BJOG Perspectives – qualitative research: analysing data and rigour

1.

Learning points

• Qualitative research produces copious amounts of data which need to be interpreted by the researcher

• Data collection and analysis may be conducted simultaneously

• Analytical rigour is achieved through transparency and establishing trustworthiness

Qualitative research produces copious amounts of data, most commonly in the form of textual records from interviews, focus groups and/or fieldnotes. It may also produce visual or audio records in forms such as photos and videos. To analyse data, researchers undertake a rigorous, systematic (and often time‐consuming) process of sifting through and interpreting them. The preliminary analysis begins as data are being collected, enabling research questions to be refined and new unforeseen lines of inquiry to be pursued.

Within qualitative research, the researcher selects the analysis method (or combination of methods) based on which best help address the research question(s). There is a wide range of methods for analysing qualitative data; some of the most commonly used within health research include thematic, narrative and interpretive phenomenological analysis.

Thematic approach: a usually inductive (bottom‐up) process of identifying, analysing and reporting of patterns (or themes) across data. (see Boyatzis. Transforming qualitative Information: Thematic Analysis and Code Development. Thousand Oaks, CA: Sage; 1998).

Narrative approach: provides rich, detailed accounts (or stories) of individuals' subjective experiences of healthcare and illness (see Riessman. Narrative Analysis. Thousand Oaks, CA: Sage; 1993).

Interpretive phenomenological analysis (IPA) is a method of analysis, originating from phenomenological theory, that provides an in‐depth exploration of people's lived experiences to examine closely how people understand those experiences (see Smith, Flowers & Larkin. Interpretive Phenomenological Analysis: Theory, Method and Research. Los Angeles, CA: Sage; 2009).

Each approach has its unique features; however, there are some common practices across all modes of qualitative analysis. Coding (a means of identifying, defining and naming themes) is a method for data reduction during the analysis process, which can be done with the assistance of software packages (such as NVIVO) to organise and retrieve data. Such software facilitates basic coding as well as more sophisticated algorithms identifying co‐occurring codes, but it cannot carry out the interpretive elements of the analysis process, which can only be undertaken by skilled researcher(s). Rigour in the analytical process is achieved by transparency in the research process and by establishing ‘trustworthiness’ in the data (White et al. Management of a large qualitative data set: establishing trustworthiness of the data. Int J Qual Methods 2012;11:244–58). This can be accomplished through the use of more than one analyst, the checking of data findings with original research participants, and/or the use of multiple data sources. In the reporting of findings, trustworthiness is also achieved by transparently stating how selected quotes are representative of findings and/or through the use of outlier/deviant cases. The theory that underpins qualitative analysis will be addressed in the next article.

2. USEFUL RESOURCES

Example of the use of IPA in an obstetrics and gynaecology study

• Nuzum D, Meaney S, O'Donoghue K. The impact of stillbirth on consultant obstetrician gynaecologists: a qualitative study. BJOG 2014;121:1020–8.

Analysing qualitative data and ensuring trustworthiness

• Pope C, Ziebland S, Mays N. Analysing qualitative data. BMJ; 2000320:114–6.

• Rolfe G. Validity, trustworthiness and rigour: quality and the idea of qualitative research. J Adv Nursing 2006;53:304–10.

Use of qualitative analysis computer software

• Keele U (ed.) Computer‐Aided Qualitative Data Analysis: Theory, Methods and Practice. Thousand Oaks, CA: Sage; 1995.

Supporting information

Appendix S1

Appendix S2

Weckesser A, Denny E. BJOG Perspectives – qualitative research: analysing data and rigour. BJOG. 2022;129:1406–1407. 10.1111/1471-0528.17148