DCE-IMPACT: Does Preference-based HIV Testing Increase Uptake in High Risk Populations?
Study Details
Study Description
Brief Summary
Despite worldwide efforts to promote HIV Counseling and Testing (HCT), rates of testing remain low. Understanding how high risk groups decide to test and adapting available testing options to their preferences has the potential to broadly improve HCT uptake and cost-effectiveness. This study proposes to use a Discrete Choice Experiment, a survey method increasingly used by health economists for the design of patient-centered health care options, to rigorously quantify HIV testing preferences among two high-risk populations, identify their preferred testing options, and evaluate, in a pragmatic randomized controlled trial (RCT), the effect of a preference-based HIV counseling and testing (PB-HCT) intervention on testing uptake. At a time of heightened focus on health preferences research and patient-centered care, this study evaluates the critical link between preference-based intervention design and efficacy. If the RCT indicates that PB-HCT increases testing rates, the testing options evaluated in this R01 can be offered to high-risk populations in the study area, and the preference elicitation method and tools can be used to inform the design of testing options that better match the preferences of other high-risk populations and in other settings.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
|
N/A |
Detailed Description
HIV counseling and testing (HCT) is a highly cost-effective intervention for increasing serostatus awareness, a point of entry into HIV care and treatment, and an important means of primary and secondary HIV prevention. Public health officials have called for dramatic increases in HIV testing to achieve an HIV-free generation. Yet, testing rates are plateauing and rates of repeat-testing among those with ongoing risk remain low. Thus, there is a need to better understand and address deterrents of HIV testing.
Evaluations of population preferences for testing have typically focused on the acceptability of specific venue-based testing options, such as home-based, provider-initiated, or workplace testing, usually without consideration or offer of other options. Results from these assessments do not probe the potential diversity in testing preferences of target populations; they do not ascertain how individuals value diverse characteristics of testing options; nor can they identify combinations of testing options that could maximize uptake of testing. The investigators posit that systematically designed HIV testing interventions, matched specifically to the heterogeneous preferences of diverse target populations, hold potential to greatly improve uptake of testing.
In this study the investigators will extend the use of the DCE method to design an HIV testing intervention that is matched to the specific preferences of two high-risk populations and to establish, in a pragmatic randomized controlled trial, whether a Preference-Based HIV Counseling and Testing (PB-HCT) intervention increases uptake of HIV testing. In short, the investigators are adapting concepts from health and behavioral economics, marketing, and patient-centered care to apply a groundbreaking, client-focused perspective to the context of HIV testing.
This application will address the following Specific Aims:
Aim 1 will identify which combination of HIV counseling and testing options is expected to maximize uptake of HIV testing in two high-risk populations. We will use formative work and DCE surveys with female barworkers and male Kilimanjaro mountain porters, two high HIV risk populations in Moshi, Tanzania, to quantify the relative importance of characteristics such as home-based vs. facility-based testing, venipuncture vs. finger prick vs. oral swab, individual vs. couples counseling, the availability of services such as health check-ups, and options for HIV serostatus disclosure, for individuals' testing decisions. Latent class analysis of DCE choice data will identify distinct sets of testing preferences within each high-risk population, and identify a combination of testing options that is predicted to maximize uptake of testing.
Aim 2 will evaluate whether an HIV testing offer, matched to the testing preferences of each high-risk population, increases testing uptake relative to a common option. Representative samples of 600 female barworkers and 600 male mountain porters will be randomized into three groups (Groups A, B, and C). Participants will be offered one common option (this option is the same regardless of which group a participant is randomized into) and 3 group-specific testing options. Group A participants will be offered 3 currently available testing options targeted at the distribution of preferences among participants. Group B participants will be offered 3 preference-informed "enhanced" testing options, which include features that may not yet be available in the study area. Group C participants will be offered an equal number of predicted less-preferred options. The primary outcome is uptake of HIV testing.
The findings from this project have significant public health relevance. The proposed study will a) rigorously characterize the HIV testing preferences of two high-risk populations; b) identify feasible HIV testing interventions that are predicted to increase HCT uptake; and c) identify the effect of a preference-informed HIV testing intervention on rates of testing. More generally, this study evaluates the critical link between an intervention that is systematically designed to match a population's preferences and the efficacy of that intervention. If successful, preference assessments among small samples from key populations could be used widely as an implementation research tool to inform the design of diverse HIV prevention, testing, and treatment interventions; preference-informed interventions, in turn, hold potential to broadly increase intervention uptake and efficacy, both internationally and in the United States.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Experimental: Group A: More preferred Existing + Common Group A participants will be offered the common option and 3 currently available testing options that are targeted at the distribution of preferences among participants. |
Behavioral: PB-HCT +
Participants will be offered 3 HIV testing options. The investigators will rank the predicted utility of all EXISTING HIV testing options for each participant and select those 3 PB-HCT options that jointly maximize the share of participants predicted to prefer at least one of the three options over the common option.
