| 1. |
- Falkenström, Fredrik, et al.
(författare)
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Do therapist effects really impact estimates of within-patient mechanisms of change? A Monte Carlo simulation study
- 2020
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Ingår i: Psychotherapy Research. - : ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD. - 1050-3307 .- 1468-4381. ; 30:7, s. 885-899
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Tidskriftsartikel (refereegranskat)abstract
- Objective:Existing evidence highlights the importance of modeling differential therapist effectiveness when studying psychotherapy outcome. However, no study to date examined whether this assertion applies to the study of within-patient effects in mechanisms of change. The study investigated whether therapist effects should be modeled when studying mechanisms of change on a within-patient level. Methods:We conducted a Monte Carlo simulation study, varying patient- and therapist level sample sizes, degree of therapist-level nesting (intra-class correlation), balanced vs. unbalanced assignment of patients to therapists, and fixed vs random within-patient coefficients. We estimated all models using longitudinal multilevel and structural equation models that ignored (2-level model) or modeled therapist effects (3-level model). Results:Across all conditions, 2-level models performed equally or were superior to 3-level models. Within-patient coefficients were unbiased in both 2- and 3-level models. In 3-level models, standard errors were biased when number of therapists was small, and this bias increased in unbalanced designs. Ignoring random slopes led to biased standard errors when slope variance was large; but 2-level models still outperformed 3-level models. Conclusions:In contrast to treatment outcome research, when studying mechanisms of change on a within-patient level, modeling therapist effects may even reduce model performance and increase bias.
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| 2. |
- Falkenström, Fredrik, 1972-, et al.
(författare)
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How to Model and Interpret Cross-Lagged Effects in Psychotherapy Mechanisms of Change Research : A Comparison of Multilevel and Structural Equation Models
- 2022
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Ingår i: Journal of Consulting and Clinical Psychology. - : American Psychological Association (APA). - 0022-006X .- 1939-2117. ; 90:5, s. 446-458
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Tidskriftsartikel (refereegranskat)abstract
- Objective: Modeling cross-lagged effects in psychotherapy mechanisms of change studies is complex and requires careful attention to model selection and interpretation. However, there is a lack of field-specific guidelines. We aimed to (a) describe the estimation and interpretation of cross lagged effects using multilevel models (MLM) and random-intercept cross lagged panel model (RI-CLPM); (b) compare these models' performance and risk of bias using simulations and an applied research example to formulate recommendations for practice. Method: Part 1 is a tutorial focused on introducing/describing dynamic effects in the form of autoregression and bidirectionality. In Part 2, we compare the estimation of cross-lagged effects in RI-CLPM, which takes dynamic effects into account, with three commonly used MLMs that cannot accommodate dynamics. In Part 3, we describe a Monte Carlo simulation study testing model performance of RI-CLPM and MLM under realistic conditions for psychotherapy mechanisms of change studies. Results: Our findings suggested that all three MLMs resulted in severely biased estimates of cross-lagged effects when dynamic effects were present in the data, with some experimental conditions generating statistically significant estimates in the wrong direction. MLMs performed comparably well only in conditions which are conceptually unrealistic for psychotherapy mechanisms of change research (i.e., no inertia in variables and no bidirectional effects). Discussion: Based on conceptual fit and our simulation results, we strongly recommend using fully dynamic structural equation modeling models, such as the RI-CLPM, rather than static, unidirectional regression models (e.g., MLM) to study cross-lagged effects in mechanisms of change research. What is the public health significance of this article? We describe the differences between multilevel and structural equation modeling in the study of mechanisms of change in psychotherapy research. We argue that the common application of multilevel modeling assumes that there is no within-patient inertia in predictor or outcome variable, and the outcome variable does not impact the predictor, both of which seem highly unrealistic in psychotherapy research. Moreover, we demonstrate that violations of these assumptions may lead to severe bias in estimated coefficients, resulting in inaccurate recommendations for clinical practice. Thus, we recommend researchers to use structural equation modeling to estimate the effects of proposed change mechanisms over time.
