Embracing the positive: an examination of how well resilience factors at age 14 can predict distress at age 17.

One-in-two people suffering from mental health problems develop such distress before or during adolescence. Research has shown that distress can predict itself well over time. Yet, little is known about how well resilience factors (RFs), i.e. those factors that decrease mental health problems, predict subsequent distress. Therefore, we investigated which RFs are the best indicators for subsequent distress and with what accuracy RFs predict subsequent distress. We examined three interpersonal (e.g. friendships) and seven intrapersonal RFs (e.g. self-esteem) and distress in 1130 adolescents, at age 14 and 17. We estimated the RFs and a continuous distress-index using factor analyses, and ordinal distress-classes using factor mixture models. We then examined how well age-14 RFs and age-14 distress predict age-17 distress, using stepwise linear regressions, relative importance analyses, as well as ordinal and linear prediction models. Low brooding, low negative and high positive self-esteem RFs were the most important indicators for age-17 distress. RFs and age-14 distress predicted age-17 distress similarly. The accuracy was acceptable for ordinal (low/moderate/high age-17 distress-classes: 62-64%), but low for linear models (37-41%). Crucially, the accuracy remained similar when only self-esteem and brooding RFs were used instead of all ten RFs (ordinal = 62%; linear = 37%); correctly predicting for about two-in-three adolescents whether they have low, moderate or high distress 3 years later. RFs, and particularly brooding and self-esteem, seem to predict subsequent distress similarly well as distress can predict itself. As assessing brooding and self-esteem can be strength-focussed and is time-efficient, those RFs may be promising for risk-detection and translational intervention research.

Cognitive behavioral therapy may have a rehabilitative, not normalizing, effect on functional connectivity in adolescent depression.

BACKGROUND: Whether the differences in brain structure and function, characteristic of adult major depressive disorder (MDD1), are present in adolescent MDD is still unclear, but it has been shown that cognitive behavioral therapy (CBT2) affects resting-state functional connectivity in both adult and adolescent MDD patients, with the claim that CBT has a normalizing effect on MDD-related functional disruption, but this has not been directly tested. METHODS: 128 adolescent MDD patients and 40 adolescent controls were enrolled in the study. We investigated pre-treatment differences in cortical thickness, white matter volume, and resting-state functional connectivity. We also investigated the longitudinal effects of CBT on resting-state functional connectivity, and the relationship between pre-treatment functional disruption and CBT-related changes to resting-state functional connectivity was assessed by the correlation of pre-treatment cross-sectional effects and longitudinal CBT-related effects across multiple brain regions. RESULTS: Patients had greater cortical thickness and white matter volume within fronto-limbic regions of the brain. Patients had greater pre-treatment resting-state functional connectivity within the default-mode, fronto-limbic, central-executive, and salience networks. CBT increased resting-state functional connectivity of the subgenual anterior cingulate and amygdala seeds with predominantly frontal regions. Regions showing the greatest pre-treatment functional disruption showed the weakest CBT-related changes. LIMITATIONS: For ethical reasons, there was no placebo group. CONCLUSIONS: Adolescent MDD is associated with structural and functional differences also seen in adult patients. CBT-related changes in resting-state functional connectivity do not appear to show a normalizing effect, but instead indicate rehabilitative effects on resting-state functional connectivity.

Unravelling the complex nature of resilience factors and their changes between early and later adolescence.

BACKGROUND: Childhood adversity (CA) is strongly associated with mental health problems. Resilience factors (RFs) reduce mental health problems following CA. Yet, knowledge on the nature of RFs is scarce. Therefore, we examined RF mean levels, RF interrelations, RF-distress pathways, and their changes between early (age 14) and later adolescence (age 17). METHODS: We studied 10 empirically supported RFs in adolescents with (CA+; n = 631) and without CA (CA-; n = 499), using network psychometrics. RESULTS: All inter-personal RFs (e.g. friendships) showed stable mean levels between age 14 and 17, and three of seven intra-personal RFs (e.g. distress tolerance) changed in a similar manner in the two groups. The CA+ group had lower RFs and higher distress at both ages. Thus, CA does not seem to inhibit RF changes, but to increase the risk of persistently lower RFs. At age 14, but not 17, the RF network of the CA+ group was less positively connected, suggesting that RFs are less likely to enhance each other than in the CA- group. Those findings underpin the notion that CA has a predominantly strong proximal effect. RF-distress pathways did not differ in strength between the CA+ and the CA- group, which suggests that RFs have a similarly protective strength in the two groups. Yet, as RFs are lower and distress is higher, RF-distress pathways may overall be less advantageous in the CA+ group. Most RF interrelations and RF-distress pathways were stable between age 14 and 17, which may help explain why exposure to CA is frequently found to have a lasting impact on mental health. CONCLUSIONS: Our findings not only shed light on the nature and changes of RFs between early and later adolescence, but also offer some accounts for why exposure to CA has stronger proximal effects and is often found to have a lasting impact on mental health.

A Network Model of Resilience Factors for Adolescents with and without Exposure to Childhood Adversity.

Resilience factors (RFs) help prevent mental health problems after childhood adversity (CA). RFs are known to be related, but it is currently unknown how their interrelations facilitate mental health. Here, we used network analysis to examine the interrelations between ten RFs in 14-year-old adolescents exposed ('CA'; n = 638) and not exposed to CA ('no-CA'; n = 501). We found that the degree to which RFs are assumed to enhance each other is higher in the no-CA compared to the CA group. Upon correction for general distress levels, the global RF connectivity also differed between the two groups. More specifically, in the no-CA network almost all RFs were positively interrelated and thus may enhance each other, whereas in the CA network some RFs were negatively interrelated and thus may hamper each other. Moreover, the CA group showed more direct connections between the RFs and current distress. Therefore, CA seems to influence how RFs relate to each other and to current distress, potentially leading to a dysfunctional RF system. Translational research could explore whether intervening on negative RF interrelations so that they turn positive and RFs can enhance each other, may alter 'RF-mental distress' relations, resulting in a lower risk for subsequent mental health problems.