Abstract
Using survey data collected immediately after referral for ART (N = 87), this study examined ART-readiness among individuals (18 years and older) attending a mobile health clinic in South Africa. Most participants reported being very ready (84%) and motivated (85%) to start ART, but only 72% were assessed as ready for ART on all measures. Treatment readiness was lower among individuals who did not think they would test HIV-positive (aOR 0.26, p < 0.05) and among individuals who reported being in good health (aOR 0.44, p < 0.1). In contrast, higher readiness was associated with better ART knowledge (aOR 4.31, p < 0.05) and knowing someone who had experienced positive health effects from ART (aOR 2.65, p < 0.05). Results indicate that post-test counselling will need to be designed to deal with surprise at HIV diagnosis, and that health messaging needs to be carefully crafted to support uptake of ART among HIV-positive but healthy individuals. Further research is needed on effective post-test counselling approaches and effective framing of health messaging to increase awareness of the multiple positive benefits of early ART initiation and corresponding readiness to engage in treatment.
Keywords: Linkage to care, HIV/AIDS, Barriers to ART initiation, Treatment readiness
Introduction
Antiretroviral therapy (ART) reduces AIDS-related morbidity, increases life expectancy [1, 2] and reduces the onward transmission of HIV [3–5]. Consequently, linking individuals diagnosed HIV-positive to care and treatment is a central component of the UNAIDS 90–90–90 strategy that aims to maximise the therapeutic and prevention benefits of ART [6]. To reach the UNAIDS targets we need to increase the proportion of HIV-infected individuals who initiate ART [7–13].
In South Africa, the country with the largest global epidemic, 42% of people living with HIV are estimated to be accessing treatment [14]. Prior to the adoption of the test-and-treat policy in South Africa in September 2016—all HIV-positive individuals are ART-eligible regardless of CD4 count [15, 16]—a large proportion of HIV-positive individuals not on treatment were diagnosed HIV-positive but were lost to follow-up before ART-eligibility assessment [8, 17–20]. Although all HIV-positive individuals are now ART-eligible, large challenges remain in linking individuals to HIV care and treatment services. Studies have shown that between 32 and 50% of HIV-positive individuals assessed at public sector hospitals and clinics as ART-eligible do not initiate treatment [8, 21–23]. Moreover, rates of linkage to care and treatment are particularly poor from community-based HIV-testing services, such as mobile clinics and home-based testing services [24, 25]. While community-based testing services are effective at reaching previously undiagnosed HIV-positive individuals [26–28], it may be more difficult to ensure that those individuals begin ART.
ART readiness is a key predictor of ART initiation [29] and lower readiness is associated with poorer adherence outcomes [30]. However, our understanding of factors driving ART readiness is poor. In particular, there is a paucity of data on ART readiness among individuals at the time of HIV-diagnosis and ART eligibility assessment in the context of community-based services. Understanding the underlying psychosocial factors associated with ART readiness can inform strategies to support and increase individuals’ readiness to initiate ART and early engagement in care [31]. For example, insights from behavioural economics theory may be relevant for ART decision-making. The tendency of people to favour immediate rewards and heavily discount future outcomes [32] may, for instance, undermine ART readiness if the benefits of ART are perceived to be gained in the future, especially among asymptomatic individuals.
Capitalizing on the opportunity to increase readiness for treatment and linkage to care is critical, given evidence that ART-referral often is the last point of contact with health services before being lost to follow-up. The importance of improving our understanding of ART readiness in South Africa is highlighted by a test-and-treat approach as the number of individuals referred for treatment increases and ART programs accordingly need to adapt to help them initiate their treatment.
In this study we assess demographic and psychosocial factors associated with ART readiness among patients referred for ART by a mobile health clinic in Cape Town, South Africa, using key components of this concept identified in the literature [33]: (1) an awareness that treatment will be beneficial; (2) motivation to initiate treatment; and (3) the intention to start treatment soon.
Methods
Data
This article uses cross-sectional baseline survey data collected in the iLink Study, a pilot randomised controlled trial assessing the feasibility of using conditional economic incentives to increase ART initiation. The iLink Study enrolled individuals diagnosed HIV-positive—during standard HIV testing involving pre- and post-test counselling— and referred for ART (based on National Department of Health guidelines at the time of a CD4 count ≤500 cells/µL [34]) by a mobile health clinic in Cape Town. The mobile clinic offers free screening for several health conditions to a predominately black, Xhosa-speaking, African population residing in resource-poor areas. Between April 2015 and May 2016 a total of 147 individuals were screened for study eligibility (which included being 18 years or older; never having been on ART; and owning a cell phone). There were 112 (76%) participants who were eligible for enrolment and, of those, 87 (78%) participated in the study and completed a face-to-face survey administered by a counsellor from the mobile clinic. The main reasons for being ineligible for the study were not owning a cell phone (32%) and having previously been on ART (11%). Eighteen percent of eligible participants refused to participate, with a lack of time being the main reason given.
Measures
The survey was designed to be concise in order to minimise effort among individuals recently diagnosed HIV-positive. Single item questions or brief measures were used, most derived from previously validated multi-item measurement tools.
ART Readiness
Readiness is an abstract concept that has been defined and measured in multiple ways [33, 35–37]. Our measure of ART readiness was based on responses to questions designed to measure essential elements identified in the literature that must be present for readiness to exist [33, 35–37]: (1) an awareness that treatment will be beneficial; (2) motivation to initiate treatment; and (3) the intention to start treatment soon. To assess belief about treatment efficacy we used the question ‘Overall, how confident are you that ARVs would have a positive effect on your health?’ Motivation to initiate treatment was measured by asking participants ‘How motivated are you to start ARVs?’ Two questions were asked to assess behavioural intentions, with the time frame based on the Transtheoretical Model of Change that posits that individuals who intend to wait for more than a month to start treatment are still in the contemplation phase [38]: (1) ‘How likely is it that you’ll visit an HIV/ARV clinic in the next 30 days?’ and (2) ‘When do you intend to start ARVs?’ In addition, consistent with the hypothesis that patients can judge their own readiness [39], we asked individuals to indicate their level of readiness using the question ‘How ready do you feel to start ARVs?’
