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Objective: This study aimed to provide evidence for treatment credibility (TC) as a potential mechanism of change in cognitive behavioral therapy (CBT). Therefore, it focused on within-person effects that are free of the influence of stable characteristics and thus allow to exclude certain alternative explanations for the association under study. Method: The sample included 1,423 patients receiving outpatient CBT, who presented a wide variety of psychiatric diagnoses (mostly affective and anxiety disorders). TC, depression, and anxiety were measured every fifth session from Session 5 to 25 using the Credibility Expectancy Questionnaire (CEQ), the Patient Health Questionnaire–9 (PHQ-9), and the General Anxiety Disorder–7 (GAD-7), respectively. Symptom severity was assessed every session using the Hopkins Symptom Checklist–11. Within- and between-person effects of TC, depression, and anxiety were analyzed using the latent curve model with structured residuals (LCM-SRs). In exploratory analyses, within-person effects of TC on next-session symptom severity were assessed using a modification of the LCM-SR. Results: LCM-SRs exhibited excellent fit in main analyses. There were significant negative correlations of both intercepts and slopes (between-person level) of CEQ and PHQ-9 as well GAD-7. No significant cross-lagged effects (within-person level) were found over the five-session interval. However, session-wise analyses revealed significant cross-lagged effects of CEQ on Hopkins Symptom Checklist–11. Conclusions: This study is the first to find significant within-person effects of TC in session-wise analyses. This lends preliminary support to the notion of TC as a mechanism of change. The lack of significant findings at the five-session interval is discussed considering the specific design used in this study. What is the public health significance of this article?: This study did not find significant effects for treatment credibility on symptoms of depression and anxiety at a time interval of five sessions. However, in exploratory analyses significant effects of treatment credibility on next-session symptom severity were found. Thus, this study provides only preliminary evidence that treatment credibility has a negative causal effect on patients' symptom severity, meaning an increase in the patients' perception of treatment credibility may lead to an improvement of symptom severity. While more research is needed to support the findings of this study, we suggest that therapists pay attention to how credible patients perceive their treatment during the course of treatment and act accordingly in therapy phases in which patients lose confidence in their treatment, for example, by discussing the treatment rational or changing the treatment approach according to their patients' treatment beliefs. [ABSTRACT FROM AUTHOR]

To train novice students adequately, it is crucial to understand where they start and how they develop their skills. This study examined the impact of novice students' characteristics on their initial clinical micro-skills when treating simulated patients with cognitive behavior therapy. The sample consisted of 44 graduate psychology students treating seven simulated patients. Clinical micro-skills were measured both using video-based ratings in reaction to short video clips of simulated patients (via the Facilitative Interpersonal Skills (FIS) performance task) and by using video-based ratings within a session with a simulated patient (using the Inventory of Therapeutic Interventions and Skills; ITIS). Two separate LASSO regressions were performed using machine learning to select potential predictors for both skills assessments. Subsequently, a bootstrapping algorithm with 10,000 iterations was used to examine the variability of regression coefficients. Using LASSO regression, we identified two predictors for clinical micro-skills in standardized scenarios: extraversion (b = 0.10) and resilience (b = 0.09), both were not significantly associated with clinical micro-skills. Together, they explained 15% of the skill variation. Bootstrapping confirmed the stability of these predictors. For clinical micro-skills in sessions, only competitiveness was excluded by LASSO regression, and all predictors showed significant instability. The results provide initial evidence that trainees' resilience and extraversion should be promoted in the clinical training of cognitive behavior therapy. More studies on clinical micro-skills and training with larger sample sizes are needed to fully understand clinical development. [ABSTRACT FROM AUTHOR]

Psychotherapy can be improved by integrating the study of mediators (how it works) and moderators (for whom it works). To demonstrate this integration, we studied the relationship between resource activation, problem-coping experiences and symptoms in cognitive-behavior therapy (CBT) for depression, to obtain preliminary insights on causal inference (which process leads to symptom improvement?) and prediction (which one for whom?). A sample of 715 patients with depression who received CBT was analyzed. Hierarchical Bayesian continuous time dynamic modeling was used to study the temporal dynamics between the variables analyzed within the first ten sessions. Depression and self-efficacy at baseline were examined as predictors of these dynamics. There were significant cross-effects between the processes studied. Under typical assumptions, resource activation had a significant effect on symptom improvement. Problem-coping experience had a significant effect on resource activation. Depression and self-efficacy moderated these effects. However, when system noise was considered, these effects may be affected by other processes. Resource activation was strongly associated with symptom improvement. To the extent of inferring causality, for patients with mild-moderate depression and high self-efficacy, promoting resource activation can be recommended. For patients with severe depression and low self-efficacy, promoting problem-coping experiences can be recommended. [ABSTRACT FROM AUTHOR]

