Psychotherapy for depression: enhancing positive and reducing negative affect?

190078748_d8e3d76813_o

Evidence from over 350 randomised controlled trials (RCTs) indicates that a broad variety of psychotherapeutic interventions effectively reduce depressive symptoms (Cuijpers, van Straten, Andersson, & van Oppen, 2008).

Additionally, research suggests that affect can be divided into two separate dimensions: positive affect (PA) and negative affect (NA) (Watson & Tellegan, 1985). Furthermore, studies indicate that decreased PA is associated with sadness, lack of energy, inattententiveness, and lack of interest; key indicators of depression (Clark & Watson, 1991). Conversely, greater PA may operate as a source of resilience in buffering stress levels, therefore providing a protective factor against depressive symptoms (Steptoe & Wardle, 2005).

In support of this, a 2012 study by Hofmann presented a trans-diagnostic model suggesting that mood (and anxiety) disorders are a result of dysregulated NA and decreased PA. However to date, there has been no systematic review on the impact of these psychotherapeutic interventions on negative and positive affect dimensions in depression.

The present study by Boumparis, Karyotaki, Kleiboer, Hofmann, & Cuijpers (2016) aimed to rectify this gap in the literature by examining the effect of psychotherapy on negative affect (NA) and positive affect (PA) in adults with depression. The authors anticipated that psychotherapy would be significantly associated with a decrease in NA and an increase in PA. In support of Hofmann’s 2012 findings, the authors also anticipated that changes in depression would be primarily associated with an increase in PA.

Positive affect refers to positive moods such as joy, interest, and alertness. Negative affect refers to unpleasant feelings or emotions such as sadness, fear and anger.

Positive affect refers to positive moods such as joy, interest and alertness. Negative affect refers to unpleasant feelings or emotions such as sadness, fear and anger.

Methods

A systematic review incorporating all randomised controlled trials (RCTs) of psychotherapeutic-based interventions for adults with depression was conducted, using an existing database which was developed and updated utilising a systematic literature search of the Cochrane Central Register of Controlled Trials, PubMed, PsycINFO, and EMBASE, from 1996 to December 31st, 2014. An additional systematic search for studies published from January 1st, 2015 to December 31st, 2015 was also conducted.

Inclusion criteria

  • Randomised Controlled Trials (RCTs) comparing psychotherapeutic interventions with waiting lists, psycho-education, or placebos
  • Participants must be adults with depression based on a clinical interview or validated self-report scale
  • All studies must include the measurement of participants’ PA and NA levels at baseline and post-intervention as assessed via a validated self-report scale.

Quality assessment

The validity of the included studies was assessed according to the criteria of the Cochrane Risk of Bias Assessment Tool, which includes an assessment of the following:

  • Participant randomisation sequence (treatment versus control)
  • Adequate concealment of treatment allocation
  • Blinding of participants and personnel to treatment conditions
  • Blinding of outcome assessors to participant treatment allocation
  • Handling of incomplete outcome data
  • Selective outcome reporting.
This study reviewed all of the high quality trials that explore the impact that psychotherapy has on negative and positive affect in adults with depression.

This study reviewed all of the high quality trials that explore the impact that psychotherapy has on negative and positive affect in adults with depression.

Results

From 18,114 abstracts (12,364 after duplicate removal), 1,769 full-text papers were selected for possible inclusion. A further 1,759 were excluded as they did not meet the inclusion criteria, resulting in 10 RCTs reporting on PA and NA outcomes for adults with depression. A total of 793 participants were included (386 treatment condition and 407 control condition) of which 76% were female.

Effect sizes were calculated from the variation in pre- and post- PA and NA outcome scores, and standardised using change scores. The program Comprehensive Meta-Analysis (CMA: version 2.2.021) was used to calculate pooled mean effect sizes. A random effects model was used to account for heterogeneity across the included studies as this statistical model assumes that the included studies were drawn from populations of studies systematically different from each other.

Effect of psychotherapeutic interventions on positive affect

  • Psychotherapeutic interventions resulted in significantly increased PA (g = 0.41; 95% CI: 0.16 to 0.66, p = 0.001)
  • The I-square test indicated substantial heterogeneity amongst included studies (I2 = 59; 95% CI: 16 to 79, p = 0.010).

