About the lab

Our goal is to understand and support what makes a good work system. To achieve this goal, we continuously reflect the methodological and theoretical toolbox of Human Factors and Ergonomics (HF/E) as well as our own research agenda in work domains such as medicine, manufacturing, or public administration. You can find more information about our work at: https://www.awb.tu-berlin.de/menue/aktuelles/parameter/en/.

By the way:
If you are looking for an institution to host your Marie Curie Individual Fellowship, we would be happy to have you! Find our host offer on the webpage of the European Liaison Office of the German Research Organisations: http://www.kowi.de/kowi/services/msca-host-offers.aspx

Featured projects (4)

Project
Women with genetic alterations in the BRCA1 or BRCA2 genes have a significantly increased risk of developing breast or ovarian cancer. After receiving a positive test result affected women find themselves in the stressful situation of having to understand and base life-changing decisions on highly complex information. This is where the iKNOW project comes in: The project aims to develop an online counseling tool for affected women. The counseling tool helps physicians to easily explain the complicated disease probabilities to those affected. It also ensures that the information on how to handle these risks continually complies with the latest scientific findings. Affected women can also look at individual risk scores and tailored information on themes such as lifestyle changes after the initial interview situation. iKNOW examines whether women counselled with the new online tool have a better understanding of risk than those who are given traditional counseling. In addition, the project analyzes how the counseling tool alters one’s subjective risk perception, one’s fear of illness, one’s quality of life, and how often or which medical services affected women use afterwards. (Funding provided through Innovationsfonds: Gemeinsamer Bundesausschuss Innovationsausschuss - project partners are Dr. Dorothee Speiser und PD Dr. Friederike Kendel at the Charité Berlin)
Project
Wir wollen aus den Denk-Modellen von Denker*innen aller Disziplinen lernen und sie für unser eigenes Denken nutzbar machen. Joseph Beuys berühmter Satz „wer nicht denken will, fliegt raus“ - nach einem erschöpfenden Seminartag auf der documenta - ist geflügeltes Wort. Seine kaum bekannte Anmerkung „(sich selbst)“ ist ein Hinweis auf die Eigenverantwortlichkeit eines jeden. Niemand soll rausgeworfen werden... Jeder wirft sich selbst raus. Mensch ärgere Dich nicht, sondern denke selbst und tu was. Auch in Vol. 2 unserer Vorlesungsreihe geht es darum, Denken als reflektierenden und praktisch-kreativen Prozess zu verstehen und umzusetzen. Jeder Mensch ist eine Denker*in, wenn sie sich nicht selbst rauswirft. Nach dem Motto „wer nicht denken will, fliegt (sich selbst) raus“ werden wir von unseren Gästen in unterschiedliche Disziplinen verführt auf der Suche nach neuen, im Alltag hilfreichen “Denk-Modellen” und letztlich nach Kompetenzen, die kritischem und produktivem Denken zugrunde liegen.
Project
Das durch den Innovationsfonds geförderte Projekt (4.3 Millionen Euro) zielt darauf ab, die medizinische Versorgung bei familiärer Krebsbelastung durch eine digitale Plattform zu verbessern: Das frühzeitige Wissen um ein erhöhtes familiäres Krebsrisiko birgt eine große Chance. Heute stehen individualisierte Maßnahmen zur Verfügung, mit denen Krebserkrankungen früher erkannt und im Idealfall sogar verhindert werden können. Dafür müssen Betroffene und Akteure aller Sektoren - von der Allgemeinarztpraxis bis hin zur spezialisierten Sprechstunde – eng zusammenarbeiten. Ziel des neu geförderten Projekts ist deshalb eine nachhaltige Stärkung der transsektoralen Versorgung. Paradigmatisch wird eine digitale Versorgungsplattform für Personen mit einem familiären Krebsrisiko und ihre Ärzt*innen (dVP_FAM) entwickelt und evaluiert. Die dVP_FAM besteht aus mehreren Modulen, die auf die jeweiligen Anforderungen von Patient*innen und Ärzt*innen zugeschnitten sind. Dabei werden keine parallelen Strukturen geschaffen, vielmehr wird die Plattform in die Telematikinfrastruktur (TI) und die elektronische Patientenakte (ePA) eingebunden. Mit einer clusterrandomisierten Studie, semi-strukturierten Interviews und Beobachtungen im Alltag der Plattform-Nutzer*innen wird überprüft, wie sich die dVP_FAM auf die Versorgungsqualität auswirkt und sich Arbeitsprozesse verbessern lassen. Eine Besonderheit des Projekts ist seine starke Interdisziplinarität. Neben der Arbeitswissenschaft der TU Berlin sind Mediziner*innen, Patientenvertreter*innen, Jurist*innen und Psycholog*innen der Charité und Humboldt Universität Berlin beteiligt. Gemeinsam erarbeiten sie Best-Practice-Lösungsansätze für digitale Innovationen der transsektoralen Versorgung. Entwickelt wurde dVP_FAM aus den Vorerfahrungen des ebenfalls durch den Innovationsausschuss geförderten Projektes iKNOW, in dem Dorothee Speiser, Friederike Kendel und Markus Feufel bereits erfolgreich ein digitales Tool zur verbesserten Krebsberatung entwickeln. Das Projekt wird vom Innovationsausschuss beim G-BA (Innovationsfonds) gefördert. Durchführung: 12/21 – 11/25 Konsortialführung: PD Dr. Dorothee Speiser (Gynäkologie), Charité – Universitätsmedizin Berlin Konsortialpartner: PD Dr. Friederike Kendel (Psychologie), Charité – Universitätsmedizin Berlin Prof. Dr. Markus Feufel (Arbeitswissenschaft), TU Berlin Dr. Sven Asmussen (Rechtswissenschaften) HU Berlin André Sander (Softwareentwicklung), ID Berlin GmbH PD Dr. Simone Wesselmann (Onkologie), Deutsche Krebsgesellschaft e.V. Lars Straubing (Kostenträger), BKK VBU Fördersumme: 4.3 Millionen Euro
Project
The question of how particularly vulnerable patient groups can be cared for without exposing them to infection risks has particullary arisen with great urgency since the Corona pandemic. Although digital consultation services such as video consultations have gained enormous importance, systematic studies on the differences between online and face-to-face consultations are lacking. Based on a mixed method design using data from oncology patients, we are investigating how physician-patient interactions change as a result of video consultations and what barriers may stand in the way of their use.

