In Table 2, the method for Aim 1 was a literature review, which we have already discussed. The methods for Aims 2 and 4 can be described as qualitative research, whereas the methods for Aims 3 and 5 are described quantitative research. Because the proposed study contains both qualitative and quantitative components, it could be best described as a mixed methods PhD.  

Qualitative research

In the qualitative approach the type of data to be acquired focuses on experiences, thought, feelings and behaviours. The data themselves are usually words or observations, unlike quantitative research, where the data are numbers. Qualitative Research is primarily exploratory research, used to gain an understanding of underlying reasons, opinions, and motivations. Qualitative research can be either a study in its own right, usually undertaken when little is known about a topic, or as an aid to undertaking quantitative research. For example, qualitative research is often used to help develop a questionnaire.  Qualitative research can also be used as an adjunct to quantitative research. For example, a clinical trial might show that an intervention is not effective, and additional qualitative research might help explain why it did not work. Some common methods of collecting qualitative data include focus groups (group discussions), individual interviews, and participation/observations. The sample size is typically small, and respondents deliberately selected because of their characteristics.

There are many different ways of analysing data obtained from qualitative research. Quite often, a simple thematic analysis is suitable, as long as it is undertaken in a systematic and reproducible fashion. Phenomenology or analysing the lived experience is another method of analysis. There are at least three schools of thought on how to undertake a phenomenological analysis. A second major method of analysing qualitative data is by using ethnography.  This is an approach developed by anthropologists to learn about cultures, and is now used to study behaviour and social interactions. Finally, grounded theory focuses on generating a theory from research data to describe what is happening in a social setting.  The above explanation only touches on many of the different theories used in qualitative research.

Quantitative research 

As its name implies, quantitative research is all about numbers. It is broadly covered by the disciplines of biostatistics and epidemiology.

Biostatistics

Biostatistics (also called medical statistics) is the discipline of statistical theory and methods applied in the health context. Whilst statisticians are usually trained in Schools of Mathematics and Statistics, biostatistics is taught in Schools of Public Health and Epidemiology, however, there is much overlap. Biostatistics focusses on areas such as design and analysis of clinical trials, the analysis of rates of disease, measures of the association between exposures and outcome, survival analysis, diagnostic testing, disease clustering and surveillance, disease screening, reliability and method comparison studies and biological assays. The analysis of genetic studies has formed its own discipline called bioinformatics, which is somewhat different. 

The wide availability of statistical software has made it much easier for students to undertake their own statistical analysis, but this has come with a downside. All statistical tests and procedures are based on assumptions, and it is very easy to either use the wrong statistical test, or break the assumptions required for a statistical test, and end up with nonsense results.

Epidemiology

Epidemiology is the study of the distribution, causation, diagnosis, prevention and treatment of diseases. It is very much interwoven with biostatistics since almost all epidemiological analyses require methods from biostatistics.

Descriptive epidemiology examines how much of a particular disease is in a community, whether it is endemic (always in the community), epidemic (rapidly increasing in the community), or pandemic (going globally). It also includes details of who gets the disease, when it first started and who is immune.  Disease causation (also called aetiology) is most often researched using case-control studies.  For example, case-control studies were used to demonstrate the link between smoking and lung cancer. Diagnostic testing including screening programs, requires an understanding of diagnostic accuracy, and covers indicators such as sensitivity and specificity. Epidemiology also covers the whole area of study design including clinical trials.

Which is better, qualitative or quantitative research?

That is a bit like in carpentry, asking what is better, a hammer or a saw. Each has a place in the toolbox of research. Quantitative research is better for providing the evidence for clinical practice, but addresses the question “Does it work?” rather than “Why does it work?” Qualitative research is ideal when you are investigating a very new area of research where very little is known. You might hate or be afraid of statistics, but qualitative research is equally if not more difficult to undertake – it is absolutely not an easy option.

In many ways, mixed methods is the ideal as it produces researchers trained in both qualitative and quantitative methods – a well-rounded researcher!

Having said that, the choice of a qualitative, quantitative or mixed methods PhD should not be based on personal preference, or the preference of your supervisors. It should be based on Table 2, a careful statement of your research question, aims, and the most appropriate method to address each aim. You must use the right tool for the job.