Effect of psychotherapeutic interventions on negative affect

  • Psychotherapeutic interventions resulted in significantly decreased NA (g = 0.32; 95% CI: 0.15 to 0.78, p = 0.001).
  • After the exclusion of one outlying study, the I-square test indicated low heterogeneity amongst included studies (I2 = 0; 95% CI: 0 to 65, p = 0.484).

Depressive symptoms

  • Psychotherapeutic interventions resulted in significantly decreased depressive symptoms (g = 0.38; 95% CI: 0.14 to 0.62, p = 0.002)
  • The I-square test indicated moderate heterogeneity amongst included studies (I2 = 47; 95% CI: 0 to 75, p = 0.056).

Subgroup and sensitivity analysis

  • Subgroup analysis demonstrated no significant differences between study characteristics and effect sizes for PA and NA outcomes
  • To conduct a sensitivity analysis, studies which applied non-conventional psychotherapeutic treatments were removed (to aid comparability between conventional major types of psychotherapeutic interventions) resulting in a decreased effect size for PA (g = 0.37, p = 0.007) and significantly decreased effect size for NA (g = 0.29, p = 0.01).

Association of depressive symptoms with PA and NA

  • The small number and heterogeneity of the included studies meant the meta-regression analysis produced conflicting results and consequently, the authors were unable to effectively demonstrate any relationship between depressive symptoms with PA and NA.
Findings demonstrated low-to-moderate effects for psychotherapeutic interventions in enhancing positive affect and decreasing negative affects in adults with depression.

Findings demonstrated low-to-moderate effects for psychotherapies in enhancing positive affect and decreasing negative affect in adults with depression.

Conclusions

Consistent with the authors’ hypotheses, psychotherapeutic interventions increased PA and decreased NA in depressed adults (small-to-moderate effect). However, conflicting results from the meta-regression analyses rendered the authors unable to demonstrate sufficient evidence as to whether or not depressive symptoms, and PA and NA are associated with each other.

The authors summarise that:

PA and NA levels might be significant factors moderating the efficacy of psychotherapeutic interventions for depressive symptoms and should be assessed in clinical settings as secondary variables besides depressive symptoms.

Strengths and limitations

The systematic review and meta-analysis were carried out to a high standard according to best practice. Unfortunately, perhaps due to the heterogeneity in methodological practices across the included studies, the authors were unable to statistically determine whether an association exists between depressive symptoms with PA and NA. This is a major limitation of the study as one of the main objectives was to determine the impact of psychotherapeutic interventions on these affective dimensions in relation to depression.

The authors acknowledge the potential methodological issues of their study including the varying quality and variety of included psychotherapeutic interventions (e.g., the type of intervention, clinical or community setting, format of therapy, different outcome measures, and varying definitions of depression). And in order to account for the considerable heterogeneity across studies, the authors used a random effects model when calculating mean effect sizes. Another strength worth noting is that in an attempt to ensure no relevant study was missing, the authors conducted additional searches by checking the references of the included studies.

The inclusion of a broad range of conventional treatments for depression is another strength of the Boumparis et al. (2016) study as the variety of treatment modalities analysed reflects the widely accepted intervention means amongst mental health professionals in the greater community. Nonetheless, it is also a major limitation as the evidence base for these interventions varies greatly. Building on from Hofmann’s (2012) work, it may be more informative for future research to compare PA and NA outcomes arising from the gold standard treatment for depression; cognitive-behavioural therapy (Carter, 2010), to that of other evidence-based treatment modalities (e.g., interpersonal therapy) and a control group, to identify the greatest relative benefit.

Additionally, understanding how a treatment works involves identifying the mechanisms of change, the specific processes by which the treatment produces outcomes. Future research should therefore also aim to investigate the potential mediators of affective treatment outcomes. For example, it may be that the therapeutic alliance (common to all psychotherapeutic modalities) statistically accounts for the treatment-outcome relationship, or alternatively addressing negative cognitions (often a candidate for treating internalising disorders in RCTs) impacts upon PA and NA domains differently.