Background: Although psychotherapy has shown to be effective for most patients, about one‐third of patients do not benefit or deteriorate during treatment. Technical progress has allowed the integration of routine outcome monitoring (ROM) into treatment, helping therapists detect patients at risk for a nonresponse or poor outcome early on. Psychological therapy can be enhanced by providing therapists with individual treatment recommendations for these at‐risk patients. One example of such a comprehensive feedback system is the Trier Treatment Navigator (TTN). Objective/Method: This clinical case study aims to illustrate the implementation of the TTN in a cognitive behavioral therapy (CBT) outpatient clinic in the treatment of a 30‐year‐old patient called Ms. Daun, who has a recurrent depressive disorder. Based on this case, the benefits of applying information from ROM in psychotherapy, important context factors, and possible implementation issues are discussed. Results/Conclusion: We conclude by encouraging practitioners to integrate ROM into their clinical thinking and daily practice. [ABSTRACT FROM AUTHOR]

• Technological augmentation of cognitive behavior therapy. • Internet therapy and video therapy. • Precision mental health. • Digital assessment and decision support tools in clinical practice. The augmentation of technology to the delivery of CBT has enormously increased in recent years. This commemoration of Dr. Aaron T. Beck's contribution to the field focuses on examples such as CBT internet treatments, video treatments, but especially on data-informed CBT, precision mental health and digitally based treatment navigation systems. It ends with an outlook on continuous outcome measurement as the basis for a broader understanding of clinical concepts and data-driven clinical practice in the future. [ABSTRACT FROM AUTHOR]

This study investigated symptom change trajectory for patients with persistent somatic symptoms (PSS) during psychotherapy and the association of these patterns with pre-treatment characteristics and long-term outcome. Growth mixture modeling was used to identify trajectory curves in a sample of N = 210 outpatients diagnosed with PSS and treated either with conventional cognitive behavioral therapy (CBT) or CBT enriched with emotion regulation training (ENCERT). We identified three subgroups of patients with similar symptom change patterns over the course of treatment (a "no change," "strong response," and "slow change" subgroup). Higher initial anxiety symptoms were significantly associated with the no change and strong response subgroups; symptom-related disability in daily routine with no changes. Patients with a strong response had the highest proportion of reliable improvement at termination and at six-month-follow-up. Our results indicate that, instead of one common change pattern, patients with PSS respond differently to treatment. Due to the high association of symptom curves with long-term outcome, the identification and prediction of an individual's trajectory could provide important information for clinicians to identify non-responding patients that are at risk for failure. Selecting personalized treatment interventions could increase the effectiveness of psychotherapy. Trial registration: ClinicalTrials.gov identifier: NCT01908855.. [ABSTRACT FROM AUTHOR]

Despite evidence showing that systematic outcome monitoring can prevent treatment failure, the practical conditions that allow for implementation are seldom met in naturalistic psychological services. In the context of limited time and resources, session-by-session evaluation is rare in most clinical settings. This study aimed to validate innovative prediction methods for individual treatment progress and dropout risk based on basic outcome monitoring. Routine data of a naturalistic psychotherapy outpatient sample were analyzed (N = 3902). Patients were treated with cognitive behavioral therapy with up to 95 sessions (M = 39.19, SD = 16.99) and assessment intervals of 5–15 sessions. Treatment progress and dropout risk were predicted in two independent analyses using the nearest neighbor method and least absolute shrinkage and selection operator regression, respectively. The correlation between observed and predicted patient progress was r =.46. Intrinsic treatment motivation, previous inpatient treatment, university-entrance qualification, baseline impairment, diagnosed personality disorder, and diagnosed eating disorder were identified as significant predictors of dropout, explaining 11% of variance. Innovative outcome prediction in naturalistic psychotherapy is not limited to elaborated progress monitoring. This study demonstrates a reasonable approach for tracking patient progress as long as session-by-session assessment is not a valid standard. [ABSTRACT FROM AUTHOR]

Objective: We aimed to develop and test an algorithm for individual patient predictions of problem coping experiences (PCE) (i.e., patients' understanding and ability to deal with their problems) effects in cognitive–behavioral therapy. Method: In an outpatient sample with a variety of diagnoses (n=1010), we conducted Dynamic Structural Equation Modelling to estimate within-patient cross-lagged PCE effects on outcome during the first ten sessions. In a randomly selected training sample (2/3 of the cases), we tried different machine learning algorithms (i.e., ridge regression, LASSO, elastic net, and random forest) to predict PCE effects (i.e., the degree to which PCE was a time-lagged predictor of symptoms), using baseline demographic, diagnostic, and clinically-relevant patient features. Then, we validated the best algorithm on a test sample (1/3 of the cases). Results: The random forest algorithm performed best, explaining 14.7% of PCE effects variance in the training set. The results remained stable in the test set, explaining 15.4% of PCE effects variance. Conclusions: The results show the suitability to perform individual predictions of process effects, based on patients' initial information. If the results are replicated, the algorithm might have the potential to be implemented in clinical practice by integrating it into monitoring and therapist feedback systems. [ABSTRACT FROM AUTHOR]

Objective: Thus far, most applications in precision mental health have not been evaluated prospectively. This article presents the results of a prospective randomized-controlled trial investigating the effects of a digital decision support and feedback system, which includes two components of patient-specific recommendations: (a) a clinical strategy recommendation and (b) adaptive recommendations for patients at risk for treatment failure. Method: Therapist–patient dyads (N = 538) in a cognitive behavioral therapy outpatient clinic were randomized to either having access to a decision support system (intervention group; n = 335) or not (treatment as usual; n = 203). First, treatment strategy recommendations (problem-solving, motivation-oriented, or a mix of both strategies) for the first 10 sessions were evaluated. Second, the effect of psychometric feedback enhanced with clinical problem-solving tools on treatment outcome was investigated. Results: The prospective evaluation showed a differential effect size of about 0.3 when therapists followed the recommended treatment strategy in the first 10 sessions. Moreover, the linear mixed models revealed therapist symptom awareness and therapist attitude and confidence as significant predictors of an outcome as well as therapist-rated usefulness of feedback as a significant moderator of the feedback—outcome and the not on track—outcome associations. However, no main effects were found for feedback. Conclusions: The results demonstrate the importance of prospective studies and the high-quality implementation of digital decision support tools in clinical practice. Therapists seem to be able to learn from such systems and incorporate them into their clinical practice to enhance patient outcomes, but only when implementation is successful. What is the public health significance of this article?: This randomized clinical implementation trial provides insight into the evaluation of a clinical decision support and feedback system including personalized pretherapy recommendations and enhanced psychometric feedback during treatment. As it is one of the first decision systems to have been implemented and evaluated prospectively in mental health, this study helps to improve such systems designed to support and change the way psychotherapy is conducted. The results underscore the importance of high-quality implementation of digital decision support tools in clinical practice. [ABSTRACT FROM AUTHOR]

Objective: Both good therapeutic bond as well as extra-therapeutic social support seem to enhance treatment outcomes. Some features of the therapeutic bond are similar to experiences in extra-therapeutic relationships (e.g., feelings of trust or belongingness). Patients with a lack of social support might benefit particularly from a good therapeutic bond, because a well-formed bond can partly substitute relationship needs. This study replicates former research (main effects of bond and social support) and investigates the hypothesized interaction between both constructs. Method: Data from 1206 adult patients receiving cognitive-behavioral outpatient therapy were analyzed. Patients rated early therapeutic bond, their impairment, as well as their social support. Multilevel regression analyses were applied to test for main effects and interactions between bond and social support predicting therapy outcome post treatment. Results: Consistent with prior research, both therapeutic bond and social support predicted therapy outcome. Among patients with high social support, the impact of the therapeutic bond was minimal, while patients with low social support benefited most from a good therapeutic bond. Conclusions: Results suggest that both the therapeutic bond and social support play a role in therapy outcomes and that good therapeutic bond quality might be especially important if a patient lacks social support. [ABSTRACT FROM AUTHOR]

Objective: There is little evidence-based knowledge of how psychotherapists should handle both sudden gains and more gradual session-by-session changes, either in general or in individuals suffering from generalized anxiety disorder. Methods: Using an ABAB crossed-therapist randomized clinical implementation trial design (N = 80 patients and 20 therapists), we contrasted a Prolonged Focus on Change (PFC, N = 40) implementation with a State-Of-The-Art (SOTA, N = 40) implementation. Both implementations were based on a widely used cognitive behavioral therapy approach (Mastery of your Anxiety and Worry package) with the only difference that in the PFC implementation, the therapists were instructed to systematically explore eventual changes at the beginning of the therapy sessions. Results: Based on a 3-level hierarchical linear model, PFC implementation showed faster symptom reduction in worry over therapy (i.e., linear change) and a decelerated (quadratic) change until 12-month follow-up in comparison to the SOTA implementation. Conclusion: These findings provide clinically useful information about potential short-term and long-term effects of exploring occurring change in GAD populations. Randomized clinical implementation trial designs are a step forward allowing to experimentally investigate basic psychotherapeutic strategies in process-based psychotherapy. What is the public health significance of this article?: This randomized clinical implementation trial provides empirical evidence for good clinical wisdom that exploring occurring change is helpful to facilitate further change during therapy. These results underscore the relevance of understanding patient's proactive engagement in change behaviors, competences, skills, and behavioral preferences in individuals that suffer from generalized anxiety disorder to positively impact worry outcomes. [ABSTRACT FROM AUTHOR]

In psychotherapy research, the measurement of treatment processes and outcome are predominantly based on self-reports. However, given new technological developments, other potential sources can be considered to improve measurements. In a feasibility study, we examined whether Ecological Momentary Assessments (EMA) using digital phenotyping (stress level) can be a valuable tool to investigate change processes during cognitive behavioral therapy (CBT). Seven outpatients undergoing psychological treatment were assessed using EMA. Continuous stress levels (heart rate variability) were assessed via fitness trackers (Garmin) every 3 min over a 2-week time period (6,720 measurements per patient). Time-varying change point autoregressive (TVCP-AR) models were employed to detect both gradual and abrupt changes in stress levels. Results for seven case examples indicate differential patterns of change processes in stress. More precisely, inertia of stress level changed gradually over time in one of the participants, whereas the other participants showed both gradual and abrupt changes. This feasibility study demonstrates that intensive longitudinal assessments enriched by digitally assessed stress levels have the potential to investigate intra- and interindividual differences in treatment change processes and their relations to treatment outcome. Further, implementation issues and implications for future research and developments using digital phenotyping are discussed. [ABSTRACT FROM AUTHOR]

