e65.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eReligion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eChristians\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e267\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e70.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMoslems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e28.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo religion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eAge difference with any partner\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;10 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e52.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;10 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e47.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eLive with primary partner\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e27.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e274\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e72.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEmployment status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e41.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNot Employed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e56.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eMonthly income (USD)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e42.9 (28.6\u0026ndash;57.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cem\u003e*Exchange rate at the time of writing: 1 USD\u0026thinsp;\u0026asymp;\u0026thinsp;3500 Uganda Shillings (UGX).\u003c/em\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eBehavioral characteristics\u003c/h2\u003e\n \u003cp\u003eAmong the 377 participants, 82.8% had ever tested for HIV, 73.7% had tested within the past 12 months, and 43.2% had ever been pregnant. In the six months preceding the study, 13.3% had consistently used condoms, 29.2% reported to have multiple sexual partners and more than half (55.2%) reported to have had a sexually transmitted infection (STI). In the six months preceding the study, 11.7% of participants reported anal sex, 4.5% reported sharing injections, and 30.0% reported engaging in sexual intercourse in exchange for money or gifts. Additionally, 15.4% reported using illicit drugs before sexual intercourse. Use of HIV prevention methods was low, with only 6.6% and 5.7% of participants reporting the use of post-exposure prophylaxis (PEP) and pre-exposure prophylaxis (PrEP), respectively (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBehavioral characteristics of AGYW enrolled in the study\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eFrequency (N\u0026thinsp;=\u0026thinsp;377)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003ePercentage (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEver tested for HIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e312\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e82.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e17.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHad HIV test in past 12 months*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e73.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e26.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEver pregnant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e43.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e56.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eConsistent condom use in past six months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e13.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e86.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHad more than one sexual partner\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e29.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e267\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e70.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHad STI in past six months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e55.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e44.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eShared injections in past six months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e95.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHad anal sex in past six months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e(11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e(88.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHad sex in exchange of money/gifts in past six months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e30.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e264\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e70.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eUsed illicit drugs before sex in past six months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e15.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e84.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eUsed PEP in past six months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e352\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e93.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eUsed PrEP in past six months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e357\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e94.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003cp\u003e*N\u0026thinsp;=\u0026thinsp;312\u003c/p\u003e\n \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\n \u003ch2\u003eExploratory factor analysis (EFA)\u003c/h2\u003e\n \u003cp\u003eThe data had a KMO of 0.88 and the Bartlett\u0026rsquo;s test of Sphericity was statistically significant (P value\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The scree plot showed three factors to be extracted (Fig. \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eExtraction of factors (rotated factor solution)\u003c/h2\u003e\n \u003cp\u003eOn rotation of the factor loadings, all the variables load significantly on one factor (factor 1) with the loadings ranging from 0.64 to 0.82 (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRotated solution of factor loadings (pattern matrix) and unique variances\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIndicator item\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eFactor 1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eFactor 2*\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eUniqueness\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eAffective attitude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eBurden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSelf-efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEthicality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eOpportunity cost\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEffectiveness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCoherence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003cp\u003e*Factor loadings of \u0026lt;\u0026thinsp;0.3 were suppressed\u003c/p\u003e\n \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\n \u003ch2\u003eConfirmatory factor analysis (CFA)\u003c/h2\u003e\n \u003cdiv id=\"Sec17\" class=\"Section4\"\u003e\n \u003ch2\u003eStructural equation modelling (SEM)\u003c/h2\u003e\n \u003cp\u003eThe global model fit indices for the SEM were; RMSEA of 1.224, CFI of 0.173, TLI of -0.103, SRMR of 0.078 and the coefficient of determination (CD) was 0.917.