100 Chapter 5 each personality component with itself and other components at the previous time-point t-1. Personality networks thus represent either contemporaneous or delayed interdependencies between various personality components. Idiographic network models thereby enable studying individual differences in personality bottom-up, by first estimating each individual’s personality network structure separately and then comparing individuals’ networks. Such comparisons of different individuals have demonstrated high between-person personality heterogeneity – even within sets of variables and samples where larger homogeneity may have been expected based on shared sample characteristics. For instance, Beck and Jackson (2020) showed that estimated idiographic networks of identical personality-related items were highly heterogeneous in a student sample. Most of the research that reveals between-person heterogeneity of idiographic networks, however, has looked samples that share a clinical diagnosis. Dotterer et al. (2020) used idiographic networks to assess the interrelations between negative affect, detachment, impulsivity, and hostility in 91 clients with various personality disorders. Using a procedure that searches for commonalities between edges in idiographic networks (i.e., group iterative multiple method estimation (GIMME)), they found no edge that was significantly present for more than 75 % of the sample, indicating high between-person heterogeneity. Lane et al. (2019) reanalyzed the same dataset to explore idiographic networks for the 35 participants included with a borderline personality disorder, identifying only one association as a group-level edge, once more revealing high betweenperson differences. Similar heterogeneity was found in various other clinical samples (e.g., Fisher et al., 2017; Reeves & Fisher, 2020). While between-person network comparisons indicate substantial heterogeneity, there is far less evidence on the stability of idiographic networks within-persons over time. Beck and Jackson (2020) found that some individuals’ networks were relatively consistent over two years while other individuals showed vastly different structures across the two waves (cf. Beck & Jackson, 2021; Jackson & Beck, 2021). The lag-1 estimates even demonstrated odd–even and split-half unreliability within-waves (Beck & Jackson, 2020), indicating structural variability over time within a timeframe of two weeks. A small body of psychopathology network studies found similar within-person variability (Nemesure et al., 2024; Wichers et al., 2016). This preliminary evidence of within-person network variability prompts the question what network (in)stability exactly tells us, and what could theoretically be expected. Theoretical models highlight that assuming stability may be a fool’s errand. The Cognitive–Affective Personality System (CAPS; Mischel & Shoda, 1995)
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