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Detecting levels of psychological defence mechanisms in supportive conversations is inherently ambiguous. In the PsyDefDetect shared task at BioNLP 2026 the eight positive defence categories share surface language and differ only in pragmatic function and trained raters reach only moderate inter-annotator agreement. On such a task the decisive lever is not a stronger single model but error independence, since any single representation will waver on the overlapping defence boundaries. We translate this insight into a 9-voter ensemble spanning three orthogonal axes: class granularity (all nine classes for the gatekeeper, only the eight defence classes for the specialists), training method (generative and discriminative) and base model. The system reaches F1 = .420 on the hidden test set, placing first among 21 registered teams.
Shift work is associated with an increased risk of sleep disorders, yet tailored prevention and treatment programs remain rare and understudied. Cognitive behavioral therapy for insomnia is the first-line treatment for insomnia in the general population. We thus developed an anonymous online counselling service based on cognitive behavioral principles, adapted it to shift workers’ needs, and evaluated it in a sample of German shift workers from various industries. This prospective, randomized, controlled superiority trial compares two parallel groups: an intervention group that received four personalized counselling messages and completed four weekly sleep diaries, and a waiting-list control-group that completed sleep diaries only during the four-week waiting period. In the Intention to Treat sample (n = 66), significant improvements were observed in both groups for the primary outcome, sleep efficiency, and for the secondary outcomes, symptoms of insomnia and depression. Daytime sleepiness did not improve in either group. However, improvements were not significantly greater in the treatment than in the control group. We can thus not demonstrate superiority of the counselling intervention over the control condition, where repeated sleep diary completion and study participation may themselves have had therapeutic effects. Limitations regarding time frame and sample size, as well as implications for research and practice are discussed.
Trial registration:
The study was registered with the German Clinical Trials Register DRKS under the trial ID DRKS00017777 ( https://drks.de/search/en/trial/DRKS00017777
). Date of registration: 14.01.2020. This study was registered during the early stages of data collection. Of the 27 participants in the final sample, the first four had initiated data collection at the date of registration. No complete data sets were available at that time.
Transition-Matrix Regularization for Next Dialogue Act Prediction in Counselling Conversations
(2026)
This paper studies how empirical dialogue-flow statistics can be incorporated into Next Dialogue Act Prediction (NDAP). A KL regularization term is proposed that aligns predicted act distributions with corpus-derived transition patterns. Evaluated on a 60-class German counselling taxonomy using 5-fold cross-validation, this improves macro-F1 by 9-42% relative depending on encoder and substantially improves dialogue-flow alignment. Cross-dataset validation on HOPE suggests that improvements transfer across languages and counselling domains. In systematic ablations across pretrained encoders and architectures, the findings indicate that transition regularization provides consistent gains and disproportionately benefits weaker baseline models. The results suggest that lightweight discourse-flow priors complement pretrained encoders, especially in fine-grained, data-sparse dialogue tasks.
This study investigates the capabilities of Large Language Models to simulate counselling clients in educational roleplays in comparison to human role-players. Initially, we recorded role-playing sessions, where novice counsellors interacted with human peers acting as clients, followed by role-plays between humans and clients simulated by Mistrals Mixtral 8x7b using 4-bit quantization. These interactions were analysed with a counselling communication pattern system at sentence level. We investigated two key questions: (1) to what extent LLM-generated responses replicate authentic conversational dynamics and (2) whether counsellors’ communication behaviour differs when interacting with human versus LLM-simulated clients. The findings highlight both similarities and differences in the application of counselling patterns across scenarios, showing the potential of LLM-based role-playing exercises to enhance counselling competencies and to identify areas for further refinement in virtual client simulations.
Digitale Räume sind Sozialräume – und dies nicht erst seit der Corona-Pandemie mit ihren Lockdowns, in denen Angebote der Sozialen Arbeit in digitalen Räumen noch einmal deutlich zugenommen haben. Mit der umfassenden Verfügbarkeit digitaler Medien im Lebensalltag hat auch die Soziale Arbeit sich zunehmend diesen Medien zugewandt und dort etabliert: Seit Mitte der 1990er-Jahre gibt es Angebote der Onlineberatung, es folgten Projekte und Angebote digitaler Jugendarbeit (damals noch unter dem Namen „e-Youth Work“), und inzwischen hat auch das Arbeitsfeld Streetwork sich mit den digitalen Räumen und Möglichkeiten auseinandergesetzt, da in digitalen
Räumen Zielgruppen auch mithilfe von Streetwork-Angeboten erreicht werden können. Dieser Artikel bietet eine aktuelle Standortbestimmung samt Definitionen, Methoden und Hinweisen zu ersten Forschungsergebnissen. Im Rahmen eines Ausblicks werden Themen benannt, die für das Arbeitsfeld und die Methode Digital Streetwork künftig wesentlich sein werden.