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| 3. |
- Falkenström, Fredrik, Professor, 1972-, et al.
(författare)
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To Detrend, or Not to Detrend, That Is the Question? : The Effects of Detrending on Cross-Lagged Effects in Panel Models
- 2023
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Ingår i: Psychological methods. - : American Psychological Association (APA). - 1082-989X .- 1939-1463.
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Tidskriftsartikel (refereegranskat)abstract
- Intervention studies in psychology often focus on identifying mechanisms that explain change over time. Cross-lagged panel models (CLPMs) are well suited to study mechanisms, but there is a controversy regarding the importance of detrending-defined here as separating longer-term time trends from cross-lagged effects-when modeling these change processes. The aim of this study was to present and test the arguments for and against detrending CLPMs in the presence of an intervention effect. We conducted Monte Carlo simulations to examine the impact of trends on estimates of cross-lagged effects from several longitudinal structural equation models. Our simulations suggested that ignoring time trends led to biased estimates of auto- and cross-lagged effects in some conditions, while detrending did not introduce bias in any of the models. We used real data from an intervention study to illustrate how detrending may affect results. This example showed that models that separated trends from cross-lagged effects fit better to the data and showed nonsignificant effect of the mechanism on outcome, while models that ignored trends showed significant effects. We conclude that ignoring trends increases the risk of bias in estimates of auto- and cross-lagged parameters and may lead to spurious findings. Researchers can test for the presence of trends by comparing model fit of models that take into account individual differences in trends (e.g., autoregressive latent trajectory model, the latent curve model with structured residuals, or the general cross-lagged model).
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| 4. |
- Falkenström, Fredrik, 1972-, et al.
(författare)
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Using time-lagged panel data analysis to study mechanisms of change in psychotherapy research: Methodological recommendations
- 2020
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Ingår i: Counselling and Psychotherapy Research. - : WILEY. - 1473-3145 .- 1746-1405. ; 20:3, s. 435-441
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Tidskriftsartikel (refereegranskat)abstract
- The introduction of novel methodologies in the past decade has advanced research on mechanisms of change in observational studies. Time-lagged panel models allow us to track session-by-session changes and focus on within-patient associations between predictors and outcomes. This shift is crucial as change in mechanisms inherently takes place at a within-patient level. These models also enable preliminary casual inferences, which can guide the development of effective personalised interventions that target mechanisms of change, used at specific treatment phases for optimal effect. Given their complexity, panel models need to be implemented with caution, as different modelling choices can significantly affect results and reduce replicability. We outline three central methodological recommendations for use of time-lagged panel analysis to study mechanisms of change: (a) taking patient-specific effects into account, separating out stable between-person differences from within-person fluctuations over time; (b) properly controlling for autoregressive effects; and (c) considering long-term time trends. We demonstrate these recommendations in an applied example examining the session-by-session alliance-outcome association in a naturalistic psychotherapy study. We present limitations of time-lagged panel analysis and future directions.
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| 5. |
- Fisher, Hadar, et al.
(författare)
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Therapists' oxytocin response mediates the association between patients' negative emotions and psychotherapy outcomes
- 2023
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Ingår i: Journal of Affective Disorders. - : Elsevier. - 0165-0327 .- 1573-2517. ; 338, s. 163-170
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Tidskriftsartikel (refereegranskat)abstract
- Background: Existing literature suggests that patients' experiences of emotions, especially negative emotions, predict outcomes in psychotherapies for major depressive disorder. However, the specific mechanisms underlying this effect remain unclear. Based on studies pointing to the role of oxytocin (OT) in attachment relationships, we proposed and tested a mediation model where the therapists' hormonal responses, as represented by increases in their OT levels, mediates the association between negative emotions and symptomatic change. Method: OT saliva samples (pre- and post-session, N = 435) were collected on a fixed schedule over 16 sessions from the therapists of 62 patients receiving psychotherapy for major depression. The Hamilton Rating Scale for Depression was administered to the patients before the sessions, and the patients reported their in-session emotions after the sessions. Results: The findings support the proposed within-person mediation model: (a) higher levels of negative emotions in patients predicted greater increases in therapist OT levels pre- to post-session throughout treatment; (b) greater OT levels in therapists, in turn, predicted reduction in patients' depressive symptoms on the subsequent assessment; and (c) the therapists' OT levels significantly mediated the association between patients' negative emotions and reduction in their depressive symptoms. Limitations: This design precluded establishing a time sequence between patients' negative emotions and therapists' OT; thus, causality could not be inferred. Conclusion: These findings point to a possible biological mechanism underlying the effects of patients' experiences of negative emotions on treatment outcomes. The findings suggest that therapists' OT responses could potentially serve as a biomarker of an effective therapeutic processes.
