Behavioral Activation as a Mechanism of Change in Residential Treatment for Mood Problems: A Growth Curve Model Analysis

Feasibility and preliminary efficacy of behavioral activation for treatment of depression in autistic adolescents

LAY ABSTRACT

Depression is common among autistic youth and has a significant negative impact on quality of life and day-to-day functioning. Despite great need for efficacious treatments, there are currently limited research-supported interventions for depression symptoms in autistic young people. This study tested a novel, behavior-based approach or psychotherapy for treatment of depression symptoms in autistic adolescents without intellectual disability (i.e. Behavioral Activation for Autistic Adolescents, BA-A) with 15 youth (11-16 years old). BA-A is an individually delivered 12-session therapy that was developed for and to meet the needs of autistic youth with depression. Results found that autistic youth and their caregivers were able to participate in BA-A therapy sessions, and clinicians were able to deliver BA-A in accordance with the treatment manual. Notably, results demonstrated that autistic youth depression symptoms significantly improved after participating in BA-A. Furthermore, anxiety symptoms and social skills significantly improved following BA-A.

Validation of a Behavioral Activation Model Including Self-Compassion: A Longitudinal Study at Three Time Points

INTRODUCTION

Depression is highly prevalent among university students. While behavioral activation has been shown to be an effective psychotherapy for depression, there is a lack of research regarding the behavioral activation mechanism. Furthermore, although self-compassion seems to be a factor in promoting behavioral activation, no studies have attempted to validate a behavioral activation model that includes positive self-compassion. In addition, mechanistic studies have lacked consideration in longitudinal studies of behavioral activation. Thus, in this longitudinal study, we constructed and validated an exploratory model of behavioral activation.

METHODS

A total of 300 undergraduate students completed online surveys in 2019, 2020, and 2021. We examined the longitudinal effects of five factors (value-based behavior, goal-oriented and scheduled activities, positive reinforcement, self-compassion, and depressive symptoms) using structural equation modeling based on maximum likelihood estimation using bootstrapping.

RESULTS

The exploratory model was found to be valid and to have a good fit with the data. The results indicate that value-based behaviors increase the frequency of goal-oriented and scheduled activities, which in turn increases the frequency of positive reinforcement in everyday life. Additionally, when self-compassion, value-based behavior, goal-oriented and scheduled activities, and positive reinforcement are considered together, self-compassion may be indirectly related to activation via value-based behavior.

CONCLUSION

From the perspective of preventing depressive symptoms, it is important to increase the frequency of value-based activities. Furthermore, adding self-compassion is effective in behavioral activation to increase value-based activities. However, to address the limitations of this study, future studies should investigate the relationship among behavioral characteristics during interventions.

Co-designing behavioural activation for depression for autistic adolescents: A case series

Autistic youth are at high risk of depression, but there are few psychological interventions that have been specifically designed for use with this population. Behavioural activation (BA) is a particularly promising approach for autistic adolescents, having an established evidence-base for the treatment of depression in non-autistic people, and with a strong focus on behavioural, rather than cognitive change, which is a challenge for some autistic people. In this study, we worked with autistic adolescents and clinicians to co-design a BA-informed intervention to be delivered in an online format. We then conducted a pilot case-series with seven autistic adolescents with depression. Our focus was on establishing the acceptability and feasibility of the intervention but clinical outcomes on both self- and parent-reported symptoms of depression and anxiety are also presented. Our results indicate the intervention to be acceptable and feasible for autistic adolescents, with six out of seven participants being retained to the end of the intervention. Qualitative feedback indicated that all participants found the intervention a positive experience and would recommend it to others. Similarly, all participants found the online format acceptable, with 64% preferring this format to face-to-face therapy. Qualitative feedback and suggestions for refinement will also be discussed.

Investigating the role of action-contingent expectancy biases in dysphoria-linked activity engagement behavioural choice

Reduced tendency to engage in potentially rewarding activities is a hallmark of depression. The present study investigated the role of future expectancy biases in depression-linked behavioural choice, in participants varying in self-reported depression symptoms (dysphoria). A novel laboratory paradigm was developed to test the hypotheses that the degree to which higher dysphoria is associated with reduced tendency to engage in a potentially rewarding activity is dependent on the presence of negative biases in the expected outcomes of activity engagement. Specifically, two types of expectancy biases were distinguished: a) the expected likelihood of a negative rather than positive outcome, and b) the expected emotional impact of either outcome. N = 176 undergraduate students with varied levels of dysphoria were given the opportunity to choose to engage in a coin-tossing game that could result in a win or loss monetary outcome in terms of charity donations, and then rated both types of expectancies. Results indicated that higher dysphoria was associated with more negative expectations concerning the likelihood of objective outcomes and the emotional impact of such outcomes, and as hypothesised, such negative expectancy biases mediated indirect associations between dysphoria and behavioural choice.