\u003c/p\u003e\n \u003cp\u003eThe standardized factor loadings ranged from 0.72 to 0.807, of which the highest were observed for perceived effectiveness (0.81), intervention coherence (0.80) and affective attitude (0.80), while ethicality showed the lowest (0.72). All the factor loadings were significant with P values\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe standardized factor loadings of the indicator items estimated by Structural Equation Modelling model\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIndicator item\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eStandardized factor loading (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eResidual variance (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eAffective attitude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.80 (0.76, 0.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.37 (0.32, 0.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eBurden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.77 (0.73, 0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.41 (0.36, 0.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSelf-efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.77 (0.73, 0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.41 (0.36, 0.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEthicality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.72 (0.68,0.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.48 (0.43, 0.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eOpportunity cost\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.79 (0.76, 0.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.38 (0.33, 0.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEffectiveness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.81 (0.78, 0.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.35 (0.31, 0.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCoherence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.80 (0.77, 0.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.36 (0.31, 0.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003eGeneralized structural equation modelling with ordinal logit model\u003c/h2\u003e\n \u003cp\u003eThe GSEM yielded positive and significant log-odds coefficients for all domains. The strongest associations were observed for coherence (1.15) and perceived effectiveness (1.08), followed by opportunity cost (0.88) and ethicality (0.74). slightly lower associations were observed for burden (0.67) and self-efficacy (0.65). All estimated coefficients were significant with P values\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe log-odds coefficients for the indicator items in a GSEM model\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"3\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eIndicator item\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eLog-odds coefficients (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eAffective attitude\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eBurden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.67 (0.49, 0.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSelf-efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.65 (0.48, 0.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEthicality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.74 (0.53, 0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eOpportunity cost\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.88 (0.65, 1.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEffectiveness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e1.08 (0.76, 1.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCoherence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e1.15 (0.82, 1.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n \u003ch2\u003eConvergent and divergent validity\u003c/h2\u003e\n \u003cp\u003eThe Pearson correlation coefficient between the acceptability score from the seven constructs of TFA and the perceived willingness to accept HIV self-testing was 0.7 (Fig. \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). The Pearson correlation coefficient between the acceptability score from the seven constructs of TFA and perceived HIV risk was 0.1 (Fig. \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb)\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\n \u003ch2\u003eReliability of the TFA questionnaire\u003c/h2\u003e\n \u003cp\u003eThe seven item TFA acceptability scale had an overall internal consistency (Cronbach\u0026rsquo;s alpha) of 0.889. The item-test and item-rest correlations were all \u0026gt;\u0026thinsp;0.3 (recommended threshold). The removal of any individual item did not result in a higher alpha value (Table \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eInternal consistency reliability of the TFA acceptability scale\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eItem\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eItem-test correlation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eItem-rest correlation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eAverage inter-item covariance\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eAlpha\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eAffective attitude\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.870\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eBurden\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.768\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.657\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.518\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.877\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthicality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.720\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.627\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.519\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.880\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eIntervention coherence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.803\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.539\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.868\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eOpportunity cost\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.787\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.533\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.870\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003ePerceived