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  • Intervention Against The Stigmatization of Men With Eating Disorders in Primary Care: Video-Based Training Modules

    Description:
    The content of this dataset (videos, subtitle files, and cover image files) derives from the research project "Intervention against the stigmatization of men with eating disorders in primary care (iSMEsH)" funded by the German Federal Ministry of Health (BMG). The aim of the project “Intervention against the stigmatization of men with eating disorders in primary care (iSMEsH)” was to develop and scientifically evaluate the online training course “Eating disorders in boys and men” for doctors. The intervention was developed to sensitize general practitioners to the topic of eating disorders in boys and men and to impart knowledge and skills. In addition to examining the effectiveness of the training in terms of reducing stigma among GPs, iSMEsH was also investigating the practical applicability of the intervention, including its acceptance, feasibility, willingness to adopt, and sustainability. The video training comprises the following 6 modules: - Facts on Eating Disorders (duration: 11:34) - Symptoms and Diagnostics (duration: 11:22) - Communication Strategies (duration: 10:06) - Muscle Dysmorphia (duration: 5:21) - Support and Assistance Services (duration: 8:03) - Caretakers (duration: 6:09) and Die Inhalte dieses Datensatzes (Videos, Untertiteldateien und Coverbilddateien) stammen aus dem vom Bundesministerium für Gesundheit (BMG) geförderten Forschungsprojekt „Intervention gegen die Stigmatisierung von Männern mit Essstörungen in der Primärversorgung (iSMEsH)“. Ziel des Projekts „Intervention gegen die Stigmatisierung von Männern mit Essstörungen in der Primärversorgung (iSMEsH)“ war die Entwicklung und wissenschaftliche Evaluation des Online-Trainings „Essstörungen bei Jungen und Männern“ für Ärzte. Die Intervention wurde entwickelt, um Allgemeinmediziner für das Thema Essstörungen bei Jungen und Männern zu sensibilisieren und ihnen Wissen und Fertigkeiten zu vermitteln. Neben der Untersuchung der Wirksamkeit der Schulung im Hinblick auf die Reduktion der Stigmatisierung bei Hausärzten untersuchte iSMEsH auch die praktische Anwendbarkeit der Intervention, einschließlich ihrer Akzeptanz, Machbarkeit, Bereitschaft zur Übernahme und Nachhaltigkeit. Das Videotraining umfasst die folgenden 6 Module: - Fakten zu Essstörungen (Dauer: 11:34) - Symptome und Diagnostik (Dauer: 11:22) - Gesprächsführung (Dauer: 10:06) - Muskeldysmorphie (Dauer: 5:21) - Unterstützungs- und Hilfsangebote (Dauer: 8:03) - Rolle von Angehörigen (Dauer: 6:09)
    Keyword:
    Stigma, Anti-Stigma, Behandlungshürde, Help-Seeking, Intervention, Stigmatisierung, Hausarzt, Essstörung, Männer, Men, Hilfesuche, Treatment Barrier, Stigmatization, Eating Disorder, and Primary Care
    Subject:
    Medicine, Psychotherapy, and Psychosomatic Medicine
    Publisher:
    Based Near Label Tesim:
    Bochum, North Rhine-Westphalia, Germany
    Language:
    German
    Date Uploaded:
    2025-06-16
    Date Modified:
    2025-06-17
    License:
    Creative Commons BY Attribution 4.0 International
    Resource Type:
    Audiovisual

  • PSC522 Dataset

    Description:
    This dataset is part of the publication "A PLM-Integrated automated synthetic image generation pipeline for object detection" presented at the PLM conference 2025 in Sevilla. The paper presents an automated synthetic image data generation pipeline aimed at streamlining the training process of object detection models supporting manual assembly processes. By automating the rendering of images from CAD models instead of relying on manually created physical product images, the pipeline enables dataset creation in earlier phases of the product lifecycle while also significantly reducing manual effort. This approach enhances the accessibility for finetuned object detection model development. The pipeline integrates two core components: object similarity analysis and synthetic image generation. The similarity analysis groups visually similar objects into unified classes for the object detection model, reducing confusion during detection. The image generation process can be augmented with contextual information from virtual 3D workplace scenes, thereby significantly mitigating the sim-to-real gap. The pipeline is accessed via a REST API, enabling seamless integration with PLM systems for automated retrieval of CAD models and workplace scene data. A workflow manager orchestrates interactions between the user, the PLM system, and the generation pipeline. The effectiveness of the system is validated by evaluating object detection models trained on the synthetically generated datasets against real-world images, demonstrating its potential to improve detection accuracy and robustness in industrial environments. By publishing the data used, we aim to strengthen the traceability of the results obtained and that we can encourage further research in this field.
    Keyword:
    object detection, industrial object detection, synthetic data, plm, and product lifecycle management
    Publisher:
    Language:
    English and German
    Date Uploaded:
    2025-06-03
    Date Modified:
    2025-06-05
    License:
    Creative Commons BY Attribution 4.0 International
    Resource Type:
    Dataset