Featured research (23)

OBJECTIVE: Hospital information systems (HIS) are meant to manage complex work processes across healthcare organizations. We describe limitations of HIS to address local information requirements and how they are circumvented at different organizational levels. Results can be used to better support collaboration in socio-technical systems. BACKGROUND: Workarounds describe a mismatch between a technology’s purpose and its actual use, whereas shadow systems are unofficial IT systems circumventing limitations of official systems to support workflows. Boundary infrastructures are conceptualized as the entirety of all (in)formal digital and analog systems connecting different communities of practice in a socio-technical system. METHODS: An ethnographic study with observations and semi-structured interviews was conducted and analyzed through categorization and iterative coding. RESULTS: Several digital-analog workarounds are employed for documentation and a shared server functions as a shadow system to support workflows in ways the HIS cannot. For collaborative documentation, all (official and informal) information sources were used simultaneously as part of an interconnected boundary infrastructure. CONCLUSION: Formal and informal IT systems are interconnected across different organizational levels and provide insights into unmet information requirements, effective and problematic work practices, and how to address them to improve system functioning. An integrated perspective on boundary infrastructures, workarounds, and shadow systems may advance system analysis, providing a more comprehensive picture of IT requirements than any concept alone. APPLICATION: Workarounds and shadow systems highlight that HIS should support systemic and local needs. Customized interfaces in HIS to support search, access, and exchange of relevant data might help to mitigate current shortcomings.
A first impression matters, in particular when encounters are brief as in most doctor-patient interactions. In this study, we investigate how physicians’ body postures impact patients’ first impressions of them and extend previous research by exploring posture effects on the perception of all roles of a physician – not just single aspects such as scholarly expertise or empathy. In an online survey, 167 participants ranked photographs of 4 physicians (2 female, 2 male) in 4 postures (2 open, 2 closed). The results show that male physicians were rated more positively when assuming open rather than closed postures with respect to all professional physician roles. Female physicians in open postures were rated similarly positive for items related to medical competence, but they tended to be rated less favorably with respect to social skills (such as the ability to communicate with and relate to the patient). These findings extend what is known about the effects of physicians’ body postures on the first impressions patients form to judge physicians’ medical versus social competencies. We discuss practical implications and the need for more research on interaction effects of body postures and physician gender on first impressions.
Background: Symptom checker apps are patient-facing decision support systems aimed at providing advice to laypersons on whether, where, and how to seek health care (disposition advice). Such advice can improve laypersons' self-assessment and ultimately improve medical outcomes. Past research has mainly focused on the accuracy of symptom checker apps' suggestions. To support decision-making, such apps need to provide not only accurate but also trustworthy advice. To date, only few studies have addressed the question of the extent to which laypersons trust symptom checker app advice or the factors that moderate their trust. Studies on general decision support systems have shown that framing automated systems (anthropomorphic or emphasizing expertise), for example, by using icons symbolizing artificial intelligence (AI), affects users' trust. Objective: This study aims to identify the factors influencing laypersons' trust in the advice provided by symptom checker apps. Primarily, we investigated whether designs using anthropomorphic framing or framing the app as an AI increases users' trust compared with no such framing. Methods: Through a web-based survey, we recruited 494 US residents with no professional medical training. The participants had to first appraise the urgency of a fictitious patient description (case vignette). Subsequently, a decision aid (mock symptom checker app) provided disposition advice contradicting the participants' appraisal, and they had to subsequently reappraise the vignette. Participants were randomized into 3 groups: 2 experimental groups using visual framing (anthropomorphic, 160/494, 32.4%, vs AI, 161/494, 32.6%) and a neutral group without such framing (173/494, 35%). Results: Most participants (384/494, 77.7%) followed the decision aid's advice, regardless of its urgency level. Neither anthropomorphic framing (odds ratio 1.120, 95% CI 0.664-1.897) nor framing as AI (odds ratio 0.942, 95% CI 0.565-1.570) increased behavioral or subjective trust (P=.99) compared with the no-frame condition. Even participants who were extremely certain in their own decisions (ie, 100% certain) commonly changed it in favor of the symptom checker's advice (19/34, 56%). Propensity to trust and eHealth literacy