Nicole Geschwind

Mindfulness Training Increases Momentary Positive Emotions and Reward Experience in Adults Vulnerable to Depression: A Randomized Controlled Trial

OBJECTIVE To examine whether mindfulness-based cognitive therapy (MBCT) increases momentary positive emotions and the ability to make use of natural rewards in daily life. METHOD Adults with a life-time history of depression and current residual depressive symptoms (mean age = 43.9 years, SD = 9.6; 75% female; all Caucasian) were randomized to MBCT (n = 64) or waitlist control (CONTROL; n = 66) in a parallel, open-label, randomized controlled trial. The Experience Sampling Method was used to measure momentary positive emotions as well as appraisal of pleasant activities in daily life during 6 days before and after the intervention. Residual depressive symptoms were measured using the 17-item Hamilton Depression Rating Scale (Hamilton, 1960). RESULTS MBCT compared to CONTROL was associated with significant increases in appraisals of positive emotion (b* = .39) and activity pleasantness (b* = .22) as well as enhanced ability to boost momentary positive emotions by engaging in pleasant activities (b* = .08; all ps < .005). Associations remained significant when corrected for reductions in depressive symptoms or for reductions in negative emotion, rumination, and worry. In the MBCT condition, increases in positive emotion variables were associated with reduction of residual depressive symptoms (all ps < .05). CONCLUSIONS MBCT is associated with increased experience of momentary positive emotions as well as greater appreciation of, and enhanced responsiveness to, pleasant daily-life activities. These changes were unlikely to be pure epiphenomena of decreased depression and, given the role of positive emotions in resilience against depression, may contribute to the protective effects of MBCT against depressive relapse.

A Network Approach to Psychopathology: New Insights into Clinical Longitudinal Data

In the network approach to psychopathology, disorders are conceptualized as networks of mutually interacting symptoms (e.g., depressed mood) and transdiagnostic factors (e.g., rumination). This suggests that it is necessary to study how symptoms dynamically interact over time in a network architecture. In the present paper, we show how such an architecture can be constructed on the basis of time-series data obtained through Experience Sampling Methodology (ESM). The proposed methodology determines the parameters for the interaction between nodes in the network by estimating a multilevel vector autoregression (VAR) model on the data. The methodology allows combining between-subject and within-subject information in a multilevel framework. The resulting network architecture can subsequently be analyzed through network analysis techniques. In the present study, we apply the method to a set of items that assess mood-related factors. We show that the analysis generates a plausible and replicable network architecture, the structure of which is related to variables such as neuroticism; that is, for subjects who score high on neuroticism, worrying plays a more central role in the network. Implications and extensions of the methodology are discussed.

Dimensions of Normal Personality as Networks in Search of Equilibrium: You Can't Like Parties if You Don't Like People

In one currently dominant view on personality, personality dimensions (e.g. extraversion) are causes of human behaviour, and personality inventory items (e.g. ‘I like to go to parties’ and ‘I like people’) are measurements of these dimensions. In this view, responses to extraversion items correlate because they measure the same latent dimension. In this paper, we challenge this way of thinking and offer an alternative perspective on personality as a system of connected affective, cognitive and behavioural components. We hypothesize that these components do not hang together because they measure the same underlying dimension; they do so because they depend on one another directly for causal, homeostatic or logical reasons (e.g. if one does not like people and it is harder to enjoy parties). From this ‘network perspective’, personality dimensions emerge out of the connectivity structure that exists between the various components of personality. After outlining the network theory, we illustrate how it applies to personality research in four domains: (i) the overall organization of personality components; (ii) the distinction between state and trait; (iii) the genetic architecture of personality; and (iv) the relation between personality and psychopathology. Copyright

Resilience in mental health: linking psychological and neurobiological perspectives

To review the literature on psychological and biological findings on resilience (i.e. the successful adaptation and swift recovery after experiencing life adversities) at the level of the individual, and to integrate findings from animal and human studies.

Unveiling patterns of affective responses in daily life may improve outcome prediction in depression: A momentary assessment study

OBJECTIVE Daily life affective responses are closely linked to vulnerability and resilience in depression. Prediction of future clinical course may be improved if information on daily life emotional response patterns is taken into account. METHOD Female subjects with a history of major depression (n=83), recruited from a population twin register, participated in a longitudinal study using momentary assessment technology with 4 follow-up measurements. The effect of baseline daily life emotional response patterns (affect variability, stress-sensitivity and reward experience) on follow-up depressive symptomatology was examined. RESULTS Both reward experience (B=-0.30, p=0.001) and negative affect variability (B=0.46, p=0.001) predicted future negative affective symptoms independent of all other dynamic emotional patterns and conventional predictors. CONCLUSION Daily life information on dynamic emotional patterns adds to the prediction of future clinical course, independent of severity of symptoms and neuroticism score. Better prediction of course may improve decision-making regarding quantitative and qualitative aspects of treatment.

