The EffectLiteR Approach for Analyzing Average and Conditional Effects.

We present a framework for estimating average and conditional effects of a discrete treatment variable on a continuous outcome variable, conditioning on categorical and continuous covariates. Using the new approach, termed the EffectLiteR approach, researchers can consider conditional treatment effects given values of all covariates in the analysis and various aggregates of these conditional treatment effects such as average effects, effects on the treated, or aggregated conditional effects given values of a subset of covariates. Building on structural equation modeling, key advantages of the new approach are (1) It allows for latent covariates and outcome variables; (2) it permits (higher order) interactions between the treatment variable and categorical and (latent) continuous covariates; and (3) covariates can be treated as stochastic or fixed. The approach is illustrated by an example, and open source software EffectLiteR is provided, which makes a detailed analysis of effects conveniently accessible for applied researchers.

A theory of states and traits--revised.

We present a revision of latent state-trait (LST-R) theory with new definitions of states and traits. This theory applies whenever we study the consistency of behavior, its variability, and its change over time. States and traits are defined in terms of probability theory. This allows for a seamless transition from theory to statistical modeling of empirical data. LST-R theory not only gives insights into the nature of latent variables but it also takes into account four fundamental facts: Observations are fallible, they never happen in a situational vacuum, they are always made using a specific method of observations, and there is no person without a past. Although the first fact necessitates considering measurement error, the second fact requires allowances for situational fluctuations. The third fact implies that, in the first place, states and traits are method specific. Furthermore, compared to the previous version of LST theory (see, e.g., Steyer et al. 1992 , 1999 ), our revision is based on the notion of a person-at-time-t. The new definitions in LST-R theory have far-reaching implications that not only concern the properties of states, traits, and the associated concepts of measurement errors and state residuals, but also are related to the analysis of states and traits in longitudinal observational and intervention studies.

[Typical patterns of depressive disorders during outpatient psychotherapy and their prediction]. / Verlaufsmuster depressiver Störungen bei ambulanten psychotherapeutischen Behandlungen und deren Vorhersage.

OBJECTIVES: Are there typical patterns of outpatient psychotherapy among depressed patients? What characterizes patients with different patterns? METHODS: We examined N= 548 patients with primary depressive disorders using a naturalistic design. Using a latent-state-mixture model and depression measures at baseline, therapy end and 1-year follow-up we found a total of five patterns. Subgroups were compared with respect to sociodemographic and treatment-related variables. RESULTS: Responders with moderate depressive symptoms at baseline and responders with severe symptoms at baseline were most common (54% and 25% of the sample, respectively) compared to late responders (9 %), small-response patients (9 %) and recidivists (4 %). Patterns of change were related to symptom intensity at baseline and ratings of perceived helpfulness at the end of treatment. CONCLUSIONS: Since psychometric scales better predicted change pattern than sociodemographic characteristics, primary and secondary diagnoses, psychometric assessments and feedback systems could be a useful supplement to traditional quality assurance procedures.

Benefits and challenges in practice-oriented psychotherapy research in Germany: the TK and the QS-PSY-BAY projects of quality assurance in outpatient psychotherapy.

OBJECTIVE: Two patient-focused long-term research projects performed in the German outpatient psychotherapy system are focused on in this article. The TK (Techniker Krankenkasse) project is the first study to evaluate a quality assurance and feedback system with regard to its practical feasibility in German routine care. The other study ("Quality Assurance in Outpatient Psychotherapy in Bavaria"; QS-PSY-BAY) was designed to test a new approach for quality assurance in outpatient psychotherapy using electronic documentation of patient characteristics and outcome parameters. In addition this project provides the opportunity to analyze data on health-related costs for the patients undergoing outpatient psychotherapy. METHOD: Both projects and their results indicating high effect sizes are briefly described. RESULTS: From the perspectives of the research teams, advisory boards and other stakeholders, the experiences with these projects are discussed focusing on obstacles, challenges, difficulties, and benefits in developing and implementing the studies. The triangle collaboration of therapists, researchers, and health insurance companies/health service institutions turned out to be fruitful in both studies. CONCLUSIONS: Despite some controversies between the partners the experiences indicate the importance of practiced-research collaborations to provide relevant information about the delivery of outpatient psychotherapy in the health system.

Theory and Analysis of Total, Direct, and Indirect Causal Effects.

