A Randomised Equivalency Study of the EQ-5D-5L Shona Versions - Evaluation of Measurement Equivalency Between Digital and Paper Formats

A Randomised Equivalency Study of the EQ-5D-5L Shona Versions - Evaluation of Measurement Equivalency Between Digital and Paper Formats | 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 A Randomised Equivalency Study of the EQ-5D-5L Shona Versions - Evaluation of Measurement Equivalency Between Digital and Paper Formats Jermaine M. Dambi, Fredrick D. Purba, Beatrice K. Shava, Anotida R. Hove, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7287257/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Introduction: Comorbid anxiety and depression are common among people living with HIV (PLHIV), underscoring the necessity for concise diagnostic tools for routine mental health evaluations. Efficient screening can be supported by digital tools even in lower-income countries where HIV is a population health issue. The aims of this study were to: (1) examine the measurement equivalency between digital and paper versions of the Shona EQ-5D-5L, and (2), identify factors affecting the health-related quality of life (HRQoL) of PLHIV. Methods and materials: We conducted a parallel randomised study in Zimbabwe involving 700 participants equally divided into digital and paper groups. Results The study included 611 participants with a mean age of 37.5 years (SD 12.2). Most were female (70.7%), had secondary education (68.0%), and reported inadequate financial adequacy (68.7%). Both digital and paper-based versions of the EQ-5D-5L Shona displayed measurement equivalency. After adjusting for confounding and co-variation, only increased age (AOR = .60: 95% CI .41-.88, p = .008), food insecurity (AOR = 1.8: 95% CI 1.2: 2.8, p = .01), and elevated comorbid anxiety/depression symptoms (AOR = 0.45: 95% CI: 0.29–0.68, p < .001) were associated with lower HRQoL. Conclusion This study demonstrated the measurement equivalency of the digital and paper-based versions of the EQ-5D 5L Shona. These two versions can be used confidently for routine clinical care and research. The study emphasises the need for tailored interventions to improve the HRQoL of PLHIV. Digital EQ-5D-5L measurement equivalency validation Zimbabwe Figures Figure 1 Plain language summary Many people living with HIV experience anxiety and depression, which can harm their overall health. These mental health issues often go unnoticed, so it's important to have quick tools for regular checks. This study compares the digital and paper versions of the Shona EQ-5D-5L to see which one is more accurate for measuring the well-being of people living with HIV. Understanding these tools will help improve care for people with HIV. We studied 700 participants, split evenly between those using the digital version and those using the paper version of the Shona EQ-5D-5L. Our findings showed that both versions of the Shona EQ-5D-5L produced similar results. This means both can be reliably used to measure well-being in people living with HIV. We also found that older age, food insecurity, and higher anxiety or depression levels are linked to lower well-being. This shows a need for targeted programs to help improve the well-being of people living with HIV. Background The Sub-Saharan region bears the highest burden of HIV/AIDS worldwide, with 69% of the 39 million individuals living with HIV/AIDS (PLHIV) located in Sub-Saharan Africa [ 1 , 2 ]. Unfortunately, non-communicable diseases, particularly common mental health disorders (CMDs), are highly prevalent in PLHIV [ 3 ]. For example, up to 30% of PLIHV suffer from comorbid depression [ 4 ]. Comorbid CMDs are associated with negative impacts across the care continuum, including increased morbidity and mortality [ 3 ]. Consequently, early detection and treatment of CMDs are essential for optimal treatment outcomes in PLHIV [ 5 ]. There is also an increasing use of generic health status outcomes for routine health outcome measurement and screening for CMDs in people living with chronic conditions, including HIV [ 6 ]. Unlike condition-specific CMDs screeners, generic patient-reported outcome measures have greater utility as they can be used for CMDs screening, routine health assessments and comparative health evaluations [ 7 ]. The European Quality of Life 5 Dimensions (EQ-5D) is a widely used routine health status measurement in health systems [ 8 , 9 ]. The EQ-5D assesses health in five domains, i.e. mobility, usual activities, self-care, pain /discomfort and anxiety/depression [ 8 ]. The EQ-5D is extensively used globally and has been translated and standardised in over 150 languages [ 10 ]. Also, the EQ-5D is available in different versions (e.g. five-level (5L) vs three-level (3L) versions [ 10 ]). The EQ-5D-3L, which consists of three response options, “no problem”, “some problems”, and “severe problems”, has been translated and validated into Shona, a Zimbabwean native language. The translated version demonstrates strong validity and reliability, with utility values that are available and have been widely utilised in research [ 11 – 13 ]. However, the EQ-5D-3L is prone to floor and ceiling effects [ 14 ]. A large cohort study (N = 1,023,218) found lower ceiling effects of the EQ-5D-5L (43.8%) compared to the EQ-5D-3L (54.4%) [ 15 ]. Consequently, the EuroQol Group recommends the EQ-5D-5L version as their generic HRQoL outcome of choice. The EQ-5D is available in paper or digital formats and can be self-, interviewer- or proxy-administered [ 16 ]. Owing to exponential digitalisation globally, digital versions are increasingly used compared to paper-based versions [ 16 ]. Digital administration increases clinical utility and psychometric performance as it eliminates missing responses, automatically creates a database and facilitates sharing clients’ HRQoL valuations in real-time, optimising clinical care further [ 17 , 18 ]. Previous studies have demonstrated the measurement equivalency of both digital and paper-based versions of the EQ-5D [ 16 – 18 ]. Due to the identified floor and ceiling effects of the 3L version, the Zimbabwean 3L versions were upgraded to the 5L versions in this study. This process included translating and validating the newly introduced 5L digital version, which was not empirically tested in Zimbabwe. Therefore, we set out to evaluate the psychometric performance of the digital EQ-5D-5L Shona version in PLHIV, explicitly evaluating these properties: Comparing the measurement equivalency of the paper and digital versions Known-groups validity - comparing scores across participants’ characteristics (e.g., age, sex, education, socio-economic status); thus, assessing factors associated with HRQoL in PLHIV. Methods Study setting The study was done at the Family Care Centre at Parirenyatwa Group of Hospitals in Harare, Zimbabwe. The FCC offers in-house testing, medical, and psychological services to PLHIV. The FCC is the biggest referral centre for the provision of HIV-related services countrywide, serving about 3000 clients per month. Study design A parallel, individualised, randomised study design was used. Participants were individually randomised to complete either the digital or paper version. Study participants’ selection criteria We recruited consenting adult patients (aged ≥ 18 years) with a confirmed diagnosis of HIV and proficiency in either English or the Shona language. Patients with a known diagnosis of a psychiatric condition, such as major depression, according to the doctor’s notes, were similarly excluded. Sample size calculation A minimum of 234 participants per group were required to demonstrate equivalence to rule out differences of 0.3 standard deviations across the paper and digital versions at a 95% confidence interval and 80% goal power [ 19 ]. Outcome Measures Demographic questionnaire This questionnaire extracted participants’ demographics, i.e., age, gender, education level, employment status, and marital status. EQ-5D-5L The EQ-5D is a standardised, self-report HRQoL measure with five dimensions, i.e., mobility, self-care, usual, pain/discomfort and anxiety/depression. Participants also rate their HRQoL on a visual analogue scale with scores in the range of 0-100. The EQ-5D-3L paper version is translated into Shona, a Zimbabwean native language, and validated in both the general population and PLHIV [ 11 , 13 ]. Normative utility scores are available for the Zimbabwean population [ 11 ]. In this study, we validate the newly upgraded EQ-5D-5L Shona version. Shona symptoms questionnaire (SSQ-14) The SSQ is a proven, psychometrically sound, native Zimbabwean 14-item tool for the screening of CMDs [ 5 ]. Respondents indicate whether they experienced the 14 psychological symptoms in the past seven days. A reported symptom (“yes” response) is rated as one, and a “no” symptom is rated zero. A score of eight is regarded as a case exhibiting psychiatric morbidity. The SSQ only takes 2–3 minutes to complete and is validated in PLHIV in the research setting [ 5 ]. Patient Health Questionnaire-9 (PHQ-9) The PHQ is a generic, nine-item depression screen. Respondents rate the frequency of experience of the enlisted depressive symptoms in the previous two weeks on a four-point Likert scale, which ranges from “not at all = all = 0” to “all the time = 3” to give a cumulative score range of 0–27. Scores in the ranges 0–9, 15–19 and 20–27 are interpreted as follows: minor, moderate and severe depression, respectively [ 5 ]. The PHQ-9 has been extensively used for clinical and research purposes and is validated in PLHIV in the research setting [ 5 ]. Generalised Anxiety Disorders Scale (GAD-7) The GAD-7 is a seven-item, self-report anxiety screen [ 20 ]. Respondents rate the frequency of experience of the enlisted anxiety symptoms in the previous two weeks on a four-point Likert scale, which ranges from “not at all = all = 0” to “all the time = 2” to give a cumulative score range of 0–21. The criteria values for low, moderate and severe anxiety are 5,10 and 15, respectively [ 20 ]. The GAD-7 has been validated in PLHIV in the research setting [ 5 ]. Data collection procedure Prospective participants were recruited as they presented for routine HIV care. Participants were addressed by three research assistants (RAs) in the treatment waiting areas; those who expressed interest were given identification stickers. Another set of two RAs thereafter approached attendees with stickers, checked for eligibility, and initiated the consenting process. Individuals who met the selection criteria and consented to participate were requested to pick a concealed envelope. The envelopes contained codes to randomly assign participants to two study arms, i.e., tablet and paper. The research team then administered a demographic questionnaire to elicit participant demographics, e.g., age and sex. They also assessed literacy levels and familiarity with technological devices to evaluate the feasibility of self-completion of the EQ-5D questionnaires. The EQ-5D and test battery were self-completed; however, the research team was available to assist participants as necessary through the completion process. Training To standardise the data collection procedures, we conducted a training workshop for the research team. The research team received training in good clinical practice, including informed consent and administering questionnaires. Data analysis plan Descriptive statistics (e.g. means, frequencies) were used to analyse participants’ characteristics. Multivariate binary logistic regression was used to investigate the influence of administration mode (paper vs digital) and participants’ characteristics (e.g., age, gender, education) on EQ-5D-5L Visual Analogue Scale (VAS) and utility scores. Both crude odds ratios (COR) and adjusted odds ratios (AOR), along with their associated 95% confidence intervals, are presented to depict the univariate and adjusted analyses. The analysis was done using SPSS (Version 29). The significance level was set at α = 0.05. Data management/Ethical considerations Data were collected electronically using RedCap, programmed onto Android tablets. The Android tablets required a two-step authentication process: a fingerprint scan and a personal identification (PIN) code. The raw data were de-identified by assigning arbitrary numeric codes for participants. Files containing the consent forms are stored in a secure locker at the University of Zimbabwe. The digital copy of the data is saved on a password-protected laptop and backed up on OneDrive. Participants were treated as autonomous agents and participated