CONSIDERATION #3 The sampling strategy that you select
The sampling strategy that you are following can raise a number of ethical issues that must be understood and overcome. When thinking about the impact of sampling strategies on research ethics, you need to take into account: (a) the sampling techniques that you use; (b) the sample size you select; and (c) the role of
gatekeepers that influence access to your sample:
When sampling, you need to decide what units (i.e., what people, organisations, data, etc.) to include in your sample and which ones to exclude. As you'll know by now, sampling techniques act as a guide to help you select these units, and you will have chosen a specific probability or non-probability sampling
technique:
If you are following a probability sampling technique, you'll know that you require a list of the population from which you select units for your sample. This raises potential data protection and confidentiality issues because units in the list (i.e., when people are your units) will not necessarily have given you permission to access the list with their details. Therefore, you need to check that you have the right to access the list in
the first place.
If using a non-probability sampling technique, you need to ask yourself whether you are including or excluding units for theoretical or practical reasons. In the case of purposive sampling, the choice of which units to include and exclude is theoretically-driven. In such cases, there are few ethical concerns. However, where units are included or excluded for practical reasons, such as ease of
access or personal preferences (e.g., convenience sampling), there is a danger that units will be excluded unnecessarily. For example, it is not uncommon when select units using convenience sampling that researchers' natural preferences (and even prejudices) will influence the selection process. For example, maybe the researcher would avoid approaching certain groups (e.g., socially marginalised individuals, people who speak little English, disabled people, etc.). Where this
happens, it raises ethical issues because the picture being built through the research can be excessively narrow, and arguably, unethically narrow. This highlights the importance of using theory to determine the creation of samples when using non-probability sampling techniques rather than practical reasons, whenever possible.
Sample size
Whether you are using a probability sampling or non-probability sampling technique to help you create
your sample, you will need to decide how large your sample should be (i.e., your sample size). Your sample size becomes an ethical issue for two reasons: (a) over-sized samples and (b) under-sized samples.
Over-sized samples
A sample is over-sized when there are more units (e.g., people, organisations) in the sample than are needed to achieve you goals (i.e., to answer your research questions robustly).
An over-sized sample is considered to be an ethical issue because it potentially exposes an excessive number of people (or other units) to your research. Let's look at where this may or may not be a problem:
Not an ethical issue Imagine that you were interested in the career choices of students at your university, and you were only asking students to complete a questionnaire taking no more than 10 minutes, all an
over-sized sample would have done was waste a little of the students' time. Whilst you don't want to be wasting peoples' time, and should try and avoid doing so, this is not a major ethical issue.
A potential ethical issue Imagine that you were interested in the effect of a carbohydrate free diet on the concentration levels of female university students in the classroom. You know that carbohydrate free diets (i.e., no breads,
pasta, rice, etc.) are a new fad amongst female university students because some female students feel that it helps them loose weight (or not put weight on). However, you have read some research showing that such diets can make people feel lethargic (i.e., low on energy). Therefore, you want to know whether this is affecting students' performance; or more specifically, the concentration levels of female students in the classroom. You decide to conduct an experiment where you measure
concentration levels amongst 40 female students that are not on any specific diet. First, you measure their concentration levels. Then, you ask 20 of the students to go on a carbohydrate free diet and whilst the remaining 20 continue with the normal food consumption. After a period of time (e.g., 14 days), you measure the concentration levels of all 40 students to compare any differences between the two groups (i.e., the normal group and the group on the carbohydrate free diet). You find that
the carbohydrate free diet did significantly impact on the concentration levels of the 20 students. So here comes the ethical issue: What if you could have come to the same conclusion with fewer students? What if you only needed to ask 10 students to go on the carbohydrate free diet rather than 20? Would this have meant that the performance of 10 students would not have been negatively for a 14 day period as a result? The important point is that you do not want to expose individuals to distress
or harm unnecessarily.
Under-sized samples
A sample is under-sized when you are unable to achieve your goals (i.e., to answer your research questions robustly) because you insufficient units in your sample. The important point is that you fail to answer your research questions not because a potential answer did not exist, but because your sample size was too small for such an answer to be discovered (or
interpreted). Let's look where this may or may not be a problem:
Not an ethical issue Let's take the example of the career choices of students at your university. If you did not collect sufficient data; that is, you did not ask enough students to complete your questionnaire, the answers you get back from your sample may not be representative of the population of all students at your university.
