Emotional Dysregulation in Para-suicidal Behavior

This naturalistic pre-port study tests if Dialectical Behavior Therapy (DBT) - an established therapy addressing emotion regulation and reduction of non-suicidal self-injury and suicidal ideation - result in increased emotion regulation capacity, indicated by lowered heart rate variability (HRV) and self-report measures. The study will also test the impact of DBT on lowered non-suicidal self-injury and suicidal ideation. Standard Clinical symptom scales will be included in order to control for anxiety, depression, as well as a measure of impulsivity, which is common co-morbidities.

Since DBT was developed in the 80ies, DBT has gathered increased empirical support as a treatment that reduce suicidality, para-suicidal behavior, experienced and expressed anger, and increased social skills. In DBT, emotional dysregulation is assumed to arise from a combination of biological vulnerability and living in an invalidating environment.

Self-harm and chronic suicidality is considered to be an emotion regulation strategy. In DBT, the ability to regulate emotions adaptively requires a set of skills; the ability to experience emotions, the ability to label emotions, and the ability to modulate stimuli that serve to reactivate negative or positive emotions. In the absence of these skills, or instances where the individual is hindered from applying them, more maladaptive behavior is learned and applied. Individuals that engage in non-suicidal self-injury often report greater emotion dysregulation than those without an non-suicidal self-injury history. Such behavior can e.g. be self-inflicted harm, cutting, burning, or hitting , and/or suicidal ideation. Non-suicidal self-injury is viewed as a learned emotion regulation strategy; because such behavior instantly can decrease the experience of negative affect. Therapies that focus on increasing adaptive emotion regulations skills have demonstrated reduced non-suicidal self-injury and suicidal ideation.

The physiological manifestations of emotions rely on an activation of the Autonomic Nervous System. The individual experience of emotions is reciprocally related to the continuously changing levels of physiological arousal. The functioning of this system is in turn related to adapting to environmental demands. A well established measure of Autonomic Nervous activity is variation in inter-beat-intervals due to respiratory influence on heart rate, i.e. respiratory sinus arrhythmia, which is predominately a parasympathetic related innervation of the heart. Hence, HRV is considered a psychophysiological index of emotion regulation abilities. HRV is considered an index of the nervous system's ability to flexibly adapt to changing environmental demands and is considered a biological index of emotion regulation.

We include a matched control sample of healthy controls to complete the battery of measurements at baseline assessment of emotion regulation functions (pre-intervention assessments). This will give the opportunity to characterize the group of patients with non-suicidal self-injury and suicidal ideation included in the current planned study in relation to previous research findings of the same functions in samples of patients with non-suicidal self-injury and suicidal ideation. The combination of clinical, cognitive and psychophysiological measures is a unique feature of this study, and will provide new information regarding the mechanisms underpinning clinical change following DBT, and possibly validate heart rate variability as a possible psychophysiological outcome measure for studies on treatment for non-suicidal self-injury and suicidal ideation.

Statistical analyses Multilevel between-group analyses will be conducted to test for the between-group effects on the measures at baseline. Furthermore, a multiple regression analyses, so that dimensional variables can be included as independent variables in the model, for the pre and post measures. Regression analyses also allow for adjusting for the effects of possible confounders on the outcome measures, such as age, sex, and intensity of depressive symptoms. Furthermore, bootstrapping analysis will be conducted to examine moderator and mediator effects on the outcome measures. Interpretation of the strength of experimental effects will be guided by the use of effect size statistics. Baseline measures of demographics, life experiences, and symptoms may also be used to predict outcomes or as covariates in our analyses.