Process-Based psychotherapy personalization: considering causality with continuous-time dynamic modeling

Intake Characteristics as Predictors of Psychotherapy Outcome in a Practice Research Network in Argentina

There are few studies exploring intake diagnostic characteristics as predictors of change in integrative naturalistic settings. The aim of this study is to explore baseline variables at the intake process and establish the predictive value of the individual trajectories of the patients. We recruited 259 patients undergoing an integrative psychotherapy network of psychotherapists from Buenos Aires, Argentina. Every therapist completed the intake form of each patient involved in the routine outcome monitoring. Thereafter step-wise regressions based on forward selection strategies were used, in order to identify meaningful baseline predictors of patients' clinical evolution, derived from the intake process. The selected predictors were social support network, subjective distress, the initial measure of clinical distress, unemployment, sociocultural status and reactance. When including those six variables in a multilevel model, the results indicate that social support network, subjective distress, and the initial measure of clinical distress were significant predictors of the trajectories of OQ-30, whereas unemployment, sociocultural status and reactance were not significant. The results regarding social support network are in line with the literature, while results of socioeconomic status (unemployment and sociocultural level) move in an opposite direction in comparison to the available evidence. Moreover, the mental health findings (initial OQ-30 and subjective distress) confirm the contradictory body of literature produced in this domain. Finally, reactance seems to be a significant predictor in previous study in contradiction of our results. Overall, this endeavor constitutes important but preliminary evidence to enhance the production of bottom-up science within practice research networks in the global south.

Time-lagged panel models in psychotherapy process and mechanisms of change research: Methodological challenges and advances

In recent years, there has been increasing interest in utilizing time-lagged panel models to study mechanisms of change in psychotherapy. These models offer valuable insights into the dynamic relationships between variables over time and offer stronger causal inference capabilities than cross-sectional analyses. Therefore, they are well-suited for modeling the intricate relationships between mechanisms of change and outcomes in psychotherapy studies, which are typically beyond experimental control. However, their complexity, coupled with the fact that detailed explanations are often embedded in dense statistical or econometric texts, poses challenges. This paper provides a background on cross-lagged panel models and delves deeper into explaining the issues of 1) dynamic panel bias, 2) long-run effects, and 3) testing whether different treatments work by different mechanisms. Using data from a psychotherapy study on treatment of adolescent depression, I demonstrate how these issues manifest in real data. In conclusion, I recommend using structural equation modeling to circumvent dynamic panel bias, reporting long-run effects to reveal the long-term impact of sustained therapeutic work on mechanisms of change, and carefully considering whether mediation, moderation, or a combination of both, best describes differential effects of mechanisms between treatments.

Measuring psychotherapeutic processes in the context of psychedelic experiences: Validation of the General Change Mechanisms Questionnaire (GCMQ)

BACKGROUND

Therapeutic and salutogenic effects of psychedelic drugs have been attributed to psychotherapeutic or psychotherapy-like processes that can unfold during the acute psychedelic experience and beyond. Currently, there are no psychometric instruments available to comprehensively assess psychotherapeutic processes (as conceptualized by empirical psychotherapy research) in the context of psychedelic experiences.

AIMS

We report the initial validation of the General Change Mechanisms Questionnaire (GCMQ), a self-report instrument designed to measure five empirically established general change mechanisms (GCMs) of psychotherapy-(1) resource activation, (2) therapeutic relationship, (3) problem actuation, (4) clarification, and (5) mastery-in the context of psychedelic experiences.

METHODS

An online survey in a sample of 1153 English-speaking and 714 German-speaking psychedelic users was conducted to evaluate simultaneously developed English- and German-language versions of the GCMQ.

RESULTS

The theory-based factor structure was confirmed. The five GCMQ scales showed good internal consistency. Evidence for convergent validity with external measures was obtained. Significant associations with different settings and with therapeutic, hedonic, and escapist use motives confirmed the hypothesized context dependence of GCM-related psychedelic experiences. Indicating potential therapeutic effects, the association between cumulative stressful life events and well-being was significantly moderated by resource activation, clarification, and mastery. Factor mixture modeling revealed five distinct profiles of GCM-related psychedelic experiences.

