Violence against women remains prevalent in the United States. In 2010, six out of every 1,000 women[1] experienced intimate partner violence (IPV; sometimes referred to as "domestic violence"), and two out of every 1,000 women were raped or sexually assaulted.[2]
Victims need careful and often intensive services to help address their physical, emotional and financial suffering. To that end, the federal government funds a variety of programs that provide victims with transitional housing, legal aid, counseling, job training and other assistance. But in recent years, funding for these programs has declined. For example, in 2013, the Violence Against Women Act (VAWA) — which covers not only victims' services but also research, batterer interventions and criminal justice capacity building — received $388 million, down from $412.5 million in 2012. According to the National Network to End Domestic Violence, shrinking budgets have caused service providers to close victims' shelters, reduce programming hours and cut program staff.[3]
Given the strain on funding, it is critical that the programs that do receive money effectively increase safety, increase victims' knowledge of and confidence in legal options, and help them recover from victimization. Yet few programs to date have been evaluated using rigorous research designs and systematic study. Fewer than half of 18 seminal studies on IPV victims' services employed a randomized controlled trial (RCT), generally thought to be the strongest method for establishing whether a program is effective.[4] As we move forward, more efforts should be made to use rigorous research methods like RCTs when evaluating victims' services programs.
Prior Research
NIJ has supported efforts to understand violence against women, including preventing this type of violence and helping women to recover. NIJ has a long history of funding research on:
- Protection orders
- Policy and legislation
- Victim services and advocacy
- Risk factors for homicide and serious injury
- Evaluations of grants funded under VAWA
Program evaluations help inform policy and strategies to improve the lives of victims. To date, evaluations of victims' services in the IPV field generally have focused on advocacy programs that connect women to legal, financial and emotional support. These studies tend to show positive results: Women participating in advocacy programs are more likely to be involved in legal proceedings and have better success in obtaining resources and support.[5]
Another important branch of IPV research has focused on counseling services; studies have generally found that receiving counseling helps women build better self-esteem, assertiveness, social support, coping and self-efficacy.[6] There have also been evaluations on multidisciplinary responses to sexual assault, specifically Sexual Assault Nurse Examiner (SANE) programs. These studies indicate that SANE programs result in more cases reaching the final stages of prosecution; for example, such programs increase the likelihood of a guilty plea and conviction.[7] Finally, research has shown that shelters are one of the most important and effective services for abused women.[8] Although these findings are all promising, their "certainty" may be diminished if evaluations of the programs' effectiveness failed to use an experimental research design.
Overall, the use of strong methods to evaluate victims' services programs is wanting. In a 2009 review that examined 18 intervention studies for victims of IPV, only three of the studies qualified as rigorous based on three criteria:
- Random assignment of participants to a treatment group (i.e., individuals receiving the intervention) or a control group (i.e., individuals receiving "business as usual")
- At least 20 cases included in each group
- An outcome of IPV recidivism or violence severity[9]
Most studies to date do not account for inherent differences between participants who receive services and those who do not. This means that any benefits attributed to receiving treatment may not be due to the program itself but instead may be due to a characteristic that treatment participants share — for example, being highly motivated to receive services or having more social support encouraging them to seek services. When we evaluate programs using methods that account for this kind of "selection bias" — for example, through random assignment to groups — we might find that the programs are not as effective as once thought.
When looking at the most frequently cited studies in the IPV literature, we find that with the exception of a select few, most of the studies used a quasi-experimental design (QED) at best — that is, a design that compares a treatment group to a control group but in which researchers cannot control who is assigned to which group (more information on QED is provided below). These studies do not explain with certainty whether the treatment provided directly relates to the positive outcomes. These studies cannot say that the comparison groups are truly equivalent prior to treatment, so we are left guessing whether the effect seen is due to something other than the interventions.
See "Prior Research on Intimate Partner Violence Victims' Services"
QED methods are incredibly beneficial and often demonstrate strong correlational links between interventions and positive outcomes. However, service providers can better argue that a program works if its evaluation uses RCT methods, because they better account for differences in groups and thereby increase confidence that the outcome is due to the program.
Understanding Research Designs
The desire to improve services for victims should serve as the driving force behind the choice of a research design. In other words, we should craft research that will provide the most accurate and usable information. However, the choice of a research design must also consider the fiscal resources available to agencies and researchers as well as their capacity to carry out the research design.
Generally, RCTs are thought to be the best method for increasing the accuracy of study results because they require a comparison between a treatment group and a control group. Participants are randomly assigned to the treatment group, thus allowing researchers to balance out certain pre-existing characteristics — for example, motivation to seek treatment — or reduce their impact so that the researchers can evaluate the program more clearly.
Here's an example: An IPV services agency begins a counseling program for battered women. The agency conducts an evaluation that compares outcomes for women who volunteered for counseling with outcomes for women who declined counseling and finds that counseling improves client self-esteem and quality of life. In this example, it is easy to see that increased self-esteem and quality of life might be due to the client's desire to better herself and seek social support — and not to the program itself. On the other hand, if the agency recruits women who are interested in counseling and then randomly assigns them to either counseling or treatment-as-usual conditions, the finding that the counseling group experienced better outcomes is more clearly related to the program and not necessarily to motivation.