Mechanisms of gene–environment interactions in depression: evidence that genes potentiate multiple sources of adversity

BACKGROUND Previous work suggests that daily life stress-sensitivity may be an intermediary phenotype associated with both genetic risk for depression and developmental stress exposures. In the current analysis we hypothesized that genetic risk for depression and three environmental exposures over the course of development [prenatal stress, childhood adversity and adult negative life events (NLEs)] combine synergistically to produce the phenotype of stress-sensitivity. METHOD Twin pairs (n=279) participated in a momentary assessment study using the Experience Sampling Method (ESM), collecting appraisals of stress and negative affect (NA) in the flow of daily life. Prospective data on birthweight and gestational age, questionnaire data on childhood adversity and recent NLEs, and interview data on depression were used in the analyses. Daily life stress-sensitivity was modelled as the effect of ESM daily life stress appraisals on ESM NA. RESULTS All three developmental stress exposures were moderated by genetic vulnerability, modelled as dizygotic (DZ) or monozygotic (MZ) co-twin depression status, in their effect on daily life stress-sensitivity. Effects were much stronger in participants with MZ co-twin depression and a little stronger in participants with DZ co-twin depression status, compared to those without co-twin depression. NLE main effects and NLE genetic moderation were reducible to birthweight and childhood adversity. CONCLUSIONS The findings are consistent with the hypothesis that adult daily life stress-sensitivity is the result of sensitization processes initiated by developmental stress exposures. Genes associated with depression may act by accelerating the process of stress-induced sensitization.

Transition from stress sensitivity to a depressive state: longitudinal twin study

BACKGROUND Daily-life stress sensitivity is associated with depression, but prospective data are lacking. AIMS To examine associations between baseline ecological daily-life stress sensitivity and later depression, and to identify genetic and non-genetic factors moderating the transition from stress sensitivity to depression. METHOD Daily-life stress sensitivity was assessed at baseline in twins (n = 502). One baseline and four follow-up measurements of depressive symptoms and negative life events were collected, as well as interview-based diagnoses at baseline and last follow-up. Hypothesised genetic markers were determined. RESULTS Baseline stress sensitivity was associated with increased depressive symptoms at follow-up and risk of major depressive disorder. Both genetic liability and major life events moderated the probability of transition from stress sensitivity to depression. CONCLUSIONS Onset of depression is attributable to pre-onset ecological measurements of stress sensitivity, particularly where genetic liability is high and individuals have reached a stage where the influence of competing environmental causes is low.

Early improvement in positive rather than negative emotion predicts remission from depression after pharmacotherapy

Knowledge on mechanisms involved in early prediction of response to antidepressant medication may help optimize clinical decision making. Recent studies regarding response to pharmacotherapy implicate resilience-like mechanisms and involvement of positive, rather than negative emotions. The aim of the current study is to examine the contribution of early change in positive affect to the prediction of response to pharmacotherapy. Positive and negative emotions were measured at baseline and during the first week of pharmacotherapy, using experience sampling techniques. The association between early change in positive and negative emotions and severity of depressive symptoms at week six was examined in a sample of 49 depressed patients. The added benefits of measuring early change in positive emotions compared to early Hamilton Depression Rating Scale (HDRS) change alone were evaluated through model comparisons. Early improvement in positive affect during the first week of treatment predicted the continuous HDRS score (β=-0.64, p<0.001), response (50% reduction; OR=4.32, p<0.01), and remission (HDRS≤7; OR=9.29, p<0.001) at week six with moderate to large effect sizes. Effects of early change in negative emotions were only half as large and disappeared when evaluated simultaneously with early change in positive emotions. When early change in positive emotions was added to the models including early HDRS change only, all three models improved significantly. In conclusion, early change in positive rather than negative emotions best predicted response to treatment, supporting the notion that antidepressants activate resilience-like mechanisms. Moreover, monitoring of positive emotions in early stages of treatment may improve clinical decision making.

Meeting risk with resilience: high daily life reward experience preserves mental health

Geschwind N, Peeters F, Jacobs N, Delespaul P, Derom C, Thiery E, van Os J, Wichers M. Meeting risk with resilience: high daily life reward experience preserves mental health.

Efficacy of mindfulness-based cognitive therapy in relation to prior history of depression: randomised controlled trial

BACKGROUND There appears to be consensus that patients with only one or two prior depressive episodes do not benefit from treatment with mindfulness-based cognitive therapy (MBCT). AIMS To investigate whether the effect of MBCT on residual depressive symptoms is contingent on the number of previous depressive episodes (trial number NTR1084). METHOD Currently non-depressed adults with residual depressive symptoms and a history of depression (≤2 prior episodes: n = 71; ≥3 episodes: n = 59) were randomised to MBCT (n = 64) or a waiting list (control: n = 66) in an open-label, randomised controlled trial. The main outcome measured was the reduction in residual depressive symptoms (Hamilton Rating Scale for Depression, HRSD-17). RESULTS Mindfulness-based cognitive therapy was superior to the control condition across subgroups (β = -0.56, P<0.001). The interaction between treatment and subgroup was not significant (β = 0.45, P = 0.16). CONCLUSIONS Mindfulness-based cognitive therapy reduces residual depressive symptoms irrespective of the number of previous episodes of major depression.