effectiveness\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.807\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.867\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelf-efficacy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\n \u003cp\u003e0.768\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\n \u003cp\u003e0.659\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.519\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.877\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall scale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e0.534\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\n \u003cp\u003e0.889\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study assessed the construct validity and internal consistency reliability of the TFA-measured acceptability scores among AGYW. The findings demonstrate that the seven TFA items function as a coherent and reliable measure of acceptability in this sub-population. EFA revealed a dominant single latent factor, which supports a unidimensional TFA-theorized acceptability. Furthermore, the CFA findings provided mixed evidence on construct validity where on one had the very strong and significant factor loadings in the SEM model indicate that each construct is highly correlated with the underlying acceptability construct while on the other hand, the poor global fit indices indicate that the hypothesized one-factor model does not adequately reproduce the observed covariance structure. However, the GSEM model that accounts for the ordinal nature of the TFA domain variables showed that the latent acceptability scores were positively and significantly associated with all the seven TFA domains which indicates that higher acceptability corresponds to higher levels across each domain. The direction and magnitude of the associations were consistent with the SEM findings, thus demonstrating strong and coherent relationships between the latent acceptability construct and observed indicator items Evidence of construct validity was further observed through strong convergent validity with willingness to use HIVST and weak divergent validity with perceived HIV risk. Internal consistency reliability was excellent and all items contributed meaningfully to the scale. Collectively, these findings support the validity and reliability of the TFA- measured acceptability scores among AGYW.\u003c/p\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eValidity of the TFA- measured acceptability scores\u003c/h2\u003e \u003cp\u003eAlthough the TFA is conceptually organized into seven sub-domains, the EFA in this study identified a single dominant latent factor. This aligns with the theoretical underpinning of the TFA that all the seven constructs collectively measure one overarching domain of acceptability. Evidence from previous validation studies shows that in some settings fewer factors are extracted as compared to the theorized seven sub-domains. For instance, in the development of a digital health acceptability tool, Haydon and colleagues (2023) found that while the TFA informed the item generation, the responses primarily clustered into two broad dimensions (attitude and perceived capacity dimensions) rather than the seven sub-domains [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Similarly, another study on a telephone-facilitated health coaching intervention in Sweden identified fewer factors than the theoretical seven with items clustering under three main factors (affective attitude, coherence and burden) [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. These two studies deviate from the theory behind the TFA by Sekhon and colleagues [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In our study, much as we report poor global fit indices of RMSEA, CFI and TLI that don\u0026rsquo;t meet the established SME fit criteria of acceptable model fit of \u0026lt;\u0026thinsp;0.06, \u0026ge;\u0026thinsp;0.95 and \u0026ge;\u0026thinsp;0.95 respectively [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], we note that the use of continuous SEM with ordinal Likert scale data may have violated distribution assumptions thus leasing to inflated misfit indices as previously reported [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Nonetheless, the SRMR value (0.078) falls within the acceptable limits based on recommended threshold of \u0026le;\u0026thinsp;0.08 [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], suggesting that absolute residual differences are relatively small. This pattern has been reported in literature particularly in large samples or when analyzing ordinal data [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The use of an ordinal logit link in the GSEM provide better representation of the Likert scale responses, addressing the limitations of treating ordinal variables as continuous. The GSEM findings in our study showed that all the latent acceptability scores were positively and significantly associated with all the seven TFA domains, which reinforces the construct validity of the TFA-measured acceptability scores. The consistency in direction and strength of these associations suggests that the domains operate as coherent indicators of acceptability, even when modeled using an ordinal framework. The consistency between the SEM and GSEM findings suggest that the poor global fit in the SEM may be partly attributable to modelling assumptions rather than true construct validity. Taken together, the findings from the EFA, SEM and the GSEM support the construct validity of the TFA-measured acceptability scores.\u003c/p\u003e \u003cp\u003eFurther validity testing showed evidence of convergent validity with the acceptability score strongly correlated with the participants\u0026rsquo; willingness to use HIVST. Methodological standards suggest that a correlation coefficient of \u0026ge;\u0026thinsp;0.7 is considered evidence of strong convergence between constructs that should in theory be related [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Thus, the observed correlation in our study supports the assertion that the TFA is indeed capturing the underlying construct of acceptability. In contrast divergent validity was also supported by the weak correlation between the acceptability score and perceived HIV risk. The weak correlation in this study therefore, demonstrates that the TFA measure is not merely reflecting general perceptions but specifically capturing the intervention acceptability. Findings from other TFA validation studies further support this interpretation. For example, the higher acceptability scores were significantly associated with participants\u0026rsquo; willingness to engage in health coaching [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Similarly, in a study aimed at developing a digital health tool, the acceptability scores were strongly related to self-reported intension to use telehealth service, while showing weak correlation with unrelated psychological constructs [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. This supports both convergent and divergent validity. The observed convergent and divergent validity in our study further confirm that the TFA scale is conceptually coherent and provides empirical evidence of its construct validity of acceptability scores. This strengthens confidence in the TFA\u0026rsquo;s applicability for assessing the acceptability of health interventions like HIVST among AGYW in low-resource settings.