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The Temporal Associations of Therapeutic Alliance and Manual Adherence With Depressive Symptom Change in Cognitive Behavioral Therapy for Adult Outpatient Major Depression.

ABSTRACT: Background: The therapeutic alliance is considered an important causal agent of psychotherapy efficacy. However, studies in cognitive behavioral therapy (CBT) for depression have suggested that alliance might be more of a consequence rather than a cause of depressive symptom change, while adherence to CBT specific techniques was found to be associated with subsequent depression change. We aimed to add to this body of literature by assessing the temporal associations of both therapeutic alliance and manual adherence with depressive symptom change in a relatively large sample of depressed adult outpatients over the full course of CBT. Methods: Adults with a major depressive episode (n = 98) participating in a randomized clinical trial were offered 22 weeks of CBT and rated the Penn Helping Alliance Questionnaire (HAq-I) at weeks 5 and 22. Therapists rated their adherence to the CBT manual after each session and observers assessed the Hamilton Depression Rating Scale scores at weeks 0, 5, 10, and 22. Linear mixed model analyses were used to assess the associations of alliance and adherence with prior and subsequent depression change. Results: HAq-I Relationship and manual adherence ratings were not significantly associated with prior nor with subsequent depression change (p > 0.14). Prior depression change was associated with the HAq-I subscale Perceived helpfulness at the end of treatment (r = 0.30, CI = 0.03-0.56, p = 0.03). Conclusion: We were not able to replicate prior depression change in CBT for depression to be associated with improved quality of the therapeutic alliance when using a more "pure" measure of the therapeutic relationship. Limitations of this study include the subjective alliance and adherence assessments. Our findings indicate the need to appropriately distinguish between the perceived helpfulness and the relationship factors when examining therapeutic alliance.

SUBMITTER: Don FJ

PROVIDER: S-EPMC7838346 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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The Temporal Associations of Therapeutic Alliance and Manual Adherence With Depressive Symptom Change in Cognitive Behavioral Therapy for Adult Outpatient Major Depression.

Don Frank J FJ Driessen Ellen E Peen Jaap J Spijker Jan J DeRubeis Robert J RJ Blankers Matthijs M Dekker Jack J M JJM

Frontiers in psychiatry 20210113

<b>Background:</b> The therapeutic alliance is considered an important causal agent of psychotherapy efficacy. However, studies in cognitive behavioral therapy (CBT) for depression have suggested that alliance might be more of a consequence rather than a cause of depressive symptom change, while adherence to CBT specific techniques was found to be associated with subsequent depression change. We aimed to add to this body of literature by assessing the temporal associations of both therapeutic al ...[more]

PMID: 33519551

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Project description:BackgroundDepressive and anxiety disorders are the most common mental disorders, and there is a critical need for effective, affordable, and accessible interventions. Cognitive Behavioral Immersion (CBI) is a novel group-based cognitive behavioral skills training program delivered by lay coaches in the metaverse that can be accessed through various modalities including virtual reality (VR) head-mounted displays or flat-screen devices. Combining its ability to offer empirically supported therapy skills in a digital setting that can still facilitate interpersonal variables (eg, working alliance and sense of social support) with the aid of lay coaches, CBI has the potential to help fill this critical need.ObjectiveThis study had 2 primary aims. First, we aimed to examine changes in depression and anxiety symptoms in a sample of individuals who participated in CBI. Second, we aimed to examine 2 interpersonal process variables (working alliance and web-based social support) as predictors of symptom changes. We predicted CBI participants would experience depression and anxiety symptom improvements and that such improvements would be associated with an increase in both interpersonal process variables.MethodsThe study sample consists of 127 participants who endorsed clinical levels of depression or anxiety symptoms during their first CBI session and attended at least 2 sessions. Participants were asked to complete self-report measures of depression symptoms, anxiety symptoms, alliance, and web-based social support throughout their participation in CBI.ResultsRepeated measures ANOVAs determined that depression and anxiety symptom scores differed significantly across sessions (Ps<.01). We also found participants' web-based social support predicted improvement in depression symptoms (P=.01), but neither the alliance nor web-based social support predicted change in anxiety symptoms (Ps>.05). We also observed a significant difference in anxiety symptoms between participants who used a VR head-mounted display to access CBI and those who did not, such that participants who used VR head-mounted displays endorsed lower anxiety symptoms than those who did not at nearly every session (P=.04).ConclusionsParticipation in CBI is associated with both depression and anxiety symptom improvement. Web-based social support may play an important role in fostering changes in depression symptoms. Future studies are encouraged to continue examining the process of change in CBI with special attention paid to methods that can elucidate causal mechanisms of change.