Mediation analysis, or more generally models with direct and indirect effects, are commonly used in the behavioral sciences. As we show in our illustrative example, traditional methods of mediation analysis that omit confounding variables can lead to systematically biased direct and indirect effects, even in the context of a randomized experiment. Therefore, several definitions of causal effects in mediation models have been presented in the literature (Baron & Kenny, 1986 ; Imai, Keele, & Tingley, 2010 ; Pearl, 2012 ). We illustrate the stochastic theory of causal effects as an alternative foundation of causal mediation analysis based on probability theory. In this theory we define total, direct, and indirect effects and show how they can be identified in the context of our illustrative example. A particular strength of the stochastic theory of causal effects are the causality conditions that imply causal unbiasedness of effect estimates. The causality conditions have empirically testable implications and can be used for covariate selection. In the discussion, we highlight some similarities and differences of the stochastic theory of causal effects with other theories of causal effects.

[Extensions of the outpatient psychotherapy: a study about patient, therapist, treatment, and therapy course characteristics]. / Verlängerungen ambulanter Psychotherapien: Eine Studie zu Patienten-, Therapeuten-, Behandlungs- und Verlaufsmerkmalen.

Due to the treatment costs, extensions of the standard therapy duration are a matter of critical examination. This study investigates which factors characterize patients with treatment extensions in the German health system and how effective these extensions are for a reduction of the patients' symptoms. We analysed a disorder heterogeneous sample of 810 patients. We found that therapy extensions are more common among with more severe mental disorders, when the therapeutic relationship is positive, and little therapy success has been achieved during the standard duration. Overall, the findings suggest that outpatient psychotherapy is mainly extended for patients with a low symptom reduction after the standard therapy duration and that therapy extension allows a symptom reduction that could not have been achieved otherwise.

Effects of adult inpatient group psychotherapy on attachment characteristics: an observational study comparing routine care to an untreated comparison group.

This study investigated the changes in attachment characteristics of patients undergoing inpatient group psychotherapy in routine care. We collected data from 265 consecutively recruited patients and 260 non-clinical control persons using self-report measures of attachment, depression, and socio-demographic characteristics. The effects of treatment on patients were analyzed using propensity score techniques (propensity strata and logit-transformed propensity scores) in combination with a generalized analysis of covariance. A moderate increase of attachment security was found which could be attributed to a decrease both in attachment anxiety and avoidance. Pre-post improvements in attachment with regard to romantic partnerships were stable after a 1-year follow-up. Furthermore, we found significant treatment-covariate interactions indicating that subjects with particularly high treatment propensities (propensities were highly correlated with depression and attachment anxiety) improved the most in terms of attachment security. Our results are encouraging for psychotherapeutic practice in that they provide evidence that long-term attachment improvements can be reached via psychotherapy. Our results will also provide a sound basis for future studies in the field of clinical attachment research, e.g., studies examining whether improved attachment security is correlated to symptom improvements in different psychological disorders.

Differential change in integrative psychotherapy: a re-analysis of a change-factor based RCT in a naturalistic setting.

General Psychotherapy (GPT; Grawe, 1997) is a research-informed psychotherapy that combines cognitive-behavioral and process-experiential techniques and that assumes motivational clarification and problem mastery as central mechanisms of change. To isolate the effect of motivational clarification, GPT was compared to a treatment that proscribed motivational clarification (General Psychotherapy Minus Clarification, GPT-C) in a randomized-controlled trial with 67 diagnostically heterogeneous outpatients. Previous analyses demonstrated equal outcomes and some superiority for highly avoidant patients in GPT. Re-analyses using causal-analytic methods confirmed equal changes, but also showed superior effects for GPT in highly symptomatic patients. Results are discussed regarding theory, methodological limitations, and implications for research and practice.

The true-change model with individual method effects: reliability issues.

The true intra-individual change model is generalized by defining individual method effects. This allows the analysis of non-congeneric test-retest variables assumed to measure a common, possibly (temporally) transient, attribute. Temporal change in the attribute between different times of measurement is modelled by the true-change variable. Individual causal method effects, due to heterogeneity of the measurement methods, account for the imperfect correlation of the true-score variables at each time of measurement. The reliability of the composite scores, at each time of measurement, and the reliability of the difference composite score may be estimated with appropriate coefficients derived from the model. Measurements of daily life tension in adult females serve to illustrate how the model can be used empirically.

Outpatient Psychotherapy Reduces Health-Care Costs: A Study of 22,294 Insurants over 5 Years.

