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Invited Commentary
June 29, 2018

It Is Time to Invest in the Prevention of Depression

Author Affiliations
  • 1Behavioral Health Promotion and Technology Lab, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Bavaria, Germany
  • 2Department of Clinical Psychology, Vrije Universiteit, Amsterdam, the Netherlands
JAMA Netw Open. 2018;1(2):e180335. doi:10.1001/jamanetworkopen.2018.0335

In the article “Problem-Solving Education to Prevent Depression Among Low-Income Mothers,”1 Silverstein and colleagues investigate potential mechanisms of action for a psychological preventive intervention in low-income mothers. The study described is a secondary analysis of a well-conducted randomized clinical trial with intensive assessment during the follow-up period and very low study dropout. Core findings indicate that, although the authors investigated a broad range of theory-driven putative mediators, the mechanism for the intervention’s impact on the development of future depressive episodes remained largely unexplained. This is a timely and highly significant topic. More of this kind of research is needed.

Depression is a major public health issue and is projected to become the leading cause of disability worldwide by 2030. Traditionally, psychological and psychiatric intervention research has focused on the development and evaluation of curative interventions. However, despite decades of research, many patients do not respond to current treatments. Moreover, most affected individuals around the globe, including high-income countries, remain untreated.2 Research shows that these low treatment uptake rates are caused not only by gaps in treatment availability, but also by attitudinal barriers such as fear of stigma or a preference to solve problems on one’s own. When assuming the hypothetical scenario of 100% coverage and compliance with evidence-based treatments, modeling studies show that only approximately one-third of the disease burden associated with major depressive disorder (MDD) could be averted.3 Clearly, new approaches are needed to tackle the immense burden associated with depression.

Until recently, prevention of depression was deemed impossible. In their 2012 American Psychologist article “Major Depression Can Be Prevented,” Muñoz et al quote a National Institute of Mental Health publication from 1984 stating that “the onset of a clinical depression cannot be prevented.”4 Since then, a considerable number of trials have provided clear-cut evidence that this assumption was not true. A systematic review of psychological interventions for the prevention of MDD found that interventions were able to reduce the risk of MDD by 21% on average compared with control groups.5 A recent study shows that such interventions can also be effectively delivered remotely, using an internet-based self-help intervention.6 Using digital interventions might help not only to reach individuals who are not willing to use face-to-face interventions, but also to quickly make these treatments widely available around the globe. Health economic outcome evaluations indicate that focusing on preventing depression, instead of waiting until the full-blown disorder occurs, can provide a good return on investment even in the short term.7 Preventive interventions cost less than the accepted willingness to pay threshold for 1 additional quality-adjusted life-year and less than many accepted depression treatments.

However, compared with treatment research, the number of trials examining the efficacy of preventive psychological interventions is still rather small. Even fewer studies examine the important questions of what mechanisms make these interventions work, who might benefit from them, and who does not. More studies are needed to examine the best procedure for prevention as well as relevant mechanisms and moderators of intervention outcome.

It remains unknown through which specific mechanisms such interventions work. Do they mainly work through a reduction of risk factors, or by supporting protective factors, such as mastery and self-efficacy? They might also be effective simply by enabling individuals to cope with early symptoms of depression and thereby prevent the development of more severe symptoms. It is also possible that mechanisms vary across patients. The same intervention may work through different mechanisms in different participants, and there may be interactions between risk factors and protective factors. Another possibility that has, to our knowledge, not been examined yet is that some interventions work simply through the activation of a variety of self-help skills participants already possess.

Identification of mechanisms is an important step toward increasing the benefits of current intervention approaches. Although the potential of both selective and indicated preventive approaches has been clearly documented, there is still much room for improvement. Although preventive interventions have been found to significantly reduce the incidence of MDD, a considerable number of participants still develop depression.

One problem in examining mediators of intervention outcome is statistical power. Randomized clinical trials are typically designed to examine the direct efficacy of an intervention. Testing indirect effects, such as mechanisms of change, requires much larger sample sizes. This holds even truer when interactions between patient characteristics, eg, preexisting risk factors, with specific mechanisms are considered. This may be one of the reasons why such important research questions are seldom examined and rarely replicated, and why authors often do not consider these questions in their research designs. Another problem is that when such variables are examined, different instruments are used to measure them, making comparisons between studies impossible.