in the study voluntarily. Parirenyatwa Group of Hospitals granted institutional approval, and ethical approval was obtained from the Medical Research Council of Zimbabwe (Ref: MRCZ/A/2496). Results CONSORT flowchart We screened 930 participants, of whom 700 met the inclusion criteria and were randomly assigned equally to either the paper or digital group (350 participants per group). In the digital group, 340 participants completed the form. However, 10 participants dropped out due to time pressure, leaving 330 participants for analysis. In the paper group, 337 participants completed the form. However, 38 participants dropped out due to time pressure, and 18 had missing VAS scores, resulting in 281 participants for analysis (see Fig. 1 ). Demographics A total of 611 participants were included in the study, with a mean age of 37.5 years (SD 12.2). Most participants were female (70.7%), attained secondary education (68.0%), and reported inadequate financial adequacy (68.7%) and food insecurity (51.2%). Participants did not generally smoke (93.7%), consume alcohol (80.5%), or use substances (96.7%); however, 65.5% reported experiencing an adverse event in the past month. The two groups were comparable across all domains, except for substance intake. The prevalence of substance intake was higher in the digital than paper group, i.e. 2.6% vs. 0.7%, and the difference was statistically significant, X 2 df = 1 = 4.59, p = .032 - See Table 1 . Table 1 Participant characteristics, N = 611 Variable Attribute Digital, n (%) Paper, n (%) Total, n (%) Statistic p-value Gender Female 232 (38.0) 200 (32.7) 432 (70.7) X 2 df = 1 = .022 .883 Male 98 (16.0) 81 (13.3) 179 (29.3) *Age Mean (SD) 37.4 (11.7) 37.8 (12.8) 37.5 (12.2) t(df = 609) = 0.409 .682 Education Primary 35 (5.7) 24 (2.9) 59 (9.7) X 2 df = 2 = 2.050 .359 Secondary 216 (35.4) 199 (32.6) 415 (67.9) Tertiary 79 (12.9) 58 (9.5) 137 (22.4) Financial Inadequate 224 (36.7) 196 (32.1) 420 (68.7) X 2 df = 1 = .168 .682 Adequacy Adequate 106 (17.3) 85 (13.9) 191 (31.3) Food security Inadequate 164 (26.8) 149 (24.4) 313 (51.2) X 2 df = 1 = .546 .460 Adequate 166 (27.2) 132 (21.6) 298 (48.8) Smoking No 307 (50.2) 267 (43.7) 574 (93.9) X 2 df = 1 = .733 .392 Yes 23 (3.8) 14 (2.3) 37 (6.1) Alcohol Intake No 262 (42.9) 230 (37.6) 492 (80.5) X 2 df = 1 = .438 .508 Yes 68 (11.1) 51 (8.3) 119 (19.5) **Substance No 315 (51.4) 277 (45.3) 591 (96.7) X 2 df = 1 = 4.593 .032 Intake Yes 16 (2.6) 4 (0.7) 20 (3.3) Adverse event No 223 (36.5) 179 (29.3) 402 (65.8) X 2 df = 1 = .848 .357 Yes 107 (17.5) 102 (16.7) 209 (34.2) SSQ-14 0–8 (No risk) 211 (34.5) 178 (29.1) 389 (63.7) X 2 df = 1 = .005 .946 9–14 (At risk) 119 (19.5) 103 (16.9) 222 (36.3) PHQ-9 0–10 (No risk) 278 (45.5) 241 (39.4) 519 (84.9) X 2 df = 1 = .169 .681 11–27 (At risk) 52 (8.5) 40 (6.5) 92 (15.1) GAD-7 0–9 (No risk) 268 (43.9) 241 (29.4) 509 (83.3) X 2 df = 1 = 1.947 .163 10–21 (At risk) 62 (10.1) 40 (6.5) 102 (16.7) * Data not in n (%) format; ** Bolded values are statistically significant HRQoL evaluations comparability across administration modes Most participants had no problems with mobility (79.3%), self-care (89.5%), and usual activities (81.2%). Pain and discomfort (41.7%) and anxiety/depression (39.9%) were the most reported problems. The reported problems were comparable across groups (digital vs. paper) in all domains – See Table 2 . Table 2 Frequencies of responses on the EQ-5D-5L Dimension Level of problems Digital, n (%) Paper, n (%) Total, % Statistic p-value Mobility No 252 (41.2) 233 (38.1) 79.4 X 2 df = 4 =5.1 .276 Slight 43 (7.0) 28 (4.6) 11.6 Moderate 24 (3,9) 11 (1.8) 5.8 Severe 8 (1.3) 7 (1.1) 2.5 Unable/extreme 3 (0.5) 2 (0.3) .8 Self-care No 294 (48.1) 253 (41.4) 89.5 X 2 df = 4 =2.9 .583 Slight 13 (2.1) 12 (2.0) 4.1 Moderate 9 (1.5) 10 (1.6) 3.1 Severe 7 (1.1) 4 (0.7) 1.8 Unable/extreme 7 (1.1) 2 (0.3) 1.5 Usual activities No 268 (43.9) 228 (37.3) 81.2 X 2 df = 4 =.22 .995 Slight 36 (5.9) 33 (5.4) 11.3 Moderate 13 (2.1) 10 (1.6) 3.8 Severe 8 (1.3) 6 (1.0) 2.3 Unable/extreme 5 (0.8) 4 (0.7) 1.5 Pain/Discomfort No 197 (32.2) 159 (26.0) 58.3 X 2 df = 4 =2.7 .615 Slight 90 (14.7) 78 (12.8) 27.5 Moderate 27 (4.4) 31 (5.1) 9.5 Severe 8 (1.3) 9 (1.5) 2.8 Unable/extreme 8 (1.3) 4 (0.7) 2.0 Anxiety/ Not 188 (30.8) 179 (29.3) 60.1 X 2 df = 4 =3.5 .485 depression Slight 89 (14.6) 62 (10.1) 24.7 Moderate 24 (3.9) 20 (3.3) 7.2 Severe 21 (3.4) 13 (2.1) 5.6 Unable/extremely 8 (1.3) 7 (1.1) 2.5 * EQ-5D-5L Utility Mean (SD) 0.81 (0.14) 0.82 (0.11) t (df = 609) = 0.99 .324 * EQ-5D-5L VAS Score Mean (SD) 77.5 (23.8) 80.5 (19.9) t (df = 600) = 1.63 .104 * Data not in n (%) format Measurement equivalency evaluation Univariate binary logistic regression showed that EQ-5D-5L scores were independent of group allocation for both the EQ-5D 5L scores [COR = 0.906, 95% CI (-0.656: 1.252), p = .549] and EQ-5D 5L utility scores [COR = .915, 95% (.656: 1.275), p = .599], thus demonstrating measurement equivalency of the paper and digital versions of the EQ-5D-5L Shona Version -see Table S1 for the rest of the univariate analyses. HRQoL determinants assessment Also, the unadjusted odds ratios (bivariate binary logistic regression) show that increased age, low educational attainment, food insecurity, perceived financial inadequacy, smoking, substance intake/usage, experiencing an adverse event, and elevated anxiety and depression symptoms were associated with lower HRQoL – See Table S1 . After adjusting for confounding and co-variation in multivariate binary logistic regression, only increased age (AOR = .60: 95% CI .41-.88, p = .008), food insecurity (AOR = 1.8: 95% CI 1.2: 2.8, p = .01), financial insecurity, (AOR = 1.72: 95% CI 1.10–2.69, p = 0.017) and elevated comorbid anxiety/depression symptoms (AOR = 0.45: 95% CI: 0.29–0.68, p < .001) were associated with lower HRQoL – See Table 3 . Table 3 Factors associated with EQ-5D-5L scores (Adjusted Odds Ratios) EQ-5D-5L VAS Scores EQ-5D-5L Utility Scores Variable Attribute AOR (95% CI) p-value AOR (95% CI) p-value **Age 18–37 years 0.768 (0.541–1.091) .06 0.601 (0.413–0.875) 0.008 38–77 years Ref Ref Sex Male 1.189 (0.803–1.759) 0.388 1.389 (0.908–2.125) 0.13 Female Ref Ref Education Primary 1.525 0.763–3.049) 0.233 1.125 (0.545–2.323) 0.75 Secondary 1.039 (0.667–1.618) 0.866 0.929 (0.572–1.511) 0.767 Tertiary Ref Ref **Food Inadequate 1.222 (0.805–1.854) 0.346 1.793 (1.153–2.788) 0.01 Security Adequate Ref Ref **Financial Inadequate 1.724 (1.104–2.693) 0.017 1.603 (0.978–2.627) 0.061 Security Adequate Ref Ref Smoking status No 0.514 (0.241–1.098) 0.086 0.577 (0.266–1.251) 0.164 Yes Ref Ref Adverse No 0.79 (0.543–1.148) 0.216 0.687 (0.464–1.015) 0.06 Event Yes Ref Ref **SSQ-14 scores 0–8 (Not at risk) 0.472 (0.314–0.708) < .001 0.447 (0.294–0.678) < .001 Categories 9–14 (At risk) Ref Ref PHQ-9 scores 0–10 (Not at risk) 0.812 (0.44–1.498) 0.504 0.765 (0.408–1.436) 0.404 Categories 11–27 (At risk) Ref Ref GAD-7 scores 0–9 (Not at risk) 0.944 (0.522–1.707) 0.85 0.626 (0.342–1.146) 0.129 Categories 10–21 (At risk) Ref Ref ** Bolded values are statistically significant Discussion Overall synthesis Electronic patient-reported outcome measures are increasingly used for routine data collection and research. We aimed to validate the digital EQ-5D-5L Shona version and compare its measurement equivalency to the paper version, as well as assess HRQoL determinants in PLHIV. Both digital and paper-based versions of the EQ-5D-5L Shona displayed measurement equivalency. Also, increased age, food insecurity, financial insecurity, and elevated comorbid anxiety/depression symptoms were associated with lower HRQoL. Measurement equivalence of digital and paper versions This study demonstrated the equivalency of the newly translated paper and digital versions of the EQ-5D-5L, as psychometric performance was independent of administration mode. This is significant because both paper and digital versions can confidently be used for routine and research purposes [ 17 , 18 , 21 , 22 ]. Elsewhere, a randomised crossover study among American Irritable Bowel Syndrome patients (N = 72) showed the measurement equivalency of paper and digital/mobile device versions [ 21 ]. In the American study, the intraclass correlation coefficients for the EQ-5D-5L VAS and index scores were 0.822 and 0.77, respectively, showing a high agreement of scores across the administration modes [ 21 ]. Also, a UK-based randomised crossover study among health participants (n = 60) and patients with chronic conditions (n = 30) also supports the measurement equivalency of paper and multiple digital EQ-5D-5L versions, i.e., handheld, tablet, interactive voice response and web. The wide array of modes utilised in the UK study enables the feasibility of electronic data collection according to patient preferences and resource availability [ 17 ]. Like our study, using a parallel randomised study design, Mulhern et al. (2015) also demonstrated the measurement equivalency of paper and digital versions of the EQ-5D-5L among UK-based adults without (n = 60) and with chronic conditions (n = 30). Mulhern et al. (2015) also showed acceptability and a greater preference towards the digital EQ-5D-5L version. Digital versions can be programmed to negate missing responses, which increases their utility and psychometric performance [ 17 , 18 ]. Our study supports this proposition, as the paper version had respondents with 6.0% missing data. However, in low-income countries such as Zimbabwe, paper-based versions have equally important utility, as not all studies and healthcare facilities may have access to digital infrastructure for electronic data collection of HRQoL evaluations. The ISPOR ePRO task force warns against the bias towards using digital over paper-based patient-reported outcome measures [ 22 ]. Thus, access to both modes is invaluable, and our study supports the equivalency of paper and digital versions of the EQ-5D-5L Shona versions. HRQoL determinants Findings from the adjusted multivariate binary logistic regression showed that increased CMDs symptoms were associated with lower HRQoL scores on both the VAS and utility scores. Comorbid mental disorders are highly prevalent in PLHIV, coupled with variable daily life challenges faced by PLHIV, the fluctuations in mental health states are unsurprising [ 5 ]. Zimbabwe has faced decades of ongoing socioeconomic challenges, with most people living in poverty; this is likely to contribute to the high burden of CMDs in people living with HIV, given the positive association between lower HRQoL and lower financial insecurity reported in this study and elsewhere [ 5 , 23 ]. Also, in this study, PLHIV without food security were nearly likely to report lower HRQoL when compared to those with adequate food security, AOR = 1.8 (95% CI:1.2–2.8); this is consistent with our previous study in the same setting [ 23 ]. Food insecurity is a salient predictor of mental health function and HRQoL in PLHIV, particularly those residing in low-resource settings. Last, the decrease in HRQoL with ageing in PLHIV is unsurprising, as increased age is associated with comorbid conditions that are both HIV-related and age-related. For instance, regardless of treatment status, immune function gradually declines with time, with age-related musculoskeletal disorders increasing with age, which leads to a decline HRQoL over time [ 24 ]. Strengths and limitations Our study outcomes need to be considered in view of the inherent methodological strengths and limitations. Using a randomised study design is a major methodological strength as it increases the study’s internal and external validity. Second, this is the first study to determine the equivalence of translated EQ-5D-5L versions in low-resource settings. Our study adds to the increasing body of knowledge on the psychometric robustness of EQ-5D-5L digital versions [ 17 , 21 ]. Electronic versions of the EQ-5D-5L can be used for multi-national comparative studies. Third, we exceeded the recommended minimum sample size for measurement equivalency studies i.e. we recruited 611 participants against the recommended 234 [ 19 ]. For example, an almost similar study recruited 90 participants [ 18 ]. Our large sample size increases the study’s internal and external validity. Fourth, recruiting participants with diverse characteristics (e.g., sex, age, education, and economic status levels) ensures the study’s external validity. Our study was also prone to some biases. First, all items on the electronic data collection were set to mandatory. Thus, there were no inherent missing responses on the EQ-5D-5L digital version compared to the paper version; this may have led to biased data completeness for the electronic version. Second, no clinical variables were collected. We had initially planned to collect clinical variables (e.g. treatment duration, CD4+) to compare EQ-5D-5L’s known-group validity. However, collecting clinical variables was not possible at the time of data collection as the electronic data collection system was being upgraded, and few participants had meaningful data recorded on paper records. Future studies should collect salient clinical predictors of HRQoL. Third, we did not record the completion time for the paper versions; the time taken for the digital versions could be deduced from the system. Completion time would offer more information on the feasibility of the different administration modes, which should be explored in future studies. Fourthly, we only recruited PHLIV due to a limited budget. Nevertheless, individuals living with HIV often experience multiple comorbid conditions, which are likely applicable to other chronic illnesses. Also, condition-specific nuances, for example, HIV-related stigma, may impact HRQoL evaluations/perceptions, hence the need for additional studies in other conditions, including comparative studies recruiting healthy participants. Conclusions This study demonstrated the measurement equivalency of the digital and paper-based versions of the EQ-5D-5L Shona. These two versions can be used confidently for routine clinical care and research. The study also underscores the need for bespoke interventions to improve the HRQoL of PLHIV. Abbreviations AOR - adjusted odds ratios CMDs - common mental health disorders COR- crude odds ratios EQ-5D - The European Quality of Life 5 Dimensions GAD-7 - Generalised Anxiety Disorders Scale HRQoL - health-related quality of life PHQ-9 - Patient Health Questionnaire PLHIV - people living with HIV RAs - research assistants SSQ-14 - Shona symptoms questionnaire VAS- Visual Analogue Scale Declarations Ethics approval and Consent to participate Parirenyatwa Group of Hospitals granted institutional approval, and ethical approval was obtained from the Medical Research Council of Zimbabwe (Ref: MRCZ/A/2496). All methods were carried out in accordance with The Declaration of Helsinki. Participants were treated as autonomous agents and were requested to sign written consent before participation. Written informed consent was obtained from all subjects before participation in this study. Randomised participant ID numbers were used to preserve confidentiality. Data and signed informed consent forms were stored securely, only the researchers could access the information gathered, and participants could voluntarily withdraw from the study without any consequences. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. The datasets will be made available on online repositories once all manuscripts related to the study have been published online. Competing interests All the authors declare no competing interests. Funding The study was funded by the EuroQol Foundation, Grant Number: Project 212-RA. Authors contributions Conceptualisation: JMD, FDP, BD, DC, ASP Funding acquisition: JMD, FDP, DC, ASP Data collection: JMD, BKS, ARH, SRD, TDT Data analysis and interpretation: JMD, FDP, BD, ASP, DC Writing – original draft: JMD, BKS, ARH, SRD, TDT Writing – review and editing: JMD, FDP, BKS, ARH, SRD, TDT, BD, DC, ASP All authors read and approved the final manuscript version. Disclosures ASP and FDP are members of the EuroQol Group. The funder had no role in study design, analysis and results interpretation. Acknowledgements We want to acknowledge participants for their contribution to the study. Authors ORCID information Jermaine M Dambi (JMD): https://orcid.org/0000-0002-2446-7903 Fredrick D. Purba (FDP): https://orcid.org/0000-0002-7336-3043 Beatrice K Shava (BKS): https://orcid.org/0000-0002-9130-7010 Anotida R Hove (ARH): https://orcid.org/0009-0005-4050-0135 Shalom R Doyce (SRD): https://orcid.org/0009-0006-7593-3253 Tariro D. Tunduwani (TDT): https://orcid.org/0009-0004-8073-7068 Ben Domingue (BD): https://orcid.org/0000-0002-3894-9049 Dixon Chibanda (DC): https://orcid.org/0000-0003-2505-8607 A. Simon Pickard (ASP): https://orcid.org/0000-0001-5645-7091 References Tsai AC. Reliability and validity of depression assessment among persons with HIV in sub-Saharan Africa: systematic review and meta-analysis. J Acquir Immune Defic Syndr. 2015;66: 503–511. doi:10.1097/QAI.0000000000000210.Reliability UNAID. IN DANGER: UNAIDS Global AIDS Update 2022. 2022; 1–376. Ayano G, Solomon M, Abraha M. A systematic review and meta-analysis of epidemiology of depression in people living with HIV in east Africa. BMC Psychiatry. 2018;18: 1–13. doi:10.1186/s12888-018-1835-3 Ssebunnya J, Mugisha J, Mpango R, Kyohangirwe L, Taasi G, Ssentongo H, et al. Using Theory of Change to inform the design of the HIV+D intervention for integrating the management of depression in routine HIV care in Uganda. PLoS ONE. 2021;16: 1–14. doi:10.1371/journal.pone.0259425 Chibanda D, Verhey R, Gibson LJ, Munetsi E, Machando D, Rusakaniko S, et al. Validation of screening tools for depression and anxiety disorders in a primary care population with high HIV prevalence in Zimbabwe. J Affect Disord. 2016;198: 50–55. doi:10.1016/j.jad.2016.03.006 Kulisewa K, Stockton MA, Hosseinipour MC, Gaynes BN, Mphonda S, Udedi MM, et al. The Role of Depression Screening and Treatment in Achieving the UNAIDS 90–90–90 Goals in Sub-Saharan Africa. AIDS Behav. 2019;23: 153–161. doi:10.1007/s10461-019-02593-7 Sayah F Al, Ohinmaa A, Johnson JA. Screening for Anxiety and Depressive Symptoms in Type 2 Diabetes Using Patient-Reported Outcome Measures: Comparative Performance of the EQ-5D-5L and SF-12v2. MDM Policy Pract. 2018;3: 1–11. doi:10.1177/2381468318799361 Feng YS, Kohlmann T, Janssen MF, Buchholz I. Psychometric properties of the EQ-5D-5L: a systematic review of the literature. Qual Life Res. 2021;30: 647–673. doi:10.1007/s11136-020-02688-y Herdman M, Gudex C, Lloyd A, Janssen Mf, Kind P, Parkin D, et al. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011;20: 1727–1736. doi:10.1007/s11136-011-9903-x Devlin N, Pickard S, Busschbach J. The development of the EQ-5D-5L and its value sets. Value Sets EQ-5D-5L Compend Comp Rev User Guide. 2022; 1–12. doi:10.1007/978-3-030-89289-0_1 Jelsma J, Mhundwa K, De Weerdt W, De Cock P, Chimera J, Chivaura V. The reliability of the Shona version of the EQ-5D. Cent Afr J Med. 2001;47: 8–13. Chibanda D, Weiss HA, Verhey R, Simms V, Munjoma R, Rusakaniko S, et al. Effect of a primary care-based psychological intervention on symptoms of common mental disorders in Zimbabwe: A randomized clinical trial. JAMA - J Am Med Assoc. 2016;316: 2618–2626. doi:10.1001/jama.2016.19102 Mafirakureva N, Dzingirai B, Postma MJ, van Hulst M, Khoza S. Health-related quality of life in HIV/AIDS patients on antiretroviral therapy at a tertiary care facility in Zimbabwe. AIDS Care - Psychol Socio-Med Asp AIDSHIV. 2016;28: 904–912. doi:10.1080/09540121.2016.1173639 Janssen MF, Buchholz I, Golicki D, Bonsel GJ. Is EQ-5D-5L Better Than EQ-5D-3L Over Time? A Head-to-Head Comparison of Responsiveness of Descriptive Systems and Value Sets from Nine Countries. PharmacoEconomics. 2022;40: 1081–1093. doi:10.1007/s40273-022-01172-4 Thompson AJ, Turner AJ. A Comparison of the EQ-5D-3L and EQ-5D-5L. PharmacoEconomics. 2020;38: 575–591. doi:10.1007/s40273-020-00893-8 Bagattini ÂM, Camey SA, Miguel SR, Andrade MV, de Souza Noronha KVM, Monica MA, et al. Electronic Version of the EQ-5D Quality-of-Life Questionnaire: Adaptation to a Brazilian Population Sample. Value Health Reg Issues. 2018;17: 88–93. doi:10.1016/j.vhri.2017.11.002 Lundy JJ, Joel S, Emuella C, Mira F, Patel J. Agreement Among Paper and Electronic Modes of the EQ-5D‑5L. Patient - Patient-Centered Outcomes Res. 2020;13: 435–443. doi:10.1007/s40271-020-00419-6 Mulhern B, O’Gorman H, Rotherham N, Brazier J. Comparing the measurement equivalence of EQ-5D-5L across different modes of administration. Health Qual Life Outcomes. 2015;13: 1–9. doi:10.1186/s12955-015-0382-6 Coons SJ, Gwaltney CJ, Hays RD, Lundy JJ, Sloan JA, Revicki DA, et al. Recommendations on evidence needed to support measurement equivalence between electronic and paper-based patient-reported outcome (PRO) measures: ISPOR ePRO good research practices task force report. Value Health. 2009;12: 419–429. doi:10.1111/j.1524-4733.2008.00470.x Williams N. The GAD-7 questionnaire. Occup Med. 2014;64: 224. doi:10.1093/occmed/kqt161 Bushnell DM, Reilly MC, Galani C, Martin ML, Ricci JF, Patrick DL, et al. Validation of electronic data capture of the irritable bowel syndrome - Quality of life measure, the work productivity and activity impairment questionnaire for irritable bowel syndrome and the EuroQol. Value Health. 2006;9: 98–105. doi:10.1111/j.1524-4733.2006.00087.x O’Donohoe P, Reasner DS, Kovacs SM, Byrom B, Eremenco S, Barsdorf AI, et al. Updated Recommendations on Evidence Needed to Support Measurement Comparability Among Modes of Data Collection for Patient-Reported Outcome Measures: A Good Practices Report of an ISPOR Task Force. Value Health. 2023;26: 623–633. doi:10.1016/j.jval.2023.01.001 Tigirigi TO, Sithole GY, Chakara P, Chirombo GZ, Chiweza AR, Mubayiwa TR, et al. Evaluation of the health-related quality of life and associated factors in Zimbabwean adults living with HIV: a cross-sectional study. BMC Res Notes. 2023;16: 1–8. doi:10.1186/s13104-023-06536-3 Parker R, Stein DJ, Jelsma J. Pain in people living with HIV/AIDS: A systematic review. J Int AIDS Soc. 2014;17. doi:10.7448/IAS.17.1.18719 Additional Declarations No competing interests reported. Supplementary Files Additionalfiles.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 21 Oct, 2025 Reviews received at journal 21 Oct, 2025 Reviews received at journal 17 Oct, 2025 Reviews received at journal 17 Oct, 2025 Reviewers agreed at journal 30 Sep, 2025 Reviewers agreed at journal 29 Sep, 2025 Reviewers agreed at journal 27 Sep, 2025 Reviewers invited by journal 24 Aug, 2025 Editor assigned by journal 07 Aug, 2025 Submission checks completed at journal 07 Aug, 2025 First submitted to journal 04 Aug, 2025 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. 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Dambi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIiWNgGAWjYBACxgYQaQDEBxjYGBIqgAxm5gZStJwBaWHErwUBQFoY2xDG4ATM7b1PN/wouCPHd/x02oOH82qj+duBWn5UbMPtsJ7jZjd7DJ4ZS57J3W6QuO147ozDjA2MPWdu49YyI43tBo/B4cQNB3K3SSRuO5bbANTCzNiGR8v8Z2w3/xgcrt9w/i1Qy5xjufMJapnBxnYbaEuCwQ2QLQ01uRsIaulJY7stY3DYcOaNt9sNEo4dyN0I1HIQn18M24+x3Xzz57A83/ncbQ9/1NTlzjt/+OCDHxV4tDSg8g+DyQM41QOBPBq/Dp/iUTAKRsEoGKEAAO12Zi150vqKAAAAAElFTkSuQmCC","orcid":"","institution":"University of Zimbabwe","correspondingAuthor":true,"prefix":"","firstName":"Jermaine","middleName":"M.","lastName":"Dambi","suffix":""},{"id":505887348,"identity":"aa007b58-539e-4645-a2f3-31cac19a9420","order_by":1,"name":"Fredrick D. Purba","email":"","orcid":"","institution":"Universitas Padjadjaran","correspondingAuthor":false,"prefix":"","firstName":"Fredrick","middleName":"D.","lastName":"Purba","suffix":""},{"id":505887349,"identity":"1b429d7a-3265-488f-ac9c-3ff93fd62101","order_by":2,"name":"Beatrice K. Shava","email":"","orcid":"","institution":"University of Zimbabwe","correspondingAuthor":false,"prefix":"","firstName":"Beatrice","middleName":"K.","lastName":"Shava","suffix":""},{"id":505887350,"identity":"fb5e8a29-8e87-4fcf-9670-04a89fc7a2b9","order_by":3,"name":"Anotida R. Hove","email":"","orcid":"","institution":"University of Zimbabwe","correspondingAuthor":false,"prefix":"","firstName":"Anotida","middleName":"R.","lastName":"Hove","suffix":""},{"id":505887351,"identity":"8e1efd9a-6fb5-4d5f-8cad-b2a8f5ebe0de","order_by":4,"name":"Shalom R. Doyce","email":"","orcid":"","institution":"University of Zimbabwe","correspondingAuthor":false,"prefix":"","firstName":"Shalom","middleName":"R.","lastName":"Doyce","suffix":""},{"id":505887352,"identity":"b2c06200-4551-4666-855e-3bd82304bcd3","order_by":5,"name":"Tariro Tunduwani","email":"","orcid":"","institution":"University of Zimbabwe","correspondingAuthor":false,"prefix":"","firstName":"Tariro","middleName":"","lastName":"Tunduwani","suffix":""},{"id":505887353,"identity":"8ba6c89f-9638-41c9-b86b-031fafab84d8","order_by":6,"name":"Ben Domingue","email":"","orcid":"","institution":"Stanford University","correspondingAuthor":false,"prefix":"","firstName":"Ben","middleName":"","lastName":"Domingue","suffix":""},{"id":505887354,"identity":"db76d1b5-034f-4ea7-b221-3215733c207b","order_by":7,"name":"Dixon Chibanda","email":"","orcid":"","institution":"Friendship Bench","correspondingAuthor":false,"prefix":"","firstName":"Dixon","middleName":"","lastName":"Chibanda","suffix":""},{"id":505887355,"identity":"ef282c0c-9f24-4db8-82e7-ca36190cc1bc","order_by":8,"name":"A. Simon Pickard","email":"","orcid":"","institution":"University of Illinois at Chicago","correspondingAuthor":false,"prefix":"","firstName":"A.","middleName":"Simon","lastName":"Pickard","suffix":""}],"badges":[],"createdAt":"2025-08-04 05:53:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7287257/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7287257/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90383356,"identity":"6aff9cfa-7b04-4a86-8308-3c21ff668127","added_by":"auto","created_at":"2025-09-02 06:56:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":181022,"visible":true,"origin":"","legend":"\u003cp\u003eStudy flowchart\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7287257/v1/9c0885d23fc6c852152e4abc.png"},{"id":90383797,"identity":"b0d1bb11-0822-49cb-87a1-d8ae74c1c6ed","added_by":"auto","created_at":"2025-09-02 07:04:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1557667,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7287257/v1/39a978fc-87cb-42f4-aac2-1111e1920398.pdf"},{"id":90381502,"identity":"3f9615f3-1b73-4aed-a1aa-dc713cadccab","added_by":"auto","created_at":"2025-09-02 06:48:26","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":19197,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfiles.docx","url":"https://assets-eu.researchsquare.com/files/rs-7287257/v1/e6e3f7fb2f24c753117e4958.