Читать книгу Practitioner's Guide to Using Research for Evidence-Informed Practice - Allen Rubin - Страница 18

Suppose you work in a Big Brother/Big Sister agency and are concerned about the high rate of mentor-youth matches that end prematurely. A helpful study might analyze case-record data in a large sample of Big Brother/Big Sister agencies and assess the relationships between duration of mentor-youth match and the following mentor characteristics: age, race, ethnicity, socioeconomic status, family obligations, residential mobility, reasons for volunteering, benefits expected from volunteering, amount and type of volunteer orientation received, and so on. Knowing which factors are most strongly related to the duration of a match (whether long or short) can inform your decisions about how to improve the duration of matches. For example, suppose you find that when taking into consideration lots of different factors, the longest matches are those in which the youth and mentor are of the same race and ethnicity. Based on what you learn, you may decide more volunteers who share the same ethnicity as the youth being served are needed, efforts to match existing volunteers and youth based on race and ethnicity should be implemented, or (evidence-informed) training in culturally sensitively mentoring should be provided to mentors.

Suppose you are a child welfare administrator or caseworker and want to minimize the odds of unsuccessful foster-care placements, such as placements that are short-lived, that subject children to further abuse or that exacerbate their attachment problems. Your EIP question might be: “What factors best distinguish between successful and unsuccessful foster-care placements?” The type of research evidence you would seek to answer your question (and thus inform practice decisions about placing children in foster care) likely would come from case-control studies and other forms of correlational studies that are discussed in Chapter 9 of this book.

A child welfare administrator might also be concerned about the high rate of turnover among direct-service practitioners in the agency, and thus might pose the following EIP question: “What factors best predict turnover among child welfare direct-care providers?” For example, is it best to hire providers who have completed specialized training programs in child welfare or taken electives in it? Or will such employees have such idealistic expectations that they will be more likely to experience burnout and turnover when they experience the disparity between their ideals and service realities of the bureaucracy? Quite a few studies have been done addressing these questions, and as an evidence-informed practitioner, you would want to know about them.