Traditional Beliefs of Illness and Use of Modern Medicine in Kananga, DRC

Last registered on May 16, 2022


Trial Information

General Information

Traditional Beliefs of Illness and Use of Modern Medicine in Kananga, DRC
Initial registration date
May 16, 2022

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
May 16, 2022, 5:01 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.


Primary Investigator

Harvard University

Other Primary Investigator(s)

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
In Kananga, Democratic Republic of Congo, use of traditional medicine is high and illness is often explained through witchcraft and other supernatural forces. I design a field experiment to study whether explaining the origin and treatment possibilities of an exemplifying disease can alter the classification of diseases into supernatural and natural diseases, affect beliefs about modern medicine efficacy, and ultimately increase demand for modern medicine.

Specifically, I examine whether informational videos on epilepsy can induce
1) belief updating regarding the origin and modern medicine treatment efficacy of epilepsy and demand for modern treatment for epilepsy and
2) spillover effects on other diseases: updating beliefs about their origin, modern treatment efficacy, and demand for modern medicine.
Epilepsy is highly prevalent and salient and the disease most frequently explained through witchcraft in Kananga.
External Link(s)

Registration Citation

Sievert, Clara. 2022. "Traditional Beliefs of Illness and Use of Modern Medicine in Kananga, DRC." AEA RCT Registry. May 16.
Experimental Details


I will show an informational video on epilepsy to the survey respondent. The video shows two local doctors explaining the biological mechanisms during an epileptic attack and potential causes. A woman gives a testimony for how modern medicine had helped her epileptic daughter. The respondent gets an information leaflet with the same information.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
1. Incentivized estimation of modern treatment efficacy for epilepsy in Kananga
2. Willingness to pay for a consultation for somebody with seizures: the respondent indicates whether he/she would prefer giving a voucher for a consultation or money to a third person looking for a consultation for seizures at the hospital for different amounts of money. One of the choices is implemented with a probability.
3. Incentivized measure for stigmatizing beliefs: whether the respondent wants to be put on a list of people to be called if an NGO wants to hire people for a project working with epileptic patients.
4. Accepting a voucher for a free consultation for somebody with seizures at the hospital, which the respondent can give to anybody.
5. Whether somebody uses the voucher for free consultation for seizures at the local hospital given to respondent x

Other diseases:
1. Beliefs on the origin of illnesses
2. Beliefs of treatment efficacy of modern medicine and traditional medicine for list of diseases.
3. Willingness to pay (Becker-DeGroot-Marschak method) for vouchers for consultation and testing for malaria, typhoid, tuberculosis, anemia, hypertension, diabetes, and HIV.
4. Using a voucher for a free consultation and testing for HIV at the hospital.
5. Using a voucher for a free consultation and testing for hypertension at the hospital.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
In the first visit of the respondent, I will conduct a baseline survey to elicit baseline beliefs and use of modern medicine. Then, the respondent watches a video (treatment or control). In the immediate mini endline, the incentivized measures are elicited. The respondent is provided with a voucher for a free HIV test and with a voucher for a free hypertension test at the hospital.

In the endline survey during the second visit of the respondent, I measure beliefs again. The respondent is provided with a voucher he/she can give to anybody for a free consultation for somebody with seizures at the hospital. The second visit is planned to take place one week after the first visit.

In my regressions, I will control for the relevant baseline measures. For the willingness to pay measures for the health vouchers, I will control for past testing/examination experience. For the incentivized stigmatising beliefs measure in the endline, I will control for baseline stigmatising beliefs.

Respondents are randomly assigned into one of the two treatment arms:
1. Treatment: Respondents watch a video on epilepsy, its origin, and treatment. Two doctors explain how epilepsy happens in the brain, what can cause epilepsy (e.g. infectious diseases), and what treatment consists of. A woman gives a testimonial on how modern medicine has worked for her daughter. Respondents receive an information voucher on epilepsy.
2. Control: Respondents watch a video on children games. The same two doctors (now in their role as citizens) explain which games children can play with little resources. Respondents receive an information voucher on how to make paper planes.
Experimental Design Details
Randomization Method
The randomization will be conducted by the tablet at the moment of the survey using a random number generator.
Randomization Unit
I randomize at the level of the individual respondent.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
No clustering
Sample size: planned number of observations
800 respondents in the baseline survey.
Sample size (or number of clusters) by treatment arms
400 respondents are expected to be in the treatment group and 400 respondents are expected to be in the control group.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
Harvard University-Area Committe on the Use of Human Subjects
IRB Approval Date
IRB Approval Number


Post Trial Information

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials