Introduction
In any academic study, there are inevitably going to be limitations to the study that have to be taken into account when evaluating the results of the study. The authors are supposed to build these limitations into their conclusions, but if they do not then the reader must. Therefore, it is important to understand what the limitations of any given study are, and how they might have influenced the results.
Britz & Dunn
Britz & Dunn (2009) studied the relationship between self-care and quality of life. The authors begin with the hypothesis that decreased quality of life among patients with heart failure arise from self-care deficits. In other words, if people don't look after themselves the don't do as well. So, rocket science, but okay.
The limitation of this study are listed by the authors as having a small sample size and the potential homogeneity of the sample. These two limitations can influence the ability of a researcher to extrapolate these results across a wider population. A small samples size can reduce the reliability of the results. Homogeneity of the subjects makes the findings less reliable across a wider population, because in that case the sample is not representative of the entire population. The sample can still be representative of a population, just not the broadest segment; it would still be representative of members of that particular in-group.
The authors posit that there is another limitation. However, they are poor writers and cannot actually explain in clear language what this limitation is. Terms like "low reliabilities" and "subscale alphas" are used to describe the limitation, but those words have no meaning unless given context, which they are not. Extra credit for the five dollar word "coefficient" and for referencing a Greek letter. Writing rambling gobbledegook is less a limitation of the study than of the authors themselves, who with such purple prose cast doubt as to their knowledge of the subject matter. If they knew what they were talking about, they would be able to express their ideas clearly and simply, rather than hiding behind a blizzard of academic buzzwords.
The study was conducted with a convenience sample from a single hospital. They made a point to exclude patients from facilities where they receive care, to isolate patients who were responsible for self-care. The patients...
The interviews were then subject to evaluation by the researchers. The qualitative inputs were pumped into SPSS, yet interestingly the authors don't bother to explain how they coded the qualitative answers to fit into statistical software. Each answer would have to have been converted into a number to be subject to statistical analysis, yet there is nothing in the paper that describes this process.
The data analysis procedure is thus missing a fairly important gap. If the researchers have interviews, and then they skip directly to an explanation of the statistics that they got from SPSS, that leaves out a rather important step. While we're on the subject of limitations, this isn't necessarily a limitation in the study but it is one in the paper because it puts the reader in a position of not being able to verify the results. A sound paper has to be vetted by people other than the authors – the reader has to be able to read the paper and know exactly how the authors reached their conclusions. The omission of the how the authors translated interviews into statistics did not go unnoticed.
Tang et al
Tang et al (2014) examine the role of depression in medication adherence. The basic principle is that medication adherence is correlated with health outcomes for heart failure patients. Thus, it is worth investigating potential risk factors for lack of medication adherence. Interestingly, the hypothesis of the study was that depression is associated with lower self-reported medication adherence than objectively measured medication adherence. Whatever the merits of that study might be – what people report doesn't matter in terms of health outcomes, what matters is what they do. Barking up the wrong tree aside, let's take a look at the limitations of the study.
The authors argue that one limitation of the study was the exclusion of severely depressed individuals. They offered up a pretty flimsy excuse for this, which is weird, because there's a good one to be had – that there is a significant difference between the severely depressed and more mild forms of depression. Some examination of the research would probably show that there are differences between different levels of depression that can affect things like taking medication – it's hard to imagine why the authors passed up the opportunity…