Objective: This study aims at developing a treatment selection algorithm using a combination of machine learning and statistical inference to recommend patients' optimal treatment based on their pre-treatment characteristics. Methods: A disorder-heterogeneous, naturalistic sample of N = 1,379 outpatients treated with either cognitive behavioral therapy or psychodynamic therapy was analyzed. Based on a combination of random forest and linear regression, differential treatment response was modeled in the training data (n = 966) to indicate each individual's optimal treatment. A separate holdout dataset (n = 413) was used to evaluate personalized recommendations. Results: The difference in outcomes between patients treated with their optimal vs. non-optimal treatment was significant in the training data, but non-significant in the holdout data (b = –0.043, p =.280). However, for the 50% of patients with the largest predicted benefit of receiving their optimal treatment, the average percentage of change on the BSI in the holdout data was 52.6% for their optimal and 38.4% for their non-optimal treatment (p =.017; d = 0.33 [0.06, 0.61]). Conclusion: A treatment selection algorithm based on a combination of ML and statistical inference might improve treatment outcome for some, but not all outpatients and could support therapists' clinical decision-making. [ABSTRACT FROM AUTHOR]

Objective: The study explored the presence of different patterns of change in a sample of patients who received cognitive therapy for depression sequentially in two different formats: group and individual. Our hypothesis was that patients' baseline characteristics (e.g., symptom severity, self-esteem) would discriminate patterns of response to group and individual therapy. Method: 108 adults who met criteria for depression and completed the treatments included in a randomized controlled trial (RCT) were assessed with the Beck Depression Inventory—II (BDI-II), the Clinical Outcome in Routine Evaluation—Short Form B (CORE-SFB), the Global Assessment of Functioning (GAF), and the repertory grid technique. Growth mixture modeling was carried out to identify the patterns of change. Mixed linear models and repeated measures analysis of variance were performed to compare patients' characteristics in each pattern. Multinomial logistic regression was used to compute predictive models for the patterns from patients' characteristics. Finally, hierarchical linear regression was used to establish the power of each pattern to predict treatment outcome. Results: A 3-class solution was obtained: group therapy improvers, individual therapy improvers, and nonimprovers. Group therapy improvers started therapy with less severe levels of depression and psychological distress, higher functioning and self-esteem, lower perceived social isolation, and lower dilemmatic construction of the self than the other groups. Individual therapy improvers and nonimprovers presented similar characteristics at baseline. However, a significant proportion of nonimprovers presented a concurrent diagnosis of fibromyalgia. Conclusion: The greater the impairment that patients present at baseline, the more likely they are to benefit from individual therapy after group therapy. A diagnosis of fibromyalgia can be considered a risk factor for therapy failure in the treatment of depression. What is the public health significance of this article?: Identification of the profile of patients who respond better to group than to individual therapy for depression and vice versa can help to personalize treatments for depression from an early stage. [ABSTRACT FROM AUTHOR]

Early change is an increasing area of investigation in psychotherapy research. In this study, we analyzed patterns of early change in interpersonal problems and their relationship to nonverbal synchrony and multiple outcome measures for the first time. We used growth mixture modeling to identify different latent classes of early change in interpersonal problems with 212 patients who underwent cognitive–behavioral treatment including interpersonal and emotion-focused elements. Furthermore, videotaped sessions were analyzed using motion energy analysis, providing values for the calculation of nonverbal synchrony to predict early change in interpersonal problems. The relationship between early change patterns and symptoms as well as overall change in interpersonal problems was also investigated. Three latent subgroups were identified: 1 class with slow improvement (n = 145), 1 class with fast improvement (n = 12), and 1 early deterioration class (n = 55). Lower levels of early nonverbal synchrony were significantly related to fast improvement in interpersonal change patterns. Furthermore, such patterns predicted treatment outcome in symptoms and interpersonal problems. The results suggest that nonverbal synchrony is associated with early change patterns in interpersonal problems, which are also predictive of treatment outcome. Limitations of the applied methods as well as possible applications in routine care are discussed. Public Significance Statement: This study suggests that lower levels of nonverbal synchrony may be a predictor of early improvement in interpersonal problems, which furthermore predict treatment outcome in symptoms and interpersonal problems. Given further research, nonverbal synchrony might become a useful addition to monitor successful treatment processes. [ABSTRACT FROM AUTHOR]

Background: Studies with heterogeneous samples in naturalistic treatment settings suggest that movement synchrony (MS) between therapists and patients correlates with therapeutic success. In this study, we examined a homogeneous sample of patients with social anxiety disorder and investigated whether MS in sessions 3 and 8 would be associated with therapy outcome and therapeutic alliance, and whether these associations depend on the therapeutic approach. Methods: The patients (N = 267) were treated with either manual-guided cognitive behavior therapy (CBT), manual-guided psychodynamic therapy (PDT), or naturalistic CBT. The Helping Alliance Questionnaire (HAQ), the Inventory of Interpersonal Problems (IIP) and the Beck-Depression-Inventory (BDI) were used as measures. Body motions were coded with motion energy analysis. MS was quantified using time series analysis methods. Results: MS was observed more frequently in both CBT conditions than in PDT. In both CBT groups, more synchrony was predictive of lower IIP scores at the end of therapy. If the patient lead synchrony more often than the therapist, higher IIP and BDI scores were observed at the end of treatment. PDT showed the largest effect size for the synchrony-alliance-association. Conclusion: Movement synchrony and therapeutic success are associated. The effect of therapeutic approach and leading/following are relevant for this association. [ABSTRACT FROM AUTHOR]

