Common errors and their avoidance
Inadequate sample
Inexperienced qualitative researchers may be led by the positivist approach to analysis and attempt to pre-define the sample for the research in terms of size and composition. This potentially limits the data and analysis as it far more effective to select participants based on the data already analysed (constant-comparative) and base the sample size on theoretical saturation.
Insufficient time for data collection and analysis
Qualitative interviews can take a while to organise and focus groups require logistical planning to ensure a date and time that is suitable for all participants. Furthermore, the transcription of interviews and focus groups may take many more hours than anticipated and requires a skilled and experienced transcriber in order to capture the nuances in the conversation as well as the content. If an ethnographic study is being undertaken it is possible that the researcher may need to observe a large number of interactions and behaviour before being satisfied that he or she has collected sufficient data to analyse. Such unpredictable and potentially lengthy timescales make it difficult to estimate resources required for qualitative studies beforehand, which can be difficult for funders. If necessary, such estimates should be based on experiences from previous, similar studies, and the researcher’s understanding of the field.
Using a quantitative approach to analysing the data
Very occasionally it is useful to analyse qualitative data in a quantitative, deductive manner, such as the simple content analysis (“counts” of concepts and summaries of the frequencies with which different concepts appear in the data). However, this approach should be undertaken with caution as it may lead to a waste of rich data which could be analysed inductively to generate new theories about health behaviour and attitudes. A data analysis plan, carefully considered and reviewed by experienced qualitative researchers, should be devised before the research begins and may help ensure the analysis maximises the value from the data.
© I Crinson & M Leontowitsch 2006, G Morgan 2016