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Conflicts in working memory (WM) can occur when retrieval cues activate competing items, which impairs the efficiency of retrieval. It has recently been shown that WM retrieval adapts similarly to these conflicts as predicted by conflict monitoring theory for selective attention tasks. Here, we utilized event‐related potentials (ERPs) to investigate whether conflict and adaptive control in WM are reflected by the same neural markers that have previously been described for selective attention tasks. In our task, participants encoded two differently colored memory lists that contained four digits each (i.e., 2 5 7 1 and 4 5 9 1), and had to recognize whether a probe item from a specific list and position was correct or incorrect. Conflict during retrieval emerged when digits at corresponding positions (e.g., 2 and 5 at the first position) were different (incongruent), but not when these digits were the same (congruent). In behavioral data, we found a congruency sequence effect, that is, responses to incongruent probe items were slower, and this effect was reduced following trials with incongruent probe items. In ERPs, this behavioral marker of adaptive control was accompanied by two effects. First, congruency affected the amplitude of an N450, and this conflict effect was reduced after incongruent trials. Second, the posterior P3 amplitude varied with the congruency of the current and the previous trial. Both results resemble those found for the Stroop task and thus highlight the similarity between conflict and adaptive control in WM and selective attention tasks. Our study links theoretical ideas from two research fields—working memory (WM) and adaptive cognitive control. Utilizing event‐related potentials, our findings show that adaptive cognitive control in WM is reflected by the same neural markers as adaptive cognitive control of selective attention. Furthermore, our results suggest that adaptive cognitive control plays a critical role in optimizing the use of limited WM storage. [ABSTRACT FROM AUTHOR]

Timely and relevant information enables clinicians to make informed decisions about patient care outcomes. However, discovering related and understandable information from the vast medical literature is challenging. To address this problem, we aim to enable the development of search engines that meet the needs of medical practitioners by incorporating text difficulty features. We collected a dataset of 209 scientific research abstracts from different medical fields, available in both English and German. To determine the difficulty aspects of readability and technical level of each abstract, 216 medical experts annotated the dataset. We used a pre-trained BERT model, fine-tuned to our dataset, to develop a regression model predicting those difficulty features of abstracts. To highlight the strength of this approach, the model was compared to readability formulas currently in use. Analysis of the dataset revealed that German abstracts are more technically complex and less readable than their English counterparts. Our baseline model showed greater efficacy than current readability formulas in predicting domain-specific readability aspects. Conclusion: Incorporating these text difficulty aspects into the search engine will provide healthcare professionals with reliable and efficient information retrieval tools. Additionally, the dataset can serve as a starting point for future research. [ABSTRACT FROM AUTHOR]

For time-sensitive treatment of a patient with malignant melanoma, physicians must obtain a rapid overview of the patient's status. This study aimed to analyze context-specific features and processes at the point of care to derive requirements for a dashboard granting more straightforward access to information. The Think-Aloud method, contextual inquiries, and interviews were performed with physicians from the Department of Dermatology at the University Hospital Essen in Germany. The user statements and observations that were obtained were grouped and categorized using an affinity diagram. Based on the derived subjects, requirements were defined, confirmed, and prioritized. The resulting affinity diagram revealed four topics of importance at the point of care. These topics are "Identifying and Processing the Important", a comprehensive "Patient Record", tasks and challenges in the "Clinical Routine", and interactions and experiences with the available "Systems". All aspects have been reflected in 135 requirements for developing context- and indication-specific patient dashboards. Our work has elucidated the most important aspects to consider when designing a dashboard that improves patient care by enabling physicians to focus on the relevant information. Furthermore, it has been demonstrated that the aspects most often mentioned are not context-specific and can be generalized to other medical contexts., (© 2024. The Author(s).)