The effects of once- versus twice-weekly sessions on psychotherapy outcomes in depressed patients

Bruijniks, Sanne J. E.; Lemmens, Lotte H.J.M.; Hollon, Steven D.; Peeters, Frenk; Cuijpers, Pim; Arntz, Arnoud; Dingemanse, Pieter; Willems, L.M.; Oppen, Patricia van; Twisk, Jos W. R.; Boogaard, Michael van den; Spijker, Jan; Bosmans, Judith E.; Huibers, Marcus J.H.

doi:10.1192/bjp.2019.265

Cited by 76 publications

(84 citation statements)

References 24 publications

(33 reference statements)

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“…In a recent meta-analysis summarizing data from 366 trials, Cuijpers and colleagues reported that "[psychotherapy] effect sizes are small in childhood, become larger in adolescents, and grow further in early adulthood, before decreasing to more modest effect sizes in the rest of the adult population" (Cuijpers et al, 2020). Although the authors do not report CBT-specific data, a substantial proportion of the studies analyzed were CBT studies, and the age effects did not appear to vary across treatment modalities.…”

Section: Agementioning

confidence: 99%

Personalized Medicine and Cognitive Behavioral Therapies for Depression: Small Effects, Big Problems, and Bigger Data

et al. 2020

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Cognitive-behavioral therapies (CBTs) are the most widely studied form of psychotherapy for disorders like depression and anxiety. Nonetheless, there is heterogeneity in response to CBTs vs. other treatments. Researchers have become increasingly interested in using pre-treatment individual differences (i.e., moderators) to match patients to the most effective treatments for them. Several methods to combine multiple variables to create precision treatment rules (PTRs) that identify subgroups have been proposed. We review the rationale behind multivariable PTRs as well as the findings of studies that have used different PTRs. We identify conceptual and methodological issues in the literature. Multivariable treatment assignment is a promising avenue of research. Nonetheless, effect sizes appear to be small and most of the samples that have been used to study these questions have been grossly underpowered to detect small effects. We recommend researchers explore multivariable treatment selection strategies, particularly those resembling risk-stratification, in heterogeneous samples of patients undergoing low-intensity CBTs vs. realistic minimal controls.

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Section: Agementioning

confidence: 99%

Personalized Medicine and Cognitive Behavioral Therapies for Depression: Small Effects, Big Problems, and Bigger Data

et al. 2020

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“…The second trial is the FreqMech trial (n = 200), which was conducted between November 2014 and January 2018, randomizing depressed patients into different session frequencies of CBT and IPT (i.e., CBT weekly (n = 49), CBT twice weekly (n = 49), IPT weekly (n = 55), IPT twice weekly (n = 47)). A higher session frequency led to more reduction of depression, but there were no average group differences between CBT and IPT (Bruijniks et al, 2020). Although the studies used the same treatment protocols for CBT and IPT (i.e., only the session frequency differed), the studies differed in a number of other important aspects.…”

Section: Study Design and Clinical Trial Datamentioning

confidence: 99%

“…In the STEPd trial patients received weekly sessions with some flexibility to schedule appointments less often then weekly. Treatment competence was rated good to excellent in 83-90% of the videotapes from the STEPd trial (Lemmens et al, 2015) and poor to excellent in the FreqMech trial (only 12-16% of the video-tapes were rated good-excellent; Bruijniks et al, 2020) using the Cognitive Therapy Scale for CBT (Dobson et al, 1985), and the short version of the IPT Adherence and Quality Scale for IPT (Stuart, 2011). 1 In both trials, there were significant differences in therapy-specific behaviour, with higher CBT-specific behaviour in CBT as compared to IPT, and higher IPT-specific behaviour in IPT as compared to CBT (rated with the Collaborative Study Psychotherapy Rating Scale version 6; Hollon et al, 1988).…”

Section: Treatmentsmentioning

confidence: 99%

Cross-trial prediction in psychotherapy: External validation of the Personalized Advantage Index using machine learning in two Dutch randomized trials comparing CBT versus IPT for depression

