Direct and indirect effects of adverse and protective childhood experiences on symptom improvement in psychotherapy.

To investigate the effects of adverse and protective childhood experiences on symptom improvement in outpatient psychotherapy.We evaluated n = 648 completed outpatient psychodynamic psychotherapies. First, we estimated the rate of symptom improvement for each patient using a two-stage hierarchical linear model. We then calculated the direct and indirect influences of childhood experiences on the improvement rate using a structural equation model. Personality functioning, according to the Operationalized Psychodynamic Diagnosis system, was examined as being a possible mediating factor.The presence of adverse childhood experiences was directly associated with a slower improvement rate in psychotherapy. Moreover, a higher number of adverse childhood experiences was associated with greater impairments in the ability to communicate as one dimension of personality functioning, which in turn was associated with a slower improvement of symptoms. Protective childhood experiences were associated with fewer impairments in specific dimensions of personality functioning, but had no direct effect on the improvement rate.Adverse childhood experiences can directly influence the course of psychotherapy. In addition, the communication dimension of personality functioning appears to be a central mediator on which adverse and protective childhood experiences act antagonistically and can thus indirectly affect the improvement rate in psychotherapy.

Tutors´ and Students' Agreement on Social and Cognitive Congruence in a Sonography Peer-assisted-learning Scenario.

Purpose: Peer-assisted learning has become an integral part within medical education and has been proven to be effective in teaching medical skills. Cognitive and social congruence are important factors that explain the effectiveness of peer-assisted learning. However, although theory suggests this, there is no study to date that demonstrates that students and tutors agree upon the level of cognitive and social congruence. Thus, we compared tutors' and students' perception of cognitive and social congruence and their agreement on the causes of congruence. Methods: 36 students and 9 tutors from 9 courses were asked to answer questionnaires for their perception of cognitive and social congruence in a peer-assisted learning sonography scenario. Results: Students and tutors experienced cognitive congruence (t = 0.8277, df = 8, p = .4318, 95% CI = [-0.232; 0.491]) and social congruence (t = 0.962, df = 8, p = .364, 95% CI = [-0.145; 0.354]) similarly. In contrast, students and tutors disagreed on causes of cognitive congruence (agreement = 53.90%) and social congruence (agreement = 58.49%). Tutors rated their empathy and interest toward students as the main cause. Students rated the helpfulness, effectiveness, and approachableness of the tutor as the main cause. Conclusions: Our study filled the gap in previous research on cognitive and social congruence. Consistent with theoretical considerations, it was shown that students and tutors do indeed experience cognitive and social congruence similarly. Nevertheless, differences also emerged that may carry more or less weight depending on the research question. Future studies should therefore carefully examine whether the assessment of cognitive and social congruence of students and tutors is necessary.

Characterization of different types of anxiety disorders in relation to structural integration of personality and adverse and protective childhood experiences in psychotherapy outpatients - a cross-sectional study.

BACKGROUND: Current research has emphasized the role of structural integration of personality and childhood experiences for the understanding of anxiety disorders. In this study, we examined the relationship between anxiety disorders (generalized anxiety disorder vs. panic disorder vs. phobic disorders), the level of structural integration of personality, and negative and protective childhood experiences at the beginning of outpatient psychodynamic psychotherapy treatment. Differences were characterized in comparison to patients with no anxiety disorders. METHODS: The sample included a total of 1646 outpatient psychodynamic psychotherapy treatments, of which 695 treatments included the diagnosis of at least one anxiety disorder. Levels of structural integration of personality were assessed according to the Operationalized Psychodynamic Diagnosis (OPD-2) system. Self-reported negative and protective childhood experiences were examined by using the Questionnaire for the Assessment of Adverse and Protective Childhood Experiences (APC). Associations were tested using single factor ANOVAs. RESULTS: Patients with anxiety disorders showed lower levels of structural integration of personality and reported more adverse childhood experiences than patients with no anxiety disorders. Regarding the subscales of structural integration of personality, phobic disorders were associated with impaired external communication, whereas for generalized anxiety disorder, an (uncorrected) association with impaired self-regulation was found. Also, generalized anxiety disorder was associated with sexual abuse and other traumatization (accidents etc.) during childhood, while panic disorder and phobic disorders were associated with emotional neglect, abuse, and fewer protective childhood experiences. CONCLUSIONS: Our findings emphasize the need of considering structural integration of personality and childhood experiences in order to understand and treat various types of anxiety disorders.

Interaction of mental comorbidity and physical multimorbidity predicts length-of-stay in medical inpatients.

BACKGROUND: Mental comorbidities of physically ill patients lead to higher morbidity, mortality, health-care utilization and costs. OBJECTIVE: The aim of the study was to investigate the impact of mental comorbidity and physical multimorbidity on the length-of-stay in medical inpatients at a maximum-care university hospital. DESIGN: The study follows a retrospective, quantitative cross-sectional analysis approach to investigate mental comorbidity and physical multimorbidity in internal medicine patients. PATIENTS: The study comprised a total of n = 28.553 inpatients treated in 2017, 2018 and 2019 at a German Medical University Hospital. MAIN MEASURES: Inpatients with a mental comorbidity showed a median length-of-stay of eight days that was two days longer compared to inpatients without a mental comorbidity. Neurotic and somatoform disorders (ICD-10 F4), behavioral syndromes (F5) and organic disorders (F0) were leading with respect to length-of-stay, followed by affective disorders (F3), schizophrenia and delusional disorders (F2), and substance use (F1), all above the sample mean length-of-stay. The impact of mental comorbidity on length-of-stay was greatest for middle-aged patients. Mental comorbidity and Elixhauser score as a measure for physical multimorbidity showed a significant interaction effect indicating that the impact of mental comorbidity on length-of-stay was greater in patients with higher Elixhauser scores. CONCLUSIONS: The findings provide new insights in medical inpatients how mental comorbidity and physical multimorbidity interact with respect to length-of-stay. Mental comorbidity had a large effect on length-of-stay, especially in patients with high levels of physical multimorbidity. Thus, there is an urgent need for new service models to especially care for multimorbid inpatients with mental comorbidity.

Systematic review of machine learning utilization within outpatient psychodynamic psychotherapy research.

Introduction: Although outpatient psychodynamic psychotherapy is effective, there has been no improvement in treatment success in recent years. One way to improve psychodynamic treatment could be the use of machine learning to design treatments tailored to the individual patient's needs. In the context of psychotherapy, machine learning refers mainly to various statistical methods, which aim to predict outcomes (e.g., drop-out) of future patients as accurately as possible. We therefore searched various literature for all studies using machine learning in outpatient psychodynamic psychotherapy research to identify current trends and objectives. Methods: For this systematic review, we applied the Preferred Reporting Items for systematic Reviews and Meta-Analyses Guidelines. Results: In total, we found four studies that used machine learning in outpatient psychodynamic psychotherapy research. Three of these studies were published between 2019 and 2021. Discussion: We conclude that machine learning has only recently made its way into outpatient psychodynamic psychotherapy research and researchers might not yet be aware of its possible uses. Therefore, we have listed a variety of perspectives on how machine learning could be used to increase treatment success of psychodynamic psychotherapies. In doing so, we hope to give new impetus to outpatient psychodynamic psychotherapy research on how to use machine learning to address previously unsolved problems.