The third wave of cognitive behavioral therapy (CBT) has increased the heterogeneity of today's CBT practice, while developments in patient-focused research are paving the road to the empirical personalization of CBT. This paper presents the development and psychometric properties of a therapy video rating instrument, which was designed to adequately assess the treatment integrity (adherence and competence) of modern, personalized CBT. The Inventory of Therapeutic Interventions and Skills (ITIS) was developed based on two existing CBT adherence and competence scales and augmented with third wave content and overarching therapeutic strategies. The instrument was then applied by graduate students and post-graduate clinicians to rate N = 185 therapy videos from N = 70 patients treated at a university outpatient clinic. Descriptive results, inter-rater reliability, item structure, and associations with session outcome and alliance were examined. Average inter-rater reliability was excellent for Interventions items and good for Skills items. Intercorrelations were low between Interventions items, but higher and significant between Skills items, which loaded on a single factor. Several ITIS items were shown to be predictive of session outcome and alliance, even after controlling for the nested data structure. Implications of these results for future research and clinical training are discussed. [ABSTRACT FROM AUTHOR]

Background: The therapeutic alliance is an important factor in psychotherapy, affecting both therapy processes and outcome. Therapy transfers may impair the quality of the therapeutic alliance and increase symptom severity. The aim of this study is to investigate the impact of patient transfers in cognitive behavioural therapy on alliance and symptoms in the sessions after the transfer. Method: Patient‐ and therapist‐rated therapeutic alliance and patient‐reported symptom severity were measured session‐to‐session. Differences in the levels of alliance and symptom severity before (i.e., with the original therapist) and after (i.e., with the new therapist) the transfer session were analysed. The development of alliance and symptom severity was explored using multilevel growth models. Results: A significant drop in the alliance was found after the transfer, whereas no differences were found with regard to symptom severity. After an average of 2.93 sessions, the therapeutic alliance as rated by patients reached pretransfer levels, whereas it took an average of 5.05 sessions for therapist‐rated alliance levels to be at a similar level as before the transfer. Inter‐individual differences were found with regard to the development of the therapeutic alliance over time. Conclusions: Therapy transfers have no long lasting negative effects on either symptom impairment or the therapeutic alliance. [ABSTRACT FROM AUTHOR]

We analyzed the verbal behavior of patients with mood or/and anxiety disorders during psychotherapy. Investigating the words people used, we expected differences due to cognitive and emotional foci in patients with depression vs. anxiety. Transcripts of therapy sessions from 85 outpatients treated with cognitive behavioral therapy were analyzed using the software program Linguistic Inquiry and Word Count. Multivariate group comparisons were carried out investigating the LIWC-categories first-person-singular pronouns, sad, anxiety and fillers. Differences between the three diagnostic groups were found in verbal utterances related to sadness (p =.05). No differences were found for first-person-singular pronouns and content-free fillers. Comparing the distinct groups “depression” and “anxiety”, depressed patients used more words related to sadness (p =.01). Mood and anxiety disorders differ in the experience of emotions, but only slightly in self-focused attention. This points to differences in language use for different diagnostic groups and may help to improve diagnostic procedures or language-driven interventions which enhance therapists’ attention to patients’ verbal behavior. [ABSTRACT FROM AUTHOR]

Background: Trauma-focused cognitive behavioral therapy (Tf-CBT) and eye movement desensitization and reprocessing (EMDR) are two highly effective treatment options for posttraumatic stress disorder (PTSD). Yet, on an individual level, PTSD patients vary substantially in treatment response. The aim of the paper is to test the application of a treatment selection method based on a personalized advantage index (PAI).Method: The study used clinical data for patients accessing treatment for PTSD in a primary care mental health service in the north of England. PTSD patients received either EMDR (N = 75) or Tf-CBT (N = 242). The Patient Health Questionnaire (PHQ-9) was used as an outcome measure for depressive symptoms associated with PTSD. Variables predicting differential treatment response were identified using an automated variable selection approach (genetic algorithm) and afterwards included in regression models, allowing the calculation of each patient's PAI.Results: Age, employment status, gender, and functional impairment were identified as relevant variables for Tf-CBT. For EMDR, baseline depressive symptoms as well as prescribed antidepressant medication were selected as predictor variables. Fifty-six percent of the patients (n = 125) had a PAI equal or higher than one standard deviation. From those patients, 62 (50%) did not receive their model-predicted treatment and could have benefited from a treatment assignment based on the PAI.Conclusions: Using a PAI-based algorithm has the potential to improve clinical decision making and to enhance individual patient outcomes, although further replication is necessary before such an approach can be implemented in prospective studies. [ABSTRACT FROM AUTHOR]

