Does Preference-based HIV Testing Increase Uptake in High Risk Populations?
NCT ID: NCT02714140
Last Updated: 2021-08-18
Study Results
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Basic Information
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COMPLETED
NA
1194 participants
INTERVENTIONAL
2018-01-03
2020-10-31
Brief Summary
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Detailed Description
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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.
Conditions
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Study Design
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RANDOMIZED
PARALLEL
DIAGNOSTIC
SINGLE
Study Groups
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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.
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.
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.
SMS Reminder
Participants will receive an SMS reminder to test.
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.
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.
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.
SMS Reminder
Participants will receive an SMS reminder to test.
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.
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
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.
SMS Reminder
Participants will receive an SMS reminder to test.
Interventions
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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.
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
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.
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.
SMS Reminder
Participants will receive an SMS reminder to test.
Eligibility Criteria
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Inclusion Criteria
* Eligible participants will be ages 18+, reside in Moshi, Tanzania and have no plans to leave the study area.
Exclusion Criteria
18 Years
ALL
Yes
Sponsors
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Duke University
OTHER
Kilimanjaro Christian Medical Centre, Tanzania
OTHER
University of South Carolina
OTHER
Responsible Party
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Jan Ostermann
Associate Professor
Principal Investigators
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Jan Ostermann, PhD
Role: PRINCIPAL_INVESTIGATOR
University of South Carolina
Locations
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Duke University
Durham, North Carolina, United States
University of South Carolina
Columbia, South Carolina, United States
Kilimanjaro Clinical Research Institute
Moshi, Kilimanjaro, Tanzania
Countries
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References
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Ostermann J, Njau B, Brown DS, Muhlbacher 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.
Njau B, Ostermann J, Brown D, Muhlbacher 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, Njau B, Mtuy T, Brown DS, Muhlbacher 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.
Ostermann J, Brown DS, Muhlbacher 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, Hobbie A, Mtuy T, Masaki ML, Shayo A, van Zwetselaar M, Masnick M, Flaherty B, Brown DS, Muhlbacher 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, Hobbie AM, Mtuy TB, Masnick M, Brown DS, Muhlbacher AC, Thielman NM. Divergent preferences for enhanced HIV testing options among high-risk populations in northern Tanzania: a short report. AIDS Care. 2023 Sep;35(9):1270-1278. doi: 10.1080/09540121.2022.2119471. Epub 2022 Sep 5.
Ostermann J, Njau B, Masaki M, Mtuy T, Itemba D, Hobbie A, Yelverton V, Moore S, Yamanis T, Thielman NM. Feasibility, Acceptability, and Potential Cost-Effectiveness of a Novel Mobile Phone Intervention to Promote Human Immunodeficiency Virus Testing Within Social Networks in Tanzania. Sex Transm Dis. 2022 Nov 1;49(11):778-781. doi: 10.1097/OLQ.0000000000001611. Epub 2022 Jan 29.
Other Identifiers
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