To provide an overview of the current state of international research on technology-based applications for informal caregivers of people with advanced cancer, with a particular focus on advanced breast cancer. This scoping review was conducted in accordance with the Joanna Briggs Institute methodology and reported in line with the PRISMA-ScR guideline. The PCC framework was used to define the search terms, and develop the search strategy for the databases PubMed, CINAHL, and Web of Science. The systematic search identified 13 relevant articles describing ten different technology-based applications. One additional article was identified through a manual search. In total, 14 studies covering ten distinct interventions were included. Some interventions were adapted from face-to-face programmes for digital delivery, whereas only a minority were explicitly informed by theoretical models from psychology or health science. The included studies addressed five main areas: informational support, mental and psychosocial support and enhancement of quality of life, physical and practical support, communication support, and preparation for caregiving and death. Evaluations reported predominantly positive findings, particularly with regard to quality of life, anxiety, depressive symptoms, and coping. However, most studies focused on advanced cancer more broadly rather than on advanced breast cancer specifically. The reviewed literature suggests that technology-based interventions for informal caregivers of people with advanced cancer are available in several countries and address a range of support needs. However, no intervention tailored to relatives of patients with advanced breast cancer was identified as having been fully developed and evaluated. The findings highlight the need for future research on targeted, sustainable digital support for this group. The development of the Gesi-BK platform is based on the results of this scoping review.
Large language models (LLMs) are increasingly promoted to practitioners as tools for inferring personality traits from LinkedIn profiles, promising scalable and innovative assessments. Yet, the psychometric foundations of such inferences remain untested. Building on the lens model, we presented 406 LinkedIn profiles to Microsoft Copilot (powered by GPT-4) twice, using single-shot prompting to assess personality (Big Five, narcissism) and intelligence. Inferences showed satisfactory intra-rater reliability for observable traits (up to r = .81), but poor reliability for less visible traits, suggesting unstable inferences (as low as r = .31). Correlations with ground-truth test scores indicate above-chance yet limited convergent validity for intelligence (r = .24), openness (r = .20), and extraversion (r = .20), but not for less visible traits. Analysis of 32 coded LinkedIn cues suggests that this above-chance convergence reflects Copilot drawing on LinkedIn information with some consistency and sensitivity to valid trait signals. While this suggests a rudimentary functional grasp of personality, inferences were undermined by serious flaws, including positivity bias, range restriction, poor discriminant validity, cue overgeneralization, and adverse demographic impacts. By extending the lens model to LLMs as perceivers, we offer a theoretical and empirical foundation for understanding LLM-based trait inferences. Overall, claims that LLMs can validly infer personality from LinkedIn profiles are not just overoptimistic, but potentially harmful—they risk encouraging the adoption of practices that could lead to invalid selection decisions, unfair treatment of applicants, and legal exposure for organizations.
Zusammenfassung Sekundärdatenanalysen mit Abrechnungs- bzw. Routinedaten der Kranken- und Pflegekassen sind zentraler Bestandteil von Versorgungsforschung, nicht zuletzt im Rahmen von Projekten des Innovationsfonds des G-BA. Ein Zugriff auf die für die Evaluation notwendigen Routinedaten der Krankenkassen ist nicht immer systematisch möglich. An der Intervention teilnehmende Proband:innen von Krankenkassen, die nicht am Projekt beteiligt sind, können dadurch nicht in die Evaluation einbezogen werden. Die Erhebung und Analyse von Patientenquittungen stellt eine Alternative zur systematischen Routinedaten-Lieferung beteiligter Krankenkassen dar. Die Heterogenität der Patientenquittungen, die vorwiegend papierbasierte Übermittelung und die individuelle Digitalisierung stellen Herausforderungen im Umgang mit Patientenquittungen dar.
Hospitals are increasingly dependent on interconnected digital infrastructures, which are essential for clinical and administrative operations. Outages of IT systems can significantly jeopardize patient care and impact business continuity. While frameworks provide methodological guidance for IT outage management, their practical implementation remains challenging. Therefore, this work presents a Minimum Viable Product (MVP) guideline developed through an iterative design process. It is structured according to different time phases, processes, governance structures, and tools for dealing with an IT outage in hospitals.