BACKGROUND: The project "Quality Assurance in Ambulatory Psychotherapy in Bavaria" (QS-PSY-BAY) focuses on the quality assurance of outpatient psychotherapy (OPT) in Germany in terms of symptom reduction and cost reduction under naturalistic conditions. In this study, we examined the effectiveness of psychotherapy in terms of pre-post cost reduction. METHOD: The health-care costs of N = 22,294 insurants over a 5-year period were examined in a naturalistic longitudinal design. Six participating health insurance funds provided data on costs related to inpatient treatment, outpatient treatment, drugs, and hospitalization and work disability days. RESULTS: We found that the average annual total costs for inpatient and outpatient treatments as well as drug costs and work disability days increased from the second to the first year before OPT. Besides a large and significant reduction of work disability days (41.8%), hospitalization days (27.4%), and inpatient costs (21.5%) from the first year before versus the first year following OPT, we found evidence for long-term effects: the number of work disability days in the second year after OPT was lower (23.8%), and drug costs were higher than in the second year before OPT (41.5%). CONCLUSION: We conclude that OPT as a part of the health insurance system is an investment which can pay off in the future especially in terms of lower inpatient costs and work disability.

Analyzing average and conditional effects with multigroup multilevel structural equation models.

Conventionally, multilevel analysis of covariance (ML-ANCOVA) has been the recommended approach for analyzing treatment effects in quasi-experimental multilevel designs with treatment application at the cluster-level. In this paper, we introduce the generalized ML-ANCOVA with linear effect functions that identifies average and conditional treatment effects in the presence of treatment-covariate interactions. We show how the generalized ML-ANCOVA model can be estimated with multigroup multilevel structural equation models that offer considerable advantages compared to traditional ML-ANCOVA. The proposed model takes into account measurement error in the covariates, sampling error in contextual covariates, treatment-covariate interactions, and stochastic predictors. We illustrate the implementation of ML-ANCOVA with an example from educational effectiveness research where we estimate average and conditional effects of early transition to secondary schooling on reading comprehension.

[Non-completion of insurance-funded outpatient psychotherapy: frequency, risk factors, outcome]. / Abbrüche antragspflichtiger ambulanter Psychotherapien: Häufigkeit, Risikofaktoren, Outcome.

OBJECTIVE: Because premature discontinuation of psychotherapy limits the effectiveness of the interventions, in a naturalistic design we examined the prevalence, predictors, and outcome of premature discontinuation. METHODS: The sample included N = 584 patients with various mental disorders. Risk factors were identified using regression analysis. As outcome Patient Health Questionnaire scales were considered. We compared pre and post averages as well as post averages of premature discontinuation versus regular termination. RESULTS: Risk factors were: female and/or unemployed patient, low patient and/or therapist ratings regarding therapy success, and extraordinarily high therapist ratings of the therapeutic alliance. Despite premature discontinuation we found significant reductions of depression, anxiety, somatic symptoms, and stress (ES = 0.30, …, 0.44). Compared to regular termination though, patients with premature discontinuation were more impaired at last measurement (ES = 0.17, …, 0.37). CONCLUSION: Not each premature discontinuation is a psychotherapeutic failure. Warning signals for looming premature discontinuation are low ratings of therapy success while psychotherapeutic treatment.

How much power and speed is measured in this test?

An old issue in psychological assessment is to what extent power and speed each are measured by a given intelligence test. Starting from accuracy and response time data, an approach based on posterior time limits (cut-offs of recorded response time) leads to three kinds of recoded data: time data (whether or not the response precedes the cut-off), time-accuracy data (whether or not a response is correct and precedes the cut-off), and accuracy data (as time-accuracy data, but coded as missing when not preceding the time cut-off). Each type of data can be modeled as binary responses. Speed and power are investigated through the effect of posterior time limits on two main aspects: (a) the latent variable that is measured: whether it is more power-related or more speed-related; (b) how well the latent variable (of whatever kind) is measured through the item(s). As empirical data, we use responses and response times for a verbal analogies test. The main findings are that, independent of the posterior time limit, basically the same latent speed trait was measured through the time data, and basically the same latent power trait was measured through the accuracy data, while for the time-accuracy data the nature of the latent trait moved from power to speed when the posterior time limit was reduced. It was also found that a reduction of the posterior time limit had no negative effect on the reliability of the latent trait measures (of whatever kind).

Modeling Common Traits and Method Effects in Multitrait-Multimethod Analysis.

Method effects often occur when constructs are measured by different methods. In traditional multitrait-multimethod (MTMM) models method effects are regarded as residuals, which implies a mean method effect of zero and no correlation between trait and method effects. Furthermore, in some recent MTMM models, traits are modeled to be specific to a certain method. However, often we are not interested in a method-specific trait but in a trait that is common to all methods. Here we present the Method Effect model with common trait factors, which allows modeling "common" trait factors and method factors that represent method "effects" rather than residuals. The common trait factors are defined as the mean of the true-score variables of all variables measuring the same trait and the method factors are defined as differences between true-score variables and means of true-score variables. Because the model allows estimating mean method effects, correlations between method factors, and correlations between trait and method factors, new research questions may be investigated. The application of the model is demonstrated by 2 examples studying the effect of negative, as compared with positive, item wording for the measurement of mood states.