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eInternal consistency reliability of the TFA\u003c/h2\u003e \u003cp\u003eThe TFA acceptability scale demonstrated good internal consistency reliability in measuring acceptability scores with a strong Cronbach\u0026rsquo;s alpha. All items exhibited strong item-test and item-rest correlations, suggesting that each construct contributed meaningfully to the overall scale without redundancy. Importantly, removal of any individual item did not improve the Cronbach\u0026rsquo;s alpha thus supporting retention of all seven TFA sub-domains in the final TFA-based measurement of acceptability. According to psychometric standards, Cronbach\u0026rsquo;s alpha of \u0026gt;\u0026thinsp;0.8 reflects strong internal coherence of multi-item scales assessing latent constructs [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Similar levels of internal consistency have been reported in other studies applying TFA-informed measures of acceptability across health interventions [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. This further supports the reliability of the framework when operationalized quantitatively. Therefore, these findings provide evidence that the TFA-based measurement of acceptability is reliable for measuring health intervention acceptability among AGYW in low-resource settings.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis study has some limitations that should be considered when interpreting the findings. First, the data were cross sectional, which limits the ability to assess how acceptability may change over time. Secondly, all the measures relied on self-reported data which may be subject to recall and social desirability bias, particularly given the sensitivity of HIV-related behaviors, however, the period of recall was limited to six months apart from the period of past HIV testing (12 months). Thirdly, the study participants were selected using a non-probability sampling technique which may have introduced selection bias. The study focused on AGYW in urban settings, and while this is a key population for HIV prevention, the results may have limited generalizability to other age groups, gender or settings. Nonetheless, the systematic biases highlighted may have had minimal influence on the findings.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study provides empirical evidence supporting the construct validity and reliability of acceptability scores measured using the TFA among AGYW in Uganda. The seven TFA-informed items collectively formed a single latent acceptability construct and demonstrate strong convergent validity with willingness to use HIVST, weak divergent validity with perceived HIV risk, and strong internal consistency reliability. The scale may serve as a useful quantitative tool for measuring intervention acceptability among AGYW in similar low-resource settings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Makerere University School of Medicine Research Ethics Committee under the reference number Mak-SOMREC-2023-843. Further clearance was obtained from the Uganda National Council for Science and Technology (UNCST) under the reference number HS5167ES. The administrative clearance to conduct the study was obtained from the Kampala Capital City Authority (KCCA), and the Municipal Health Offices of Entebbe and Nansana Municipalities. The adult and emancipated minors provided written informed consent, while the other minors (\u0026lt;18 years) gave written informed assent in addition to their guardian\u0026rsquo;s written informed consent following the UNCST guidelines (25).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge the study participants for creating time to participate in this study. We acknowledge the Village Health Teams of Kampala and Wakiso districts for their support in participant mobilization\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe findings and data reported in this publication were supported by the Fogarty International Center and the National Institute of Mental Health of the National Institutes of Health under Award Number D43 TW010037 (to FCS). The contents are solely the responsibility of the authors and do not necessarily represent the official views of the National Institutes of Health. The funders had no role in the study conceptualization, design, data collection and analysis, decision to publish or preparation of the Manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLM, PAM, JN and FCS conceived and conceptualized the research idea. LM, PAM, IA, SN, DM and CT were instrumental in refining the research idea and methodology. LM, DM, IA, EA, CT and SN were instrumental in data collection and management. LM, IA, CT, PAM and SN conducted the initial data analysis. LM, PAM and JN drafted the initial manuscript. All co-authors reviewed and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of datasets and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets analyzed during the current study are available from the corresponding author on reasonable request\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSekhon M, Cartwright M, Francis JJ. Acceptability of healthcare interventions: an overview of reviews and development of a theoretical framework. BMC Health Serv Res. 2017;17:1\u0026ndash;13. \u003c/li\u003e\n\u003cli\u003eMukora R, Ahumah B, Maraba N, Orrell C, Jennings L, Naidoo P, et al. Acceptability of using the medication monitor and experience of a differentiated care approach for TB treatment adherence among people living with TB in South Africa. PLOS Glob public Heal. 2023;3:e0001885. \u003c/li\u003e\n\u003cli\u003eChen A, V\u0026auml;yrynen K, Leskel\u0026auml; R, Torkki P, Heinonen S, Tekay A, et al. The acceptability of implementing patient‐reported measures in routine maternity care: A systematic review. Acta Obstet Gynecol Scand. 2023;102:406\u0026ndash;19. \u003c/li\u003e\n\u003cli\u003eNyumwa P, Bula AK, Nyondo-Mipando AL. Perceptions on acceptability of the 2016 WHO ANC model among the pregnant women in Phalombe District, Malawi\u0026ndash;a qualitative study using Theoretical Framework of Acceptability. BMC Pregnancy Childbirth. 2023;23:166. \u003c/li\u003e\n\u003cli\u003eMeades R, Moran PM, Hutton U, Khan R, Maxwell M, Cheyne H, et al. 