were associated with increased subjective trust in the symptom checker (propensity to trust b=0.25; eHealth literacy b=0.2), whereas sociodemographic variables showed no such link with either subjective or behavioral trust. Conclusions: Contrary to our expectation, neither the anthropomorphic framing nor the emphasis on AI increased trust in symptom checker advice compared with that of a neutral control condition. However, independent of the interface, most participants trusted the mock app's advice, even when they were very certain of their own assessment. Thus, the question arises as to whether laypersons use such symptom checkers as substitutes rather than as aids in their own decision-making. With trust in symptom checkers already high at baseline, the benefit of symptom checkers depends on interface designs that enable users to adequately calibrate their trust levels during usage.
Background: During the COVID-19 pandemic, medical laypersons with symptoms indicative of a COVID-19 infection commonly seek guidance on whether and where to seek medical care. Numerous web-based decision support tools (DSTs) have been developed, both by public and commercial stakeholders, to assist their decision-making. Though most of the DST's underlying algorithms are similar and simple decision trees, their mode of presentation differs: some DSTs present a static flowchart, while others are designed as a conversational agent, guiding the user through the decision tree's node step-by-step in an interactive manner. Objective: To investigate whether interactive DSTs provide greater decision support than non-interactive (ie, static) flowcharts. Methods: We developed mock interfaces for two DST (one static, one interactive), mimicking patient-facing, freely available DSTs for COVID-19 related self-assessment. Their underlying algorithm was identical and based on the Center for Disease Control's guidelines. We recruited adult US residents online in November 2020. Participants appraised the appropriate social and care-seeking behavior for seven fictitious descriptions of patients (case vignettes). Participants in the experimental groups received either the static or interactive mock DST as support, while the control group appraised the case vignettes unsupported. We determined participants' accuracy, decision certainty (after deciding) and mental effort to measure quality of decision support. Participants' ratings of the DSTs' usefulness, ease of use, trust and future intention to use the tools served as measures to analyze differences in participants' perception of the tools. We used ANOVAs and t-tests to assess statistical significance. Results: Our survey yielded 196 responses. The mean number of correct assessments was higher in the intervention groups (interactive DST group: M=11.71, SD=2.37; static DST group: M=11.45, SD=2.48) than in the control group (M=10.17, SD=2.00). Decisional certainty was significantly higher in the experimental groups (interactive DST group: M=80.7%, SD=14.1%; static DST group: M=80.5%, SD=15.8%) compared to the control group (M=65.8%, SD=20.8%). The differences in these measures proved statistically significant in t-tests comparing each intervention group with the control group (p<.001 for all four t tests). The ANOVA detected no significant differences regarding mental effort between the three study groups. Differences between the two intervention groups were of small effect sizes and non-significant for all three measures of quality of decision support and most measures of users' perception of the DSTs. Conclusions: When the decision space is limited as is the case in common COVID-19 self-assessment DSTs, static flowcharts might prove as beneficial in enhancing decision quality as interactive tools. Given that static flowcharts reveal the underlying decision algorithm more transparently and require less effort to develop, they might prove more efficient in providing guidance to the public. Further research should validate our findings on different use cases, elaborate on the trade-off between transparency and convenience in DSTs, and investigate whether subgroups of users benefit more of one type of user interface than the other. Clinicaltrial:

Lab head

Markus A Feufel
Department
  • Department of Psychology and Ergonomics
About Markus A Feufel
  • Markus A Feufel heads the Division of Ergonomics of the Department of Psychology and Ergonomics at Technische Universität Berlin. Markus does research in Human Factors & Ergonomics with the goal to help improve efficiency and reliability of work and decision processes. One of our current projects is 'iKNOW - Development and evaluation of an online-based counseling tool for BRCA1/2- mutation carriers.'

Members (9)

Frauke Mörike
  • Technische Universität Berlin
Christine Schmid
  • Technische Universität Berlin
Maren Heibges
  • Technische Universität Berlin
Felix Christian Grün
  • Technische Universität Berlin
Niklas von Kalckreuth
  • Technische Universität Berlin
Alina Rörig
  • Technische Universität Berlin
Viola Westfal
  • Technische Universität Berlin
Veronica Hoth
  • Technische Universität Berlin
Felix C. Grün
Felix C. Grün
  • Not confirmed yet

Alumni (6)

Gudrun Rauwolf
  • Technische Universität Berlin
Sven Schulz-Niethammer
  • Technische Universität Berlin
Marc Wittmann
  • Technische Universität Berlin
Veronika Schweighoferova
  • University of Cologne