About-Weekly Pattern in the Dynamic Complexity of a Healthy Subject’s Cellular Immune Activity: A Biopsychosocial Analysis

In a previous integrative single-case study, we collected biological, psychological and social time-series data on a 25-year-old healthy woman over the course of 126 12-h intervals (63 days) and used urinary neopterin as an indicator of cellular immune activity [Schubert et al. 2012 (1)]. The present re-evaluation introduced Dynamic Complexity (DC) as an additional non-linear and non-stationary measure to further investigate the subject’s biopsychosocial dynamics during the study. The new time series dealing with urinary neopterin complexity revealed a cyclic, circaseptan (about-weekly) repeating pattern (6.59 days). The only weekly reoccurring events over the course of the study that were associated with this immunological pattern were the in-depth interviews with the subject (mean distance between interviews: 6.5 days). Superposed epoch analysis (SEA) revealed a U-shaped relation between neopterin complexity and interviews, with a decrease in neopterin complexity before and during interviews and an increase after interviews. Furthermore, the complexity scores for irritation, anxiousness/depressiveness and mental activity were positively correlated with neopterin complexity. The results suggest that the interviews, which had been found to be related to the subject’s need for educational and/or social accomplishment, were marked by stress (decrease in psycho-immunological flexibility and adaptability), which was then relieved after the interviews (increase in psycho-immunological flexibility and adaptability). It appears that the subject’s cellular immune activity, as indicated by neopterin complexity, functionally mirrored the emotional meaning she ascribed to the in-depth interviews. This re-evaluation is in line with the view that biopsychosocial research requires multimodal analysis of single cases based on qualitative (e.g., in-depth interviews) and quantitative (e.g., time series analysis) data under conditions of “life as it is lived”.