Randomized Evaluation of HIV Testing. Example of Random Promotion or Encouragement Design. Rebecca Thornton University of Michigan

Transcription

1 Randomized Evaluation of HIV Testing Example of Random Promotion or Encouragement Design Rebecca Thornton University of Michigan

2 Recall Promotion Design 1. Promotion was random: those who get the promotion are just like those who didn t 2. Promotion worked: those who get the promotion actually act on it 3. Promotion doesn t affect outcome behavior except through the behavior itself

3 HIV Testing Taking an HIV test is the single most influential driver for behavior change (Global Business Coalition; Richard Holbrooke) Making people aware of their HIV status is the only way to make them change their sexual behavior (Bill Clinton) 55% of the total HIV/AIDS expenditure spent on testing (Mozambique) Can we justify these financial resources being spent on HIV testing?

4 Conventional View #1 Once people learn their HIV status, they will engage in safer sexual behavior Why might this be ambiguous for HIV positives? Altruistic towards partner but safe sex is costly and there is no longer a return to use protection Why might this be ambiguous for HIV negatives? Increased return to safe sex but no longer a need to act altruistically Individuals may also believe that they face lower risk

5 Conventional View #2 It is difficult to get people to learn their HIV status I cannot accept to be tested. It is better to just live without knowing my status and see if I get sick than to know that I have AIDS in advance because then I cannot be living happily. The cost of stigma is quite high, more than the bus fare to town.

6 Research Questions How does the demand for learning HIV results respond to small changes in costs and benefits? What is the impact of learning HIV results on sexual behavior?

7 Research Design Limitations with existing studies and challenges Self-reported behavior How might this bias the results? Selection Who chooses to test or learn results Where testing centers are located How might self-selection bias the results?

8 Research Design We want to measure the effect of learning HIV results Think through your exact question and plan for analysis Among HIV positives: compare those who know their results with those who don t Among HIV negatives: compare those who know their results with those who don t Y = a + b Got Results + e i 1 i i Potential for selection bias? What would we randomize?

9 Research Design How can we randomize getting HIV results? Incentives to learn results (subsidies of price) Distance to results centers (subsidies of time/transport)

10 Malawi Panel Study Panel study (1998, 2001, 2004) 125 rural villages in three districts why important? Randomly selected households (one in four) Women and their husbands, adolescents 2004: Offered free HIV and STI tests 93% accepted (2,859) 6.7% HIV Positive

11 Experimental Design Randomly assigned voucher to learn HIV results Between $0-$3.00 (average=$1.04) 20% received no incentive How much were the incentives? Average daily wage: ~$1.00 Smallest amount: $0.10 Why randomize by individual?

12 Experimental Design Results centers Randomly placed based on household GPS coordinates and clustered by village Average distance = 2 km

13 Experimental Design

14 Experimental Design

15 Experimental Design

16 Percent Learning HIV Results 80% 60% 40% 20% 0 Received No Incentive Received Some Incentive

17 Percent Learning HIV Results 80% 60% 40% 20% Amount of Incentive (Dollars)

18 Percent Learning HIV Results 90% 80% 70% 60% km 1 km 2 km 3 km 4km Distance from the results center

19 Experimental Design How do we measure the effect of learning HIV results (going to the tent)? Need a follow-up with outcome variables like what? Follow-up survey (2 districts) Gave $0.30 why do this? Sold condoms at half retail price Only allowed individuals to purchase condoms from the money they were given Design issues Why have respondents purchase condoms? Why give them any money? Why cap the number of condoms allowed?

20 Impact of Learning HIV Status Two months after HIV results were available 62% reported having sex 8% reported purchasing condoms Sold condoms 24% purchased condoms 3.7 condoms on average We want to measure the demand for safe sex. Why might using condom sales be problematic for this? One idea: Distinguish between those that were sexually active and those that were not

21 Percent Purchasing Condoms HIV Negatives who had sex at Baseline 50% 40% 30% 20% 10% 0 Did Not Get Results Got Results

22 Percent Purchasing Condoms HIV Positives who had sex at Baseline 50% 40% 30% 20% 10% 0 Did Not Get Results Got Results

23 Effects after Learning HIV Results HIV positives with a sexual partner: Significant increase in the likelihood of purchasing subsidized condom But the number of condoms purchased was small only 2 additional condoms No effects among HIV negatives No effects among those not having sex No effect on likelihood of sexual activity

24 How could this apply to MC? Prices of MC Prizes Location of mobile clinics Information counselors, media Other ways?

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26 Distribution of Incentives Day 1 Theoretical and Actual Total Distribution Theoretical Actual

27 Distribution of Incentives - overall Kernal Density Total Amount of Incentive (Dollars) Actual Distribution Theoretical Distribution