Background: Most individuals with depression do not receive adequate treatment. Internet interventions may help to bridge this gap. Research on attitudes toward Internet interventions might facilitate the dissemination of such interventions by identifying factors that help or hinder uptake and implementation, and by clarifying who is likely to benefit. This study examined whether attitudes toward Internet interventions moderate the effects of a depression-focused Internet intervention, and how attitudes change over the course of treatment among those who do or do not benefit.Methods: We recruited 1,004 adults with mild-to-moderate depression symptoms and investigated how attitudes toward Internet interventions are associated with the efficacy of the program deprexis, and how attitudes in the intervention group change from pre to post over a 3 months intervention period, compared to a control group (care as usual). This study consists of a subgroup analysis of the randomized controlled EVIDENT trial.Results: Positive initial attitudes toward Internet interventions were associated with greater efficacy (η2p  = .014) independent of usage time, whereas a negative attitude (perceived lack of personal contact) was associated with reduced efficacy (η2p  = .012). Users' attitudes changed during the trial, and both the magnitude and direction of attitude change were associated with the efficacy of the program over time (η2p  = .030).Conclusions: Internet interventions may be the most beneficial for individuals with positive attitudes toward them. Informing potential users about evidence-based Internet interventions might instill positive attitudes and thereby optimize the benefits such interventions can provide. Assessing attitudes prior to treatment might help identify suitable users. [ABSTRACT FROM AUTHOR]

Objective: The concept of alliance ruptures has had a large impact on contemporary studies of the alliance. Although this debate mainly focuses on the effect of ruptures and repairs on subsequent alliance and outcome levels within patients, to date no study has actually examined these within-patient effects. The present study fills this lacuna by examining the effect of alliance ruptures and in-session repairs on alliance ratings and symptom impairment in the subsequent session, accounting for the temporal sequence of ruptures and symptom impairment. Method: Ruptures and in-session repairs were rated by 1.210 patients and 147 therapists using a postsession questionnaire (PSQ-P/-T). Alliance was assessed with the Bern postsession reports and symptomatic impairment with the Hopkins symptom checklist, short form. Results: Patient- and therapist-reported ruptures were significant predictors of subsequent alliance and symptom impairment. While sessions in which both patient and therapist perceived a rupture were especially detrimental for next session symptom distress, they were less damaging to next session alliance levels than sessions in which either only the patient or the therapist experienced the rupture. Neither the intensity of the rupture nor the perceived level of in-session repair were associated with next-session fluctuations in symptom or alliance levels within-patient. Conclusion: The findings demonstrate the importance of disentangling between- and within-patient rupture and in-session repair processes to better understand the roles of rupture and repair in treatment. [ABSTRACT FROM AUTHOR]

Objective: Sudden gains are sudden symptom improvements from 1 psychotherapy session to the next. This study investigates the processes that may facilitate treatment outcome after a sudden gain occurred. Method: A sample of 211 depressed patients who underwent cognitive-behavioral therapy was analyzed. Sudden gains were identified using a session-by-session self-report symptom measure. Patient ratings of general change factors (therapeutic alliance; coping skills) in the sessions before and after a sudden gain were investigated as predictors of outcome. Propensity score matching was used to compare sudden gain patients with similar patients who did not experience a sudden gain. Results: Therapeutic alliance and coping skills increased in the postgain sessions. There were no comparable processes of change among patients without sudden gains. The therapeutic alliance was found to moderate the association between sudden gains and treatment outcome. Conclusion: Results suggest that sudden gains trigger change factors that facilitate the association between gains and treatment outcome. Patient-therapist dyads should work with sudden gains to consolidate symptom relief. [ABSTRACT FROM AUTHOR]

Background: Mild to moderate depressive symptoms are common but often remain unrecognized and treated inadequately. We hypothesized that an Internet intervention in addition to usual care is superior to care as usual alone (CAU) in the treatment of mild to moderate depressive symptoms in adults.Methods: This trial was controlled, randomized and assessor-blinded. Participants with mild to moderate depressive symptoms (Patient Health Questionnaire, PHQ-9, score 5-14) were recruited from clinical and non-clinical settings and randomized to either CAU or a 12-week Internet intervention (Deprexis) adjunctive to usual care. Outcomes were assessed at baseline, 3 months (post-assessment) and 6 months (follow-up). The primary outcome measure was self-rated depression severity (PHQ-9). The main analysis was based on the intention-to-treat principle and used linear mixed models.Results: A total of 1,013 participants were randomized. Changes in PHQ-9 from baseline differed signixFB01;cantly between groups (t825 = 6.12, p < 0.001 for the main effect of group). The post-assessment between-group effect size in favour of the intervention was d = 0.39 (95% CI: 0.13-0.64). It was stable at follow-up, with d = 0.32 (95% CI: 0.06-0.69). The rate of participants experiencing at least minimally clinically important PHQ-9 change at the post-assessment was higher in the intervention group (35.6 vs. 20.2%) with a number needed to treat of 7 (95% CI: 5-10).Conclusions: The Internet intervention examined in this trial was superior to CAU alone in reducing mild to moderate depressive symptoms. The magnitude of the effect is clinically important and has public health implications. [ABSTRACT FROM AUTHOR]

