Location-scale modeling as an integrative approach to symptom dynamics during psychotherapy: An illustration with depressive symptoms.

OBJECTIVE: Depressive symptom dynamics, including change trajectories and symptom variability, have been related to therapy outcomes. However, such dynamics have often been examined separately and related to outcomes of interest using two-step analyses, which are characterized by several limitations. Here, we show how to overcome these limitations using location-scale models in a dynamic structural equation modeling framework. METHOD: We introduce location-scale modeling in an accessible manner to pave the way for its use in research integrating within-person dynamics and intervention-related change in psychopathology, and we illustrate this modeling approach in a large-scale internet-based intervention for depression (N = 1,656). Using eight data points sampled across about 8 weeks, we predicted improvement across the intervention (50% symptom reduction) as a function of early change and symptom variability. RESULTS: Early symptom change was associated with a more likely improvement across therapy. Variability of symptoms beyond change trajectories during the intervention was associated with less likely improvement. CONCLUSIONS: Location-scale models, and dynamic structural equation modeling more generally, are well suited to modeling how patterns of symptom change during psychotherapy are related to important (e.g., therapy) outcomes. Our illustrative application of location-scale modeling showed that symptom variability was associated with less overall improvement in depressive symptoms. However, this finding requires replication with more intensive sampling of symptoms before final conclusions can be drawn on when and how to distinguish maladaptive from adaptive variability during psychotherapy. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Select or adjust? How information from early treatment stages boosts the prediction of non-response in internet-based depression treatment.

BACKGROUND: Internet-based interventions produce comparable effectiveness rates as face-to-face therapy in treating depression. Still, more than half of patients do not respond to treatment. Machine learning (ML) methods could help to overcome these low response rates by predicting therapy outcomes on an individual level and tailoring treatment accordingly. Few studies implemented ML algorithms in internet-based depression treatment using baseline self-report data, but differing results hinder inferences on clinical practicability. This work compares algorithms using features gathered at baseline or early in treatment in their capability to predict non-response to a 6-week online program targeting depression. METHODS: Our training and test sample encompassed 1270 and 318 individuals, respectively. We trained random forest algorithms on self-report and process features gathered at baseline and after 2 weeks of treatment. Non-responders were defined as participants not fulfilling the criteria for reliable and clinically significant change on PHQ-9 post-treatment. Our benchmark models were logistic regressions trained on baseline PHQ-9 sum or PHQ-9 early change, using 100 iterations of randomly sampled 80/20 train-test-splits. RESULTS: Best performances were reached by our models involving early treatment characteristics (recall: 0.75-0.76; AUC: 0.71-0.77). Therapeutic alliance and early symptom change constituted the most important predictors. Models trained on baseline data were not significantly better than our benchmark. CONCLUSIONS: Fair accuracies were only attainable by involving information from early treatment stages. In-treatment adaptation, instead of a priori selection, might constitute a more feasible approach for improving response when relying on easily accessible self-report features. Implementation trials are needed to determine clinical usefulness.

Sequencing effects of behavioral activation and cognitive restructuring in an Internet-based intervention for depressed adults are negligible: Results from a randomized controlled trial.

OBJECTIVE: Applying elements of cognitive behavioral therapy (CBT) in internet-based interventions (IBIs) is effective in treating depression. However, CBT-based IBIs differ in which kind of components are applied and the order of their application. Furthermore, it is as yet unknown whether such sequencing matters. Using an IBI for depression, we examined whether the sequence of two major CBT components, behavioral activation (BA) and cognitive restructuring (CR), affect patterns of symptom changes and dropout rates. METHOD: Individuals with moderate to mild depressive symptoms (N = 2,304, 59% female) were randomly assigned to two groups: one group that received BA in Modules 2 and 3 and CR in Modules 4 and 5, and another group with the opposite sequence. The component contents were identical. We investigated group differences in dropout rates, symptom changes, and change trajectories across the intervention. RESULTS: The groups had similar dropout rates and showed similar changes pre- to postassessment, and from pre- to 3-, 6-, and 12-month follow-up assessments. Between-group differences were small enough to be considered equivalent. Three classes of change trajectories emerged in both groups, but they did not differ in shape or size and did not show diverging associations with person-level characteristics. CONCLUSIONS: Results suggest that the sequence of the CBT components BA and CR in IBIs for depression does, on average, not systematically impact how individuals change during and after participation, which provides flexibility in designing CBT-based interventions. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

On the Meaning of the "P Factor" in Symmetrical Bifactor Models of Psychopathology: Recommendations for Future Research From the Bifactor-(S-1) Perspective.

