Speaker
Description
Most studies of bullying have been quantitative. Smith et al. (2021) found little qualitative research, and a small but declining proportion of mixed methods studies. Qualitative data are likely to be most useful when some aspects of the phenomena are under-explored, for example cyberbullying where there are still disputes about definition and measurement, and the phenomena are changing rapidly.
This was acknowledged by the Medical Research Council in the UK (Moore et al. (2015), with Key recommendations for process evaluation: ensure that the research team has expertise in qualitative and quantitative research methods; and select a combination of methods appropriate to the research questions: Use quantitative methods to measure key process variables and allow testing of pre-hypothesised mechanisms of impact and contextual moderators and Use qualitative methods to capture emerging changes in implementation, experiences of the intervention and unanticipated or complex causal pathways, and to generate new theory/ Ensure that quantitative and qualitative analyses build upon one another (eg, qualitative data used to explain quantitative findings or quantitative data used to test hypotheses generated by qualitative data)
This has been partly acknowledged by bullying researchers: e.g. Spadafora et al (2022), Hong & Espelage (2012). Palinkas et al. (2011) delineate 7 different structural arrangements of qualitative and quantitative methods.
This paper will review these issues, and argue that a combination of quantitative and qualitative methods should be the norm in bullying research. Rather than justifying mixed methods, any article or research proposal should justify why mixed methods are not being used.
Keywords
Quantitative Qualitative Mixed methods
| Please indicate what type of scientific contribution it is | Not applicable |
|---|---|
| Please also indicate what kind of contribution it is: | Mixed |