Transgender and Gender Diverse Patients in Intensive Mood Disorder Treatment: A Comparative Examination of Clinical Presentation and Treatment Outcomes

Individuals who are transgender and gender diverse (TGD) are more likely to suffer from and to seek mental health services for mood disorders. Some literature suggests that TGD individuals, because of pervasive and systemic minority stress, may have more complex clinical presentations (i.e., psychiatric conditions and severity of symptoms) and may benefit from empirically based treatments to a lesser degree than their cisgender peers. However, research has yet to examine individuals who are TGD receiving treatment in specialized, intensive mood disorder treatment despite the propensity for them to be diagnosed with and treated for mood disorders. Using a sample of 1,326 adult patients in intensive mood disorder treatment (3.8% TGD), the clinical presentation and treatment outcomes were compared between patients who are TGD and cisgender. Contrary to previous research, TGD patients were largely similar if not healthier than their cisgender counterparts, including similar depression severity, quality of life, emotion dysregulation, and behavioral activation, and less severe rumination at admission. Despite similar to better reported mental health symptoms, TGD patients were diagnosed with more psychiatric conditions overall, including greater prevalence of social anxiety and neurodevelopmental diagnoses. Those who are TGD did not experience attenuated treatment response as predicted. Findings suggest that patients in intensive mood disorder treatment who are TGD may be more resilient than previously assumed, or supports may have increased to buffer effects of stigma on mental health, and emphasize the need to exercise discretion and sensitivity in diagnostic practices to prevent over-diagnosis and pathologizing of TGD individuals.

Explaining the efficacy of an internet-based behavioral activation intervention for major depression: A mechanistic study of a randomized-controlled trial

Background

Behavioral activation is an effective treatment for depression that is theorized to facilitate structured increases in enjoyable activities that increase opportunities for contact with positive reinforcement; to date, however, only few mechanistic studies focused on a standalone intervention.

Method

Interventions using internet-based behavioral activation or psychoeducation were compared based on data from a randomized-controlled trial of 313 patients with major depressive disorder. Activation level and depression were measured fortnightly (baseline, Weeks 2, 4, 6, 8, 10), using the Patient Health Questionnaire-9 and the Behavioral Activation for Depression Scale-Short Form, respectively. Analysis was performed to determine if a change in activation level mediated treatment efficacy.

Results

Latent growth modeling showed that internet-based behavioral activation treatment significantly reduced depressive symptoms from baseline to the end of treatment (standardized coefficient = −.13, p = .017) by increasing the rate of growth in the activation level (mediated effect estimate = −.17, 95% CI [−.27, −.07]. Results from mixed effects and simplex models showed that it took 4 weeks before mediation occurred (i.e., a significant change in activation that led to a reduction in depressive symptoms).

Conclusion

Activation level likely mediated the therapeutic effect of behavioral activation on depression in our intervention. This finding may be of significant value to clinicians and depressed individuals who should anticipate a 4-week window before seeing a prominent change in activation level and a 6-week window before depressive symptomatology reduces. Future research must consolidate our findings on how behavioral activation works and when mediation occurs.

Enhanced Brief Motivational Intervention for College Student Drinkers With ADHD: Goal-Directed Activation as a Mechanism of Change

College students with attention-deficit/hyperactivity disorder (ADHD) are at risk for alcohol-related problems and disorders relative to their typically developing peers. Despite risk, the optimal therapeutic approach for reducing problem alcohol use in students with ADHD, and mechanisms of change underlying treatment effects in this population, are largely unknown. The current study evaluated putative mechanisms of change in a randomized controlled trial of two harm reduction interventions for college student drinkers with ADHD (N = 113; 49% male): brief motivational intervention plus supportive counseling (BMI + SC) versus brief motivational intervention plus behavioral activation (BMI + BA). Results showed that participants in the BMI + BA condition engaged in more goal-directed activation and less avoidant behavior over the course of treatment compared to those in the BMI + SC condition, in turn predicting reductions in alcohol-related negative consequences. Effects were more robust 1 month following intervention, and diminished by 3 months. Sensitivity analyses revealed a significant indirect effect of treatment condition on alcohol-related negative consequence via reductions in avoidance over treatment. Post hoc moderated mediations showed that BMI + BA engaged target mechanisms more robustly for students with more severe ADHD and depressive symptoms compared to BMI + SC. These findings support the application of BMI + BA intervention, particularly in targeting goal-directed activation and avoidance/rumination in at-risk student drinkers with ADHD.