Symmetrical bifactor models are frequently applied to diverse symptoms of psychopathology to identify a general P factor. This factor is assumed to mark shared liability across all psychopathology dimensions and mental disorders. Despite their popularity, however, symmetrical bifactor models of P often yield anomalous results, including but not limited to nonsignificant or negative specific factor variances and nonsignificant or negative factor loadings. To date, these anomalies have often been treated as nuisances to be explained away. In this article, we demonstrate why these anomalies alter the substantive meaning of P such that it (a) does not reflect general liability to psychopathology and (b) differs in meaning across studies. We then describe an alternative modeling framework, the bifactor-(S-1) approach. This method avoids anomalous results, provides a framework for explaining unexpected findings in published symmetrical bifactor studies, and yields a well-defined general factor that can be compared across studies when researchers hypothesize what construct they consider "transdiagnostically meaningful" and measure it directly. We present an empirical example to illustrate these points and provide concrete recommendations to help researchers decide for or against specific variants of bifactor structure.

Increasing the effectiveness of psychotherapy in routine care through blended therapy with transdiagnostic online modules (PsyTOM): study protocol for a randomized controlled trial.

BACKGROUND: In blended therapy, face-to-face psychotherapy and Internet-based interventions are combined. Blended therapy may be advantageous for patients and psychotherapists. However, most blended interventions focus on cognitive behavioral therapy or single disorders, making them less suitable for routine care settings. METHODS: In a randomized controlled trial, we will compare blended therapy and face-to-face therapy in routine care. We intend to randomize 1152 patients nested in 231 psychotherapists in a 1:1 ratio. Patients in the blended therapy group will receive access to a therapeutic online intervention (TONI). TONI contains 12 transdiagnostic online modules suited for psychodynamic, cognitive behavioral, and systemic therapy. Psychotherapists decide which modules to assign and how to integrate TONI components into the psychotherapeutic process to tailor treatment to their patients' specific needs. We will assess patients at baseline, 6 weeks, 12 weeks, and 6 months. Patients enrolled early in the trial will also complete assessments at 12 months. The primary outcomes are depression and anxiety at 6-month post-randomization, as measured by PHQ-8 and GAD-7. The secondary outcomes include satisfaction with life, level of functioning, personality traits and functioning, eating pathology, sexual problems, alcohol/drug use, satisfaction with treatment, negative effects, and mental health care utilization. In addition, we will collect several potential moderators and mediators, including therapeutic alliance, agency, and self-efficacy. Psychotherapists will also report on changes in symptom severity and therapeutic alliance. Qualitative interviews with psychotherapists and patients will shed light on the barriers and benefits of the blended intervention. Furthermore, we will assess significant others of enrolled patients in a sub-study. DISCUSSION: The integration of online modules which use a common therapeutic language and address therapeutic principles shared across therapeutic approaches into regular psychotherapy has the potential to improve the effectiveness of psychotherapy and transfer it into everyday life as well help save therapists' resources and close treatment gaps. A modular and transdiagnostic setup of the blended intervention also enables psychotherapists to tailor their treatment optimally to the needs of their patients. TRIAL REGISTRATION: German Clinical Trials Register (DRKS) DRKS00028536. Registered on 07.06.2022.

Mind the context-The relevance of personality for face-to-face and computer-mediated communication.

