Anxiety Regulation: From Affective Neuroscience to Clinical Practice

Unpredictable Mixed-Valence Outcomes Induce a Chronic and Reversible Generalized Anxiety-like Phenotype in Male Mice

Background

Clinical anxiety is a generalized state characterized by feelings of apprehensive expectation and is distinct from momentary responses such as fear or stress. In contrast, most laboratory tests of anxiety focus on acute responses to momentary stressors.

Methods

Apprehensive expectation was induced by subjecting mice (for 18 days) to manipulations in which a running response (experiment 1) or a conditioned stimulus (experiment 2) were unpredictably paired with reward (food) or punishment (footshock). Before this treatment, the mice were tested in an open field and light/dark box to assess momentary responses that are asserted to reflect state anxiety. After treatment, the mice were assessed for state anxiety in an elevated plus maze, social interaction test, startle response test, intrusive object burying test, and stress-induced corticosterone elevations. In experiment 3, we treated mice similarly to experiment 1, but after mixed-valence training, some mice received either no additional training, additional mixed-valence training, or were shifted to consistent (predictable) reinforcement with food.

Results

We consistently observed an increase in anxiety-like behaviors after the experience with mixed-valence unpredictable reinforcement. This generalized anxiety persisted for at least 4 weeks after the mixed-valence training and could be reversed if the mixed-valence training was followed by predictable reinforcement with food.

Conclusions

Results indicate that experience with unpredictable reward/punishment can induce a chronic state analogous to generalized anxiety that can be mitigated by exposure to stable, predictable conditions. This learned apprehension protocol provides a conceptually valid model for the study of the etiology and treatment of anxiety in laboratory animals.

Anxious Brains: A Combined Data Fusion Machine Learning Approach to Predict Trait Anxiety from Morphometric Features

Trait anxiety relates to the steady propensity to experience and report negative emotions and thoughts such as fear and worries across different situations, along with a stable perception of the environment as characterized by threatening stimuli. Previous studies have tried to investigate neuroanatomical features related to anxiety mostly using univariate analyses and thus giving rise to contrasting results. The aim of this study is to build a predictive model of individual differences in trait anxiety from brain morphometric features, by taking advantage of a combined data fusion machine learning approach to allow generalization to new cases. Additionally, we aimed to perform a network analysis to test the hypothesis that anxiety-related networks have a central role in modulating other networks not strictly associated with anxiety. Finally, we wanted to test the hypothesis that trait anxiety was associated with specific cognitive emotion regulation strategies, and whether anxiety may decrease with ageing. Structural brain images of 158 participants were first decomposed into independent covarying gray and white matter networks with a data fusion unsupervised machine learning approach (Parallel ICA). Then, supervised machine learning (decision tree) and backward regression were used to extract and test the generalizability of a predictive model of trait anxiety. Two covarying gray and white matter independent networks successfully predicted trait anxiety. The first network included mainly parietal and temporal regions such as the postcentral gyrus, the precuneus, and the middle and superior temporal gyrus, while the second network included frontal and parietal regions such as the superior and middle temporal gyrus, the anterior cingulate, and the precuneus. We also found that trait anxiety was positively associated with catastrophizing, rumination, other- and self-blame, and negatively associated with positive refocusing and reappraisal. Moreover, trait anxiety was negatively associated with age. This paper provides new insights regarding the prediction of individual differences in trait anxiety from brain and psychological features and can pave the way for future diagnostic predictive models of anxiety.

Interpersonal emotion regulation questionnaire: psychometric properties of the Italian version and associations with psychopathology

The emerging field of interpersonal emotion regulation (IER) is drawing attention to forms of emotion regulation which involve communication and social interaction as part of the regulation process. The availability of instruments to measure IER in different languages represents significant promise for future work in this field. The goal of the present study was to validate an Italian adaptation of a self-report instrument for the assessment of IER, the Interpersonal Emotion Regulation Questionnaire (IERQ; Hofmann et al., 2016). In an Italian sample (N=448), exploratory and confirmatory factor analyses confirmed the original structure comprising four factors (Enhancing Positive Affect, Perspective Taking, Soothing and Social Modelling). Correlations with other measures of emotion regulation showed good convergent validity of the questionnaire.

The Mediating Effects of Diabetes Distress, Anxiety, and Cognitive Fusion on the Association Between Neuroticism and Fear of Hypoglycemia in Patients With Type 2 Diabetes

Purpose: To explore the relationship between neuroticism and fear of hypoglycemia (FoH) among patients with type 2 diabetes (T2D), as well as the mediating effects of diabetes distress, anxiety, and cognitive fusion on the relationship between neuroticism and FoH.

Methods: A total of 494 patients with T2D (39.9% females, n = 197) were analyzed using the neuroticism scale of the Eysenck Personality Questionnaire-Revised Short Scale (EPQ-RS), the Fear of Hypoglycemia-15 Scale (FH-15), the Diabetes Distress Scale (DDS), the Self-Rating Anxiety Scale (SAS), and the Cognitive Fusion Questionnaire (CFQ). The bootstrapping method was used to test the separate and parallel mediation models.

Results: FoH was noted in 17.4% (n = 86) of patients. The correlations between neuroticism, diabetes distress, anxiety, cognitive fusion, and FoH were positive. Diabetes distress, anxiety, and cognitive fusion were significant mediators in the association between neuroticism and FoH in both separate and parallel mediation models. In the parallel mediation model, the mediating effect of anxiety was the highest, and the mediating effect of diabetes distress was the lowest, but no significant differences were found in the comparison of these three indirect effects.

Conclusion: This study indicated that neuroticism not only directly affected FoH, but also indirectly influenced FoH via the increase of diabetes distress, anxiety, and cognitive fusion in patients with T2D. The results provide a theoretical basis for the development of intervention programs to ameliorate patients’ FoH directly and indirectly. Healthcare providers should be encouraged to develop appropriate programs based on improving diabetes distress, anxiety, and cognitive fusion to help patients with T2D improve FoH.

Case Report: Individualization of Intensive Transactional Analysis Psychotherapy on the Basis of Ego Strength

In intensive transactional analysis psychotherapy (ITAP), intensity is obtained with both technical expedients and the relational manner with the patient. In ITAP, the therapist modulates pressure and support commensurately to the patients' ego strength. In the present article, we contrast two clinical cases of young adults in which ego strength produced different therapy outcomes and processes. We present excerpts of the psychotherapy process that illustrates technical aspects of ITAP as well as the therapist's attitude that we describe as holding. We show quantitative therapy outcomes consisting of effects size values of changes in Clinical Outcome in Routine Evaluation—Outcome Measure scores in baseline, treatment, and follow-up phases and qualitative outcome evaluated with the Change Interview at the end of the therapy. In the patient with high ego strength, we observed a rapid improvement and a complete recovery at the end of the therapy, whereas the results of the patient with low ego strength were less consistent (more fluctuations in Clinical Outcome in Routine Evaluation—Outcome Measure scores including deterioration but good qualitative outcome). We conclude that quantitative and qualitative outcome data, together with process observations, are required to have a complete picture of therapy effectiveness. Moreover, we conclude that qualitative ego strength is not a limitation for the use of expressive therapy such as ITAP, but rather, it is an important variable that should be considered to dose confrontations and support.