Resilience after Childhood Maltreatment: The Establishment of a Resilience Network Model and the Investigation of Its Fluctuations over Time

Lead Research Organisation: University of Cambridge
Department Name: Psychiatry

Abstract

Resilience after Childhood Adversity:
The Establishment of a Resilience Network Model
PhD Candidate: Jessica Fritz MSc
Primary Supervisor: Dr. Paul O. Wilkinson
Associate Supervisor: Dr. Anne-Laura van Harmelen
Facing adversities in childhood is a serious environmental hazard with deleterious mental consequences over the subsequent lifecourse (Gilbert et al., 2009; Kessler, Davis, & Kendler, 1997). Up to 53.4% of the population suffers from at least one type of childhood adversities (CA; US National Comorbidity Replication Survey; Greif Green et al., 2010). Many studies have shown that CAs are highly associated with the development of psychopathology (e.g. Dunn et al., 2011; Greif Green et al., 2010; Heim, Shugart, Craighead, & Nemeroff, 2010; Hovens, Giltay, Spinhoven, van Hemert, & Penninx, 2015; Kessler et al., 1997; McLaughlin, Greif Green, Gruber, Berglund, et al., 2010; McLaughlin, Greif Green, Gruber, Sampson, et al., 2010; Scott, McLaughlin, Smith, & Ellis, 2012; Spinhoven et al., 2010). Yet, a strong network of interrelated resilience promoting factors (e.g. friendship support, impulse control, positive future orientation, daily life skills: Afifi & MacMillan, 2011; Kinard, 1998; Schultze-Lutter, Schimmelmann, & Schmidt, 2016) could potentially support mental health in these individuals.
Resilience can be described as beneficial adaptation following exposure to adverse experiences (Curtis & Cicchetti, 2007; Kalisch, Muller, & Tuscher, 2016; van der Werff, van den Berg, Pannekoek, Elzinga, & van der Wee, 2013; Zolkoski & Bullock, 2012) and should not be understood as exclusive capacity but as a concept of multiple resilience promoting factors (Afifi & MacMillan, 2011; Kinard, 1998; Schultze-Lutter et al., 2016). To date, resilience promoting factors have been studied on social (e.g. family support, social connectedness), behavioural (e.g. daily living skills, impulse control), cognitive (e.g. locus of control, future orientation) and emotional (e.g. low neuroticism, low self-blame) domains (e.g. Afifi & MacMillan, 2011; Aslan, in press; Curtis & Cicchetti, 2007; Dang, 2015; Folger & Wright, 2013; Holmes, Yoon, Voith, Kobulsky, & Steigerwald, 2015; Masten et al., 1999; Schultze-Lutter et al., 2016; van Harmelen et al., 2015; Williams & Nelson-Gardell, 2012). Importantly, resilience promoting factors do not function in isolation, rather, they have strong interrelationships (Afifi & MacMillan, 2011; Rutter, 1985). For instance, an individual with better self-regulation may be better company to be around and therefore may evoke better social support from others. To the best of our knowledge, no research has yet investigated the interconnectedness of these factors. I shall use cutting edge network analysis techniques (see Figure 1), to find the best fitting resilience network model which conceptualizes the interconnectedness of resilience promoting factors (Borsboom, & Cramer, 2010; Borsboom, Cramer, Schmittmann, Epskamp, & Waldorp, 2011; Costantini et al., 2015; Cramer et al., 2012; Cramer & Waldorp, 2010; Epskamp, Cramer, Waldorp, Schmittmann, & Borsboom, 2011; Freeman, 1978; Fried, Epskamp, Nesse, Tuerlinckx, & Borsboom, 2015; van Borkulo, Waldorp, Boschloo, Schoevers, & Borsboom, 2015).
I propose five projects for my PhD: Firstly, I shall establish the network structure of resilience factors in the general population. Next, I will validate the proposed network model of resilience factors, through establishing accuracy, stability, as well as external and predictive validity. Third, I intend to examine the network structure of resilience in individuals with a history of CA and to compare it to the resilience network of the general population. Moreover, I shall prospectively investigate whether resilience network structures are stable over time during the course of adolescence, to discover potential resilience network fluctuations. Finally, I aim to disentangle, whether resilience network fluctuations differ between