A large body of research has examined the link between personality and face-to-face (FtF) communication knowledge, skills, abilities, and other characteristics (KSAOs). With the rise of digital media, text-based computer-mediated (CM) communication KSAOs have gained increasing attention. We conducted two studies to investigate how personality relates to KSAOs in the different contexts of FtF and CM communication. Contrasting perspectives hypothesize that the results in the FtF and CM contexts would be very similar or distinctly different. In Study 1 (n = 454), an online panel study, the Big Five personality dimensions were assessed and their relationships to FtF and CM communication KSAOs were investigated. Structural equation models and relative weight regression analyses showed that these personality dimensions, mostly extraversion and neuroticism, explained more variance in FtF as compared to CM communication KSAOs. Study 2 (n = 173), conducted in a laboratory context, showed similar results compared to Study 1. In addition, when the Big Five personality dimensions were assessed with a CM frame of reference, more variance was explained in CM than in FtF communication KSAOs. These results point to the importance of considering context effects in communication and in personality research: FtF and CM communication KSAOs need to be differentiated. If not properly contextualized, the relevance of personality and communication competencies in predicting criteria may be underestimated due to contextual mismatches.

Negative effects in internet-based interventions for depression: A qualitative content analysis.

An increasing number of studies is proving the efficacy of Internet-based interventions (IBI) for treating depression. While the focus of most studies is thereby lying on the potential of IBI to alleviate emotional distress and enhance well-being, few studies are investigating possible negative effects that might be encountered by participants. The current study was therefore exploring self-reported negative effects of participants undergoing a cognitive-behavioral IBI targeting mild to moderate depression over 6 weeks. Data from the client pool of a German insurance company (n = 814, 68% female) revealed that 8.6% of the participants reported the experience of negative effects. Qualitative content analysis yielded two broad categories and five subcategories for the nature of participants' experiences of negative effects: participant-related negative effects (insight and symptom) and program-related negative effects (online format, contact, and implementation). By using both, qualitative and quantitative methods, results did not only shed light on the characteristics of negative effects but analyses also found that working alliance was a predictor for the experience of negative effects. Monitoring the occurrences of negative effects as well as working alliance throughout treatment was considered essential to help prevent negative effects and attrition among participants undergoing IBI for depression.

Factors contributing to symptom change in standardized and individualized Internet-based interventions for depression: A randomized-controlled trial.

Research suggests 4 categories of outcome predictors in face-to-face therapy (i.e., treatment expectations, extratherapeutic factors, relationship factors, and factors specific to a treatment approach/technique). However, it is unclear whether these factors are relevant in standardized and individualized Internet-based interventions. To investigate this question, a secondary analysis of data from 1,089 mildly to moderately depressed adults undergoing 6 weeks of cognitive-behavioral Internet-based intervention for depression randomized to receive either weekly written feedback individualized by a counselor or automated and fully standardized feedback was performed. The following variables corresponding to the 4 categories were tested regarding associations with depressive symptom change during multiple treatment periods within a multigroup structural equation model: (a) outcome expectations, (b) extratherapeutic stressors and stress change during treatment, (c) midtreatment working alliance (task/goal and bond), and (d) uptake of treatment-specific components (logins and specific tool use). Results suggest similar regressive associations across treatment conditions: Previous symptom change was the most important predictor for subsequent symptom developments. Stress at baseline and the uptake of specific treatment components only played a minor role, and stronger task/goal ratings were associated with later symptom improvements. Early symptom improvements predicted stronger midtreatment task/goal and bond ratings, whereas only stronger task/goal ratings were associated with later symptom improvements. Outcome expectations were only indirectly related with symptom change mediated through goal/task ratings. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Giving G a Meaning: An Application of the Bifactor-(S-1) Approach to Realize a More Symptom-Oriented Modeling of the Beck Depression Inventory-II.

The Beck Depression Inventory-II is one of the most frequently used scales to assess depressive burden. Despite many psychometric evaluations, its factor structure is still a topic of debate. An increasing number of articles using fully symmetrical bifactor models have been published recently. However, they all produce anomalous results, which lead to psychometric and interpretational difficulties. To avoid anomalous results, the bifactor-(S-1) approach has recently been proposed as alternative for fitting bifactor structures. The current article compares the applicability of fully symmetrical bifactor models and symptom-oriented bifactor-(S-1) and first-order confirmatory factor analysis models in a large clinical sample (N = 3,279) of adults. The results suggest that bifactor-(S-1) models are preferable when bifactor structures are of interest, since they reduce problematic results observed in fully symmetrical bifactor models and give the G factor an unambiguous meaning. Otherwise, symptom-oriented first-order confirmatory factor analysis models present a reasonable alternative.

