Literature DB >> 29719989

Challenges Facing Evidence-Based Prevention: Incorporating an Abductive Theory of Method.

W Alex Mason1, Jasney Cogua-Lopez1, Charles B Fleming2, Lawrence M Scheier3.   

Abstract

Current systems used to determine whether prevention programs are "evidence-based" rely on the logic of deductive reasoning. This reliance has fostered implementation of strategies with explicitly stated evaluation criteria used to gauge program validity and suitability for dissemination. Frequently, investigators resort to the randomized controlled trial (RCT) combined with null hypothesis significance testing (NHST) as a means to rule out competing hypotheses and determine whether an intervention works. The RCT design has achieved success across numerous disciplines but is not without limitations. We outline several issues that question allegiance to the RCT, NHST, and the hypothetico-deductive method of scientific inquiry. We also discuss three challenges to the status of program evaluation including reproducibility, generalizability, and credibility of findings. As an alternative, we posit that extending current program evaluation criteria with principles drawn from an abductive theory of method (ATOM) can strengthen our ability to address these challenges and advance studies of drug prevention. Abductive reasoning involves working from observed phenomena to the generation of alternative explanations for the phenomena and comparing the alternatives to select the best possible explanation. We conclude that an ATOM can help increase the influence and impact of evidence-based prevention for population benefit.

Keywords:  abductive inference; evidence-based prevention; generalizability; methodology; randomized controlled trial; reproducibility

Mesh:

Year:  2018        PMID: 29719989     DOI: 10.1177/0163278718772879

Source DB:  PubMed          Journal:  Eval Health Prof        ISSN: 0163-2787            Impact factor:   2.651


  1 in total

1.  Parenting interventions for families with refugee backgrounds: a randomized factorial, mixed-methods design study protocol.

Authors:  Joshua Patras; Merete Saus; Marcela Douglas; Ragnhild Bjørknes; Siri Gammelsæter; Lene-Mari Potulski Rasmussen; Therese Halvorsen; Ida Mari Haug; Ragnhild Risholm; Tuva Øktedalen; Reidar Jakobsen; Simon Peter Neumer
Journal:  Trials       Date:  2021-11-11       Impact factor: 2.279

  1 in total

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