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PLoS One. 2020;15:e0236141. \u003c/li\u003e\n\u003cli\u003eSekhon M, Cartwright M, Francis JJ. Development of a theory-informed questionnaire to assess the acceptability of healthcare interventions. BMC Health Serv Res. 2022;22:279. \u003c/li\u003e\n\u003cli\u003eProctor E, Silmere H, Raghavan R, Hovmand P, Aarons G, Bunger A, et al. Outcomes for implementation research: conceptual distinctions, measurement challenges, and research agenda. Adm policy Ment Heal Ment Heal Serv Res. 2011;38:65\u0026ndash;76. \u003c/li\u003e\n\u003cli\u003eSmith GT. On construct validity: issues of method and measurement. Psychol Assess. 2005;17:396. \u003c/li\u003e\n\u003cli\u003eDeVellis RF, Thorpe CT. Scale development: Theory and applications. Sage publications; 2021. \u003c/li\u003e\n\u003cli\u003eHu Z, Li J. The integration of EFA and CFA: One method of evaluating the construct validity. 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Application of the Theoretical Framework of Acceptability to assess a telephone-facilitated health coaching intervention for the prevention and management of type 2 diabetes. PLoS One. 2022;17:e0275576. \u003c/li\u003e\n\u003cli\u003eHu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct Equ Model a Multidiscip J. 1999;6:1\u0026ndash;55. \u003c/li\u003e\n\u003cli\u003eKline RB. Principles and practice of structural equation modeling. Guilford publications; 2023. \u003c/li\u003e\n\u003cli\u003eHair JF. Multivariate data analysis. 2009; \u003c/li\u003e\n\u003cli\u003eFornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Mark Res. 1981;18:39\u0026ndash;50. \u003c/li\u003e\n\u003cli\u003eNunnally J, Bernstein I. Psychometric Theory 3rd edition (MacGraw-Hill, New York). 1994. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"implementation-science-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"iscm","sideBox":"Learn more about [Implementation Science Communications](https://implementationsciencecomms.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ISCM/default.aspx","title":"Implementation Science Communications","twitterHandle":"@ImplementSci","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Acceptability, Theoretical Framework of Acceptability, construct validity, Reliability, adolescent girls and young women, low-resource setting, HIV self-testing","lastPublishedDoi":"10.21203/rs.3.rs-9271781/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9271781/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe Theoretical Framework of Acceptability (TFA) provides a comprehensive lens for assessing acceptability of healthcare interventions. While the TFA has seven constructs, limited literature exists on its psychometric properties in low-resource settings and in the context of HIV prevention. This study assessed the validity and reliability of HIV self-testing (HIVST) acceptability scores measured using the TFA among adolescent girls and young women (AGYW) in Uganda.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe enrolled 377 AGYW aged 15\u0026ndash;24 years in a cross sectional study and a structured questionnaire was used to collect data. The primary outcome was acceptability of HIVST defined as willingness to accept HIVST services if offered \u0026ndash; measured using the seven constructs of the TFA where each was assessed with one 5-level Likert item question. Construct validation of TFA was examined using the exploratory factor analysis (EFA), confirmatory factor analysis (CFA) \u0026ndash; through structural equation modelling (SEM), and convergent and divergent validity, while reliability was assessed with the Cronbach\u0026rsquo;s alpha. Factor extraction was guided by the scree plot, and factor rotation was performed using Oblimin method. Convergent and divergent validity were assessed by correlating the TFA acceptability scores with willingness to use HIVST and perceived HIV risk respectively.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe median age of participants was 20 years (IQR: 18, 22). Although the scree plot suggested that three factors should be extracted, the rotated solution of the EFA yielded a single dominant factor, with all seven items loading strongly onto one latent factor. In the CFA, both SEM and generalized SEM showed consistent direction and strength of association between the TFA domains and the underlying acceptability construct despite the poor SEM global fit indices (RMSEA\u0026thinsp;=\u0026thinsp;1.224, CFI\u0026thinsp;=\u0026thinsp;0.173, TLI= -0.103). The correlation between acceptability scores and willingness to use HIVST, and perceived HIV risk was 0.7 and 0.1 respectively. The overall Cronbach\u0026rsquo;s alpha for the questionnaire items was 0.889.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis study provides empirical evidence supporting the construct validity and reliability of the TFA-measured acceptability scores among AGYW. All seven constructs demonstrated strong loadings on a single latent factor, indicating that the TFA operates as a coherent and unidimensional tool for measuring overall acceptability.\u003c/p\u003e","manuscriptTitle":"Psychometric evaluations of the Theoretical Framework of Acceptability (TFA) among adolescent girls and young women in a low-resource setting","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-23 09:16:02","doi":"10.21203/rs.3.rs-9271781/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-19T09:38:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-12T22:20:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"53673228217322724576490749645223875721","date":"2026-05-01T20:32:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-26T09:35:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"87730157817924010536414700396706930777","date":"2026-04-15T10:24:16+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-14T20:13:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-13T11:07:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-01T03:29:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"Implementation Science Communications","date":"2026-03-30T20:21:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"implementation-science-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"iscm","sideBox":"Learn more about [Implementation Science Communications](https://implementationsciencecomms.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ISCM/default.aspx","title":"Implementation Science Communications","twitterHandle":"@ImplementSci","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8256918d-89d9-45ff-b912-16cab13209f1","owner":[],"postedDate":"April 23rd, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-19T09:38:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-12T22:20:49+00:00","index":12,"fulltext":""},{"type":"reviewerAgreed","content":"53673228217322724576490749645223875721","date":"2026-05-01T20:32:15+00:00","index":11,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-19T09:56:00+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-23 09:16:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9271781","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9271781","identity":"rs-9271781","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}