How individuals change during internet-based interventions for depression: A randomized controlled trial comparing standardized and individualized feedback.

BACKGROUND: Standardized and individualized Internet-based interventions (IBI) for depression yield significant symptom improvements. However, change patterns during standardized or individualized IBI are unknown. Identifying subgroups that experience different symptom courses during IBI and their characteristics is vital for improving response. METHODS: Mildly to moderately depressed individuals according to self-report (N = 1,089) were randomized to receive module-wise feedback that was either standardized or individualized by a counselor within an otherwise identical cognitive-behavioral IBI for depression (seven modules over six weeks). Depressive symptoms were assessed at baseline and before each module (Patient Health Questionnaire; PHQ-9). Other individual characteristics (self-report) and the presence of an affective disorder (structured clinical interview) were assessed at baseline. Growth mixture modeling was used to identify and compare subgroups with discernable change patterns and associated client variables across conditions. RESULTS: Model comparisons suggest equal change patterns in both conditions. Across conditions, a group of immediate (62.5%) and a group of delayed improvers (37.5%) were identified. Immediate improvers decreased their PHQ-9 score by 5.5 points from pre to post, with 33% of improvement occurring before treatment commenced. Delayed improvers were characterized by stable symptom severity during the first two modules and smaller overall symptom decrease (3.4 points). Higher treatment expectations, a current major depressive disorder (interview), and lower social support were associated with delayed improvement. CONCLUSION: Internet-based interventions for depression with individualized and with standardized feedback lead to comparable patterns of change. Expectation management and bolstering of social support are promising strategies for individuals that are at risk for delayed improvement.

Efficacy of Cyberbullying Prevention on Somatic Symptoms-Randomized Controlled Trial Applying a Reasoned Action Approach.

The theory of reasoned action (ToRA) has been proposed as a framework for cyberbullying prevention design, targeting attitudes and norms. In this study effects of a long (10 weekly sessions) and a short (one day, four sessions) cyberbullying prevention program based on the ToRA were compared with a control group over 9 months. Longitudinal data from 722 students (mean age = 13.36) on cyberbullying, somatic symptoms, attitudes, and norms were analyzed within a structural equation model. Participation in the long intervention group significantly reduced cyberbullying (d = -0.584) and somatic symptoms (d = -0.316). No between-group differences emerged for attitudes and norms. Developmental trajectories and associations were found to be as suggested by ToRA in both cross-sectional and change-score analyses.

Benefits of Individualized Feedback in Internet-Based Interventions for Depression: A Randomized Controlled Trial.

BACKGROUND: Even though there is an increasing number of studies on the efficacy of Internet-based interventions (IBI) for depression, experimental trials on the benefits of added guidance by clinicians are scarce and inconsistent. This study compared the efficacy of semistandardized feedback provided by psychologists with fully standardized feedback in IBI. METHODS: Participants with mild-to-moderate depression (n = 1,089, 66% female) from the client pool of a health insurance company participated in a cognitive-behavioral IBI targeting depression over 6 weeks. Individuals were randomized to weekly semistandardized e-mail feedback from psychologists (individual counseling; IC) or to automated, standardized feedback where a psychologist could be contacted on demand (CoD). The contents and tasks were identical across conditions. The primary outcome was depression; secondary outcomes included anxiety, rumination, and well-being. Outcomes were assessed before and after the intervention and 3, 6, and 12 months later. Changes in outcomes were evaluated using latent change score modeling. RESULTS: Both interventions yielded large pre-post effects on depression (Beck Depression Inventory-II: dIC = 1.53, dCoD = 1.37; Patient Health Questionnaire-9: dIC = 1.20, dCoD = 1.04), as well as significant improvements of all other outcome measures. The effects remained significant after 3, 6, and 12 months. The groups differed with regard to attrition (IC: 17.3%, CoD: 25.8%, p = 0.001). Between-group effects were statistically nonsignificant across outcomes and measurement occasions. CONCLUSION: Adding semistandardized guidance in IBI for depression did not prove to be more effective than fully standardized feedback on primary and secondary outcomes, but it had positive effects on attrition.

