Examining the Theoretical Framework of Behavioral Activation for Major Depressive Disorder: Smartphone-Based Ecological Momentary Assessment Study

Claire Rosalie van Genugten, Josien Schuurmans, Adriaan W Hoogendoorn, Ricardo Araya, Gerhard Andersson, Rosa Baños, Cristina Botella, Arlinda Cerga Pashoja, Roman Cieslak, David Daniel Ebert, Azucena García-Palacios, Jean-Baptiste Hazo, Rocío Herrero, Jérôme Holtzmann, Lise Kemmeren, Annet Kleiboer, Tobias Krieger, Ewelina Smoktunowicz, Ingrid Titzler, Naira Topooco, Antoine Urech, Johannes H Smit, Heleen Riper, Claire Rosalie van Genugten, Josien Schuurmans, Adriaan W Hoogendoorn, Ricardo Araya, Gerhard Andersson, Rosa Baños, Cristina Botella, Arlinda Cerga Pashoja, Roman Cieslak, David Daniel Ebert, Azucena García-Palacios, Jean-Baptiste Hazo, Rocío Herrero, Jérôme Holtzmann, Lise Kemmeren, Annet Kleiboer, Tobias Krieger, Ewelina Smoktunowicz, Ingrid Titzler, Naira Topooco, Antoine Urech, Johannes H Smit, Heleen Riper

Abstract

Background: Behavioral activation (BA), either as a stand-alone treatment or as part of cognitive behavioral therapy, has been shown to be effective for treating depression. The theoretical underpinnings of BA derive from Lewinsohn et al's theory of depression. The central premise of BA is that having patients engage in more pleasant activities leads to them experiencing more pleasure and elevates their mood, which, in turn, leads to further (behavioral) activation. However, there is a dearth of empirical evidence about the theoretical framework of BA.

Objective: This study aims to examine the assumed (temporal) associations of the 3 constructs in the theoretical framework of BA.

Methods: Data were collected as part of the "European Comparative Effectiveness Research on Internet-based Depression Treatment versus treatment-as-usual" trial among patients who were randomly assigned to receive blended cognitive behavioral therapy (bCBT). As part of bCBT, patients completed weekly assessments of their level of engagement in pleasant activities, the pleasure they experienced as a result of these activities, and their mood over the course of the treatment using a smartphone-based ecological momentary assessment (EMA) application. Longitudinal cross-lagged and cross-sectional associations of 240 patients were examined using random intercept cross-lagged panel models.

Results: The analyses did not reveal any statistically significant cross-lagged coefficients (all P>.05). Statistically significant cross-sectional positive associations between activities, pleasure, and mood levels were identified. Moreover, the levels of engagement in activities, pleasure, and mood slightly increased over the duration of the treatment. In addition, mood seemed to carry over, over time, while both levels of engagement in activities and pleasurable experiences did not.

Conclusions: The results were partially in accordance with the theoretical framework of BA, insofar as the analyses revealed cross-sectional relationships between levels of engagement in activities, pleasurable experiences deriving from these activities, and enhanced mood. However, given that no statistically significant temporal relationships were revealed, no conclusions could be drawn about potential causality. A shorter measurement interval (eg, daily rather than weekly EMA reports) might be more attuned to detecting potential underlying temporal pathways. Future research should use an EMA methodology to further investigate temporal associations, based on theory and how treatments are presented to patients.

Trial registration: ClinicalTrials.gov, NCT02542891, https://ichgcp.net/clinical-trials-registry/NCT02542891; German Clinical Trials Register, DRKS00006866, https://tinyurl.com/ybja3xz7; Netherlands Trials Register, NTR4962, https://www.trialregister.nl/trial/4838; ClinicalTrials.Gov, NCT02389660, https://ichgcp.net/clinical-trials-registry/NCT02389660; ClinicalTrials.gov, NCT02361684, https://ichgcp.net/clinical-trials-registry/NCT02361684; ClinicalTrials.gov, NCT02449447, https://ichgcp.net/clinical-trials-registry/NCT02449447; ClinicalTrials.gov, NCT02410616, https://ichgcp.net/clinical-trials-registry/NCT02410616; ISRCTN registry, ISRCTN12388725, https://www.isrctn.com/ISRCTN12388725.

Keywords: EMA; behavior; behavioral activation; depression; ecological momentary assessment; engagement; framework; mental health; mood; random-intercept cross-lagged panel model; smartphone; theoretical framework; treatment.

Conflict of interest statement

Conflicts of Interest: DDE has served as a consultant to/on the scientific advisory boards of Sanofi, Novartis, Minddistrict, Lantern, Schoen Klinike, Ideamed and German health insurance companies (BARMER, Techniker Krankenkasse) and a number of federal chambers for psychotherapy. He is also stakeholder of the Institute for health training online (formerly GET.ON/ now HelloBetter), which aims to implement scientific findings related to digital health interventions into routine care. IT reports to have received fees for lectures/workshops in the e-mental-health context from training institutes for psychotherapists. All other authors declare that they have no conflicts of interest.

©Claire Rosalie van Genugten, Josien Schuurmans, Adriaan W Hoogendoorn, Ricardo Araya, Gerhard Andersson, Rosa Baños, Cristina Botella, Arlinda Cerga Pashoja, Roman Cieslak, David Daniel Ebert, Azucena García-Palacios, Jean-Baptiste Hazo, Rocío Herrero, Jérôme Holtzmann, Lise Kemmeren, Annet Kleiboer, Tobias Krieger, Ewelina Smoktunowicz, Ingrid Titzler, Naira Topooco, Antoine Urech, Johannes H Smit, Heleen Riper. Originally published in JMIR Mental Health (https://mental.jmir.org), 06.12.2021.

Figures

Figure 1
Figure 1
Circles of depression and BA based on the theoretical framework of depression by Lewinsohn et al [14,15]. BA: behavioral activation.
Figure 2
Figure 2
RI-CLPM for 4 measurement points. α and ζ are autoregressive regression coefficients; γ and δ are same-week (residual) covariances, β and ε are cross-lagged regression coefficients, and η is between-person correlation. Based on Hamaker, Kuiper, and Grasman [55]. RI: random intercept; RI-CLPM: random-intercept cross-lagged panel model.
Figure 3
Figure 3
Simplified RI-CLPM engaging in pleasant activities and experiencing pleasure. The between-person double-headed arrow represents a correlation. Within-person double-headed arrows represent (residual) covariances; single-headed arrows display standardized regression coefficients. Light-gray arrows represent nonsignificant covariances/coefficients. *P<.001, **P=.01, ***P=.02. A: activity; P: pleasure; RI: Random Intercept; RI-CLPM: random-intercept cross-lagged panel model.
Figure 4
Figure 4
Simplified RI-CLPM experiencing pleasure and mood. The between-person double-headed arrow represents a correlation. Within-person double-headed arrows represent (residual) covariances; single-headed arrows display standardized regression coefficients. Light-gray arrows represent nonsignificant covariances/coefficients. *P<.001, **P=.01. M: mood; P: pleasure; RI: Random Intercept; RI-CLPM: random-intercept cross-lagged panel model.
Figure 5
Figure 5
Simplified RI-CLPM mood and engaging in pleasant activities. The between-person double-headed arrow represents a correlation. Within-person double-headed arrows represent (residual) covariances; single-headed arrows display standardized regression coefficients. Light-gray arrows represent nonsignificant covariances/coefficients. *P<.001, **P=.02. A: activity; M: mood; RI: Random Intercept; RI-CLPM: random-intercept cross-lagged panel model.

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