Evidence-based prevention: methods and limitations

There has been considerable debate amongst health-promotion professionals and researchers over what constitutes evidence of effectiveness in health promotion. One of the chief disagreements has arisen over the question of the research methodology that should be used to measure effectiveness. Oakley and colleagues1 have argued that the gold standard measure for effectiveness is a randomised controlled trial (RCT). However, others have said that a form of experiment designed for research into medical interventions is an inappropriate and unreliable tool for measuring the effectiveness of behavioural interventions.2

Part of the problem lies in controlling the sheer amount of variables that can influence the outcome of a behavioural intervention. RCTs of medical treatments are designed to eliminate these so-called confounders, as far as possible. They are designed to eliminate researcher bias, minimise social-desirability bias (the tendency of trial subjects to report favourable outcomes to ‘please’ the researcher) and ensure any placebo effect (the expectation that the treatment will be of benefit, which often does produce real beneficial effects) is evenly distributed between control and intervention arms, so it can be taken into account. Double-blinded, placebo-controlled trials were devised to eliminate this problem by ensuring that neither researcher nor subject knew whether or not they were getting the experimental treatment.

In trials that aim to change people’s minds or lifestyles, it may be very difficult to eliminate subject characteristics that influence the outcome, and even more difficult to eliminate researcher and social-desirability bias. Although behavioural trials can be ‘placebo controlled’ by pitting the trial intervention against standard of care, a less comprehensive intervention or a waiting list, they cannot be blinded. And although, in trials of behavioural interventions, efforts are made to rigorously standardise and script them so that every practitioner delivers an identical intervention, in practice people’s skills at delivery do vary.

Studies of counselling and psychotherapy have found, for instance, that only a tiny part of the variance between different therapeutic outcomes is due to the particular method or theoretical orientation that the counsellor uses.3 Individual personal characteristics of the counsellor and characteristics of the counselling relationship, such as a shared goal, are much more important.

In addition, subject populations need to be researched in advance so that the intervention delivered actually meets the population’s needs. Teaching condom-use negotiation, for instance, may be a waste of resources if done in a population where 95% of transmissions are via shared needles, or where taught to married women who have no power to ensure their use.

Researchers and practitioners may be unwilling to draw inferences from study results, especially if those results are counterintuitive, and may persist in advocating familiar solutions that lack evidential back-up. This is partly because of scepticism about RCTs of behavioural interventions, partly because research results are not well enough disseminated and partly because it is intrinsically more difficult to extract evidence of effectiveness from some prevention methods than others.

Over-reliance on evidence-based prevention, on the other hand, may have the opposite effect. Commissioners and providers may become rigidly prescriptive and only fund a narrow range of best-evidence interventions, rather than extrapolating from what evidence exists in order to construct a plausible, but varied, best-practice prevention strategy. Prevention programmes should have a degree of operational research and evaluation built into them, not least because the results of behavioural interventions are always going to vary. This is a result of local conditions much more than of treatments.

Funders may, therefore, choose to commission only the approaches which are validated by RCTs or the effectiveness reviews cited below. Lucas and Scott have argued that the approaches cited as most effective by such reviews should only be seen as the minimum contents of a package of prevention measures.4

Many hold the view that evaluating public health interventions requires a broad definition of evidence of effectiveness and a wide searching of the evidence base. This is, for example, the position of NICE (the National Institute for Health and Clinical Excellence) in the UK.

NICE is primarily known for its evaluation of biomedical treatments: it makes recommendations on whether the NHS should routinely provide a treatment after it has been licensed. In order to do this, NICE evaluates whether the treatment has sufficient added value compared to the current standard-of-care treatment, both in terms of cost and lives saved or improved.

However, NICE is also charged with developing broader guidelines for clinical practice and has, since 2005, been given an explicit public health remit to evaluate guidance and interventions designed to improve public health – which includes preventing HIV. It was only the second agency after the US Centers for Disease Control to be given such a task.

In 2010, Mike Kelly and colleagues from the Centre for Public Health Excellence, part of NICE, wrote a paper summarising why evidence of effectiveness for public health interventions needs to include not only a wide range of sources of evidence, but also to redefine what ‘evidence’ consists of in the case of a public health intervention.5

Traditionally, the strength of evidence for the effectiveness of interventions has been rated hierarchically, with randomised controlled trials at the top, followed by cohort studies, then cross-sectional studies, and case reports at the bottom.