Background: The efficacy of cognitive behavioral therapy (CBT) for the treatment of depressive disorders has been demonstrated in many randomized controlled trials (RCTs). This study investigated whether for CBT similar effects can be expected under routine care conditions when the patients are comparable to those examined in RCTs.Method: N=574 CBT patients from an outpatient clinic were stepwise matched to the patients undergoing CBT in the National Institute of Mental Health Treatment of Depression Collaborative Research Program (TDCRP). First, the exclusion criteria of the RCT were applied to the naturalistic sample of the outpatient clinic. Second, propensity score matching (PSM) was used to adjust the remaining naturalistic sample on the basis of baseline covariate distributions. Matched samples were then compared regarding treatment effects using effect sizes, average treatment effect on the treated (ATT) and recovery rates.Results: CBT in the adjusted naturalistic subsample was as effective as in the RCT. However, treatments lasted significantly longer under routine care conditions.Limitations: The samples included only a limited amount of common predictor variables and stemmed from different countries. There might be additional covariates, which could potentially further improve the matching between the samples.Conclusions: CBT for depression in clinical practice might be equally effective as manual-based treatments in RCTs when they are applied to comparable patients. The fact that similar effects under routine conditions were reached with more sessions, however, points to the potential to optimize treatments in clinical practice with respect to their efficiency. [ABSTRACT FROM AUTHOR]

Objective:Psychotherapy for depression emphasizes techniques that can help individuals regulate their moods. The present study investigated the affective impact and electrocortical correlates of cognitive restructuring, delivered as a 90-minute psychotherapeutic microintervention in a dysphoric sample.Method:Participants (N =92) who reported either low or high levels of dysphoric symptoms were randomly assigned to the restructuring microintervention, a control intervention or a no-intervention condition. We obtained recordings of event-related potentials (ERPs) as well as mood self-ratings during an experimental session immediately after the psychotherapeutic microintervention and the control intervention in which a set of negatively valenced pictures (IAPS) was presented with different instructions.Results:Whereas the restructuring intervention group and the control intervention group reported both increases in positive and decreases in negative affect from pre- to post-intervention, the three groups differed significantly on ERP measures.Conclusions:Findings provide support for current models of mechanisms of action in cognitive therapies. [ABSTRACT FROM PUBLISHER]

Objective: Recently, innovative statistical tools have been used to model patterns of change in psychological treatments. These tools can detect patterns of change in patient progress early in treatment and allow for the prediction of treatment outcomes and treatment length. Method: We used growth mixture modeling to identify different latent classes of early change in patients with panic disorder (N = 326) who underwent a manualized cognitive-behavioral treatment. Results: Four latent subgroups were identified, showing clusters of change trajectories over the first 5 sessions. One of the subgroups consisted of patients whose symptoms rapidly decreased and also showed the best outcomes. This information improved treatment prediction by 16.1% over patient intake characteristics. Early change patterns also significantly predicted patients' early treatment termination. Patient intake characteristics that significantly predicted class membership included functional impairment and separation anxiety. Conclusions: These findings suggest that early treatment changes are uniquely predictive of treatment outcome. [ABSTRACT FROM AUTHOR]

The article discusses a study focusing on the relapse and recurrence rates of mental health problems in people who were treated using low intensity cognitive behavioural therapy (LiCBT). Topics discussed include the patients with depression and anxiety disorders, who were part of the study; the criteria for risk event in the study; and the diagnosis of acute symptoms of depression and anxiety in the patients.

In this study, a computer-based feedback, decision and clinical problem-solving system for clinical practice will be described - the Trier Treatment Navigator (TTN). The paper deals with the underlying research concepts related to personalized pre-treatment recommendations for drop-out risk and optimal treatment strategy selection as well as personalized adaptive recommendations during treatment. The development sample consisted of 1234 patients treated with cognitive behavioral therapy (CBT). Modern statistical machine learning techniques were used to develop personalized recommendations. Drop-out analyses resulted in seven significant predictors explaining 12.0% of variance. The prediction of optimal treatment strategies resulted in differential prediction models substantially improving effect sizes and reliable improvement rates. The dynamic failure boundary reliably identified patients with a higher risk for no improvement or deterioration and indicated the usage of clinical problem-solving tools in risk areas. The probability to be reliably improved for patients identified as at risk for treatment failure was about half of the probability for other patients (35% vs. 62.15%; χ 2 df=1 = 82.77, p <.001). Results related to the computer-based feedback system are discussed with regard to the implication for clinical applications as well as clinical training and future research possibilities. • This paper presents a comprehensive feedback system: Trier Treatment Navigator (TTN). • The TTN provides personalized pre-treatment recommendations and adaptive recommendations during treatment. • Personalized predictions of drop-out risk and early treatment strategy allow a more patient-oriented treatment. • The dynamic failure boundary identifies patients with a higher risk for no improvement or deterioration. • A risk signal indicates the use of clinical problem-solving tools in risk areas to improve treatment. [ABSTRACT FROM AUTHOR]

Client--therapist synchrony in various channels (e.g., self-reported affect or physical movement) has been shown as a key process in the construction and development of therapeutic alliance. However, psychophysiological synchrony between clients and therapists has been understudied, with the few extant studies typically relying on single-session data, and no studies examining it within the context of emotionfocused techniques. The main aim of the current paper is to examine the role of client-therapist physiological synchrony during segments of one emotion-focused technique--namely, imagery (IM) work--in predicting therapeutic alliance, and to compare it to the role of synchrony during segments of more traditional cognitive--behavioral (CB) techniques. We conducted an open-trial study in which 31 clients with test anxiety received a 6-session protocol-based treatment. Both clients' and therapists' electrodermal activity (EDA) were continuously assessed during sessions. The physiological measures for 5 sessions each (N = 128) were used to compute client--therapist synchrony in IM and CB segments. Therapeutic alliance was assessed using the Session Alliance Inventory. Client--therapist dyads' synchrony during IM and CB segments was, on average, greater than chance. Synchrony varied mostly at the session (vs. the dyad) level. Multilevel analyses revealed that the synchrony within IM segments (but not within CB segments) was significantly associated with the therapeutic bond aspect (but not the task/goal aspects) of alliance. Physiological synchrony during emotion-focused IM is tied to the bond component of the therapeutic alliance at the session level. [ABSTRACT FROM AUTHOR]