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Randomised Equivalency Study of the EQ-5D-5L Shona Versions - Evaluation of Measurement Equivalency Between Digital and Paper Formats","fulltext":[{"header":"Plain language summary","content":"\u003cp\u003eMany people living with HIV experience anxiety and depression, which can harm their overall health. These mental health issues often go unnoticed, so it\u0026apos;s important to have quick tools for regular checks. This study compares the digital and paper versions of the Shona EQ-5D-5L to see which one is more accurate for measuring the well-being of people living with HIV. Understanding these tools will help improve care for people with HIV. We studied 700 participants, split evenly between those using the digital version and those using the paper version of the Shona EQ-5D-5L. Our findings showed that both versions of the Shona EQ-5D-5L produced similar results. This means both can be reliably used to measure well-being in people living with HIV. We also found that older age, food insecurity, and higher anxiety or depression levels are linked to lower well-being. This shows a need for targeted programs to help improve the well-being of people living with HIV.\u003c/p\u003e\n"},{"header":"Background","content":"\u003cp\u003eThe Sub-Saharan region bears the highest burden of HIV/AIDS worldwide, with 69% of the 39\u0026nbsp;million individuals living with HIV/AIDS (PLHIV) located in Sub-Saharan Africa [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Unfortunately, non-communicable diseases, particularly common mental health disorders (CMDs), are highly prevalent in PLHIV [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. For example, up to 30% of PLIHV suffer from comorbid depression [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Comorbid CMDs are associated with negative impacts across the care continuum, including increased morbidity and mortality [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Consequently, early detection and treatment of CMDs are essential for optimal treatment outcomes in PLHIV [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. There is also an increasing use of generic health status outcomes for routine health outcome measurement and screening for CMDs in people living with chronic conditions, including HIV [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Unlike condition-specific CMDs screeners, generic patient-reported outcome measures have greater utility as they can be used for CMDs screening, routine health assessments and comparative health evaluations [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The European Quality of Life 5 Dimensions (EQ-5D) is a widely used routine health status measurement in health systems [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The EQ-5D assesses health in five domains, i.e. mobility, usual activities, self-care, pain /discomfort and anxiety/depression [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The EQ-5D is extensively used globally and has been translated and standardised in over 150 languages [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Also, the EQ-5D is available in different versions (e.g. five-level (5L) vs three-level (3L) versions [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]).\u003c/p\u003e\u003cp\u003eThe EQ-5D-3L, which consists of three response options, \u0026ldquo;no problem\u0026rdquo;, \u0026ldquo;some problems\u0026rdquo;, and \u0026ldquo;severe problems\u0026rdquo;, has been translated and validated into Shona, a Zimbabwean native language. The translated version demonstrates strong validity and reliability, with utility values that are available and have been widely utilised in research [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, the EQ-5D-3L is prone to floor and ceiling effects [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. A large cohort study (N\u0026thinsp;=\u0026thinsp;1,023,218) found lower ceiling effects of the EQ-5D-5L (43.8%) compared to the EQ-5D-3L (54.4%) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Consequently, the EuroQol Group recommends the EQ-5D-5L version as their generic HRQoL outcome of choice. The EQ-5D is available in paper or digital formats and can be self-, interviewer- or proxy-administered [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Owing to exponential digitalisation globally, digital versions are increasingly used compared to paper-based versions [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Digital administration increases clinical utility and psychometric performance as it eliminates missing responses, automatically creates a database and facilitates sharing clients\u0026rsquo; HRQoL valuations in real-time, optimising clinical care further [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Previous studies have demonstrated the measurement equivalency of both digital and paper-based versions of the EQ-5D [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Due to the identified floor and ceiling effects of the 3L version, the Zimbabwean 3L versions were upgraded to the 5L versions in this study. This process included translating and validating the newly introduced 5L digital version, which was not empirically tested in Zimbabwe. Therefore, we set out to evaluate the psychometric performance of the digital EQ-5D-5L Shona version in PLHIV, explicitly evaluating these properties:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eComparing the measurement equivalency of the paper and digital versions\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eKnown-groups validity - comparing scores across participants\u0026rsquo; characteristics (e.g., age, sex, education, socio-economic status); thus, assessing factors associated with HRQoL in PLHIV.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy setting\u003c/h2\u003e\u003cp\u003eThe study was done at the Family Care Centre at Parirenyatwa Group of Hospitals in Harare, Zimbabwe. The FCC offers in-house testing, medical, and psychological services to PLHIV. The FCC is the biggest referral centre for the provision of HIV-related services countrywide, serving about 3000 clients per month.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStudy design\u003c/h3\u003e\n\u003cp\u003eA parallel, individualised, randomised study design was used. Participants were individually randomised to complete either the digital or paper version.\u003c/p\u003e\n\u003ch3\u003eStudy participants’ selection criteria\u003c/h3\u003e\n\u003cp\u003eWe recruited consenting adult patients (aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years) with a confirmed diagnosis of HIV and proficiency in either English or the Shona language. Patients with a known diagnosis of a psychiatric condition, such as major depression, according to the doctor\u0026rsquo;s notes, were similarly excluded.\u003c/p\u003e\n\u003ch3\u003eSample size calculation\u003c/h3\u003e\n\u003cp\u003eA minimum of 234 participants per group were required to demonstrate equivalence to rule out differences of 0.3 standard deviations across the paper and digital versions at a 95% confidence interval and 80% goal power [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eOutcome Measures\u003c/h3\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eDemographic questionnaire\u003c/h2\u003e\u003cp\u003eThis questionnaire extracted participants\u0026rsquo; demographics, i.e., age, gender, education level, employment status, and marital status.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eEQ-5D-5L\u003c/h3\u003e\n\u003cp\u003eThe EQ-5D is a standardised, self-report HRQoL measure with five dimensions, i.e., mobility, self-care, usual, pain/discomfort and anxiety/depression. Participants also rate their HRQoL on a visual analogue scale with scores in the range of 0-100. The EQ-5D-3L paper version is translated into Shona, a Zimbabwean native language, and validated in both the general population and PLHIV [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Normative utility scores are available for the Zimbabwean population [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In this study, we validate the newly upgraded EQ-5D-5L Shona version.\u003c/p\u003e\n\u003ch3\u003eShona symptoms questionnaire (SSQ-14)\u003c/h3\u003e\n\u003cp\u003eThe SSQ is a proven, psychometrically sound, native Zimbabwean 14-item tool for the screening of CMDs [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Respondents indicate whether they experienced the 14 psychological symptoms in the past seven days. A reported symptom (\u0026ldquo;yes\u0026rdquo; response) is rated as one, and a \u0026ldquo;no\u0026rdquo; symptom is rated zero. A score of eight is regarded as a case exhibiting psychiatric morbidity. The SSQ only takes 2\u0026ndash;3 minutes to complete and is validated in PLHIV in the research setting [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003ePatient Health Questionnaire-9 (PHQ-9)\u003c/h2\u003e\u003cp\u003eThe PHQ is a generic, nine-item depression screen. Respondents rate the frequency of experience of the enlisted depressive symptoms in the previous two weeks on a four-point Likert scale, which ranges from \u0026ldquo;not at all =\u0026thinsp;all =\u0026thinsp;0\u0026rdquo; to \u0026ldquo;all the time\u0026thinsp;=\u0026thinsp;3\u0026rdquo; to give a cumulative score range of 0\u0026ndash;27. Scores in the ranges 0\u0026ndash;9, 15\u0026ndash;19 and 20\u0026ndash;27 are interpreted as follows: minor, moderate and severe depression, respectively [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The PHQ-9 has been extensively used for clinical and research purposes and is validated in PLHIV in the research setting [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eGeneralised Anxiety Disorders Scale (GAD-7)\u003c/h2\u003e\u003cp\u003eThe GAD-7 is a seven-item, self-report anxiety screen [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Respondents rate the frequency of experience of the enlisted anxiety symptoms in the previous two weeks on a four-point Likert scale, which ranges from \u0026ldquo;not at all =\u0026thinsp;all =\u0026thinsp;0\u0026rdquo; to \u0026ldquo;all the time\u0026thinsp;=\u0026thinsp;2\u0026rdquo; to give a cumulative score range of 0\u0026ndash;21. The criteria values for low, moderate and severe anxiety are 5,10 and 15, respectively [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The GAD-7 has been validated in PLHIV in the research setting [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eData collection procedure\u003c/h2\u003e\u003cp\u003eProspective participants were recruited as they presented for routine HIV care. Participants were addressed by three research assistants (RAs) in the treatment waiting areas; those who expressed interest were given identification stickers. Another set of two RAs thereafter approached attendees with stickers, checked for eligibility, and initiated the consenting process. Individuals who met the selection criteria and consented to participate were requested to pick a concealed envelope. The envelopes contained codes to randomly assign participants to two study arms, i.e., tablet and paper. The research team then administered a demographic questionnaire to elicit participant demographics, e.g., age and sex. They also assessed literacy levels and familiarity with technological devices to evaluate the feasibility of self-completion of the EQ-5D questionnaires. The EQ-5D and test battery were self-completed; however, the research team was available to assist participants as necessary through the completion process.