Are randomized control trials bad for children?
18 Oct 2017
A researcher collecting health outcome data about a mother and child in Bacau County, Romania.
There was a time when UNICEF was known in development circles as the agency that “does everything but knows nothing.” Indeed, UNICEF is known for getting things done for children through persuasive advocacy, a human rights approach, and its presence on the ground. Today UNICEF is increasingly committed to evidence-based programming, and researchers around the world are studying the effectiveness of UNICEF’s work. In my role at UNICEF Innocenti, I frequently have discussions with UNICEF country staff who want to know how their programmes are working. A typical discussion with those working on violence against children, poverty reduction, emergency response, nutrition, and more starts with colleagues telling me: “We want to rigorously test how well our programme works, but we don’t want to do a randomized control trial (RCT).” For many in UNICEF, RCT is a bad word. It conjures ideas of cold-hearted researchers arbitrarily withholding programme benefits from some households and villages for the sole purpose of racking up academic publications in journals no one will read. This thinking assumes that other options are equally as good, so we can simply take those evil RCTs off the table and select from other, “pro-children” evaluation methods.
For many RCT is a bad word. It conjures ideas of cold-hearted researchers arbitrarily withholding programme benefits from some households and villages for the sole purpose of racking up academic publications in journals no one will read.And while other evaluation methods can provide powerful evidence on programme impacts, and RCTs are not always needed, before choosing a method, we need to first understand, in the words of Rachel Glennerster and Shawn Powers, “what are we judging RCTs against?” Indeed, while RCTs get the most attention when discussing the ethics of impact evaluation, all methods come with ethical implications.
To make a random selection of RCT treatment villages for an ongoing social protection programme impact evaluation in Tanzania the names of villages were literally drawn blindly from this hat.Both experimental (RCT) and quasi-experimental methods try to get at causal impacts of programmes and policies. They do so by constructing a “counter-factual,” the term researchers use to describe what would have happened to beneficiaries had they not received the program (also referred to as “treatment” or “intervention”). Since we haven’t yet invented a time machine where we can first give a group of people a treatment, see what happens, and then go back in our time machine and observe what happened without the treatment, we have to use other techniques to measure the counterfactual. RCTs do this by determining who gets the treatment and who doesn’t by chance, which usually ensures there are no systematic differences between the groups. For example, those who get the treatment aren’t getting it because they are more motivated, more informed, live closer to health facilities, or are from a privileged political group, etc. Quasi-experimental methods use other techniques to construct a comparison group of people who did not receive the treatment. However, we cannot be as certain the estimated impacts are a result of the treatment, and not due to other factors. Of all these methods (non-experimental/observational, quasi-experimental and experimental/RCT), RCTs provide the most credible evidence on programme impacts, however, they are not always possible. In my work at UNICEF with the Transfer Project, we use both RCTs and quasi-experimental methods. However, non-experimental and quasi-experimental come with limitations. If we use a poor comparison group (or no comparison group at all), we could end up overestimating or underestimating treatment impacts—and we often don’t know with certainty which is the case. A non-credible or non-rigorous evaluation is a problem because underestimating program impacts might mean that we conclude a program or policy doesn’t work when it really does (with ethical implications). Funding might be withdrawn and an effective program is cut off. Or we might overestimate program impacts and conclude that a program is more successful than it really is (also with ethical implications). Resources might be allocated to this program over another program that actually works, or works better.
Mobile health teams provide essential basic health services and collect household data in remote and isolated communities, with a special focus on maternal and neonatal care in Afghanistan.So if RCTs produce the most solid evidence, why don’t we use them everywhere? There are several reasons for this. Sometimes you just can’t randomize who gets a program due to implementation-related reasons (for example, every village in the district benefits from the same road or improved water system). Sometimes you can randomize, but programmers are reluctant to do so because of perceived ethical concerns. In the first scenario, we turn to quasi-experimental methods where possible. Now let’s break down some of the concerns in the second scenario. All research methods (not just RCTs) have ethical considerations to be mindful of. These include, among others, informed consent for research, principles of ‘do not harm’, necessary referrals for additional services if needed and review of national and international ethics review boards to ensure ethical guidelines are adhered to. However, one concern unique to RCTs is that benefits are purposefully given to one group and not to another. Implementers need to consider whether in fact this is ethical. In many cases it is. For example, if roll-out of the programme can’t reach all intended beneficiaries at the same time (say there’s a phased roll-out due to budgetary or capacity constraints) then we can take advantage of the group experiencing delayed roll-out and use them as a control group. Further, if we don’t know whether a programme is effective, it’s not unethical to randomize some individuals to not receive that programme (in fact receiving an ineffective programme may do more harm than good). Finally, we must also ask ourselves: Is it ethical to pour donor money into projects when we don’t know if they work? Is it ethical not to learn from the experience of beneficiaries about the impacts of a program? RCTs can be a powerful tool to generate evidence to inform policies and programmes to improve the lives of children. As with any type of study, researchers must adhere to ethical research principles. However, when choosing the right type of methodology to evaluate a programme, it’s important to keep the ethical implications of each in mind, as well as a clear understanding of all the options, including the option of never knowing what impact your programme is making. Tia Palermo is Social Policy Specialist in the Social & Economic Policy Section at UNICEF Innocenti, where she conducts research on social protection programmes in Sub-Saharan Africa with the Transfer Project. Explore the UNICEF Innocenti research catalogue for new publications. Follow UNICEF Innocenti on Twitter and sign up for e-newsletters on any page of the UNICEF Innocenti website.