We combined responses to these questions into a binary variable of treatment readiness indicating respondents who reported being very ready, very motivated and very confident regarding ART, and predicted they would visit a clinic and start ART within 30 days. As being fully ready to start treatment potentially involves several additional unmeasured factors [30, 37, 40, 41], we consider this variable an indicator that differentiates individuals with a higher degree of readiness for ART, rather than a measure of who was completely ready for treatment.
Independent Variables
Demographic and socioeconomic measures included gender, age, education (years completed), employment status, and household monthly income. In addition, we assessed participants’ discount rates as a measure of how much value individuals placed on present needs. Temporal discounting— the tendency to give greater value to rewards in the present or near future than those in the more distant future—could reduce ART readiness if the future benefits of ART are undervalued in the present [32]. Discount rates were measured by asking participants to imagine that they had won a prize and could choose how it was paid. A binary variable to indicate high discount rates was created for individuals who selected R200 now over R500 in 1 month.
Two self-perceived health measures were created. ‘Feeling healthy’ is a common reason reported for not linking to care and treatment services [42, 43]. As self-rated general health questions are commonly used in national surveys and are good predictors of morbidity and mortality [44], we created a general health variable based on the question ‘In general, how was your health in the last week?’ A binary variable was created to identify individuals who reported good or very good health. We also created a measure for depression, which has been shown to influence linkage to HIV care and treatment services [20], using a question adapted from the Kessler Psychological Distress Scale [45]: ‘About how often during the past 30 days did you feel depressed?’ The depression variable identified individuals who reported being depressed some, most, or all of the time.
Denial of being HIV-positive has been identified as a barrier to ART initiation [20, 46]. As surprise or shock at a positive diagnosis to a medical condition can be associated with denial [47], we used the question ‘Before you were tested for HIV today, how likely did you think it was that you would have HIV?’ to create a binary variable for individuals who thought that their HIV test would not show that they were infected (i.e., they responded “not at all likely” to this question).
Several ART-related measures were used in our analysis. As knowledge about ART impacts linkage to care [48, 49], we created a binary variable of good knowledge to indicate individuals who had heard of ART before, believed ART to be a lifelong treatment and knew that ART cannot cure HIV. We also created a binary variable to identify individuals who reported that any of their friends or family were taking ART and believed ART had a positive effect on their health. Beliefs about side-effects were measured by asking participants how likely they thought it was that they would experience any side-effects. The Theory of Planned Behaviour [50] suggests that subjective norms will influence behavioural intentions. Accordingly, we created a measure of beliefs regarding perceived norms around ART uptake by asking ‘Thinking about people like yourself, with a similar CD4 count, how many do you think start treatment within 3 months?’
Our last set of factors related to stigma and disclosure. We used two items common in the measurement of internalised stigma (i.e., the devaluation of identity by oneself and/or internalising the devaluation from others [51, 52]): (1) ‘Do you feel at all guilty that you have HIV?’ and (2) ‘Do you feel at all ashamed that you have HIV?’ We created a binary variable to represent individuals who reported either form of internalised stigma. Perceived stigma (i.e., perceptions on the part of individuals about the nature and level of stigma in the broader social environment) was measured by asking participants how likely it was that HIV-status disclosure would result in being treated unfairly or badly by (1) your spouse/partner, (2) members of your family, (3) some of your friends, (4) members of your community, and (5) health professionals. As disclosure is often related to ART initiation [24, 53, 54] we asked participants how likely it was that they would tell (1) their primary sexual partner and (2) anyone else about their HIV status.
Analysis
We first present descriptive statistics of the sample characteristics and key measures. As uptake of ART initiation is gendered [7, 12, 55], we compared responses among men and women using Chi squared tests and standard differences in proportions tests. We then conducted a bivariate analysis of factors associated with ART readiness. We extended this analysis by controlling for key demographic characteristics (gender, age and years of completed education) using multiple logistic regression models. All analyses were conducted using Stata 14.0 (Stata Corporation LP, College Station, TX).
Results
Sample characteristics (N = 87) are presented in Table 1. The majority of the sample was female (64%), 18–39 years old (72%) and black African (97%). The majority of the sample had not completed Grade 12 (71%) and was poor, with two-thirds living in an informal house/shack and reporting a household monthly income of less than R2000 (equivalent to $145 at the mid-point of study enrolment on 31 October 2015). Only one-third was employed and the majority reported food insecurity (60% of the sample reported not having enough food in the previous 30 days). As expected in this environment, a large proportion (40%) reported a high discount rate (i.e., a preference for R200 immediately rather than R500 in one month’s time) thus indicating a focus on present needs. Reflecting the high prevalence of HIV in the region, the vast majority of the sample knew someone living with HIV (84%) or knew someone who had died of AIDS (67%). A history of repeat testing was common, and significantly more common among women (96% of women compared to 74% of men, p < 0.01).
Table 1.