Kelly and colleagues maintain that the ‘hierarchy of evidence’ approach does not work so well for public health. This is partly because there may be a lengthy chain of causation between the intervention and its intended effect, and because so many other variables may intervene that it may be difficult to prove that an intervention caused a specific result - or even design a trial to demonstrate it.

Also, whereas clinical interventions aimed at improving a single outcome are usually focused on individuals, public health interventions operate on two levels, influencing the health of both individuals and communities. Public health interventions may start as an intervention in society (e.g. the legalisation of homosexuality) and produce better health outcomes in individuals (e.g. through increased HIV testing), while others intended as individual interventions (e.g. safer-sex counselling) may have societal effects (e.g. greater acceptance of sexual diversity). Diseases and health inequalities happen both to individuals and within societies and it is important for public health practitioners to be clear about whether a given intervention is intended primarily as an agent of individual or social change, as this will influence what kind of outcome evidence (e.g. change in lifespan versus change in behaviour) is relevant.

Whereas clinical sciences operate inductively, using empirical evidence to disprove or refine hypotheses and only calling a body of hypotheses a ‘theory’ if there is the highest level of evidence to support a body of observations as causally connected, social sciences more often operate deductively, developing theories (of behaviour, economics, social development, etc.) drawn from existing observations and then testing them against further observations.

Kelly and colleagues identify that: a) a great deal of the literature on social theory is contained in textbooks and ‘grey literature’ that are missed out by conventional internet literature searches; and that b) the theoretical rigour and internal logical structure of a piece of HIV programming is a valid part of the evidence base, especially with types of intervention for which it is difficult to devise conventional tests of efficacy.

This means that, although refining our knowledge of what works in HIV-prevention programmes is essential to avoid wasteful and outdated approaches, lack of evidence of effectiveness should not be taken as evidence of lack of effectiveness, especially since it is intrinsically more difficult to gather evidence on the effectiveness of some interventions (such as mass-media campaigns) than it is on others (such as counselling).  While resource allocation must be judged according to the capacity of different elements of a prevention programme to exert the best possible effect on new infections, it may prove difficult to isolate the relative contribution of different components of a prevention strategy.

Meta-analyses are reviews which collect data from all the previous studies that meet predefined quality requirements. They can help us to judge which interventions will be most effective. However, these reviews are only as powerful as the original studies whose findings they analyse.

While many studies use outcome measures like condom use and unprotected sex acts, fewer use change in partner numbers or the incidence of sexually transmitted infections (STIs). Still fewer use the ultimate endpoint of HIV-prevention interventions – change in HIV incidence. This is largely because, even in a high-risk population, incidence, at a few per cent a year, is usually too small for anything other than a huge trial to be sufficiently powered to produce a statistically significant result. See ‘Measuring Effectiveness’ for more on outcome measures.

Currently available effectiveness reviews have another weakness. They do not tell commissioners or providers what sort of agency is best suited to carry out particular types of interventions. However, a number of meta-analyses have found that prevention programmes conducted at clinics often have a statistical edge.

A basic understanding of theories of behaviour change should underlie a particular intervention package, and a defined theoretical base has been found to be associated with efficacy in meta-analyses. For example, a community mobilisation approach proposed by a local health-promotion agency needs to be considered as an example of a social-diffusion intervention. What does social-diffusion theory in general tell us about the likely nature of the agents best placed to bring about change in a community or group? See Theoretical Models of Behaviour Change’, below, for more on this.


  1. Oakley A et al. Behavioural interventions for HIV/AIDS prevention. AIDS 9 pp479-486, 1995
  2. Fraser E How effective are effectiveness reviews? Health Education Journal 55: 359-362, 1996
  3. Cooper M The Facts are Friendly: what Research tells us about therapy. Therapy Today, 19(7), 2008
  4. Lucas G and Scott P Evidence and HIV Prevention Practice. Current HIV Education Research, HEA, 1997
  5. Kelly M et al. Evidence based public health: A review of the experience of the National Institute of Health and Clinical Excellence (NICE) of developing public health guidance in England. Social Science and Medicine, 71:1056-1062, 2010
This content was checked for accuracy at the time it was written. It may have been superseded by more recent developments. NAM recommends checking whether this is the most current information when making decisions that may affect your health.
Community Consensus Statement on Access to HIV Treatment and its Use for Prevention

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We can end HIV soon if people have equal access to HIV drugs as treatment and as PrEP, and have free choice over whether to take them.

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