Individual participant data meta-analyses, in which the primary data of individual trials are pooled, allow sufficient power to examine such issues and to address research questions that have not been examined in the primary trials. Such approaches have rarely been applied in the field of psychological outcome research. To exploit the potential of this approach, it is necessary that authors include relevant measures to assess both potential specific intervention mechanisms and general unspecific mediators, as we have described. We therefore encourage researchers to include putative mediators in their trials to bring the field forward in a joint effort.

In addition to exploring mechanisms of treatment effects in general, we must also examine the interaction of effects of specific interventions and mediators of these effects with baseline characteristics of participants to select the best possible intervention for an individual. This is an important way of optimizing outcomes. Hence, we also encourage prevention researchers to assess in their randomized trials a broad set of participant characteristics at baseline, which will help to further advance the field of depression prevention research by using pooled data of several trials.

For the field of depression prevention, we recommend a broad assessment of (1) variables that predict differential treatment outcome in psychological treatments for depression in general; (2) risk factors associated with depression onset; and (3) protective factors that buffer the effect of specific risk factors. Examples of these variables include depression severity, previous MDD episodes, anxiety, comorbid mental health disorders, exposure to depression treatment, family history of mental disorders, functioning, sleep problems, neuroticism, recent life stress, childhood adversities, daily hassles, emotion regulation, quality of life, self-esteem, mastery, worrying, rumination, interpersonal problems, body dissatisfaction, physical activity, alcohol and/or substance use, resilience, and perceived social rejection.

Such a strategy might increase the effects of current preventive efforts for depression and may help to harness the tremendous potential of psychological interventions in reducing the immense disease burden associated with MDD.

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Article Information

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2018 Ebert DD et al. JAMA Network Open.

Corresponding Author: David Daniel Ebert, PhD, Clinical Psychology and Psychotherapy, Friedrich-Alexander-University of Erlangen-Nurnberg, Nagelsbachstrasse 25a, Erlangen, Bavaria 90152, Germany (david.ebert@fau.de).

Conflict of Interest Disclosures: Dr Ebert reported grants from the European Union’s Horizon 2020 program and grants from BARMER during the conduct of the study and other support from the GET.ON Institute, personal fees from Techniker Krankenkasse, personal fees from Minddistrict, personal fees from Lantern Inc, grants from BARMER, grants from the German Ministry for Education and Research, grants from the European Union’s Horizon 2020 program, and grants from the Deutsche Forschungsgemeinschaft outside the submitted work. No other disclosures were reported.

Silverstein  M, Cabral  H, Hegel  M,  et al.  Problem-solving education to prevent depression among low-income mothers: a path mediation analysis in a randomized clinical trial.  JAMA Netw Open. 2018;1(2):e180334. doi:10.1001/jamanetworkopen.2018.0334Google ScholarCrossref
Andrade  LH, Alonso  J, Mneimneh  Z,  et al.  Barriers to mental health treatment: results from the WHO World Mental Health Surveys.  Psychol Med. 2014;44(6):1303-1317. PubMedGoogle ScholarCrossref
Andrews  G, Issakidis  C, Sanderson  K, Corry  J, Lapsley  H.  Utilising survey data to inform public policy: comparison of the cost-effectiveness of treatment of ten mental disorders.  Br J Psychiatry. 2004;184:526-533.PubMedGoogle ScholarCrossref
Muñoz  RF, Beardslee  WR, Leykin  Y.  Major depression can be prevented.  Am Psychol. 2012;67(4):285-295. PubMedGoogle ScholarCrossref
van Zoonen  K, Buntrock  C, Ebert  DD,  et al.  Preventing the onset of major depressive disorder: a meta-analytic review of psychological interventions.  Int J Epidemiol. 2014;43(2):318-329. PubMedGoogle ScholarCrossref
Buntrock  C, Ebert  DD, Lehr  D,  et al.  Effect of a web-based guided self-help intervention for prevention of major depression in adults with subthreshold depression: a randomized clinical trial.  JAMA. 2016;315(17):1854-1863. PubMedGoogle ScholarCrossref
Mihalopoulos  C, Vos  T, Pirkis  J, Carter  R.  The economic analysis of prevention in mental health programs.  Annu Rev Clin Psychol. 2011;7(1):169-201. PubMedGoogle ScholarCrossref
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