Bronswijk

Bruijniks

Lorenzo‐Luaces

et al. 2020

Psychotherapy Research

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Optimizing treatment selection may improve treatment outcomes in depression. A promising approach is the Personalized Advantage Index (PAI), which predicts the optimal treatment for a given individual. To determine the generalizability of the PAI, models needs to be externally validated, which has rarely been done. Method: PAI models were developed within each of two independent trials, with substantial between-study differences, that both compared CBT and IPT for depression (STEPd: n = 151 and FreqMech: n = 200). Subsequently, both PAI models were tested in the other dataset. Results: In the STEPd study, post-treatment depression was significantly different between individuals assigned to their PAI-indicated treatment versus those assigned to their non-indicated treatment (d = .57). In the FreqMech study, posttreatment depression was not significantly different between patients receiving their indicated treatment versus those receiving their non-indicated treatment (d = .20). Cross-trial predictions indicated that post-treatment depression was not significantly different between those receiving their indicated treatment and those receiving their non-indicated treatment (d = .16 and d = .27). Sensitivity analyses indicated that cross-trial prediction based on only overlapping variables didn't improve the results. Conclusion: External validation of the PAI has modest results and emphasizes between-study differences and many other challenges.

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“…Higher session frequency in the first 3 months of treatment is associated with faster improvement and recovery (Tiemens et al, 2019). Further, patients randomized to receive twice-weekly sessions experienced greater depression reductions than those offered once-weekly therapy (Bruijniks et al, 2020).…”

Section: Treatment Need Not Occur Once-weeklymentioning

confidence: 98%

Retiring, Rethinking, and Reconstructing the Norm of Once-Weekly Psychotherapy

Schleider¹,

Dobias²,

Mullarkey³

et al. 2020

Preprint

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Psychotherapies hold clear potential to alleviate mental health problems, yet there is no scientifically-driven consensus for how long treatment should last, how intense sessions should be, or how frequently sessions should occur. In practice, once-weekly therapy is the dominant outpatient service available to youths and adults alike, largely due to long-held beliefs and insurance companies’ limiting reimbursable treatment-time to 50-minute, weekly sessions. But ubiquity cannot be mistaken for clinical or practical superiority. Indeed, weekly therapy sessions are among numerous treatment structures that can help patients achieve clinical gains, with numerous trials supporting the utility of brief, intensive, and concentrated treatments for widely-varying problem types. Further, existing psychological services—dominated by weekly, outpatient options—fall short of meeting population-level mental health needs. Most youths and adults with psychiatric disorders never access care due to financial and logistical constraints, and among those who do, premature drop-out is common. Despite repeated calls to diversify treatment options, the “weekly therapy hour” remains the practical default. Given limited accessibility of, and significant dropout from, weekly outpatient therapy, and the established efficacy of alternative treatment formats, our field’s continued overreliance on the “default” of once-weekly therapy cannot be considered benign. As clinical scientists and therapists, we assert that it is our field’s ethical obligation to retire and rebuild the longstanding “default” to once-weekly treatment. To be clear, we do not endorse eliminating weekly psychotherapy as an option for patients; many once-weekly, evidence-based treatments, if delivered as intended, may benefit patients greatly. However, repositioning weekly therapy as one of many treatment options, and diversifying available service types, may strengthen the accessibility, flexibility, and potentially the effectiveness of treatment overall.

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The effects of once- versus twice-weekly sessions on psychotherapy outcomes in depressed patients

Cited by 76 publications

References 24 publications

Personalized Medicine and Cognitive Behavioral Therapies for Depression: Small Effects, Big Problems, and Bigger Data

Personalized Medicine and Cognitive Behavioral Therapies for Depression: Small Effects, Big Problems, and Bigger Data

Cross-trial prediction in psychotherapy: External validation of the Personalized Advantage Index using machine learning in two Dutch randomized trials comparing CBT versus IPT for depression

Retiring, Rethinking, and Reconstructing the Norm of Once-Weekly Psychotherapy

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