Читать книгу Practitioner's Guide to Using Research for Evidence-Informed Practice - Allen Rubin - Страница 59

Later in this chapter, we'll see that correlational studies rank relatively low on a research hierarchy for questions about effectiveness. We'll see that although they can have value in informing practice decisions about the selection of an intervention with the best chances of effectiveness, other designs rank higher. Experimental outcome studies, for example, rank much higher. But for questions about circumstances or attributes that best predict prognosis or risk, correlational studies are the most useful. With these studies, multivariate statistical procedures (statistics that account for multiple factors at once) can be employed to identify factors that best predict things we'd like to avoid or see happen.

Returning to the foster-care example discussed earlier, suppose you are a child welfare administrator or caseworker and want to minimize the odds of unsuccessful foster-care placements. One type of correlational study that you might find to be particularly useful would employ the case-control design. A study using this design to identify the factors that best predict whether foster-care placements will be successful or unsuccessful might proceed as follows:

1 It would define what case record information distinguishes successful from unsuccessful placements.

2 It would obtain a large and representative sample of foster-care placements depicted in case records.

3 It would then divide those cases into two groups: those in which the foster-care placement was successful and those in which it was unsuccessful.

4 It would enter all of the placement characteristics into a multivariate statistical analysis, seeking to identify which characteristics differed the most between the successful and unsuccessful placements (when all other factors are controlled) and thus best predicted success or failure.

If your previous research courses extolled the wonders of experiments, at this point you might exclaim, “Wait a minute! Why rank correlational studies above experiments here?” It's a good question, and we'll answer it with three others: Can you imagine the staff members of any child welfare agency permitting children to be assigned randomly to different types of foster placements? What would they say about the ethics and pragmatics of such an idea? What might they think of someone for even asking?

Correlational studies are not the only ones that can be useful in identifying factors that predict desirable or undesirable outcomes. Qualitative studies can be useful, too. For example, let's return to the question of why so many homeless people refuse to use shelter services. As is mentioned in Chapter 1, studies that employ in-depth, open-ended interviews of homeless people – or in which researchers themselves live on the streets among the homeless and experience what it's like to sleep in a shelter – can provide valuable insights as to what practitioners can do in designing a shelter program that might alleviate the resistance homeless people might have to utilizing the shelter.