Feeling cybervictims' pain-The effect of empathy training on cyberbullying.

As the world's population increasingly relies on the use of modern technology, cyberbullying becomes an omnipresent risk for children and adolescents and demands counteraction to prevent negative (online) experiences. The classroom-based German preventive intervention "Medienhelden" (engl.: "Media Heroes") builds on previous knowledge about links between cognitive empathy, affective empathy, and cyberbullying, among others. For an evaluation study, longitudinal data were available from 722 high school students aged 11-17 years (M = 13.36, SD = 1.00, 51.8% female) before and six months after the implementation of the program. A 10-week version and a 1-day version were conducted and compared with a control group (controlled pre-long-term-follow-up study). Schools were asked to randomly assign their participating classes to the intervention conditions. Multi-group structural equation modeling (SEM) showed a significant effect of the short intervention on cognitive empathy and significant effects of the long intervention on affective empathy and cyberbullying reduction. The results suggest the long-term intervention to be more effective in reducing cyberbullying and promoting affective empathy. Without any intervention, cyberbullying increased and affective empathy decreased across the study period. Empathy change was not generally directly linked to change in cyberbullying behavior. "Media Heroes" provides effective teaching materials and empowers schools to address the important topic of cyberbullying in classroom settings without costly support from the outside.

[Promotion of media competence and prevention of cyberbullying using the Medienhelden program: results from an evaluation study ]. / Das Medienhelden-Programm zur Förderung von Medienkompetenz und Prävention von Cybermobbing: Konzept und Ergebnisse aus der Evaluation.

The manualized Medienhelden (engl. Media Heroes) program (Schultze-Krumbholz, Zagorscak, Siebenbrock, Scheithauer, 2012) is implemented in the school environment either as a ten-week program during lessons (curriculum; IGL) or as a single project day with reduced content of the long version (IGK). In consecutive lessons, topics of the program are, for example: definition of cyberbullying, its negative impact, how to protect oneself on the internet, and opportunities to react in appropriate ways. The program utilizes mainly cognitive-behavioral methods. In the present contribution the program and selected results from a controlled, pre-follow-up evaluation study with 570 adolescents (Ncontrolgroup = 289, NIGK = 98 and NIGL = 183), from one general high school and four college preparatory high schools from a German major city will be presented. Results show that cyberbullying decreased in both intervention groups (project day, curriculum) compared to the control group while at the same time an increase of social competencies, self-esteem, and subjective health was observed. These effects were more pronounced for the curriculum intervention group. An opposite pattern was found for the control group: Cyberbullying and empathy worsened, and no change was found for perspective-taking, self-esteem, and subjective health. The program shows both preventive and intervention effects.

Prevention 2.0: targeting cyberbullying @ school.

Although cyberbullying is characterized by worrying prevalence rates and associated with a broad range of detrimental consequences, there is a lack of scientifically based and evaluated preventive strategies. Therefore, the present study introduces a theory-based cyberbullying prevention program (Media Heroes; German original: Medienhelden) and evaluates its effectiveness. In a pretest-posttest design (9-month interval), schools were asked to randomly assign their participating classes to either control or intervention group. Longitudinal data were available from 593 middle school students (M Age = 13.3 years, 53 % girls) out of 35 classes, who provided information on cyberbullying behavior as well as socio-demographic and psychosocial variables. While the present results revealed worrying prevalence rates of cyberbullying in middle school, multilevel analyses clearly demonstrate the program's effectiveness in reducing cyberbullying behavior within intervention classes in contrast to classes of the control group. Hence, this study presents a promising program which evidentially prevents cyberbullying in schools.