Sample characteristics
| Total N = 87 % (n) |
Female N = 56 % (n) |
Male N = 31 % (n) |
|
|---|---|---|---|
| Female | 64 (56) | 100 (56) | 0 (0) |
| Age | |||
| 18–29 | 41 (36) | 46 (26) | 32 (10) |
| 30–39 | 31 (27) | 29 (16) | 35 (11) |
| 40–49 | 24 (21 | 21 (12) | 29 (9) |
| 50+ | 3 (3) | 4 (2) | 3 (1) |
| Black African | 97 (84) | 96 (54) | 97 (30) |
| Married | 21 (18) | 14 (8) | 32 (10) |
| Grade 12 completed | 29 (25) | 29 (16) | 29 (9) |
| Currently working | 32 (28) | 23 (13) | 48 (15) |
| House = informal/shack | 67 (77) | 86 (48) | 61 (19) |
| Household monthly income <R2000^ | 68 (55) | 70 (35) | 67 (20) |
| Household without food in last month | |||
| No days | 40 (34) | 36 (20) | 47 (14) |
| 1–5 days | 48 (41) | 52 (29) | 40 (12) |
| >5 days | 12 (10) | 11 (6) | 13 (4) |
| Choose R200 now vs. R500 in 1 month | 40 (33) | 26 (14) | 66 (19) |
| Health in last 7 days | |||
| Poor or fair | 48 (42) | 47 (26) | 52 (16) |
| Good | 34 (29) | 30 (17) | 40 (12) |
| Very good | 17 (15) | 21 (12) | 10 (3) |
| Depressed in last 30 days | |||
| None/little | 28 (24) | 27 (15) | 29 (9) |
| Sometimes | 41 (36) | 45 (25) | 35 (11) |
| Often/all the time | 31 (27) | 29 (16) | 35 (11) |
| Knows someone with HIV | 84 (73) | 91 (51) | 71 (22) |
| Knows someone who died of AIDS | 67 (58) | 75 (41) | 55 (17) |
| Repeat HIV-testers | 89 (77) | 96 (54) | 74 (23) |
Totals may not sum 100% due to rounding to the nearest integer
N refers to total sample size. The N varies slightly for some variables due to a small amount of missing data. The household income variable was missing the most data (total N = 80, female: N = 50, male: N = 30)
n refers to the size of the subset of the sample
R2000 was equivalent to $145 on 31 October 2015 (approximately the mid-point of study enrolment)
ART Readiness
Table 2 displays data on each of the five measures used to assess ART readiness and the combined readiness indicator. Most participants reported being very ready (84%) and motivated (85%) to start ART, very confident that ART would have an overall positive effect on their health (89%), and intended to visit a clinic to start ART within 30 days. Overall, 72% of respondents were assessed as ‘ready’ for ART on all measures. More men than women (77 vs. 70%, p = 0.437) were classified as ART ready, with the difference being driven mainly by a higher percentage of men reporting being very ready (15% points, p = 0.069) and very motivated (9% points, p = 0.291) to start ART.
Table 2.
Antiretroviral therapy readiness by gender
| Total N = 87 % (n) |
Female N = 56 % (n) |
Male N = 31 % (n) |
Difference in proportions test | |
|---|---|---|---|---|
| ART readiness components | ||||
| Very ready to start ARVs | 84 (73) | 79 (44) | 94 (29) | −15 (p = 0.069) |
| Very motivated to start ARVs | 85 (73) | 82 (45) | 90 (28) | −9 (p = 0.291) |
| Very confident ARVs would have positive effect | 89 (77) | 89 (50) | 87 (27) | +2 (p = 0.759) |
| Very likely to go to a clinic within 30 days | 96 (82) | 95 (52) | 100 (30) | −5 (p = 0.193) |
| Intends to start ART within 30 days | 92 (80) | 93 (52) | 90 (28) | +3 (p = 0.677) |
| Overall ART readiness | 72 (63) | 70 (39) | 77 (24) | 8 (p = 0.437) |
Totals may not sum 100% due to rounding to the nearest integer
N refers to total sample size. The N varies slightly for some variables due to a small amount of missing data
n refers to the size of the subset of the sample
p-values based on standard two group difference in proportions test for binary variables
Psychosocial Factors
Table 3 displays the sample distribution of the psychosocial factors used to assess determinants of ART readiness. Inaccuracy of perceived HIV risk was common with substantial proportions of men (45%) and women (32%) reporting that they did not think it was at all likely that they would test HIV-positive. There was a great deal of uncertainty regarding the likelihood of experiencing side-effects (49%) and a large proportion of the sample believed it was either somewhat or very likely that they would experience side-effects (35%). Men were more likely than women to believe it was not at all likely that they would experience side-effects (26% vs. 11%, p = 0.072). A greater proportion of women knew someone taking ART and believed that ART had a positive effect on the health of the persons taking treatment (73 vs. 52%, p = 0.042). Internalised stigma and perceived stigma were common. The majority (58%) reported feeling either guilty or ashamed that they have HIV and two-thirds of the sample reported some form of perceived stigma. It was most common for participants to believe that members of the community (51%) and friends (44%) would be stigmatising. Most participants (80%) believed it was very likely that they would disclose their status to their spouse/partner, but women were significantly less likely to report this than men (72 vs. 93%, p = 0.032).
Table 3.