Unraveling the comorbidity of depression and anxiety in a large inpatient sample: Network analysis to examine bridge symptoms

BACKGROUND

Comorbidities in mental disorders are often understood by assuming a common cause. The network theory of mental disorders offers an alternative to this assumption by understanding comorbidities as mutually reinforced problems. In this study, we used network analysis to examine bridge symptoms between anxiety and depression in a large sample.

METHOD

Using data from a sample of patients diagnosed with both depression and an anxiety disorder before and after inpatient treatment (N = 5,614, mean age: 42.24, 63.59% female, average treatment duration: 48.12 days), network models of depression and anxiety symptoms are estimated. Topology, the centrality of nodes, stability, and changes in network structure are analyzed. Symptoms that drive comorbidity are determined by bridge node analysis. As an alternative to network communities based on categorical diagnosis, we performed a community analysis and propose empirically derived symptom subsets.

RESULTS

The obtained network models are highly stable. Sad mood and the inability to control worry are the most central. Psychomotor agitation or retardation is the strongest bridge node between anxiety and depression, followed by concentration problems and restlessness. Changes in appetite and suicidality were unique to depression. Community analysis revealed four symptom groups.

CONCLUSION

The estimated network structure of depression and anxiety symptoms proves to be highly accurate. Results indicate that some symptoms are considerably more influential than others and that only a small number of predominantly physical symptoms are strong candidates for explaining comorbidity. Future studies should include physiological measures in network models to provide a more accurate understanding.

Maintaining Outcomes of Internet-Delivered Cognitive-Behavioral Therapy for Depression: A Network Analysis of Follow-Up Effects

Background: Depression is a highly prevalent mental disorder, but only a fraction of those affected receive evidence-based treatments. Recently, Internet-based interventions were introduced as an efficacious and cost-effective approach. However, even though depression is a heterogenous construct, effects of treatments have mostly been determined using aggregated symptom scores. This carries the risk of concealing important effects and working mechanisms of those treatments. Methods: In this study, we analyze outcome and long-term follow-up data from the EVIDENT study, a large (N = 1,013) randomized-controlled trial comparing an Internet intervention for depression (Deprexis) with care as usual. We use Network Intervention Analysis to examine the symptom-specific effects of the intervention. Using data from intermediary and long-term assessments that have been conducted over 36 months, we intend to reveal how the treatment effects unfold sequentially and are maintained. Results: Item-level analysis showed that scale-level effects can be explained by small item-level effects on most depressive symptoms at all points of assessment. Higher scores on these items at baseline predicted overall symptom reduction throughout the whole assessment period. Network intervention analysis offered insights into potential working mechanisms: while deprexis directly affected certain symptoms of depression (e.g., worthlessness and fatigue) and certain aspects of the quality of life (e.g., overall impairment through emotional problems), other domains were affected indirectly (e.g., depressed mood and concentration as well as activity level). The configuration of direct and indirect effects replicates previous findings from another study examining the same intervention. Conclusions: Internet interventions for depression are not only effective in the short term, but also exert long-term effects. Their effects are likely to affect only a small subset of problems. Patients reporting these problems are likely to benefit more from the intervention. Future studies on online interventions should examine symptom-specific effects as they potentially reveal the potential of treatment tailoring. Clinical Trial Registration: ClinicalTrials.gov, Identifier: NCT02178631.

Introduction to the Special Issue: Mechanisms of Action in Cognitive-Behavior Therapy

Research into mechanisms of treatment outcome in cognitive-behavior therapy (CBT), as work evaluating potential mechanisms through mediator and moderator analyses, has been increasing. In recognition of this growth in more refined analyses of functional components of treatment, this special issue highlights a diverse range of research-evaluating mechanisms, as well as mediators and moderators, of outcome. It is anticipated that the research described in these articles will stimulate additional investigations as well as provide important insights for clinicians in refining treatment programs.