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| 6. |
- Solomonov, Nili, et al.
(författare)
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Differential effects of alliance and techniques on Panic-Specific Reflective Function and misinterpretation of bodily sensations in two treatments for panic
- 2020
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Ingår i: Psychotherapy Research. - : Taylor & Francis Group. - 1050-3307 .- 1468-4381. ; 30:1, s. 97-111
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Tidskriftsartikel (refereegranskat)abstract
- ABSTRACTObjective: To examine whether working alliance quality and use of techniques predict improvement in Panic-Specific Reflection Function (PSRF), and misinterpretation of bodily sensations in treatments for panic disorder. Method: A sample of 161 patients received either CBT or PFPP (Panic-focused Psychodynamic therapy) within a larger RCT. Data were collected on patient-reported working alliance, misinterpretations, PSRF, observer-coded use of techniques, and interviewer-rated panic severity. Random-Intercept Cross-Lagged Panel Models assessed bi-directional associations, disentangling within- and between-patient effects, and accounting for prior change. Results: Higher alliance predicted subsequent within-patient improvement in PSRF in PFPP, but worsening in CBT. In both treatments, focus on interpersonal relationships predicted PRSF improvement (with stronger effects in CBT), while focus on thoughts and behaviors predicted worsening in PSRF. In CBT only, early focus on affect and moment-to-moment experience predicted reduced misinterpretation, while high focus on thoughts and cognitions predicted subsequent increase in misinterpretation. Conclusion: The quality of the alliance has differential effects on PSRF in distinct treatments. Interpersonal, rather than cognitive or behavioral focus, even when delivered differently within distinct treatments with high adherence, could facilitate improvement in PSRF. Additionally, early focus on affect and moment-to-moment experiences in CBT could reduce misinterpretations.
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| 7. |
- Wienicke, Frederik J., et al.
(författare)
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Efficacy and moderators of short-term psychodynamic psychotherapy for depression : A systematic review and meta-analysis of individual participant data
- 2023
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Ingår i: Clinical Psychology Review. - : Elsevier. - 0272-7358 .- 1873-7811. ; 101
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Forskningsöversikt (refereegranskat)abstract
- Background: Short-term psychodynamic psychotherapy (STPP) is frequently used to treat depression, but it is unclear which patients might benefit specifically. Individual participant data (IPD) meta-analyses can provide more precise effect estimates than conventional meta-analyses and identify patient-level moderators. This IPD meta-analysis examined the efficacy and moderators of STPP for depression compared to control conditions.Methods: PubMed, PsycInfo, Embase, and Cochrane Library were searched September 1st, 2022, to identify randomized trials comparing STPP to control conditions for adults with depression. IPD were requested and analyzed using mixed-effects models.Results: IPD were obtained from 11 of the 13 (84.6%) studies identified (n = 771/837, 92.1%; mean age = 40.8, SD = 13.3; 79.3% female). STPP resulted in significantly lower depressive symptom levels than control conditions at post-treatment (d = −0.62, 95%CI [−0.76, −0.47], p < .001). At post-treatment, STPP was more efficacious for participants with longer rather than shorter current depressive episode durations.Conclusions: These results support the evidence base of STPP for depression and indicate episode duration as an effect modifier. This moderator finding, however, is observational and requires prospective validation in future large-scale trials.
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