The current study employed machine learning to investigate whether the inclusion of observer-rated therapist interventions and skills in early sessions of psychotherapy improved dropout prediction beyond intake assessments. Patients were treated by postgraduate clinicians at a university outpatient clinic. Psychometric instruments were assessed at intake and therapeutic interventions and skills in the third session were routinely rated by independent observers. After variable preselection, an elastic net algorithm was used to build two dropout prediction models, one including and one excluding observer-rated session variables. The best model included observer-rated variables and was significantly superior to the model including intake variables only. Alongside intake variables, two observer-rated variables significantly predicted dropout: therapist use of feedback and summaries and treatment difficulty. Although not retained in the final prediction model, the observer-rated use of cognitive techniques was also significantly correlated with dropout. Observer ratings of therapist interventions and skills in early sessions of psychotherapy improve predictors of dropout from psychotherapy beyond intake variables alone. Future research could work toward personalizing dropout predictions to the specific dyad, thereby improving their validity and aiding therapists to recognize and react to increased dropout risk. [ABSTRACT FROM AUTHOR]

Background: Although a wide body of research links depression to interpersonal deficits, Cognitive-Behavioral Therapy (CBT), considered the gold standard in the treatment of this condition, has not been developed to specifically address interpersonal difficulties. However, cognitive changes on a relational level occurring during CBT might play an important role in the treatment of depression. Interpersonal clarification refers to the process of better understanding the nature of one's interpersonal patterns during therapy. The aim of this study is to analyze the effects of interpersonal clarification in CBT and how they are moderated by the therapeutic alliance.Methods: A sample of 621 patients diagnosed with depression were treated with CBT by 126 therapists in a university outpatient clinic. Patients completed measures of interpersonal problems and depression severity at baseline, measures of symptomatic evolution before each session and process measures (assessing interpersonal clarification and alliance) after each session. Multilevel models separating between-patient (BP) and within-patient (WP) effects of interpersonal clarification, and including BP and WP alliance effects as covariates and moderators of the interpersonal clarification effects were conducted.Results: Analyses showed both significant BP and WP effects interpersonal clarification, even when adjusting for alliance effects. Furthermore, significant interactive effects were found between outcome of WP interpersonal clarification with both BP alliance and WP alliance.Limitations: Interpersonal clarification was measured with one single-item and adherence to CBT was not explicitly measured.Conclusions: The results present preliminary evidence for considering interpersonal clarification a meaningful change process in CBT for depression, especially in the context of a stronger therapeutic alliance. [ABSTRACT FROM AUTHOR]

Background Internet interventions are effective in treating depressive symptoms but few studies conducted a long-term follow-up. The aim of this study was to test the effectiveness of an internet intervention in increasing the remission rate over a twelve months period. Methods A total of 1013 participants with mild to moderate depressive symptoms were randomized to either care as usual alone or a 12-week internet intervention (Deprexis) plus usual care. Self-rated depression severity (PHQ-9) was assessed regularly over twelve months. Results Remission rates over time were significantly higher in the intervention group (Cox regression: hazard ratio [HR] 1.31; p = 0.009). The intervention was more effective in the subgroup not taking antidepressant medication (Cox regression: HR 1.88; p < 0.001). PHQ-change from baseline was greater in the intervention group (linear mixed model [LMM]: p < 0.001) with the between-group effect gradually decreasing from d = 0.36 at three months to d = 0.13 at twelve months (LMM: group by time interaction: p < 0.001). Conclusion This internet intervention can contribute to achieving remission in people with mild to moderate depressive symptoms, especially if they are not on antidepressant medication (Trial Registration: NCT01636752). [ABSTRACT FROM AUTHOR]

Background Over the last decade, a substantial amount of findings have been reported on the association between sudden gains (large symptom improvements in a between-session interval) and treatment outcome. Accurate replications of previous findings are needed to tackle inconsistencies and to shed light on the clinical implications of sudden gains. This study investigates whether similar effects of sudden gains can be expected under routine care conditions, when the patients are comparable to those examined in the original study by Tang and DeRubeis (1999). Method Using propensity score matching (PSM), 462 patients treated with cognitive behavioral therapy (CBT) under routine conditions were matched stepwise to patients of the original study on sudden gains, a randomized controlled CBT trial (RCT). Results After the application of PSM, the effects of sudden gains on treatment outcome were similar to those found by Tang and DeRubeis (1999). The closer the match between the RCT and the naturalistic sample, the more similar the association between sudden gains and treatment outcome. Conclusion Sudden gains seem to have a significant impact on recovery rates, even in treatments under routine care. Results suggest that one important aspect of replication success is to control for confounding baseline covariates. [ABSTRACT FROM AUTHOR]