Psychosocial sample characteristics by gender
| Total N = 87 % (n) |
Female N = 56 % (n) |
Male N = 31 % (n) |
Difference in proportions test or Chi squared test |
|
|---|---|---|---|---|
| Perceived likelihood of having HIV | chi2 = 3.6 (p = 0.306) | |||
| Don't know | 5 (4) | 8 (4) | 0 (0) | |
| Not at all likely | 37 (31) | 32 (17) | 45 (14) | |
| Somewhat likely | 18 (15) | 17 (9) | 19 (6) | |
| Very likely | 40 (34) | 43 (23) | 35 (11) | |
| Heard of ARVs before | 94 (82) | 96 (54) | 90 (28) | +6(p= 0.241) |
| ART can't cure HIV | 87 (76) | 84 (47) | 84 (47) | −10 (p = 0.196) |
| Need to take ARVs for rest of life | 93 (81) | 96 (54) | 87 (27) | +9(p= 0.100) |
| How likely to experience ART side-effects? | chi2 = 3.3 (p = 0.191) | |||
| Don't know | 49 (42) | 51 (28) | 45 (14) | |
| Not at all likely | 16 (14) | 11 (6) | 26 (8) | |
| Somewhat/very likely | 35 (30) | 38 (21) | 29 (9) | |
| Knows friends/family taking ART and believes ART had a positive health effect | 66 (57) | 73 (41) | 52 (16) | +22 (p = 0.042) |
| How many people like yourself start ART within 3 months? | chi2 = 4.67 (p = 0.197) | |||
| Don't know | 13 (11) | 15 (8) | 10 (3) | |
| Hardly any | 6 (5) | 9 (5) | 0 (0) | |
| Some | 41 (34) | 43 (23) | 38 (11) | |
| Most | 40 (33) | 33 (18) | 52 (15) | |
| Internalised stigma | ||||
| Thinking about the way you feel about yourself, do you feel at all guilty that you have HIV? | chi2 = 2.04 (p = 0.564) | |||
| Not at all | 49 (42) | 45 (25) | 55 (17) | |
| Somewhat | 38 (33) | 38 (21) | 39 (12) | |
| Very | 12 (10) | 15 (8) | 6 (2) | |
| Do you feel at all ashamed that you have HIV? | chi2 = 5.55 (p = 0.235) | |||
| Not at all | 61 (53) | 57 (32) | 68 (21) | |
| Somewhat | 29 (25) | 27 (15) | 32 (10) | |
| Very | 8 (7) | 13 (7) | 0 (0) | |
| Either guilty or ashamed | 58 (50) | 60 (33) | 55 (17) | +5(p= 0.641) |
| Perceived stigma | ||||
| Somewhat/very likely to be treated badly by… | ||||
| Spouse/partner | 21 (17) | 24 (12) | 17 (5) | +7(p= 0.463) |
| Family | 18 (16) | 25 (14) | 6 (2) | +19 (p = 0.033) |
| Friends | 44 (37) | 44 (24) | 43 (13) | +0.3 (p = 0.979) |
| Community | 51 (44) | 57 (32) | 40 (12) | +17 (p = 0.129) |
| Health professional | 8 (7) | 11 (6) | 3 (1) | +7(p= 0.219) |
| Any perceived stigma | 66 (56) | 71 (39) | 57 (17) | +14 (p = 0.186) |
| Disclosure | ||||
| Very likely to disclose to sexual partner | 80 (57) | 72 (31) | 93 (26) | −21 (p = 0.032) |
| Very likely to disclose to someone else | 56 (49) | 59 (33) | 52 (16) | +7(p= 0.51) |
Totals may not sum 100% due to rounding to the nearest integer
N refers to total sample size. The N varies slightly for some variables due to a small amount of missing data. The variable measuring disclosure to sexual partners was missing the most data (total N = 71, female: N = 43, male: N = 28) as not all participants had a sexual partner
n refers to the size of the subset of the sample
p-values based on standard two group difference in proportions test for binary variables and Chi squared tests for variables with multiple categories
Factors Associated with ART Readiness
Results from the bivariate and multivariable analysis (controlling for gender, age and education level) are presented in Table 4. The multivariable analysis indicated that ART readiness was significantly lower among individuals who reported being in good or very good health (aOR 0.44, p < 0.1) and those who did not think it was likely that they would test HIV-positive (aOR 0.26, p < 0.05). Readiness was positively associated with ART knowledge (aOR 4.31, p < 0.05) and knowing someone who had experienced positive health effects from ART (aOR 2.65, p < 0.05). While not statistically significant, the effect size was large for three factors. First, individuals reporting any internalised stigma had half the odds of being treatment ready (aOR 0.48, p = 0.168). Second, compared to individuals who reported that it was not at all likely they would experience any side-effects, readiness was lower among those who answered ‘don’t know’ (aOR 0.21, p = 0.187) and among those who believed it was ‘somewhat/very likely’ (aOR 0.17, p = 0.132). Third, individuals who reported that it was likely that they would disclose to their sexual partner were more likely to be assessed as ART ready (aOR 2.88, p = 0.117).
Table 4.
Bivariate and multivariable logistic regression models of factors associated with ART readiness
| n | OR (95%CI) | p- value |
aOR (95%CI) | p-value | |
|---|---|---|---|---|---|
| Male (ref: female) | 87 | 1.49 (0.54–4.13) | 0.439 | 1.69 (0.54–5.33) | 0.370 |
| Age (years) | 87 | 0.99 (0.94–1.04) | 0.705 | 0.97 (0.90–1.03) | 0.328 |
| Education (years) | 87 | 0.89 (0.71–1.12) | 0.320 | 0.84 (0.58–1.21) | 0.337 |
| Working (ref: not working) | 87 | 1.08 (0.40–2.92) | 0.887 | 1.00 (0.34–2.95) | 0.998 |
| Household monthly income <R2000^ | 80 | 1.38 (0.49–3.88) | 0.544 | 1.37 (0.48–3.89) | 0.560 |
| High discount rate (ref: low discount rate) | 83 | 1.75 (0.63–4.87 | 0.285 | 1.86 (0.59–5.81) | 0.287 |
| Good health (ref: poor health) | 86 | 0.45 (0.17–1.23) | 0.119 | 0.44 (0.17–1.13)* | 0.087 |
| Depressed sometimes (ref: not depressed) | 86 | 1.47 (0.53–4.08) | 0.460 | 1.44 (0.50–4.14) | 0.500 |
| ARV knowledge is good (ref: poor knowledge) | 87 | 3.60 (1.21–10.74)** | 0.022 | 4.31 (1.41–13.24)** | 0.011 |
| Unlikely to be HIV-positive (ref: don't know/likely) | 84 | 0.28 (0.10–0.76)** | 0.013 | 0.26 (0.09–0.78)** | 0.016 |
| Any internal stigma (guilt or shame) | 86 | 0.47 (0.17–1.30) | 0.144 | 0.48 (0.17–1.37) | 0.168 |
| Any perceived stigma (ref: none) | 85 | 0.95 (0.35–2.60) | 0.924 | 0.94 (0.34–2.64) | 0.909 |
| Likely to disclose… | |||||
| To partner (ref: don't know/unlikely) | 71 | 2.81 (0.81–9.76) | 0.103 | 2.88 (0.77–10.83) | 0.117 |
| To someone else (ref: don't know/unlikely) | 87 | 1.80 (0.69–4.66) | 0.229 | 1.86 (0.71–4.84) | 0.204 |
| Likelihood of experiencing side effects (ref: not likely) | 86 | ||||
| Don't know | 0.17 (0.02–1.47) | 0.108 | 0.21 (0.02–2.13) | 0.187 | |
| Somewhat/very likely | 0.15 (0.02–1.37)* | 0.093 | 0.17 (0.02–1.70) | 0.132 | |
| Most people start ARVs within 3 months (ref: other) | 83 | 0.81 (0.30–2.16) | 0.670 | 0.87 (0.31–2.50) | 0.803 |
| Knowledge of positive ART effect for others (ref: no) | 87 | 1.96 (0.74–5.18) | 0.175 | 2.65 (1.03–6.81)** | 0.044 |
OR unadjusted odds ratio, aOR adjusted odds ratio from multivariable models including age, gender and education, CI confidence interval
p < 0.01,
p < 0.05,
p < 0.1
Discussion
Understanding ART readiness at the time of referral for treatment will help inform interventions aiming to encourage ART initiation. Findings from this study indicate that individuals referred for ART are generally highly motivated to start treatment and intend to start treatment within a month. However, some uncertainty regarding treatment readiness was found for almost a quarter of the sample. Counter to trends from other studies in which men have repeatedly been shown to be less likely to link to care and initiate ART than women [9, 12, 56], lower proportions of women in our study reported being ready to start ART than men.