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eTraining\u003c/h2\u003e\u003cp\u003eTo standardise the data collection procedures, we conducted a training workshop for the research team. The research team received training in good clinical practice, including informed consent and administering questionnaires.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eData analysis plan\u003c/h2\u003e\u003cp\u003eDescriptive statistics (e.g. means, frequencies) were used to analyse participants\u0026rsquo; characteristics. Multivariate binary logistic regression was used to investigate the influence of administration mode (paper vs digital) and participants\u0026rsquo; characteristics (e.g., age, gender, education) on EQ-5D-5L Visual Analogue Scale (VAS) and utility scores. Both crude odds ratios (COR) and adjusted odds ratios (AOR), along with their associated 95% confidence intervals, are presented to depict the univariate and adjusted analyses. The analysis was done using SPSS (Version 29). The significance level was set at α\u0026thinsp;=\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eData management/Ethical considerations\u003c/h2\u003e\u003cp\u003eData were collected electronically using RedCap, programmed onto Android tablets. The Android tablets required a two-step authentication process: a fingerprint scan and a personal identification (PIN) code. The raw data were de-identified by assigning arbitrary numeric codes for participants. Files containing the consent forms are stored in a secure locker at the University of Zimbabwe. The digital copy of the data is saved on a password-protected laptop and backed up on OneDrive. Participants were treated as autonomous agents and participated in the study voluntarily. Parirenyatwa Group of Hospitals granted institutional approval, and ethical approval was obtained from the Medical Research Council of Zimbabwe (Ref: MRCZ/A/2496).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eCONSORT flowchart\u003c/h2\u003e\u003cp\u003e\u003cb\u003e\u0026lt;Insert\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003ehere\u0026gt;\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe screened 930 participants, of whom 700 met the inclusion criteria and were randomly assigned equally to either the paper or digital group (350 participants per group). In the digital group, 340 participants completed the form. However, 10 participants dropped out due to time pressure, leaving 330 participants for analysis. In the paper group, 337 participants completed the form. However, 38 participants dropped out due to time pressure, and 18 had missing VAS scores, resulting in 281 participants for analysis (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eDemographics\u003c/h2\u003e\u003cp\u003eA total of 611 participants were included in the study, with a mean age of 37.5 years (SD 12.2). Most participants were female (70.7%), attained secondary education (68.0%), and reported inadequate financial adequacy (68.7%) and food insecurity (51.2%). Participants did not generally smoke (93.7%), consume alcohol (80.5%), or use substances (96.7%); however, 65.5% reported experiencing an adverse event in the past month. The two groups were comparable across all domains, except for substance intake. The prevalence of substance intake was higher in the digital than paper group, i.e. 2.6% vs. 0.7%, and the difference was statistically significant, \u003cem\u003eX\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003csub\u003edf\u0026thinsp;=\u0026thinsp;1\u003c/sub\u003e = 4.59, p\u0026thinsp;=\u0026thinsp;.032 - See Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003e\u0026lt;Insert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003ehere\u0026gt;\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eParticipant characteristics, N\u0026thinsp;=\u0026thinsp;611\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAttribute\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDigital, n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePaper, n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal, n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eStatistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e232 (38.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e200 (32.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e432 (70.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eX\u003csup\u003e2\u003c/sup\u003edf\u0026thinsp;=\u0026thinsp;1 =\u0026thinsp;.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e.883\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e98 (16.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e81 (13.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e179 (29.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e*Age\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e37.4 (11.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e37.8 (12.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e37.5 (12.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003et(df\u0026thinsp;=\u0026thinsp;609)\u0026thinsp;=\u0026thinsp;0.409\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.682\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eEducation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrimary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e35 (5.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24 (2.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e59 (9.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eX\u003csup\u003e2\u003c/sup\u003edf\u0026thinsp;=\u0026thinsp;2\u0026thinsp;=\u0026thinsp;2.050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e.359\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSecondary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e216 (35.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e199 (32.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e415 (67.9)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTertiary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e79 (12.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e58 (9.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e137 (22.4)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFinancial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInadequate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e224 (36.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e196 (32.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e420 (68.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eX\u003csup\u003e2\u003c/sup\u003edf\u0026thinsp;=\u0026thinsp;1 =\u0026thinsp;.168\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e.682\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdequacy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAdequate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e106 (17.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e85 (13.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e191 (31.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eFood security\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInadequate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e164 (26.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e149 (24.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e313 (51.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eX\u003csup\u003e2\u003c/sup\u003edf\u0026thinsp;=\u0026thinsp;1\u0026thinsp;=\u0026thinsp;.546\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e.460\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAdequate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e166 (27.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e132 (21.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e298 (48.8)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSmoking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e307 (50.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e267 (43.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e574 (93.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eX\u003csup\u003e2\u003c/sup\u003edf\u0026thinsp;=\u0026thinsp;1\u0026thinsp;=\u0026thinsp;.733\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e.392\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23 (3.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14 (2.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e37 (6.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAlcohol Intake\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e262 (42.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e230 (37.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e492 (80.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eX\u003csup\u003e2\u003c/sup\u003edf\u0026thinsp;=\u0026thinsp;1\u0026thinsp;=\u0026thinsp;.438\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e.508\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e68 (11.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e51 (8.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e119 (19.5)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e**Substance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e315 (51.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e277 (45.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e591 (96.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eX\u003csup\u003e2\u003c/sup\u003edf\u0026thinsp;=\u0026thinsp;1\u0026thinsp;=\u0026thinsp;4.593\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003e.032\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntake\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16 (2.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4 (0.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e20 (3.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAdverse event\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e223 (36.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e179 (29.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e402 (65.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eX\u003csup\u003e2\u003c/sup\u003edf\u0026thinsp;=\u0026thinsp;1\u0026thinsp;=\u0026thinsp;.848\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e.357\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e107 (17.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e102 (16.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e209 (34.2)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSSQ-14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u0026ndash;8 (No risk)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e211 (34.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e178 (29.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e389 (63.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eX\u003csup\u003e2\u003c/sup\u003edf\u0026thinsp;=\u0026thinsp;1\u0026thinsp;=\u0026thinsp;.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e.946\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9\u0026ndash;14 (At risk)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e119 (19.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e103 (16.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e222 (36.3)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePHQ-9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u0026ndash;10 (No risk)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e278 (45.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e241 (39.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e519 (84.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eX\u003csup\u003e2\u003c/sup\u003edf\u0026thinsp;=\u0026thinsp;1\u0026thinsp;=\u0026thinsp;.169\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e.681\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11\u0026ndash;27 (At risk)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e52 (8.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40 (6.