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Soft and hard commitment devices to increase HIV testing
Last registered on September 21, 2019

Pre-Trial

Trial Information
General Information
Title
Soft and hard commitment devices to increase HIV testing
RCT ID
AEARCTR-0004295
Initial registration date
June 21, 2019
Last updated
September 21, 2019 4:59 PM EDT
Location(s)

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Primary Investigator
Affiliation
University of Oxford
Other Primary Investigator(s)
PI Affiliation
University of Minnesota
PI Affiliation
University of Toronto
PI Affiliation
University of Minnesota
Additional Trial Information
Status
In development
Start date
2019-06-21
End date
2020-12-31
Secondary IDs
Abstract
Our goal is to study innovative ways to overcome the challenge of getting HIV-positive people into the treatment pipeline. Despite the availability of free, life-saving treatment, nearly one million people died of AIDS in 2017. This is largely driven by low HIV testing rates: a quarter of those living with HIV do not know their status (WHO 2017). In Africa this problem is worse for men, in part because pregnant women are routinely tested and treated for HIV. We will investigate whether a soft commitment device (a scheduled appointment) and a hard commitment device (a small money transfer conditional on HIV testing) can increase HIV testing among men in Zomba Town, Malawi.
External Link(s)
Registration Citation
Citation
Derksen, Laura et al. 2019. "Soft and hard commitment devices to increase HIV testing." AEA RCT Registry. September 21. https://doi.org/10.1257/rct.4295-1.1.
Former Citation
Derksen, Laura et al. 2019. "Soft and hard commitment devices to increase HIV testing." AEA RCT Registry. September 21. https://www.socialscienceregistry.org/trials/4295/history/53879.
Sponsors & Partners

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Experimental Details
Interventions
Intervention(s)
We will investigate whether a soft commitment device (a scheduled appointment) and a hard commitment device (small money transfer conditional on HIV testing) can increase HIV testing among men in Zomba Town, Malawi.

We believe that procrastination (a tendency to delay) is a barrier to HIV testing for many people. We will assess the impact of two interventions that aim at reducing procrastination and thereby overcome the problem of continuously putting off HIV testing.

(1) A soft commitment device: selected participants will be offered scheduled appointments to test for HIV. Appointments are devices for mental and social commitment.

(2) A hard commitment device: selected participants will be invited to invest in a mechanism that conditions a small transfer of money on testing for HIV.
Intervention Start Date
2019-06-21
Intervention End Date
2019-09-30
Primary Outcomes
Primary Outcomes (end points)
Our primary outcome variable is a testing dummy collected at clinics when participants redeem their voucher. The testing dummy will be equal to 1 for participants who redeemed their voucher and then agreed to get tested, and equal to 0 otherwise.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
We will consider two secondary outcomes collected at clinics:

(1) A "tested HIV+ dummy": a dummy variable equal to 1 for participants who redeemed their voucher and tested HIV+, and equal to 0 otherwise.

(2) An "ART dummy": a dummy variable equal to 1 for participants who redeemed their voucher and agreed to initiate ARV treatment after testing HIV+, and equal to 0 otherwise.

These outcomes are considered as secondary not because they are uninteresting (quite the contrary) but rather because power will most likely be insufficient to detect any effect.
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We use a factorial design.
Experimental Design Details
Not available
Randomization Method
The randomization process will be predefined in a .csv downloaded on survey tablets, and hence reproducible. Randomization will be at the individual level without stratification. Each study participant will be automatically allocated to a treatment arm based on their Study ID which is composed of their enumerator ID, day of the study, and number of the survey. For example, the first enumerator’s first respondent on the first day of the study will have Study ID 010101.
Randomization Unit
Individual
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
No cluster
Sample size: planned number of observations
1200 individuals
Sample size (or number of clusters) by treatment arms
For the soft commitment device intervention (appointments), we will have 600 participants in the treatment group and 600 participants in the control group.

For the hard commitment device intervention (conditional money transfer) , we will have 600 participants in the treatment group and 600 participants in the control group for the intent-to-treat analysis. When calculating the average treatment effect on the treated, the sample size will depend on the take-up rate of the hard commitment device: denoting this take-up rate r, 600*r participants will be in the treatment group and 600*r participants will be in the control group for this analysis.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
National Health Sciences Research Committee
IRB Approval Date
2019-04-05
IRB Approval Number
2268
IRB Name
Human research protection program
IRB Approval Date
2019-04-09
IRB Approval Number
STUDY00005587
Analysis Plan

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