Results point towards several factors that may affect readiness for treatment, and may therefore influence the uptake of ART. A large proportion of the sample, and especially of men, did not think they would test HIV-positive and these individuals were significantly less likely to be classified as ART ready. As surprise at a positive diagnosis can be associated with denial [47] this finding may, in part, explain why denial is often identified as a barrier to ART initiation [20, 57]. ART readiness may therefore be improved through counselling designed to identify and help individuals who are surprised by a positive diagnosis to come to terms with the result.
Perceived good health was also negatively associated with treatment readiness, which is consistent with several studies that show that individuals in better health are less likely to link to care and initiate treatment [42, 58, 59]. In the context of a universal test-and-treat approach [15] the proportion of individuals perceiving their health to be good when referred for treatment will increase substantially. Consequently, we require treatment counselling that actively and immediately builds ART readiness among healthy feeling individuals so as to reduce linkage to care delays.
Reflecting the high burden of HIV in the study area [60], most respondents knew someone living with HIV. Encouragingly, among the three quarters of women and half the sample of men who knew someone taking ART almost all perceived treatment to have had a positive health effect. Those who held this perception were significantly more likely to be treatment ready, pointing towards personal experience of positive treatment effects as a powerful motivator when it comes to interventions to improve ART readiness. The large gender difference in personal experience of the positive health effects of ART aligns with the fact that, as in our study, more women tend to report personal experiences relating to HIV (i.e., knowledge of people living with HIV or perceived to have died of AIDS) [61]. Increasing awareness and experience among men of the positive health effects of ART may, therefore, be of benefit to efforts to reduce gender inequities in ART uptake.
Large effect sizes on the relationship between ART readiness and two factors found to be common in the sample indicate that further investigation using larger samples powered to detect statistical significance is warranted. First, individuals who perceived it likely that they would experience side-effects were less likely to be treatment ready, which aligns with evidence from other studies that fears about ART side-effects negatively influence ART initiation [53, 62–64]. Second, our findings show that internalised stigma is common at the time of ART-referral and, in addition to a negative impact previously found on ART adherence [65], internalised stigma may also reduce treatment readiness. This study did not find any evidence that ART readiness is influenced either by social norms regarding treatment initiation or by discount rates.
The findings from this study should be considered along with the study limitations. Social desirability bias may have affected measurement error. Second, recruiting a population at the moment of ART referral is difficult and studies of this nature are often limited, as in our case, by relatively small sample sizes. Third, the ART readiness variable was created using key elements of the treatment readiness construct, but several more nuanced dimensions of this construct may not have been captured [30, 37, 40, 41]. In addition, we used an indicator of inaccurate self-perceived risk of receiving an HIV-positive diagnosis as a proxy measure of surprise by an HIV-positive diagnosis. The assumption that individuals who did not believe they would test positive would be surprised by the diagnosis might not universally apply. Finally, it is unclear whether results can be generalized to other, especially wealthier, populations.
In conclusion, as ART programs adopt a test-and-treat approach, the number of individuals referred for treatment at the time of HIV-diagnosis will increase and there will be a corresponding increase in the importance of helping individuals overcome immediate barriers to ART initiation. Results from this study point towards the need for interventions at the time of referral for ART to improve treatment readiness among individuals with self-perceived good health and those believing they would not receive a positive HIV-diagnosis. The importance of effectively marketing to healthy-feeling individuals the multiple benefits of early ART initiation is highlighted in a context with high levels of perceived stigma and uncertainty regarding treatment side-effects, where initiating treatment may well be perceived as a greater risk than benefit to one’s immediate quality of life. Further research is needed on effective post-test counselling approaches and effective framing of health messages to increase awareness of the multiple positive benefits of early ART initiation and corresponding readiness to engage in treatment. Future research and policy development should be cognizant that ART readiness and associated factors may be gendered and require targeted interventions.
Acknowledgments
The authors gratefully acknowledge the staff of the Tutu Tester Mobile Clinic for their valuable assistance with developing the study materials and with data collection.
Funding This study was partially funded by the National Research Foundation, South Africa, through the Research Career Advancement Fellowship. Data collection for this study was partially funded by the Eunice Kennedy Shriver National Institute of Child Health & Human Development of the National Institutes of Health (award number R24HD077976). Support was provided by the National Institutes of Health through the Brown University Population Studies and Training Center (PSTC) (P2CHD041020-16). Support was provided to CK and ML by the National Institute of Mental Health of the National Institutes of Health (award numbers K01096646 and 1R01 MH106600-01). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Footnotes
Conflict of interest The authors declare that they have no conflict of interest.
