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These analytic approaches do not address bias because bias assumes a misrepresentation of “truth” during collection or analysis of data. Qualitative researchers, on the other hand, tend to be guided by interpretivism, constructivism, critical theory or other perspectives that value subjectivity. This process is called deductive reasoning because it starts with a general theory that narrows to a hypothesis that is tested against observations that support (or refute) the theory. They conduct experiments that generate numerical data that define the extent to which an observation is “true.” The strength of the numerical data suggests whether the observation can be generalized beyond the study population. Quantitative researchers generate and test hypotheses to make conclusions about a theory they have developed. However, truth can be defined within a spectrum of probability. Post-positivists, unlike positivists, acknowledge that a singular truth is impossible to define. Generally, quantitative research is associated with post-positivism researchers seek to be objective and reduce their bias in order to ensure that their results are as close as possible to the truth. However, many experienced researchers on both sides of the line will tell you that these differences only go so far.ĭrawing on Chapter 1-1, there are different philosophies of science that inform researchers and their research products. And to some extent these approaches are different, in precisely the ways described. We contrast a reliance on words with a reliance on numbers, a focus on subjectivity with a focus on objectivity. Qualitative and quantitative research are often talked about as two different ways of thinking and generating knowledge.
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With a sigh of relief, Rayna reads through the attached papers (1-8) and continues her mission to craft a response. If you draft a response, I can help you wordsmith afterward. These are both good primers and will give you some language to help respond to this reviewer. and then read the one by Wright and colleagues. That said, I think we can build our field’s knowledge about qualitative research approaches by explaining some of these concepts. Don’t worry, it’s not a flaw in your study. We get these kinds of reviews all the time. Maybe the study won’t be valuable if the results aren’t generalizable! Reviewer 2 might be right that the sample size is too small! They immediately panic-email one of their co-authors:
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Rayna hadn’t seen any other qualitative studies talk about generalizability, so they weren’t entirely sure how to address this comment. Wouldn’t it be better to do a survey to get more perspectives?” The reviewer acknowledged that they came from a quantitative background, but then went on to write: “I am worried about the generalizability of this study, with a sample of only 25 residents.
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Most of the editor and reviewer comments had been relatively easy to handle, but when Rayna reached Reviewer 2’s comments, they were caught off guard.
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They had been recently invited to revise and resubmit their first qualitative research manuscript. Rayna (they/their) stared at the blinking cursor on her screen.