RCTs are not without their own limitations, however. Many practitioners and researchers alike argue that RCTs are too simplistic and verge on artificiality — that is, they may not account for the way that certain individual characteristics or environments make the treatment more or less effective.[10] An important question, then, is how well a program implemented under "optimal conditions" — that is, under careful scrutiny during an RCT — will work when implemented in the real world. Researchers should demonstrate not only that the program is effective during the research phase but also that ground-level service providers can implement the program with fidelity.[11]
It also may be problematic to assume that randomization creates unbiased treatment and control groups. Even in these types of experiments, it is important to know who the individuals are who make up the sample and whether differences exist between the groups despite randomization. Similarly, randomization does not correct for volunteer bias in the sample as a whole. In other words, even if there are no differences among people in the treatment and control groups, there may be differences among people participating in the study and those who do not.[12]
Some situations might render an RCT design inappropriate. For example, another research design might be better at encouraging participation and, therefore, might produce results that more accurately represent the population of interest as a whole.[13] This is particularly important in the IPV field, as these victims might be particularly reluctant to have any form of information collected, no matter how many assurances of confidentiality are provided.
In other cases, program staff might be highly resistant to randomization despite the researchers' best efforts to allay concerns, or the cost and resources involved in a full randomization might be prohibitive. In these cases, alternative methods such as QEDs might be available that allow researchers to manipulate the data and sampling to simulate treatment and control groups. Some argue that QEDs might even be more desirable than RCTs because researchers must be more deliberate about how comparisons are made.[14] In this article, we argue that RCTs are the best method for establishing causality, but it is worth noting that QEDs can make a valuable contribution when random assignment is not feasible.
See "Practitioner and Researcher Concerns About RCTs"
One example of a QED is the use of "nonequivalent control groups." In this method, researchers compare participants who receive treatment to those who do not, but they do not randomly assign participants to the groups. Instead, the researchers attempt to ensure that the groups are as similar as possible before the intervention begins. This can be done in IPV studies, for example, by comparing individuals who, prior to the evaluation, had similar risk for revictimization.
Another strategy is a "time-series" design. Researchers collect data for several time points prior to the treatment being introduced and for a long follow-up period to determine how incidences of victimization changed after the intervention was put into place. Having data on longer periods of time helps ensure that the intervention's effect is real and that any changes in victimization are not due to temporary fluctuations.
No matter which research method is used, researchers must always explain the reasons for their decision, be aware of any limitations that might arise from the use of that method, and understand how these limitations affect the results and the interpretation of the results. When RCTs are not feasible due to ethical concerns, costs, buy-in or other reasons, QEDs serve as an alternative that can increase the credibility of the results when compared with most non-experimental evaluations.
Of course, like RCTs, QEDs have their own limitations and might not always be appropriate for the research questions. Table 1 compares how well RCTs and QEDs establish that the intervention directly causes changes in relevant outcomes. Both methods can determine that an association exists between the program and the outcomes as well as ensure that the intervention precedes the outcome of interest (i.e., the designs establish accurate time-ordering). However, QEDs are less successful at ruling out alternative explanations for the results.
Randomized Controlled Trials | Quasi-Experimental Designs | |
---|---|---|
Can the research method establish an association between the intervention and the outcomes? | Yes. One can determine whether an individual's treatment status is related to changes in the outcome. | Yes. One can determine whether an individual's treatment status is related to changes in the outcome. |
Can the research method establish that the treatment preceded the desired outcome? | Yes. The outcome is measured after the treatment is implemented. | Yes. Generally, there are assessments prior to and after treatment implementation. |
Can the research method rule out other explanations? | Yes. Randomization helps ensure that the treatment and control groups are equivalent on both observed and unobserved variables. | No. Although matching ensures balance on observed variables, differences might exist that are not measured. With time-series designs, there might be historical events that impact the respondents, or respondents might change their attitudes or behaviors naturally over time. |
Encouraging the Use of More Rigorous Designs
The best program evaluations will use the most rigorous method possible to successfully gather evidence about a program's effect. When deciding which method is appropriate, researchers and practitioners should consider the benefits and the limitations of RCTs. However, even given the method's limitations, it is important that we do not dismiss RCTs without strong reasons for doing so. Randomization and the use of a control group generally enhance the accuracy of research findings. Furthermore, funding agencies increasingly prioritize rigorous methods, as these agencies attempt to show that public money is being used efficiently.
So how do we mitigate the concerns of both practitioners and researchers and encourage the use of RCTs?
- Establish a strong researcher-practitioner relationship: Practitioners often have strong opinions about whether a program works and whether a client needs the program (as well as potential safety concerns should the client not receive the intervention). Researchers must be ready to explain why an RCT is the best method by which to study a program and should work with practitioners to resolve any concerns about safety or nontreatment. Some research suggests that conducting an RCT soon after a program's development — that is, before practitioners establish expectations about a program's success — might be beneficial.[15]
Practitioner staff might want to override an assignment of an individual to the control group, perhaps because of potential safety concerns. In these cases, establishing a procedure where such overrides can take place with the approval of upper-level management might be necessary.[16] Alternatively, the pool of an agency's clients who are chosen for randomization might be those who are less at risk than the clientele of the agency in general — many RCTs in the IPV realm draw only from misdemeanor cases.[17]
In addition, it is often difficult to recruit clients to enroll and remain in the program for its duration; working closely with program staff can make this process much easier. Practitioners and researchers should work together to develop methods to increase safety (for example, by ensuring that no participant can be identified in the data) and to encourage clients to remain involved in the program while the evaluation is being conducted. - Link funding to research designs: A constant concern for agencies and organizations is the availability of resources. RCTs are time-intensive and at times can cost more money than alternative research methods for a variety of reasons, including the amount of training required. External funders, such as NIJ, must emphasize the desirability of RCTs and widely disseminate examples of such rigorous studies. When applying for funds, programs and researchers should make sure that they carefully calculate the resources necessary to implement the design accurately. And if RCTs show that a program has no effect, then funding should focus on alternative program development and evaluation.[18]
By using more rigorous research methods like RCTs, we can increase confidence in evaluation findings. In doing so, service providers will be better positioned to find funding for programs and to encourage clients to seek out life-enhancing resources.
About This Article
This article appeared in NIJ Journal Issue No. 274, October 2014.