This is bad from two perspectives, but only one is arguably a potential ethical issue: First, it is bad because your dissertation findings will be of a lower quality; they will not reflect the population of all students at the university that you are interested in, which will most likely lead to a lower mark (i.e., external validity is an important goal of quantitative research). This is bad for you, but not necessarily unethical. However, if the findings from your research are
incorrectly taken to reflect the views of all students at your university, and somehow wrongly influence policy within the university (e.g., amongst the Career Advisory Service), your dissertation research could have negatively impacted other students. This is a potential ethical issue. Despite this, we would expect that the likelihood of this happening is fairly low.
A potential ethical issue Going back to the example of the effect of a carbohydrate free
diet on the concentration levels of female university students in the classroom, an under-sized sample does pose potential ethical issues. After all, with the exception of students that just want to help you out, it is likely that most students are taking part voluntarily because they want to the effect of such a diet on their potential classroom performance. Perhaps they have used the diet before or are thinking about using the diet. Alternately, perhaps they are
worried about the effects of such diets, and what to further research in this area. In either case, if no conclusions can be made or the findings are not statistically significant because the sample size was too small, the effort, and potential distress and harm that these volunteers put themselves through was all in vein (i.e., completely wasted). This is where an under-sized sample can become an ethical issue.
As a researcher, even when you're an undergraduate or master's
level student, you have a duty not to expose an excessive number of people to unnecessary distress or harm. This is one of the basic principles of research ethics. At the same time, you have a duty not to fail to achieve what you set out to achieve. This is not just a duty to yourself or the sponsors of your dissertation (if you have any), but more importantly, to the people that take part in your research (i.e., your sample). To try and
minimise the potential ethical issues that come with over-sized and under-sized samples, there are instances where you can make sample size calculations to estimate the required sample size to achieve your goals.
Gatekeepers
Gatekeepers can often control access to the participants you are interested in (e.g., a manager's control over access to employees within an organisation). This has ethical implications because
of the power that such gatekeepers can exercise over those individuals. For example, they may control what access is (and is not) granted to which individuals, coerce individuals into taking part in your research, and influence the nature of responses. This may affect the level of consent that a participant gives (or is believed to have given) you. Ask yourself: Do I think that participants are taking part voluntarily? How did the way that I gained access to participants affect
not only the voluntary nature of individuals? participation, and how will it affect the data?
Problems with gatekeepers can also affect the representativeness of the sample. Whilst qualitative research designs are more likely to use non-probability sampling techniques, even quantitative research designs that use probability sampling can suffer from issues of reliability associated with gatekeepers. In the case of quantitative research designs using
probability sampling, are gatekeepers providing an accurate list of the population without missing out potential participants (e.g., employees that may give a negative view of an organisation)? If non-probability sampling is being used, are gatekeepers coercing participants to take part or influencing their responses?
Final thoughts
Before moving on to
STEP SEVEN: Data analysis techniques, make sure that you have taken into account: (a) your dissertation and university ethics guidelines; (b) your chosen research method, the way that the research method is used, and the specific measures that are selected; and (c) your chosen sampling strategy, including the type of sampling technique used, your sample size,
and the use of gatekeepers when selecting your sample. On this basis, assess whether you think you will need to get ethical approval for your dissertation research (something we address in STAGE SEVEN: Assessment point).
Which of the following should be considered when determining sample size?
Which of the following should be considered when determining sample size? The number of variables the researcher is interested in.
What are the things to consider in selecting the samples or respondents?
The essential topics related to the selection of participants for a health research are: 1) whether to work with samples or include the whole reference population in the study (census); 2) the sample basis; 3) the sampling process and 4) the potential effects nonrespondents might have on study results.
What factors should be considered when determining the sample size for a qualitative study?
In general, three or four factors must be known or estimated to calculate sample size: (1) the effect size (usually the difference between 2 groups); (2) the population standard deviation (for continuous data); (3) the desired power of the experiment to detect the postulated effect; and (4) the significance level.
What are the factors that determine the size of a sample quizlet?
Three items required to calculate the proper sample size for a survey..
the variability believed to be in the population..
the acceptable margin of sample error..
the level of confidence required in your estimates of the population values..