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e92 (15.1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eGAD-7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u0026ndash;9 (No risk)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e268 (43.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e241 (29.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e509 (83.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eX\u003csup\u003e2\u003c/sup\u003edf\u0026thinsp;=\u0026thinsp;1\u0026thinsp;=\u0026thinsp;1.947\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e.163\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10\u0026ndash;21 (At risk)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e62 (10.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40 (6.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e102 (16.7)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e* Data not in n (%) format; ** Bolded values are statistically significant\u003c/h2\u003e\u003cdiv id=\"Sec21\" class=\"Section3\"\u003e\u003ch2\u003eHRQoL evaluations comparability across administration modes\u003c/h2\u003e\u003cp\u003eMost participants had no problems with mobility (79.3%), self-care (89.5%), and usual activities (81.2%). Pain and discomfort (41.7%) and anxiety/depression (39.9%) were the most reported problems. The reported problems were comparable across groups (digital vs. paper) in all domains \u0026ndash; See Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003e\u0026lt;Insert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003ehere\u0026gt;\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFrequencies of responses on the EQ-5D-5L\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDimension\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLevel of problems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDigital, n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePaper, n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal, %\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eStatistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMobility\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e252 (41.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e233 (38.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e79.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e\u003csub\u003edf\u0026thinsp;=\u0026thinsp;4\u003c/sub\u003e =5.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.276\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSlight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e43 (7.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28 (4.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24 (3,9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11 (1.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSevere\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8 (1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnable/extreme\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (0.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (0.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSelf-care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e294 (48.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e253 (41.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e89.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e\u003csub\u003edf\u0026thinsp;=\u0026thinsp;4\u003c/sub\u003e =2.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.583\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSlight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13 (2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9 (1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSevere\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (0.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnable/extreme\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (0.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUsual activities\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e268 (43.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e228 (37.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e81.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e\u003csub\u003edf\u0026thinsp;=\u0026thinsp;4\u003c/sub\u003e =.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.995\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSlight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36 (5.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33 (5.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13 (2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSevere\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8 (1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 (1.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnable/extreme\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (0.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (0.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePain/Discomfort\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e197 (32.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e159 (26.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e58.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e\u003csub\u003edf\u0026thinsp;=\u0026thinsp;4\u003c/sub\u003e =2.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.615\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSlight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e90 (14.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e78 (12.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e27.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27 (4.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31 (5.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSevere\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8 (1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (1.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnable/extreme\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8 (1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4 (0.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnxiety/\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNot\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e188 (30.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e179 (29.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e60.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e\u003csub\u003edf\u0026thinsp;=\u0026thinsp;4\u003c/sub\u003e =3.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.485\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003edepression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSlight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e89 (14.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e62 (10.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e24.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24 (3.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20 (3.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSevere\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21 (3.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13 (2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnable/extremely\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8 (1.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (1.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e* EQ-5D-5L Utility\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.81 (0.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.82 (0.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003et (df\u0026thinsp;=\u0026thinsp;609)\u0026thinsp;=\u0026thinsp;0.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.324\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e* EQ-5D-5L VAS Score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77.5 (23.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e80.5 (19.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003et (df\u0026thinsp;=\u0026thinsp;600)\u0026thinsp;=\u0026thinsp;1.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e.104\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003e* Data not in n (%) format\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003eMeasurement equivalency evaluation\u003c/h2\u003e\u003cp\u003eUnivariate binary logistic regression showed that EQ-5D-5L scores were independent of group allocation for both the EQ-5D 5L scores [COR\u0026thinsp;=\u0026thinsp;0.906, 95% CI (-0.656: 1.252), p\u0026thinsp;=\u0026thinsp;.549] and EQ-5D 5L utility scores [COR\u0026thinsp;=\u0026thinsp;.915, 95% (.656: 1.275), p\u0026thinsp;=\u0026thinsp;.599], thus demonstrating measurement equivalency of the paper and digital versions of the EQ-5D-5L Shona Version -see Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e for the rest of the univariate analyses.\u003c/p\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003eHRQoL determinants assessment\u003c/h2\u003e\u003cp\u003eAlso, the unadjusted odds ratios (bivariate binary logistic regression) show that increased age, low educational attainment, food insecurity, perceived financial inadequacy, smoking, substance intake/usage, experiencing an adverse event, and elevated anxiety and depression symptoms were associated with lower HRQoL \u0026ndash; See Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. After adjusting for confounding and co-variation in multivariate binary logistic regression, only increased age (AOR\u0026thinsp;=\u0026thinsp;.60: 95% CI .41-.88, p\u0026thinsp;=\u0026thinsp;.008), food insecurity (AOR\u0026thinsp;=\u0026thinsp;1.8: 95% CI 1.2: 2.8, p\u0026thinsp;=\u0026thinsp;.01), financial insecurity, (AOR\u0026thinsp;=\u0026thinsp;1.72: 95% CI 1.10\u0026ndash;2.69, p\u0026thinsp;=\u0026thinsp;0.017) and elevated comorbid anxiety/depression symptoms (AOR\u0026thinsp;=\u0026thinsp;0.45: 95% CI: 0.29\u0026ndash;0.68, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) were associated with lower HRQoL \u0026ndash; See Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u0026lt;Insert\u003c/strong\u003e Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cstrong\u003ehere\u0026gt;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eFactors associated with EQ-5D-5L scores (Adjusted Odds Ratios)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eEQ-5D-5L VAS Scores\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eEQ-5D-5L Utility Scores\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\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAttribute\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**Age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u0026ndash;37 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.768 (0.541\u0026ndash;1.091)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.601 (0.413\u0026ndash;0.875)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.008\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u0026ndash;77 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.189 (0.803\u0026ndash;1.759)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.389 (0.908\u0026ndash;2.125)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.525 0.763\u0026ndash;3.049)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.125 (0.545\u0026ndash;2.323)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.039 (0.667\u0026ndash;1.618)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.866\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.929 (0.572\u0026ndash;1.511)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.767\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTertiary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**Food\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInadequate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.222 (0.805\u0026ndash;1.854)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.346\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.793 (1.153\u0026ndash;2.788)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSecurity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdequate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**Financial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInadequate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.724 (1.104\u0026ndash;2.693)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.603 (0.978\u0026ndash;2.627)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSecurity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdequate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmoking status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.514 (0.241\u0026ndash;1.098)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.577 (0.266\u0026ndash;1.251)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.164\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdverse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.79 (0.543\u0026ndash;1.148)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.687 (0.464\u0026ndash;1.015)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEvent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**SSQ-14 scores\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u0026ndash;8 (Not at risk)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.472 (0.314\u0026ndash;0.708)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.447 (0.294\u0026ndash;0.678)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCategories\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u0026ndash;14 (At risk)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePHQ-9 scores\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u0026ndash;10 (Not at risk)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.812 (0.44\u0026ndash;1.498)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.504\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.765 (0.408\u0026ndash;1.436)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.404\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCategories\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u0026ndash;27 (At risk)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGAD-7 scores\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u0026ndash;9 (Not at risk)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.944 (0.522\u0026ndash;1.707)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.626 (0.342\u0026ndash;1.146)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.129\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCategories\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u0026ndash;21 (At risk)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\n \u003ch2\u003e** Bolded values are statistically significant\u003c/h2\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e\u003ch2\u003eOverall synthesis\u003c/h2\u003e\u003cp\u003eElectronic patient-reported outcome measures are increasingly used for routine data collection and research. We aimed to validate the digital EQ-5D-5L Shona version and compare its measurement equivalency to the paper version, as well as assess HRQoL determinants in PLHIV. Both digital and paper-based versions of the EQ-5D-5L Shona displayed measurement equivalency. Also, increased age, food insecurity, financial insecurity, and elevated comorbid anxiety/depression symptoms were associated with lower HRQoL.\u003c/p\u003e\u003cdiv id=\"Sec27\" class=\"Section3\"\u003e\u003ch2\u003eMeasurement equivalence of digital and paper versions\u003c/h2\u003e\u003cp\u003eThis study demonstrated the equivalency of the newly translated paper and digital versions of the EQ-5D-5L, as psychometric performance was independent of administration mode. This is significant because both paper and digital versions can confidently be used for routine and research purposes [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Elsewhere, a randomised crossover study among American Irritable Bowel Syndrome patients (N\u0026thinsp;=\u0026thinsp;72) showed the measurement equivalency of paper and digital/mobile device versions [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In the American study, the intraclass correlation coefficients for the EQ-5D-5L VAS and index scores were 0.822 and 0.77, respectively, showing a high agreement of scores across the administration modes [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Also, a UK-based randomised crossover study among health participants (n\u0026thinsp;=\u0026thinsp;60) and patients with chronic conditions (n\u0026thinsp;=\u0026thinsp;30) also supports the measurement equivalency of paper and multiple digital EQ-5D-5L versions, i.e., handheld, tablet, interactive voice response and web. The wide array of modes utilised in the UK study enables the feasibility of electronic data collection according to patient preferences and resource availability [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Like our study, using a parallel randomised study design, Mulhern et al. (2015) also demonstrated the measurement equivalency of paper and digital versions of the EQ-5D-5L among UK-based adults without (n\u0026thinsp;=\u0026thinsp;60) and with chronic conditions (n\u0026thinsp;=\u0026thinsp;30). Mulhern et al. (2015) also showed acceptability and a greater preference towards the digital EQ-5D-5L version. Digital versions can be programmed to negate missing responses, which increases their utility and psychometric performance [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Our study supports this proposition, as the paper version had respondents with 6.0% missing data. However, in low-income countries such as Zimbabwe, paper-based versions have equally important utility, as not all studies and healthcare facilities may have access to digital infrastructure for electronic data collection of HRQoL evaluations. The ISPOR ePRO task force warns against the bias towards using digital over paper-based patient-reported outcome measures [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Thus, access to both modes is invaluable, and our study supports the equivalency of paper and digital versions of the EQ-5D-5L Shona versions.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec28\" class=\"Section2\"\u003e\u003ch2\u003eHRQoL determinants\u003c/h2\u003e\u003cp\u003eFindings from the adjusted multivariate binary logistic regression showed that increased CMDs symptoms were associated with lower HRQoL scores on both the VAS and utility scores. Comorbid mental disorders are highly prevalent in PLHIV, coupled with variable daily life challenges faced by PLHIV, the fluctuations in mental health states are unsurprising [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Zimbabwe has faced decades of ongoing socioeconomic challenges, with most people living in poverty; this is likely to contribute to the high burden of CMDs in people living with HIV, given the positive association between lower HRQoL and lower financial insecurity reported in this study and elsewhere [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Also, in this study, PLHIV without food security were nearly likely to report lower HRQoL when compared to those with adequate food security, AOR\u0026thinsp;=\u0026thinsp;1.8 (95% CI:1.2\u0026ndash;2.8); this is consistent with our previous study in the same setting [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Food insecurity is a salient predictor of mental health function and HRQoL in PLHIV, particularly those residing in low-resource settings. Last, the decrease in HRQoL with ageing in PLHIV is unsurprising, as increased age is associated with comorbid conditions that are both HIV-related and age-related. For instance, regardless of treatment status, immune function gradually declines with time, with age-related musculoskeletal disorders increasing with age, which leads to a decline HRQoL over time [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec29\" class=\"Section2\"\u003e\u003ch2\u003eStrengths and limitations\u003c/h2\u003e\u003cp\u003eOur study outcomes need to be considered in view of the inherent methodological strengths and limitations. Using a randomised study design is a major methodological strength as it increases the study\u0026rsquo;s internal and external validity. Second, this is the first study to determine the equivalence of translated EQ-5D-5L versions in low-resource settings. Our study adds to the increasing body of knowledge on the psychometric robustness of EQ-5D-5L digital versions [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Electronic versions of the EQ-5D-5L can be used for multi-national comparative studies. Third, we exceeded the recommended minimum sample size for measurement equivalency studies i.e. we recruited 611 participants against the recommended 234 [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. For example, an almost similar study recruited 90 participants [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Our large sample size increases the study\u0026rsquo;s internal and external validity. Fourth, recruiting participants with diverse characteristics (e.g., sex, age, education, and economic status levels) ensures the study\u0026rsquo;s external validity. Our study was also prone to some biases. First, all items on the electronic data collection were set to mandatory. Thus, there were no inherent missing responses on the EQ-5D-5L digital version compared to the paper version; this may have led to biased data completeness for the electronic version. Second, no clinical variables were collected. We had initially planned to collect clinical variables (e.g. treatment duration, CD4+) to compare EQ-5D-5L\u0026rsquo;s known-group validity. However, collecting clinical variables was not possible at the time of data collection as the electronic data collection system was being upgraded, and few participants had meaningful data recorded on paper records. Future studies should collect salient clinical predictors of HRQoL. Third, we did not record the completion time for the paper versions; the time taken for the digital versions could be deduced from the system. Completion time would offer more information on the feasibility of the different administration modes, which should be explored in future studies. Fourthly, we only recruited PHLIV due to a limited budget. Nevertheless, individuals living with HIV often experience multiple comorbid conditions, which are likely applicable to other chronic illnesses. Also, condition-specific nuances, for example, HIV-related stigma, may impact HRQoL evaluations/perceptions, hence the need for additional studies in other conditions, including comparative studies recruiting healthy participants.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study demonstrated the measurement equivalency of the digital and paper-based versions of the EQ-5D-5L Shona. These two versions can be used confidently for routine clinical care and research. The study also underscores the need for bespoke interventions to improve the HRQoL of PLHIV.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cul\u003e\n \u003cli\u003eAOR -\u0026nbsp;adjusted odds ratios\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCMDs - common mental health disorders\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCOR-\u0026nbsp;crude odds ratios\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eEQ-5D - The European Quality of Life 5 Dimensions\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eGAD-7 - Generalised Anxiety Disorders Scale\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eHRQoL - health-related quality of life\u003c/li\u003e\n \u003cli\u003ePHQ-9 - Patient Health Questionnaire\u003c/li\u003e\n \u003cli\u003ePLHIV - people living with HIV\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eRAs - research assistants\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSSQ-14 - Shona symptoms questionnaire\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eVAS- Visual Analogue Scale\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and Consent to participate \u003c/h2\u003e\n\u003cp\u003eParirenyatwa Group of Hospitals granted institutional approval, and ethical approval was obtained from the Medical Research Council of Zimbabwe (Ref: MRCZ/A/2496). All methods were carried out in accordance with The Declaration of Helsinki. Participants were treated as autonomous agents and were requested to sign written consent before participation. Written informed consent was obtained from all subjects before participation in this study. Randomised participant ID numbers were used to preserve confidentiality. Data and signed informed consent forms were stored securely, only the researchers could access the information gathered, and participants could voluntarily withdraw from the study without any consequences.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. The datasets will be made available on online repositories once all manuscripts related to the study have been published online.