Using Network Analysis to Identify Central Symptoms of Adolescent Depression

Abstract

Experiencing depression symptoms, even at mild to moderate levels, is associated with maladaptive outcomes for adolescents. We used network analysis to evaluate which symptoms (and associations between symptoms) are most central to adolescent depression. Participants were part of a large, diverse community sample (N = 1,409) of adolescents between 13 and 19 years of age. Network analysis was used to identify the most central symptoms (nodes) and associations between symptoms (edges) assessed by the Children's Depression Inventory. We also evaluated these centrality indicators for network robustness using stability and accuracy tests, associated symptom centrality with mean levels of symptoms, and examined potential differences between the structure and connectivity of depression networks in boys and girls. The most central symptoms in the network were self-hatred, loneliness, sadness, and pessimism. The strongest associations between symptoms were sadness-crying, anhedonia-school dislike, sadness-loneliness, school work difficulty-school performance decrement, self-hatred-negative body image, sleep disturbance-fatigue, and self-deprecation-self-blame. The network was robust to stability and accuracy tests. Notably, symptom centrality and mean levels of symptoms were not associated. Boys and girls' networks did not differ in levels of connectivity, though the link between body image and self-hatred was stronger in girls than boys. Self-hatred, loneliness, sadness, and pessimism were the most central symptoms in adolescent depression networks, suggesting that these symptoms (and associations between symptoms) should be prioritized in theoretical models of adolescent depression and could also serve as important treatment targets for adolescent depression interventions.

Hopelessness: A Network Analysis

“…In other words, specific items may constitute the "backbones" of the hopelessness network, despite being less frequently agreed upon. In line with the network approach, this evidence underlines the need to focus not only on the mere intensity, but also on the specific role played by the each component of the network (Mullarkey et al, 2018). Future studies could explore whether the relationship between between centrality indexes and mean levels holds in the clinical population too, as previously reported (Beard et al, 2016).…”

“…First, mean, standard deviation, kurtosis, skewness, and polychoric correlations of all the BHS items were inspected. Further, the informativeness of each variables was evaluated by means of standard deviation (Mullarkey, Marchetti, & Beevers, 2018) and possible items redundancy was checked. In accordance with Jones (2018), two items (i.e., "A" and "B") were deemed to measure the same phenomenon (i.e., redundancy), if the polychoric correlations between A with the rest of the items and B and the rest of the items were statistically different less than 25% of the cases.…”

Network Approach to Items and Domains From the Toronto Alexithymia Scale

“…In this framework, the unobserved interactions between psychological components (for instance symptoms, or items from a questionnaire) are often computed as regularized partial correlations (Epskamp & Fried, 2018). Network analysis has been used to explore several mental disorders, such as posttraumatic stress disorder Phillips et al, 2018), depression (Mullarkey, Marchetti, & Beevers, 2018), and autism (Ruzzano, Borsboom, & Geurts, 2015), but also psychological constructs such as empathy (Briganti, Kempenaers, Braun, Fried, & Linkowski, 2018), self-worth (Briganti, Fried, & Linkowski, 2019) and resilience (Fritz, Fried, Goodyer, Wilkinson, & van Harmelen, 2018;.…”

Network Analysis Reveals Central Symptoms of Adolescent Depression and Anxiety in Sub-Saharan Africa

“…Although the network approach is potentially beneficial to understanding the psychopathology of youth psychopathology, it has only recently been used in clinical research among adults, in which little interest/pleasure, low energy, and sad mood have emerged as the central symptoms of adult depression (Beard et al, 2016;Fried et al, 2016;Santos et al, 2017). Limited studies have investigated the network of symptoms in adolescent depression and anxiety (McElroy et al, 2018;Mullarkey et al, 2019;Wasil et al, 2020). A recent study with a community sample of American adolescents revealed that the central depression symptoms were self-hatred, loneliness, sadness, and pessimism (Mullarkey et al, 2019).…”

“…Limited studies have investigated the network of symptoms in adolescent depression and anxiety (McElroy et al, 2018;Mullarkey et al, 2019;Wasil et al, 2020). A recent study with a community sample of American adolescents revealed that the central depression symptoms were self-hatred, loneliness, sadness, and pessimism (Mullarkey et al, 2019). This contrast with central symptoms in adult depression might indicate that psychiatric symptom networks may be different between adolescents and adults.…”