Given the small number and heterogeneity of the included studies (treatment modalities and evidence-base) the findings should be considered with caution.

Given the small number and heterogeneity of the included studies (treatment modalities and evidence-base) the findings should be considered with caution.

Summary

The findings of Boumparis et al. (2016) systematic review and meta-analysis indicate low-to-moderate effects for psychotherapeutic interventions in enhancing PA and decreasing NA in adults with depression. However, given the small number and the heterogeneity of the included studies the findings should be considered with caution. The authors conclude the study by suggesting that future work should examine the impact of pharmacotherapy-only (often a sole treatment modality for many adults with depression) has on PA to determine whether the increase relapse rate is related to unaddressed PA.

Links

Primary paper

Boumparis N, Karyotaki E, Kleiboer A, Hofmann SG, Cuijpers P. (2016) The effect of psychotherapeutic interventions on positive and negative affect in depression: A systematic review and meta-analysis. Journal of Affective Disorders, Volume 202, 15 September 2016, Pages 153-162, ISSN 0165-0327 http://dx.doi.org/10.1016/j.jad.2016.05.019

Other references

Carter JD, Crowe M, Luty S, Mcintosh VV, Jordan J, Joyce P. (2010) Patient psychotherapy process in CBT and IPT for depression. Journal of Affective Disorders, 122, S42. doi.org/10.1016/j.jad.2010.02.028

Clark LA, Watson D. (1991) Tripartite model of anxiety and depression: Psychometric evidence and taxonomic implications. J. Abnorm. Psychol, 100, pp. 316–336. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/1918611

Cuijpers P, van Straten A, Andersson G, van Oppen P. (2008) Psychotherapy for depression in adults: A meta-analysis of comparative outcome studies. J. Consult. Clin. Psychol, 76, pp. 909–922 [PubMed Abstract]

Hofmann SG, Sawyer AT, Fang A, Asnaani A. (2012) Emotion dysregulation model of mood and anxiety disorders (PDF). Depression and Anxiety, 29(5), 409-416.

Steptoe A, Wardle J. (2005) Positive affect and biological function in everyday life. Neurobiol. Aging, 26, pp. 108–112. [PubMed Abstract]

Watson D, Tellegen A. (1985) Toward a consensual structure of mood. Psychol. Bull., 98, pp. 219–235. [APA PsychNet Abstract]

World Health Organization. (2012, October). Depression fact sheet. Retrieved from http://www.who.int/mediacentre/factsheets/fs369/en/

Photo credits

Share on Facebook Tweet this on Twitter Share on LinkedIn Share on Google+
Mark as read
Create a personal elf note about this blog
Profile photo of Carla McEnery

Carla McEnery

Carla McEnery is a Provisional Psychologist and final year PhD candidate (Clinical Psychology) based at the Centre of Mental Health (CMH), Swinburne University of Technology, Melbourne, Australia. Carla’s PhD is conducted in collaboration with Orygen, the National Centre of Excellence in Youth Mental Health, Melbourne, Australia and examines the clinical presentation and treatment of co-morbid social anxiety disorder (SAD) in first-episode psychosis. Specifically, Carla worked collaboratively with the eOrygen team to develop and pilot test a novel moderated online social therapy that utilizes graphic comics to treat co-morbid SAD in young individuals with a first-episode psychosis diagnosis. Carla is currently undertaking her final clinical placement within the Early Psychosis Prevention and Intervention Centre at Orygen Youth Mental Health, Melbourne, Australia. Her research and clinical areas of interest overlap and include: schizophrenia-spectrum disorders (first-episode psychosis), in addition to the assessment and treatment of SAD and social anxiety symptomatology. Other areas of interest and expertise include the assessment and treatment of anxiety and mood disorders, addressing mental-health related stigma (affective and cognitive consequences of shame), mindfulness and development of online psychosocial interventions. Carla previously completed a Bachelor of Psychological Science (First class Hons) at La Trobe University, Melbourne, Australia and has also completed studies in a wide range of disciplines including Philosophy, English Literature and Psychoanalysis. Prior to commencing her studies and ultimately changing her career path, Carla McEnery held a number of project management roles within the Financial Services and IT industries.

More posts

Follow me here –