Implementation science is the study of factors that influence the full and effective use of innovations in practice (Blase, Van Dyke, Fixsen, & Wallace Bailey, 2012). Implementation science independent variables are produced on purpose so their predicted effects can be evaluated in practice in attempts to test hypotheses derived from implementation theory.
Implementation science is advanced when independent variables are produced on purpose so their predicted effects can be evaluated in practice in attempts to test hypotheses derived from implementation theory.
Research sometimes is confused with science. Research can be done in support of science where predictions and hypotheses are tested to challenge and advance theory. Research also can be done to satisfy one’s curiosity or test an idea or survey what individuals think or believe. Thus, research evidence may not have anything to do with implementation science no matter what the title of an article may say. Implementation science, like any science, is based on predictions and hypotheses that are tested in research. The results of research strengthen implementation theory and practice and sharpen and extend the next round of prediction and hypothesis testing.
In physics, chemistry, biology, and other “hard sciences” scientists can study natural phenomena that exist everywhere (e.g. every living thing has chromosomes that can be studied at any time; chemical elements already exist and are waiting to be observed). The independent variable already exists in nature. In the so-called “soft sciences” things are much more difficult: the independent variable must be produced by the scientist. Unlike waiting for an expected solar eclipse to produce an independent variable for study, implementation scientists cannot wait for an expert implementation team (a postulated implementation independent variable) to form and begin to function then assess the outcomes. This may never happen in any predictable and assessable way.
This is an important distinction because implementation scientists must be able to produce the independent variable on demand (if this) so that predictions of its effects can be measured (then that). The independent variable in implementation science is an invention and, given this, the requirements for conducting “soft-science” increases in complexity.
What is science in the context of implementation research? If prediction is the foundation of science and theory is the source of predictions and prediction testing improves implementation theory, then …
What is the database for implementation science? A review of the implementation evaluation literature located relevant data from a wide variety of domains. A synthesis of the findings produced a draft of frameworks to make sense of the lists of variable identified as potentially potent for further use and study.