Question

Nurse Feelgood conducted a study to discover the lived experience of parents whose unborn children undergo surgery while in utero. She wanted to obtain in-depth descriptions of their experiences.

1. How did she reduce the likelihood of introducing bias into the study?

            a. power analysis

            b. random sampling

            c. bracketing

            d. control of extraneous variables

2. Was a sample of 12 large enough to find significant differences?

            a. Yes. Sample sizes are small in these types of studies.

            b. No. The power of this study would be too low to find significance.

            c. This type of study does not look for significant differences.

3. What method did she use to analyze the data?

            a. coding

            b. t tests

            c. chi square

            d. Mann Whitney U

4. Are her findings generalizable to the larger population?

            a. Yes, if she used rigor in her methods.

            b. No, the sample size is too small.

            c. Findings are not generalizable in this type of research.

Please explain all the answers as why that is correct and others are incorrect

Answer 1

1) Bracketing is the best method to reduce the likelihood of introducing bias in the study. Bracketing is a scientific process where a researcher suspends or holds in abeyance his or her presuppositions, biases, assumptions, theories, or previous experiences. This will help the researcher maintain a neutral view as and when the parents share their experiences.

As with reference to other methods we have:

Random sampling is a way of selecting a sample of observations from a population in order to make inferences about the population. It helps to find data that can be representative of the population however, the resultant impact on bias is not much.

Extraneous variables are unwanted factors in a study that, if not accounted for, could negatively affect (i.e. confound) the data subsequently collected. Controlling them improve the quality of the study but does not affect the introduction of bias in the study.

Power analysis is normally conducted before the data collection. The main purpose underlying power analysis is to help the researcher to determine the smallest sample size that is suitable to detect the effect of a given test at the desired level of significance. This has no effect on reducing the likelihood of bias.

2) The researcher wants in depth descriptions of the experiences of the parents. In such a case there is no quantifiable data that is being examined. The research is more on the lines of the qualitative study.

The objective of qualitative research is to lessen discovery failure. As qualitative research works to obtain diverse opinions from a sample size, saturated data does not serve to do anything. One respondent’s opinion is enough to generate a code, part of the analysis framework.

So in such a study a sample as small as 10 is also sufficient to conduct the study and derive inferences. It all depends on the level of responses and the quality of data that is being used.

3) She would coding to analyze the data since the entire data will be qualitative and it will be difficult to perform any of the other quantitative methods such as t tests and mann whitney U test or the chi square test to analyze the data.

4) No the findings of her research are not generalizable to the larger population, since the research takes into account the indepth descriptions of the experiences of the parents whose children underwent surgery while in utero. Such accounts are highly personal and the study cannot implicate whether these experiences are something that can be generalized to the larger population as the entire study is qualitative and there is no quantitative nature to it.