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eAll the authors declare no competing interests. \u003c/p\u003e\n\u003ch2\u003eFunding \u003c/h2\u003e\n\u003cp\u003eThe study was funded by the EuroQol Foundation, Grant Number: Project 212-RA. \u003c/p\u003e\n\u003ch2\u003eAuthors contributions \u003c/h2\u003e\n\u003cul\u003e\n\u003cli\u003eConceptualisation: JMD, FDP, BD, DC, ASP\u003c/li\u003e\n\u003cli\u003eFunding acquisition: JMD, FDP, DC, ASP\u003c/li\u003e\n\u003cli\u003eData collection: JMD, BKS, ARH, SRD, TDT\u003c/li\u003e\n\u003cli\u003eData analysis and interpretation: JMD, FDP, BD, ASP, DC\u003c/li\u003e\n\u003cli\u003eWriting \u0026ndash; original draft: JMD, BKS, ARH, SRD, TDT\u003c/li\u003e\n\u003cli\u003eWriting \u0026ndash; review and editing: JMD, FDP, BKS, ARH, SRD, TDT, BD, DC, ASP\u003c/li\u003e\n\u003cli\u003eAll authors read and approved the final manuscript version. \u003c/li\u003e\n\u003c/ul\u003e\n\u003ch2\u003eDisclosures \u003c/h2\u003e\n\u003cp\u003eASP and FDP are members of the EuroQol Group. The funder had no role in study design, analysis and results interpretation. \u003c/p\u003e\n\u003ch2\u003eAcknowledgements \u003c/h2\u003e\n\u003cp\u003eWe want to acknowledge participants for their contribution to the study. \u003c/p\u003e\n\u003ch2\u003eAuthors ORCID information \u003c/h2\u003e\n\u003cp\u003eJermaine M Dambi (JMD): https://orcid.org/0000-0002-2446-7903\u003c/p\u003e\n\u003cp\u003eFredrick D. Purba (FDP): https://orcid.org/0000-0002-7336-3043\u003c/p\u003e\n\u003cp\u003eBeatrice K Shava (BKS): https://orcid.org/0000-0002-9130-7010\u003c/p\u003e\n\u003cp\u003eAnotida R Hove (ARH): https://orcid.org/0009-0005-4050-0135 \u003c/p\u003e\n\u003cp\u003eShalom R Doyce (SRD): https://orcid.org/0009-0006-7593-3253 \u003c/p\u003e\n\u003cp\u003eTariro D. Tunduwani (TDT): https://orcid.org/0009-0004-8073-7068\u003c/p\u003e\n\u003cp\u003eBen Domingue (BD): https://orcid.org/0000-0002-3894-9049\u003c/p\u003e\n\u003cp\u003eDixon Chibanda (DC): https://orcid.org/0000-0003-2505-8607\u003c/p\u003e\n\u003cp\u003eA. Simon Pickard (ASP): https://orcid.org/0000-0001-5645-7091\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eTsai AC. Reliability and validity of depression assessment among persons with HIV in sub-Saharan Africa: systematic review and meta-analysis. J Acquir Immune Defic Syndr. 2015;66: 503\u0026ndash;511. doi:10.1097/QAI.0000000000000210.Reliability\u003c/li\u003e\n\u003cli\u003eUNAID. IN DANGER: UNAIDS Global AIDS Update 2022. 2022; 1\u0026ndash;376. \u003c/li\u003e\n\u003cli\u003eAyano G, Solomon M, Abraha M. A systematic review and meta-analysis of epidemiology of depression in people living with HIV in east Africa. BMC Psychiatry. 2018;18: 1\u0026ndash;13. doi:10.1186/s12888-018-1835-3\u003c/li\u003e\n\u003cli\u003eSsebunnya J, Mugisha J, Mpango R, Kyohangirwe L, Taasi G, Ssentongo H, et al. Using Theory of Change to inform the design of the HIV+D intervention for integrating the management of depression in routine HIV care in Uganda. PLoS ONE. 2021;16: 1\u0026ndash;14. doi:10.1371/journal.pone.0259425\u003c/li\u003e\n\u003cli\u003eChibanda D, Verhey R, Gibson LJ, Munetsi E, Machando D, Rusakaniko S, et al. Validation of screening tools for depression and anxiety disorders in a primary care population with high HIV prevalence in Zimbabwe. J Affect Disord. 2016;198: 50\u0026ndash;55. doi:10.1016/j.jad.2016.03.006\u003c/li\u003e\n\u003cli\u003eKulisewa K, Stockton MA, Hosseinipour MC, Gaynes BN, Mphonda S, Udedi MM, et al. The Role of Depression Screening and Treatment in Achieving the UNAIDS 90\u0026ndash;90\u0026ndash;90 Goals in Sub-Saharan Africa. AIDS Behav. 2019;23: 153\u0026ndash;161. doi:10.1007/s10461-019-02593-7\u003c/li\u003e\n\u003cli\u003eSayah F Al, Ohinmaa A, Johnson JA. Screening for Anxiety and Depressive Symptoms in Type 2 Diabetes Using Patient-Reported Outcome Measures: Comparative Performance of the EQ-5D-5L and SF-12v2. MDM Policy Pract. 2018;3: 1\u0026ndash;11. doi:10.1177/2381468318799361\u003c/li\u003e\n\u003cli\u003eFeng YS, Kohlmann T, Janssen MF, Buchholz I. Psychometric properties of the EQ-5D-5L: a systematic review of the literature. Qual Life Res. 2021;30: 647\u0026ndash;673. doi:10.1007/s11136-020-02688-y\u003c/li\u003e\n\u003cli\u003eHerdman M, Gudex C, Lloyd A, Janssen Mf, Kind P, Parkin D, et al. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011;20: 1727\u0026ndash;1736. doi:10.1007/s11136-011-9903-x\u003c/li\u003e\n\u003cli\u003eDevlin N, Pickard S, Busschbach J. The development of the EQ-5D-5L and its value sets. Value Sets EQ-5D-5L Compend Comp Rev User Guide. 2022; 1\u0026ndash;12. doi:10.1007/978-3-030-89289-0_1\u003c/li\u003e\n\u003cli\u003eJelsma J, Mhundwa K, De Weerdt W, De Cock P, Chimera J, Chivaura V. The reliability of the Shona version of the EQ-5D. Cent Afr J Med. 2001;47: 8\u0026ndash;13. \u003c/li\u003e\n\u003cli\u003eChibanda D, Weiss HA, Verhey R, Simms V, Munjoma R, Rusakaniko S, et al. Effect of a primary care-based psychological intervention on symptoms of common mental disorders in Zimbabwe: A randomized clinical trial. JAMA - J Am Med Assoc. 2016;316: 2618\u0026ndash;2626. doi:10.1001/jama.2016.19102\u003c/li\u003e\n\u003cli\u003eMafirakureva N, Dzingirai B, Postma MJ, van Hulst M, Khoza S. Health-related quality of life in HIV/AIDS patients on antiretroviral therapy at a tertiary care facility in Zimbabwe. AIDS Care - Psychol Socio-Med Asp AIDSHIV. 2016;28: 904\u0026ndash;912. doi:10.1080/09540121.2016.1173639\u003c/li\u003e\n\u003cli\u003eJanssen MF, Buchholz I, Golicki D, Bonsel GJ. Is EQ-5D-5L Better Than EQ-5D-3L Over Time? A Head-to-Head Comparison of Responsiveness of Descriptive Systems and Value Sets from Nine Countries. PharmacoEconomics. 2022;40: 1081\u0026ndash;1093. doi:10.1007/s40273-022-01172-4\u003c/li\u003e\n\u003cli\u003eThompson AJ, Turner AJ. A Comparison of the EQ-5D-3L and EQ-5D-5L. PharmacoEconomics. 2020;38: 575\u0026ndash;591. doi:10.1007/s40273-020-00893-8\u003c/li\u003e\n\u003cli\u003eBagattini \u0026Acirc;M, Camey SA, Miguel SR, Andrade MV, de Souza Noronha KVM, Monica MA, et al. Electronic Version of the EQ-5D Quality-of-Life Questionnaire: Adaptation to a Brazilian Population Sample. Value Health Reg Issues. 2018;17: 88\u0026ndash;93. doi:10.1016/j.vhri.2017.11.002\u003c/li\u003e\n\u003cli\u003eLundy JJ, Joel S, Emuella C, Mira F, Patel J. Agreement Among Paper and Electronic Modes of the EQ-5D‑5L. Patient - Patient-Centered Outcomes Res. 2020;13: 435\u0026ndash;443. doi:10.1007/s40271-020-00419-6\u003c/li\u003e\n\u003cli\u003eMulhern B, O\u0026rsquo;Gorman H, Rotherham N, Brazier J. Comparing the measurement equivalence of EQ-5D-5L across different modes of administration. Health Qual Life Outcomes. 2015;13: 1\u0026ndash;9. doi:10.1186/s12955-015-0382-6\u003c/li\u003e\n\u003cli\u003eCoons SJ, Gwaltney CJ, Hays RD, Lundy JJ, Sloan JA, Revicki DA, et al. Recommendations on evidence needed to support measurement equivalence between electronic and paper-based patient-reported outcome (PRO) measures: ISPOR ePRO good research practices task force report. Value Health. 2009;12: 419\u0026ndash;429. doi:10.1111/j.1524-4733.2008.00470.x\u003c/li\u003e\n\u003cli\u003eWilliams N. The GAD-7 questionnaire. Occup Med. 2014;64: 224. doi:10.1093/occmed/kqt161\u003c/li\u003e\n\u003cli\u003eBushnell DM, Reilly MC, Galani C, Martin ML, Ricci JF, Patrick DL, et al. Validation of electronic data capture of the irritable bowel syndrome - Quality of life measure, the work productivity and activity impairment questionnaire for irritable bowel syndrome and the EuroQol. Value Health. 2006;9: 98\u0026ndash;105. doi:10.1111/j.1524-4733.2006.00087.x\u003c/li\u003e\n\u003cli\u003eO\u0026rsquo;Donohoe P, Reasner DS, Kovacs SM, Byrom B, Eremenco S, Barsdorf AI, et al. Updated Recommendations on Evidence Needed to Support Measurement Comparability Among Modes of Data Collection for Patient-Reported Outcome Measures: A Good Practices Report of an ISPOR Task Force. Value Health. 2023;26: 623\u0026ndash;633. doi:10.1016/j.jval.2023.01.001\u003c/li\u003e\n\u003cli\u003eTigirigi TO, Sithole GY, Chakara P, Chirombo GZ, Chiweza AR, Mubayiwa TR, et al. Evaluation of the health-related quality of life and associated factors in Zimbabwean adults living with HIV: a cross-sectional study. BMC Res Notes. 2023;16: 1\u0026ndash;8. doi:10.1186/s13104-023-06536-3\u003c/li\u003e\n\u003cli\u003eParker R, Stein DJ, Jelsma J. Pain in people living with HIV/AIDS: A systematic review. J Int AIDS Soc. 2014;17. doi:10.7448/IAS.17.1.18719\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":"health-and-quality-of-life-outcomes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hqlo","sideBox":"Learn more about [Health and Quality of Life Outcomes](http://hqlo.biomedcentral.com)","snPcode":"12955","submissionUrl":"https://submission.nature.com/new-submission/12955/3","title":"Health and Quality of Life Outcomes","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Digital, EQ-5D-5L, measurement equivalency, validation, Zimbabwe","lastPublishedDoi":"10.21203/rs.3.rs-7287257/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7287257/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e\u003cp\u003eComorbid anxiety and depression are common among people living with HIV (PLHIV), underscoring the necessity for concise diagnostic tools for routine mental health evaluations. Efficient screening can be supported by digital tools even in lower-income countries where HIV is a population health issue. The aims of this study were to: (1) examine the measurement equivalency between digital and paper versions of the Shona EQ-5D-5L, and (2), identify factors affecting the health-related quality of life (HRQoL) of PLHIV.\u003c/p\u003e\u003ch2\u003eMethods and materials:\u003c/h2\u003e\u003cp\u003eWe conducted a parallel randomised study in Zimbabwe involving 700 participants equally divided into digital and paper groups.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe study included 611 participants with a mean age of 37.5 years (SD 12.2). Most were female (70.7%), had secondary education (68.0%), and reported inadequate financial adequacy (68.7%). Both digital and paper-based versions of the EQ-5D-5L Shona displayed measurement equivalency. After adjusting for confounding and co-variation, only increased age (AOR\u0026thinsp;=\u0026thinsp;.60: 95% CI .41-.88, p\u0026thinsp;=\u0026thinsp;.008), food insecurity (AOR\u0026thinsp;=\u0026thinsp;1.8: 95% CI 1.2: 2.8, p\u0026thinsp;=\u0026thinsp;.01), and elevated comorbid anxiety/depression symptoms (AOR\u0026thinsp;=\u0026thinsp;0.45: 95% CI: 0.29\u0026ndash;0.68, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) were associated with lower HRQoL.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThis study demonstrated the measurement equivalency of the digital and paper-based versions of the EQ-5D 5L Shona. These two versions can be used confidently for routine clinical care and research. The study emphasises the need for tailored interventions to improve the HRQoL of PLHIV.\u003c/p\u003e","manuscriptTitle":"A Randomised Equivalency Study of the EQ-5D-5L Shona Versions - Evaluation of Measurement Equivalency Between Digital and Paper Formats","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-02 06:48:21","doi":"10.21203/rs.3.rs-7287257/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-21T10:23:47+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-21T10:17:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-17T14:06:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-17T07:18:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"112607605471466479065947624517023039311","date":"2025-09-30T08:45:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"55621262690669136890706693152675804291","date":"2025-09-29T06:18:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"213637857664926424335348129235342174813","date":"2025-09-28T03:17:58+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-24T13:58:11+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-08T01:36:09+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-08T01:35:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"Health and Quality of Life Outcomes","date":"2025-08-04T05:45:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"health-and-quality-of-life-outcomes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hqlo","sideBox":"Learn more about [Health and Quality of Life Outcomes](http://hqlo.biomedcentral.com)","snPcode":"12955","submissionUrl":"https://submission.nature.com/new-submission/12955/3","title":"Health and Quality of Life Outcomes","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"688131f6-5d2b-4ea6-8231-c728c641a1a0","owner":[],"postedDate":"September 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-22T09:23:53+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-02 06:48:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7287257","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7287257","identity":"rs-7287257","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}