Project description:ImportanceMajor depressive disorder is prevalent and impairing. Parsing neurocomputational substrates of reinforcement learning in individuals with depression may facilitate a mechanistic understanding of the disorder and suggest new cognitive therapeutic targets.ObjectiveTo determine associations among computational model-derived reinforcement learning parameters, depression symptoms, and symptom changes after treatment.Design, setting, and participantsIn this mixed cross-sectional-cohort study, individuals performed reward and loss variants of a probabilistic learning task during functional magnetic resonance imaging at baseline and follow-up. A volunteer sample with and without a depression diagnosis was recruited from the community. Participants were assessed from July 2011 to February 2017, and data were analyzed from May 2017 to May 2021.Main outcomes and measuresComputational model-based analyses of participants' choices assessed a priori hypotheses about associations between components of reward-based and loss-based learning with depression symptoms. Changes in both learning parameters and symptoms were then assessed in a subset of participants who received cognitive behavioral therapy (CBT).ResultsOf 101 included adults, 69 (68.3%) were female, and the mean (SD) age was 34.4 (11.2) years. A total of 69 participants with a depression diagnosis and 32 participants without a depression diagnosis were included at baseline; 48 participants (28 with depression who received CBT and 20 without depression) were included at follow-up (mean [SD] of 115.1 [15.6] days). Computational model-based analyses of behavioral choices and neural data identified associations of learning with symptoms during reward learning and loss learning, respectively. During reward learning only, anhedonia (and not negative affect or arousal) was associated with model-derived learning parameters (learning rate: posterior mean regression β = -0.14; 95% credible interval [CrI], -0.12 to -0.03; outcome sensitivity: posterior mean regression β = 0.18; 95% CrI, 0.02 to 0.37) and neural learning signals (moderation of association between striatal prediction error and expected value signals: t97 = -2.10; P = .04). During loss learning only, negative affect (and not anhedonia or arousal) was associated with learning parameters (outcome shift: posterior mean regression β = -0.11; 95% CrI, -0.20 to -0.01) and disrupted neural encoding of learning signals (association with subgenual anterior cingulate prediction error signals: r = -0.28; P = .005). Symptom improvement following CBT was associated with normalization of learning parameters that were disrupted at baseline (reward learning rate: posterior mean regression β = 0.15; 90% CrI, 0.001 to 0.41; loss outcome shift: posterior mean regression β = 0.42; 90% CrI, 0.09 to 0.77).Conclusions and relevanceIn this study, the mapping of reinforcement learning components to symptoms of major depression revealed mechanistic features associated with these symptoms and points to possible learning-based therapeutic processes and targets.

Project description:Background: Depression and anxiety are the most common comorbid psychiatric disorders in the elderly. Psychiatrists have been reporting worsened depression symptoms and prognosis by comorbid anxiety symptoms. However, it is still unclear how anxiety affects the course of depression in the elderly. The aims of this study are (1) to identify the symptom network in late-life depression (LLD), and (2) to examine the role of anxiety in LLD with a network perspective. Methods: The study analyzed 776 community-based participants who were clinically diagnosed with depression and enrolled in Suwon Geriatric Mental Health Center. Network analysis was used to investigate the relationships between the symptoms of the Montgomery-Åsberg Depression Rating Scale (MADRS). The depression sample was divided into groups of low and high anxiety according to the Beck Anxiety Index. Propensity score matching (PSM) was used to minimize the effects of depression severity on the network. Network comparison test (NCT) were carried out to compare the global connectivity, global strength, and specific edge strength between the two subgroups. Results: Reported sadness, pessimistic thinking, and suicidal ideation are the core symptoms of LLD in terms of node strength. The MADRS sum score [mean (SD) 28.10 (9.19) vs 20.08 (7.11); P < .01] was much higher in the high anxiety group. The NCT before PSM showed the high anxiety group had significantly higher global strength (P < .01). However, the NCT after PSM did not reveal any statistical significance both in global structure (P = .46) and global strength (P = .26). A comparison between centrality indices showed a higher node strength of vegetative symptoms in the high anxiety group and this also remained after PSM. Conclusion: Based on the statistical analysis, anxiety worsens the severity of depression in the elderly. However, NCT after PSM revealed comorbid anxiety does not change the global structure and strength of the depression symptom network. Therefore, anxiety may affect LLD in a way of worsening the severity, rather than changing psychopathology. Additionally, the study revealed the centrality of vegetative symptoms was low in LLD but increased substantially in patients with comorbid anxiety.

Dataset Information

The Temporal Associations of Therapeutic Alliance and Manual Adherence With Depressive Symptom Change in Cognitive Behavioral Therapy for Adult Outpatient Major Depression.

Publications

The Temporal Associations of Therapeutic Alliance and Manual Adherence With Depressive Symptom Change in Cognitive Behavioral Therapy for Adult Outpatient Major Depression.

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