Behavioral: Economic incentive
Participants will be re-contacted three months after being offered PB-HCT options. Participants will be reminded of the options, and offered an incentive to present for testing using any of the PB-HCT options or the common option.
Behavioral: SMS Reminder
Participants will receive an SMS reminder to test.
|
| Experimental: Group B: More preferred Enhanced + Common Group B participants will be offered the common option and 3 preference-informed "enhanced" testing options, which include combinations of features that may not yet be available in the study area. |
Behavioral: Economic incentive
Participants will be re-contacted three months after being offered PB-HCT options. Participants will be reminded of the options, and offered an incentive to present for testing using any of the PB-HCT options or the common option.
Behavioral: PB-HCT ++
Participants will be offered 3 HIV testing options. The investigators will rank the predicted utility of all feasible ENHANCED HIV testing options for each participant and select those 3 PB-HCT options that jointly maximize the share of participants predicted to prefer at least one of the three options over the common option.
Behavioral: SMS Reminder
Participants will receive an SMS reminder to test.
|
| Active Comparator: Group C: Less preferred + Common Group C participants will be offered the common option and 3 predicted less-preferred options. With the common option being the best option in Group C, this group is effectively a non-PB-HCT comparison group. |
Behavioral: PB-HCT -
Participants will be offered 3 HIV testing options. The investigators will rank the predicted utility of all feasible HIV testing options for each participant and select 3 PB-HCT options that are less preferred than the common option
Behavioral: Economic incentive
Participants will be re-contacted three months after being offered PB-HCT options. Participants will be reminded of the options, and offered an incentive to present for testing using any of the PB-HCT options or the common option.
Behavioral: SMS Reminder
Participants will receive an SMS reminder to test.
|
Outcome Measures
Primary Outcome Measures
- Uptake of HIV testing - 3 months [3 months]
Percent of participants who test for HIV
Secondary Outcome Measures
- Uptake of HIV testing - 15 months [15 months]
Percent of participants who test for HIV
Eligibility Criteria
Criteria
Inclusion Criteria:
-
Males who work as Kilimanjaro mountain porters, Females who regularly work at a bar, hotel or restaurant establishment and serve alcohol to patrons.
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Eligible participants will be ages 18+, reside in Moshi, Tanzania and have no plans to leave the study area.
Exclusion Criteria:
- Participants who are not able to see will be excluded owing to the visual nature of the survey presented to elicit preferences.
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Duke University | Durham | North Carolina | United States | 27708 |
| 2 | University of South Carolina | Columbia | South Carolina | United States | 29208 |
| 3 | Kilimanjaro Clinical Research Institute | Moshi | Kilimanjaro Region | Tanzania |
Sponsors and Collaborators
- University of South Carolina
- Duke University
- Kilimanjaro Christian Medical Centre, Tanzania
Investigators
- Principal Investigator: Jan Ostermann, PhD, University of South Carolina
Study Documents (Full-Text)
None provided.More Information
Publications
- Njau B, Ostermann J, Brown D, Mühlbacher A, Reddy E, Thielman N. HIV testing preferences in Tanzania: a qualitative exploration of the importance of confidentiality, accessibility, and quality of service. BMC Public Health. 2014 Aug 12;14:838. doi: 10.1186/1471-2458-14-838.
- Ostermann J, Brown DS, Mühlbacher A, Njau B, Thielman N. Would you test for 5000 Shillings? HIV risk and willingness to accept HIV testing in Tanzania. Health Econ Rev. 2015 Dec;5(1):60. doi: 10.1186/s13561-015-0060-8. Epub 2015 Aug 19.
- Ostermann J, Njau B, Brown DS, Mühlbacher A, Thielman N. Heterogeneous HIV testing preferences in an urban setting in Tanzania: results from a discrete choice experiment. PLoS One. 2014 Mar 18;9(3):e92100. doi: 10.1371/journal.pone.0092100. eCollection 2014.
- Ostermann J, Njau B, Hobbie A, Mtuy T, Masaki ML, Shayo A, van Zwetselaar M, Masnick M, Flaherty B, Brown DS, Mühlbacher AC, Thielman NM. Using discrete choice experiments to design interventions for heterogeneous preferences: protocol for a pragmatic randomised controlled trial of a preference-informed, heterogeneity-focused, HIV testing offer for high-risk populations. BMJ Open. 2020 Nov 6;10(11):e039313. doi: 10.1136/bmjopen-2020-039313.
- Ostermann J, Njau B, Mtuy T, Brown DS, Mühlbacher A, Thielman N. One size does not fit all: HIV testing preferences differ among high-risk groups in Northern Tanzania. AIDS Care. 2015;27(5):595-603. doi: 10.1080/09540121.2014.998612. Epub 2015 Jan 23.
- R01MH106388