Bayesian Analysis for Evidence-Based Practice in Social Work (Research Note) (Report) - Social Work Research

Bayesian Analysis for Evidence-Based Practice in Social Work (Research Note) (Report)

By Social Work Research

  • Release Date - Published: 2011-03-01
  • Book Genre: Social Science
  • Author: Social Work Research
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Bayesian Analysis for Evidence-Based Practice in Social Work (Research Note) (Report) Social Work Research read online review & book description:

As evidence-based practice (EBP) continues gaining prominence in the professional literature, at least two overlapping challenges make it difficult for mainstream social workers to accept EBP as the primary mode for practice. Social workers need a robust pool of intervention research on which to base practice decisions. The research must remain current; be well formulated, for instance, conforming to the Consolidated Standards of ReportingTrials guidelines (the gold standard for reporting clear, transparent, and sufficiently detailed conference abstracts and journal articles); and be focused on ascertaining the most appropriate interventions that attain the desired outcomes for specific clients with specific problems (Hopewell et al., 2008; Thyer, 2001). Social workers also need research that values knowledge derived from clinical expertise or practice wisdom. Any apprehension social workers have with adopting the kind of transparent EBP put forward by Gambrill (2007) may be attributed in part to the lack of appreciation for practice wisdom that is hard to observe and quantify as a valid source of evidence. Over the past few years, other professions have found Bayesian analysis useful across many disciplines where data collection is difficult or expensive, most notably medicine and pharmacology. The application of Bayesian analysis to adaptive designs in clinical trials has allowed trials to stop sooner, thus getting patients on an effective medicine or off of a harmful medicine much faster than in the past (see, for instance, Giles et al., 2003, and Krams, Lees, Hacke, & Grieve, 2003).

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