Behaviours occur across complex, dynamic timelines. Research methods to analyse these complex timelines have repeatedly used behaviour sequence analysis (BSA) as a primary method. Traditional BSA outputs, however, are limited in that they do not show how prevalent a behaviour sequence is throughout a sample or group. Until now, how many people in a sample showed the sequence was not analysed and reported. This paper aims to provide a new metric to calculate prevalence scores in BSA data sets.
Open access recorded responses including nonverbal communication of deceptive and truthful individuals were analysed initially with a standard BSA approach and then the prevalence scores of transitions were calculated.
Prevalence scores offered new insights into the distribution of sequences across groups. The prevalence score showed differences in which transitions were seen across the truthful and guilty samples. This offers new approaches to analysing nonverbal communication.
This is the first paper to provide a prevalence score for BSA research and show how it can be used in applied research. The current prevalence score metric is provided and suggested for all future research into sequences.
