Abstract
Indirect observation is a recent concept in systematic observation. It largely involves analyzing textual material generated either indirectly from transcriptions of audio recordings of verbal behavior in natural settings (e.g., conversation, group discussions) or directly from narratives (e.g., letters of complaint, tweets, forum posts). It may also feature seemingly unobtrusive objects that can provide relevant insights into daily routines. All these materials constitute an extremely rich source of information for studying everyday life, and they are continuously growing with the burgeoning of new technologies for data recording, dissemination, and storage. Narratives are an excellent vehicle for studying everyday life, and quantitization is proposed as a means of integrating qualitative and quantitative elements. However, this analysis requires a structured system that enables researchers to analyze varying forms and sources of information objectively. In this paper, we present a methodological framework detailing the steps and decisions required to quantitatively analyze a set of data that was originally qualitative. We provide guidelines on study dimensions, text segmentation criteria, ad hoc observation instruments, data quality controls, and coding and preparation of text for quantitative analysis. The quality control stage is essential to ensure that the code matrices generated from the qualitative data are reliable. We provide examples of how an indirect observation study can produce data for quantitative analysis and also describe the different software tools available for the various stages of the process. The proposed method is framed within a specific mixed methods approach that involves collecting qualitative data and subsequently transforming these into matrices of codes (not frequencies) for quantitative analysis to detect underlying structures and behavioral patterns. The data collection and quality control procedures fully meet the requirement of flexibility and provide new perspectives on data integration in the study of biopsychosocial aspects in everyday contexts.
Highlights
Psychological science has shown a growing interest in the study of everyday life
We believe that it is first necessary to clarify the meaning of method/methodology and to discuss the multiple meanings attached to the term “mixed method” before we present our methodological framework for indirect observation
We have presented a structured procedure detailing the successive stages of the method we propose for studying verbal behavior and/or textual material in an indirect observation study (Table 9)
Summary
Psychological science has shown a growing interest in the study of everyday life. New methodologies have been proposed for the within-person study of real-time biopsychosocial aspects in their natural settings (Bolger et al, 2003; Conner and Lehman, 2013; Reis, 2013; Portell et al, 2015b,c). Direct and indirect observation may vary in terms of source material, level of interpretation, and level of participation, the two methods share a scientific procedure that when properly applied can provide quantitative indicators of the processes underlying everyday behavior. Mixed methods research is marked by a persistent scientific gap that requires powerful solutions rooted in two key challenges in the field of indirect observation These two challenges, discussed in this article, are (a) how to rigorously transform qualitative textual material derived largely from everyday human communication into matrices of codes, and (b) how to subsequently analyze these codes using quantitative methods suited to the categorical nature of the data in order to uncover the underlying structure. Indirect observation shares many of the characteristics previously described for systematic observation, namely, highly systematic data collection and analysis, strict data quality controls, and an approach that requires the merging of qualitative and quantitative techniques
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