The PornLoS Treatment Program: Study protocol of a new psychotherapeutic approach for treating pornography use disorder.

Background: The introduction of Compulsive Sexual Behavior Disorder (CSBD) into the 11th International Classification of Diseases has raised expectations for better treatment options for CSBD. Furthermore, the treatment demand has increased, particularly for pornography use disorder (PUD), a subtype of CSBD. Presumably due to the easy access to Internet pornography an increasing prevalence of PUD is observed. Consequently, providing tailored and effective treatment is essential. Methods: This article provides an overview of the manualized short-term PornLoS Treatment Program (Pornografienutzungsstörung effektiv behandeln- Leben ohne Suchtdruck; translation: Treating pornography use disorder effectively - life without craving). The program combines 24 individual and 6 group psychotherapy sessions with an interdisciplinary approach by offering a novel treatment framework. This includes, e.g., a mobile app, establishment of self-help groups, and access to other social services such as couple counseling. The cognitive-behavioral treatment program contains interventions addressing psychoeducation, cue exposure, impulse control, cognitive restructuring, emotional regulation, and relapse management.We here also describe the study protocol of an ongoing four-arm randomized controlled trial. The aim is to test two variants of the PornLoS Treatment Program differing with respect to their treatment goal (abstinence or reduced pornography use) against cognitive-behavioral treatment as usual and against a waitlist control group. The primary outcome is the absence of a PUD diagnosis at the end of therapy. The total target sample size will comprise n = 316 patients with PUD across eight study sites. Results: The results will be presented at international conferences and published in a scientific peer-reviewed journal.

Temporal dynamics in mental health symptoms and loneliness during the COVID-19 pandemic in a longitudinal probability sample: a network analysis.

Figuring out which symptoms are central for symptom escalation during the COVID-19 pandemic is important for targeting prevention and intervention. Previous studies have contributed to the understanding of the course of psychological distress during the pandemic, but less is known about key symptoms of psychological distress over time. Going beyond a pathogenetic pathway perspective, we applied the network approach to psychopathology to examine how psychological distress unfolds in a period of maximum stress (pre-pandemic to pandemic onset) and a period of repeated stress (pandemic peak to pandemic peak). We conducted secondary data analyses with the Understanding Society data (N = 17,761), a longitudinal probability study in the UK with data before (2019), at the onset of (April 2020), and during the COVID-19 pandemic (November 2020 & January 2021). Using the General Health Questionnaire and one loneliness item, we computed three temporal cross-lagged panel network models to analyze psychological distress over time. Specifically, we computed (1) a pre-COVID to first incidence peak network, (2) a first incidence peak to second incidence peak network, and (3) a second incidence peak to third incidence peak network. All networks were highly consistent over time. Loneliness and thinking of self as worthless displayed a high influence on other symptoms. Feeling depressed and not overcoming difficulties had many incoming connections, thus constituting an end-product of symptom cascades. Our findings highlight the importance of loneliness and self-worth for psychological distress during COVID-19, which may have important implications in therapy and prevention. Prevention and intervention measures are discussed, as single session interventions are available that specifically target loneliness and worthlessness to alleviate mental health problems.

[Urological practice in the corona pandemic]. / Die urologische Praxis in der Corona-Pandemie.

The Corona-Pandemic is an additional challenge for urological practice, as most urological patients are in the high-risk group for a severe course of COVID19 disease due to their age and accompanying illnesses. The most effective protective measures are prioritised reduction in patient contacts with the help of telemedical contacts and the consistent wearing of FFP2-masks during direct contact. Further measures such as access controls, protective walls and air-filtering can further reduce the risk of infection. Ultimately, only a nationwide vaccination programm will result in the removal of pandemic-related restrictions for further urological treatment.

[What do urologist do in daily practice? : A first "unfiltered" look at patient care]. / Was machen Urologen in der Praxis? : Ein erster "ungefilterter" Blick auf die Versorgung.

The topic of routine medical care data and healthcare science has gained in relevance and provides an important basis for both healthcare policymakers and those providing care. Access to relevant data and the ability to analyze these is highly competitive as it yields the most compelling arguments and strong facts in any discourse on the ultimately limited resources of the entire healthcare sector. All randomized clinical trials and prospective data collections harbor the inherent similarity that they contain data within a predefined frame of data elements in order to control for any confounding factors. In addition, analyses using retrospective data collections use a predefined evaluation matrix and filter the existing data according to these established data elements. However, an unfiltered and un(pre)specified view to all data would be ideal. An approximation to this goal as part of this project could be the unfiltered collection of as much data as possible and their collection in a data pool, which then could be processed, in a constantly improving analyses algorithm. The automated self-extraction of data from the private-practice information technology (IT) system to UROscience will create a data pool which could be used to answer many different questions related to the reality of healthcare. The preliminary analyses presented here demonstrate that, on basis of the existing data, this versatile sample is available to provide insight into the treatment reality of urologic outpatient care.