Compliance with Ethical Standards
Ethical Approval All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The Human Research Ethics Committee, Faculty of Health Sciences, University of Cape Town provided study approval (ref: 849/2014).
Informed Consent Informed consent was obtained from all individual participants included in the study.
References
- 1.Bor J, Herbst AJ, Newell M-L, Bärnighausen T. Increases in adult life expectancy in rural South Africa: valuing the scale-up of HIV treatment. Science. 2013;339:961–5. doi: 10.1126/science.1230413. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Johnson LF, Mossong J, Dorrington RE, et al. Life expectancies of South African adults starting antiretroviral treatment: collaborative analysis of cohort studies. PLOS Med. 2013;10:e1001418. doi: 10.1371/journal.pmed.1001418. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Cohen MS, Chen YQ, McCauley M, et al. Prevention of HIV-1 infection with early antiretroviral therapy. N Engl J Med. 2011;365:493–505. doi: 10.1056/NEJMoa1105243. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Montaner JSG, Lima VD, Barrios R, et al. Association of highly active antiretroviral therapy coverage, population viral load, and yearly new HIV diagnoses in British Columbia, Canada: a population-based study. Lancet. 2010;376:532–9. doi: 10.1016/S0140-6736(10)60936-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Tanser F, Bärnighausen T, Grapsa E, Zaidi J, Newell ML. High coverage of ART associated with decline in risk of HIV acquisition in rural KwaZulu-Natal. South Africa. Sci. 2013;339:966–71. doi: 10.1126/science.1228160. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.UNAIDS. 90-90-90: An ambitious treatment target to help end the AIDS epidemic [Internet] Geneva: Joint United Nations Programme on HIV/AIDS; 2014. [Accessed 27 September 2016]. [updated 08 October 2014]. Available from: http://www.unaids.org/en/resources/documents/2014/90-90-90. [Google Scholar]
- 7.Bassett IV, Wang B, Chetty S, et al. Loss to care and death before antiretroviral therapy in Durban, South Africa. J Acquir Immune Defic Syndr. 2009;51:135–9. doi: 10.1097/qai.0b013e3181a44ef2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Kranzer K, Zeinecker J, Ginsberg P, et al. Linkage to HIV care and antiretroviral therapy in Cape Town South Africa. PLoS ONE. 2010;5:e13801. doi: 10.1371/journal.pone.0013801. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Lamb MR, Fayorsey R, Nuwagaba-Biribonwoha H, et al. High attrition before and after ART initiation among youth (15–24 years of age) enrolled in HIV care. AIDS. 2014;28:559–68. doi: 10.1097/QAD.0000000000000054. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Maman D, Chilima B, Masiku C, et al. Closer to 90–90–90. The cascade of care after 10 years of ART scale-up in rural Malawi: a population study. J Int AIDS Soc. 2016;19:1–8. doi: 10.7448/IAS.19.1.20673. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.McGrath N, Glynn JR, Saul J, et al. What happens to ART-eligible patients who do not start ART? Dropout between screening and ART initiation: a cohort study in Karonga. Malawi. BMC Public Health. 2010;10:601. doi: 10.1186/1471-2458-10-601. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Plazy M, Dray-Spira R, Orne-Gliemann J, Dabis F, Newell M-L. Continuum in HIV care from entry to ART initiation in rural KwaZulu-Natal. South Africa. Trop. Med. Int. Health. 2014;19:680–9. doi: 10.1111/tmi.12301. [DOI] [PubMed] [Google Scholar]
- 13.UNAIDS. Fact Sheet 2015: Global Statistics [Internet] Geneva: UNAIDS; 2015. [Accessed 27 September 2016]. [updated 01 September 2015]. Available from: http://www.unaids.org/sites/default/files/media_asset/20150901_FactSheet_2015_en.pdf. [Google Scholar]
- 14.UNAIDS. The Gap Report. Geneva: Joint United Nations Programme on HIV/AIDS. [Accessed 13 December 2016];2014 Available from: http://www.unaids.org/en/resources/campaigns/2014/2014gapreport/gapreport.
- 15.WHO. Guideline on when to start antiretroviral therapy and on pre-exposure prophylaxis for HIV [Internet] Geneva: WHO; 2015. [updated 30 September 2015]. [Accessed 27 September 2016]. Available from: http://apps.who.int/iris/bitstream/10665/186275/1/9789241509565_eng.pdf?ua=1. [PubMed] [Google Scholar]
- 16.UNAIDS. South Africa takes bold step to provide HIV treatment for all [Internet]. UNAIDS. Geneva: Joint United Nations Programme on HIV/AIDS; 2016. [Accessed 13 December 2016]. Available from: http://www.unaids.org/en/resources/presscentre/pressreleaseandstatementarchive/2016/may/20160513_UTT. [Google Scholar]
- 17.Losina E, Bassett IV, Giddy J, et al. The “ART” of linkage: pretreatment loss to Care after HIV diagnosis at two PEPFAR sites in Durban. South Africa. PLOS ONE. 2010;5:e9538. doi: 10.1371/journal.pone.0009538. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Kranzer K, Govindasamy D, Ford N, Johnston V, Lawn SD. Quantifying and addressing losses along the continuum of care for people living with HIV infection in sub-Saharan Africa: a systematic review. J Int AIDS Soc. 2012;15:17383. doi: 10.7448/IAS.15.2.17383. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Bassett IV, Regan S, Luthuli P, et al. Linkage to care following community-based mobile HIV testing compared with clinic-based testing in Umlazi Township, Durban. South Africa. HIV Med. 2014;15:367–72. doi: 10.1111/hiv.12115. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Naik R, Doherty T, Jackson D, et al. Linkage to care following a home-based HIV counselling and testing intervention in rural South Africa. J Int AIDS Soc. 2015;18:19843. doi: 10.7448/IAS.18.1.19843. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Ingle SM, May M, Uebel K, et al. Outcomes in patients waiting for antiretroviral treatment in the free state Province. South Africa: Prospective linkage study. AIDS. 2010;24:2717–25. doi: 10.1097/QAD.0b013e32833fb71f. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Patten GE, Wilkinson L, Conradie K, et al. Impact on ART initiation of point-of-care CD4 testing at HIV diagnosis among HIV-positive youth in Khayelitsha. South Africa. J Int AIDS Soc. 2013;16:18518. doi: 10.7448/IAS.16.1.18518. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Larson BA, Schnippel K, Brennan A, et al. Same-day CD4 testing to improve uptake of HIV care and treatment in South Africa: point-of-care is not enough. AIDS Research and Treatment. 2013;2013:1–7. doi: 10.1155/2013/941493. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Govindasamy D, Kranzer K, van Schaik N, et al. Linkage to HIV, TB and Non-communicable disease care from a mobile testing unit in Cape Town, South Africa. PLoS ONE. 2013;8:e80017. doi: 10.1371/journal.pone.0080017. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Iwuji CC, Orne-Gliemann J, Larmarange J, et al. Uptake of home-based HIV testing, linkage to care, and community attitudes about ART in Rural KwaZulu-Natal, South Africa: descriptive results from the first phase of the ANRS 12249 TasP cluster-randomised trial. PLOS Med. 2016;13:e1002107–18. doi: 10.1371/journal.pmed.1002107. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Tabana H, Nkonki L, Hongoro C, et al. A cost-effectiveness analysis of a home-based HIV counselling and testing intervention versus the standard (facility based) HIV testing strategy in rural South Africa. PLoS ONE. 2015;10:e0135048. doi: 10.1371/journal.pone.0135048. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Van Rooyen H, Barnabas RV, Baeten JM, et al. High HIV testing uptake and linkage to care in a novel program of home-based HIV counseling and testing with facilitated referral in KwaZulu-Natal, South Africa. J Acquir Immune Defic Syndr. 2013;64:e1–8. doi: 10.1097/QAI.0b013e31829b567d. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Sabapathy K, Van den Bergh R, Fidler S, Hayes R, Ford N. Uptake of home-based voluntary HIV testing in sub-saharan Africa: a systematic review and meta-analysis. PLOS Med. 2012;9:e1001351. doi: 10.1371/journal.pmed.1001351. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Amuron B, Namara G, Birungi J, et al. Mortality and loss-to-follow-up during the pre-treatment period in an antiretroviral therapy programme under normal health service conditions in Uganda. BMC Public Health. 2009;9:290. doi: 10.1186/1471-2458-9-290. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Balfour L, Tasca GA, Kowal J, et al. Development and validation of the HIV Medication readiness scale. Assessment. 2007;14:408–16. doi: 10.1177/1073191107304295. [DOI] [PubMed] [Google Scholar]
- 31.Katz IT, Dietrich J, Tshabalala G, et al. Understanding treatment refusal among adults presenting for HIV-testing in Soweto, South Africa: a qualitative study. AIDS Behav. 2015;19:704–14. doi: 10.1007/s10461-014-0920-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Operario D, Kuo C, Sosa-Rubi SG, Galárraga O. Conditional economic incentives for reducing HIV risk behaviors: integration of psychology and behavioral economics. Health Psychol. 2013;32:932–40. doi: 10.1037/a0032760. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Fowler ME. Recognizing the phenomenon of readiness: concept analysis and case study. J Assoc Nurses AIDS Care. 1998;9:72–6. doi: 10.1016/S1055-3290(98)80021-6. [DOI] [PubMed] [Google Scholar]
- 34.Department of Health, Republic of South Africa. National consolidated guidelines for the prevention of mother-to-child transmission of HIV (PMTCT) and the management of HIV in children, adolescents and adults [Internet] Pretoria: Department of Health; 2014. [Accessed 27 September 2016]. [updated 24 December 2014]. Available from: http://www.kznhealth.gov.za/family/HIV-Guidelines-Jan2015.pdf. [Google Scholar]
- 35.Grimes RM, Grimes DE. Readiness: the state of the science (or the Lack Thereof) Curr HIV/AIDS Rep. 2010;7:245–52. doi: 10.1007/s11904-010-0056-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Nordqvist O, Södergård B, Tully MP, Sönnerborg A, Lindblad ÅK. Assessing and achieving readiness to initiate HIV medication. Patient Educ Couns. 2006;62:21–30. doi: 10.1016/j.pec.2005.09.014. [DOI] [PubMed] [Google Scholar]
- 37.Sodergard B. Readiness to start HIV treatment. IJAR. 2013;1:1. [Google Scholar]
- 38.Prochaska JO, Velicer WF. The transtheoretical model of health behavior change. Am J Health Promot. 1997;12:38–48. doi: 10.4278/0890-1171-12.1.38. [DOI] [PubMed] [Google Scholar]
- 39.Grimes RM, Grimes DE. Patient readiness to adhere to HAART. J Int Assoc Physicians AIDS Care. 2009;8:364–6. doi: 10.1177/1545109709351240. [DOI] [PubMed] [Google Scholar]
- 40.Fernández MI, Hosek S, Warren JC, et al. Development of an easy to use tool to assess HIV treatment readiness in adolescent clinical care settings. AIDS Care. 2011;23:1492–9. doi: 10.1080/09540121.2011.565020. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Enriquez M, Gore PA, O’Connor MC, McKinsey DS. Assessment of readiness for adherence by HIV-positive males who had previously failed treatment. J Assoc Nurses AIDS Care. 2004;15:42–9. doi: 10.1177/1055329003256209. [DOI] [PubMed] [Google Scholar]