CONCLUSION

Initial testing indicates that the GCMQ is a valid and reliable instrument that can be used in future clinical and nonclinical psychedelic research. The five identified profiles of GCM-related experiences may be relevant to clinical uses of psychedelics and psychedelic harm reduction.

Temporal relationships in the movement behaviour of adolescents: Testing and methodological considerations of the ActivityStat hypothesis

The study aimed to investigate the ActivityStat hypothesis by examining the presence and the timeframe of the temporal relationships among physical activity (PA) levels and stationary time (ST) in adolescents. A secondary analysis was performed on data involving 356 adolescents in Dunedin, New Zealand. Participants wore a waist-worn accelerometer for several consecutive days to assess PA levels [i.e. light PA (LPA), and moderate-to-vigorous PA (MVPA)] and ST. Bayesian continuous-time structural equation modelling (CT-SEM) was used to examine the relationship between the behaviours over time and the timeframe during which these relationships occur. Increases in LPA, MVPA, and ST were positively associated with their later behaviours until 2.5, 1.7, and 2 days later, respectively. A cross-behavioural reciprocal and negative relationship between LPA and ST was demonstrated 0.4 days later. A positive relationship between ST and MVPA was observed until about 0.4 days later. This is the first study to investigate the ActivityStat hypothesis using Bayesian CT-SEM in adolescents, examining the multivariate relationships among different behaviours and the associated timeframes. To conclude, evidence of activity synergy was suggested for the within-behavioural relationships, while behavioural compensation was noted for ST. Thus, the findings provide some support for the ActivityStat hypothesis in adolescents.

Using the 'Leapfrog' Design as a Simple Form of Adaptive Platform Trial to Develop, Test, and Implement Treatment Personalization Methods in Routine Practice

The route for the development, evaluation and dissemination of personalized psychological therapies is complex and challenging. In particular, the large sample sizes needed to provide adequately powered trials of newly-developed personalization approaches means that the traditional treatment development route is extremely inefficient. This paper outlines the promise of adaptive platform trials (APT) embedded within routine practice as a method to streamline development and testing of personalized psychological therapies, and close the gap to implementation in real-world settings. It focuses in particular on a recently-developed simplified APT design, the 'leapfrog' trial, illustrating via simulation how such a trial may proceed and the advantages it can bring, for example in terms of reduced sample sizes. Finally it discusses models of how such trials could be implemented in routine practice, including potential challenges and caveats, alongside a longer-term perspective on the development of personalized psychological treatments.

Between- and within-person effects of affective experiences on coping in CBT: Direct effects and interplay with therapeutic alliance and resource activation

OBJECTIVE

The role of affective experiences (AE) in cognitive-behavioral therapy (CBT) has rarely been investigated. We examined between- and within-person effects of AE on coping in CBT for family caregivers and interactions with therapeutic alliance and resource activation.

METHODS

67 family caregivers rated AE, therapeutic alliance, resource activation, and coping after each of 12 sessions of telephone-based CBT. We examined direct session-to-session effects of AE on coping in structural equation modeling and interactions of AE with therapeutic alliance and resource activation in multilevel models.

RESULTS

AE did not directly predict coping. Instead, within-person effects of AE interacted with simultaneous within-person emotional bond. Given strong emotional bond, AE positively predicted coping, whereas given weak emotional bond, AE negatively predicted coping. Further, cross-level interactions of between-person AE and within-person agreement on collaboration and resource activation indicated that these positively predicted coping only in dyads with high between-person AE.

CONCLUSION

AE may enhance coping when complemented with strong emotional bond. Further, within-person effects of agreement on collaboration and resource activation seem to rely on a certain degree of between-person AE. Results are discussed in relation to current findings on emotional processing in CBT.