Interpreting a Qualitative Research Paper

Original Editor - Mariam Hashem

Top Contributors - Mariam Hashem, Kim Jackson, Ewa Jaraczewska, Mandy Roscher and Tarina van der Stockt  

Introduction

Interpreting a qualitative research paper is an analysis of the quality of the material between your hands. It allows you to understand the reliability of the research and the construction of the paper.

CASP checklist

CASP stands for the critical appraisal skills programme. The CASP offers free downloadable checklists that help in critiquing research papers.

It is formed of ten questions.

Section A, and it looks at the validity of the study results. This can be subjective as these studies don't have statistical significance instead there is a heavy reliance on the essence of the qualitative research by critically appraise and reflect on the methods and the design of the research.

Section B looks at the findings or the results of the study.

Section C is concerned with the applicability of the results.

Analysing the qualitative research, think about these questions:

• Is there a clear statement of the aims of the study?
• What are the goals of the study?
• What was the rationale for this research?
• How relevant is this?
• Is the research question clearly formulated? Is it important?

A-The research introduction should give the context and reflect the importance of the research question leading up to the rationale of the research. It should also discuss the gap in the area that's been researched with the angle of focus. Previous research should also be discussed and a highlight on similarities and limitations to explain why this research should take place and it's significant to find answers,

B- Analysis of the qualitative research methods and the used approach. Is it appropriate for the questions? is a qualitative approach appropriate? Qualitative methods are used when illuminating some actions or subjective experiences of participants or looking to gain an in-depth understanding of a phenomenon.

C- Reflecting on the study design and whether it's appropriate for the research question or not. For example, using ethnography would be an appropriate design when studying a particular cultural group.

D- Analysing the recruitment strategy. For example, exploring the experience of rural dwelling, older adults in communicating with family members during the COVID pandemic. Recruiting participants through social media and using the snowballing technique is a good way to encourage a large sector of participants but using it a the sole recruitment strategy could dismiss or potentially exclude people who aren't good with using technology or those who haven't used technology to communicate with their families.

E- The sampling strategy. Are the inclusion and exclusion criteria clear and purposeful to recruit specific participants who the interesting subject of the research? Also, think if the sampling was probably quite inclusive and left any cohorts out?

F-The data collection method. Looking into the methods used in the research whether they were justified to meet the criteria of the research question and does it match the subject of research? are the methods varied enough to give participants choice? Also, analysing the way the authors used and documented the methods. For example, if interviews were used to collect data, we should be looking into was the interview structured? Was it semi-structured? Or was it unstructured? And why was that? so the details of the method and the rationale that justifies the use and the application of the method.

G-Data saturation. In qualitative research, particularly if it's interviews or focus groups, data saturation is the point at which new information or themes stop to emerge when the data set is saturated.

Data saturation and sample sizes in qualitative research are under-reported sometimes. Sample sizes, can often not be justified very well in qualitative research. So, for example, if it's an interpretive phenomenological analysis looking into in-depth analysis usually involves a smaller sample size.

If data saturation isn't mentioned in the qualitative paper, it could prompt to ask or query the validity of the results because I don't know for certain that there wouldn't have been any other themes that emerged or any contradicting viewpoints or sub-themes that could have emerged.

This could be challenging for researchers when writing the research protocol and determining the sample size at the stage when data saturation is still unknown at which number of participants and it needs to be monitored and reported.

H- Looking at the validity of the findings and any conflict of interest and the relationship between the researcher and the participants as this might influence the results. Looking at factors that might reflect bias in the viewpoints of the researcher, the data collection method that is known as reflexivity. Reflexivity is essentially self-awareness when a researcher reflects on their own position within the research and they consider their own biases. And importantly, when they make it fairly clear and explicit in the research paper of potential biases that they may have. COREQ is a checklist of the criteria for reporting qualitative research. It is for authors to check and tick off when writing qualitative research where there is a whole section dedicated to reflexivity and the research team and their relationships and their own self-awareness.

Section B is around the results. What are they? There are questions in the checklist to think about:

1-Ethical considerations. Mainly looking into the details of recruitment and involving participants and whether ethical standards were maintained and kept. For example, does it talk about informed consent? Do the authors talk about a participant information leaflet? Do they talk about an opportunity for participants to pose any questions? Also looking into whether the authors discussed any particular issues raised by the study, for example, the effects of the study and how they were handled particularly when a sensitive topic is explored. How did they handle participants becoming distressed or experienced discomfort?

2- Clarity and transparency of data analysis. The steps that were taken into the process and making sure they weren't biased. Looking into the in-depth description of the analysis process? Types of analysis,

The data that is presented, how was it selected from the original sample? To demonstrate the analysis process. Is there enough data to support the findings? So, for example, if we have a theme and I say that most men with prostate cancer reported fear of recurrence around their condition. But I only give one quote to support that. Is that enough? You usually need to have sufficient data, within reason. You also need to consider as the reader that qualitative papers can be quite lengthy, where the results section is quite vast often because you are really going in-depth and there's a lot of quotes and things. So, sometimes, it's possible that the authors mightn't have had enough space to put in lots and lots of quotes. So while we aren't looking for, you know, a quote from every single participant or most participants to support that theme, we do want, you know, two or three quotes, maybe that support our findings that we're claiming.

3- Contradicting data. There will often be some contradictory data that arises from the research and that needs to be recorded for clarity and transparency with the balance to discuss both sides.

4- Did the researchers consider other opinions without bias. a third party could be involved to eliminate the bias of research and reflect reflexivity

5-Clear statement about the results of the findings. The main findings should be discussed clearly in the discussion section with evidence both for and against their argument agreeing or contradicting previous literature. Do they critically analyse their findings in the context of different populations, different settings, in the context of research, practice, policy in the context of the evidence base that's out there?