- 42.Katz IT, Essien T, Marinda ET, et al. Antiretroviral therapy refusal among newly diagnosed HIV-infected adults. AIDS. 2011;25:2177–81. doi: 10.1097/QAD.0b013e32834b6464. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Hachfeld A, Ledergerber B, Darling K, et al. Reasons for late presentation to HIV care in Switzerland. J Int AIDS Soc. 2015;18:20317. doi: 10.7448/IAS.18.1.20317. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.DeSalvo KB, Fan VS, McDonell MB, Fihn SD. Predicting mortality and healthcare utilization with a single question. Health Serv Res. 2005;40:1234–46. doi: 10.1111/j.1475-6773.2005.00404.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Kessler RC, Andrews G, Colpe LJ, et al. Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol Med. 2002;32:959–76. doi: 10.1017/s0033291702006074. [DOI] [PubMed] [Google Scholar]
- 46.Otieno PA, Kohler PK, Bosire RK, Brown ER, Macharia SW, John-Stewart GC. Determinants of failure to access care in mothers referred to HIV treatment programs in Nairobi. Kenya. AIDS Care. 2010;22:729–36. doi: 10.1080/09540120903373565. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Kubler-Ross E. On death and dying. New York: Scribner; 1997. [Google Scholar]
- 48.Hatcher AM, Turan JM, Leslie HH, et al. Predictors of linkage to care following Community-based HIV counseling and testing in rural Kenya. AIDS Behav. 2012;16:1295–307. doi: 10.1007/s10461-011-0065-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Chakrapani V, Velayudham J, Shunmugam M, Newman PA, Dubrow R. Barriers to antiretroviral treatment access for injecting drug users living with HIV in Chennai. South India. AIDS Care. 2014;26:835–41. doi: 10.1080/09540121.2013.861573. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Ajzen I. The theory of planned behavior. Organ Behav Hum Decis Process. 1991;50:179–211. [Google Scholar]
- 51.Crocker J. Social stigma and self-esteem: situational construction of self-worth. J Exp Soc Psychol. 1999;35:89–107. [Google Scholar]
- 52.Nyblade L, Pande R, Mathur S, et al. Disentangling HIV and AIDS stigma in Ethiopia, Tanzania and Zambia. Washington D.C: International Center for Research on Women; 2003. [Accessed 27 September 2016]. Available from: http://www.icrw.org/publications/disentangling-hiv-and-aids-stigma-ethiopia-tanzania-and-zambia. [Google Scholar]
- 53.Govindasamy D, van Schaik N, Kranzer K, Wood R, Mathews C, Bekker L-G. Linkage to HIV care from a mobile testing unit in South Africa by different CD4 count strata. J Acquir Immune Defic Syndr. 2011;58:344–52. doi: 10.1097/QAI.0b013e31822e0c4c. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Kigozi IM, Dobkin LM, Martin JN, et al. Late-disease stage at presentation to an HIV Clinic in the era of free antiretroviral therapy in sub-saharan Africa. J Acquir Immune Defic Syndr. 2009;52:280–9. doi: 10.1097/QAI.0b013e3181ab6eab. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Mugglin C, Estill J, Wandeler G, et al. Loss to programme between HIV diagnosis and initiation of antiretroviral therapy in sub-Saharan Africa: systematic review and meta-analysis. Trop Med Int Health. 2012;17:1509–20. doi: 10.1111/j.1365-3156.2012.03089.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56.Auld AF, Shiraishi RW, Mbofana F, et al. Lower levels of antiretroviral therapy enrollment among men with HIV compared with women-12 Countries, 2002–2013. Morb Mortal Wkly Rep. 2015;64:1281–6. doi: 10.15585/mmwr.mm6446a2. [DOI] [PubMed] [Google Scholar]
- 57.Nakigozi G, Atuyambe L, Kamya M, et al. A qualitative study of barriers to enrollment into free HIV care: perspectives of never-in-care HIV-positive patients and providers in Rakai. Uganda. BioMed Research International. 2013;2013:470245–7. doi: 10.1155/2013/470245. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Ahmed I, Gugsa ST, Lemma S, Demissie M. Predictors of loss to follow-up before HIV treatment initiation in Northwest Ethiopia: a case control study. BMC Public Health. 2013;13:867. doi: 10.1186/1471-2458-13-867. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 59.Bengtson AM, Chibwesha CJ, Westreich D, et al. A risk score to identify HIV-infected women most likely to become lost to follow-up in the postpartum period. AIDS Care. 2016;28:1035–45. doi: 10.1080/09540121.2016.1144869. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 60.Shaikh N, Abdullah F, Lombard C, Smit L. Masking through averages-intraprovincial heterogeneity in HIV prevalence within the Western Cape. S Afr Med J. 2006;96:538–43. [PubMed] [Google Scholar]
- 61.Palekar R, Pettifor A, Behets F, MacPhail C. Association between knowing someone who died of AIDS and behavior change among South African youth. AIDS Behav. 2008;12:903–12. doi: 10.1007/s10461-007-9325-5. [DOI] [PubMed] [Google Scholar]
- 62.Fox MP, Mazimba A, Seidenberg P, Crooks D, Sikateyo B, Rosen S. Barriers to initiation of antiretroviral treatment in rural and urban areas of Zambia: a cross-sectional study of cost, stigma, and perceptions about ART. J Int AIDS Soc. 2010;13:8. doi: 10.1186/1758-2652-13-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 63.Kunihira NR, Nuwaha F, Mayanja R, Peterson S. Barriers to use of antiretroviral drugs in Rakai district of Uganda. African Health Sciences. 2010;10:120–9. [PMC free article] [PubMed] [Google Scholar]
- 64.Unge C, Johansson A, Zachariah R, Some D, Van Engelgem I, Ekstrom AM. Reasons for unsatisfactory acceptance of antiretroviral treatment in the urban Kibera slum. Kenya. AIDS Care. 2008;20:146–9. doi: 10.1080/09540120701513677. [DOI] [PubMed] [Google Scholar]
- 65.Earnshaw VA, Smith LR, Chaudoir SR, Amico KR, Copenhaver MM. HIV stigma mechanisms and well-being among PLWH: a test of the HIV stigma framework. AIDS Behav. 2013;17:1785–95. doi: 10.1007/s10461-013-0437-9. [DOI] [PMC free article] [PubMed] [Google Scholar]