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Designing behavior change technologies for workplace wellbeing
Get PDFHumans have become exponentially more productive at work due to advances in technology. However, these advances are spurred by a desire to increase output, often without considering wellbeing. Consequently, modern knowledge workers (i.e., occupations primarily involving applying information rather than physical tasks) experience unhealthy conditions such as sedentary behavior, social isolation, and excessive screen time. The consequences of chronic exposure to such conditions can be drastic for users' mental and physical wellbeing. Even when users make efforts to increase healthy behaviors in the workplace, such as by installing standing desks, uptake remains low in practice due to the intention-behavior gap. Technology designers have an opportunity to combat the negative effects of the modern workplace, but they should not degrade productivity for their solutions to be accepted in industrial practice.
Thus, the problem is two-fold: (1) the modern office prioritizes productivity at the expense of wellbeing, and (2) users have difficulty changing their behaviors even when healthy interventions are available. These factors reveal a spectrum of influence connected to both if and how people are motivated to change their behaviors. This thesis navigates along this spectrum by conducting studies and evaluating prototypical systems to build an understanding of this motivation. Consequently, this thesis outlines a vision for a healthy future of work through two approaches. First, we investigate how to design technology to make healthy ways of working a more attractive choice for users. Second, we explore active behavior change technologies that aim to overcome the intention-behavior gap and ethically nudge users to behave according to their own goals.
In the first series of explorations, we investigate technology that inspires users to incorporate movement in the workplace. The works in this section use passive behavior change approaches, aiming to make movement an attractive option that users will choose of their own volition. We used ethnographic methods to understand the needs of users who regularly integrate physical activity into their work routines. Drawing from this knowledge, we developed a tangible prototype to explore technology-supported walking meetings. Finally, we explored using physical exertion as a design element to generate mindful experiences. Overall, these investigations provide a new understanding of how technology can seamlessly integrate physical activity into work routines while creating positive user experiences.
Next, we explore active approaches that nudge users to act in alignment with their own goals. We designed and implemented functional prototypes and conducted mixed-methods evaluations on interventions to increase movement, foster social connectedness, and manage excessive screentime, all of which are issues in the modern office. To increase ecological validity, we conducted three of the studies in the field, including one large-scale longitudinal study. These investigations provide insights into how technology can support users in overcoming intention-behavior gaps to achieve their own behavior goals in the real world.
Based on our investigations, we propose a design framework for behavior change technologies that promote a healthy workplace. The framework draws from related work and incorporates theoretical concepts from physiology and nudge theory. We designed the framework to be beneficial for researchers and technology designers in creating behavior change technologies.
In all, this thesis contributes the following: (1) prototypical systems to facilitate improvements in physical activity, mindful screen time, and social interactions, (2) field evaluations of workplace behavior change technologies, (3) an actionable design framework highlighting important design dimensions and categorizing literature for future developers of ethical behavior change technologies, and (4) a reflection on ethical behavior change. Finally, we discuss open challenges for the field and deploying research in practice. This thesis demonstrates the potential for technology to support healthier workplaces without sacrificing productivity by providing concrete solutions and ecologically validated field evaluations. By advocating for the integration of wellbeing principles into workplace design and emphasizing user-centered approaches to behavior change technologies, our work lays the groundwork for creating healthier and more productive workplaces in the future.Die Produktivität der Menschen bei der Arbeit ist durch den technischen Fortschritt exponentiell gestiegen. Diese Fortschritte werden jedoch durch den Wunsch nach mehr Leistung angetrieben, oft ohne Rücksicht auf das Wohlbefinden. Infolgedessen sind moderne Wissensarbeiter (d. h. Berufe, bei denen es in erster Linie um die Anwendung von Informationen und nicht um physische Aufgaben geht) ungesunden Bedingungen wie sitzendem Verhalten, sozialer Isolation und übermäßiger Bildschirmarbeit ausgesetzt. Die Folgen einer chronischen Belastung durch solche Bedingungen können für das geistige und körperliche Wohlbefinden der Nutzer drastisch sein. Selbst wenn sich die Nutzer bemühen, gesundes Verhalten am Arbeitsplatz zu fördern, z. B. durch die Einrichtung von Stehpulten, bleibt die Akzeptanz in der Praxis aufgrund der Kluft zwischen Absicht und Verhalten gering. Technologiedesigner haben die Möglichkeit, die negativen Auswirkungen des modernen Arbeitsplatzes zu bekämpfen, aber sie sollten die Produktivität nicht beeinträchtigen, damit ihre Lösungen in der industriellen Praxis akzeptiert werden.
Das Problem ist also ein zweifaches: (1) im modernen Büro wird der Produktivität auf Kosten des Wohlbefindens Vorrang eingeräumt, und (2) den Nutzern fällt es schwer, ihr Verhalten zu ändern, selbst wenn gesunde Interventionen zur Verfügung stehen. Diese Faktoren zeigen ein Spektrum von Einflüssen auf, die damit zusammenhängen, ob und wie Menschen motiviert sind, ihr Verhalten zu ändern. Die vorliegende Arbeit bewegt sich entlang dieses Spektrums, indem sie Studien durchführt und prototypische Systeme evaluiert, um ein Verständnis für diese Motivation zu entwickeln. Folglich skizziert diese Arbeit eine Vision für eine gesunde Zukunft der Arbeit durch zwei Ansätze. Erstens untersuchen wir, wie Technologien entwickelt werden können, um gesunde Arbeitsweisen für die Nutzer attraktiver zu machen. Zweitens erforschen wir Technologien zur aktiven Verhaltensänderung, die darauf abzielen, die Kluft zwischen Absicht und Verhalten zu überwinden und die Nutzer auf ethische Weise dazu zu bewegen, sich entsprechend ihren eigenen Zielen zu verhalten.
In der ersten Reihe von Untersuchungen erforschen wir Technologien, die die Nutzer dazu anregen, Bewegung am Arbeitsplatz einzubauen. Die Arbeiten in diesem Abschnitt verwenden Ansätze zur passiven Verhaltensänderung und zielen darauf ab, Bewegung zu einer attraktiven Option zu machen, für die sich die Nutzer aus eigenem Antrieb entscheiden. Wir haben ethnografische Methoden eingesetzt, um die Bedürfnisse von Nutzern zu verstehen, die regelmäßig körperliche Aktivität in ihre Arbeitsroutine integrieren. Auf der Grundlage dieses Wissens entwickelten wir einen greifbaren Prototyp, um technologiegestützte Geh-Meetings zu erforschen. Schließlich untersuchten wir die Nutzung körperlicher Anstrengung als Gestaltungselement, um achtsame Erfahrungen zu erzeugen. Insgesamt liefern diese Untersuchungen ein neues Verständnis dafür, wie Technologie körperliche Aktivität nahtlos in den Arbeitsalltag integrieren und gleichzeitig positive Nutzererfahrungen schaffen kann.
Als Nächstes erforschen wir aktive Ansätze, die die Nutzer dazu anregen, im Einklang mit ihren eigenen Zielen zu handeln. Wir haben funktionale Prototypen entworfen und implementiert und Evaluierungen mit gemischten Methoden zu Interventionen zur Steigerung der Bewegung, zur Förderung sozialer Kontakte und zum Umgang mit übermäßiger Bildschirmzeit durchgeführt - allesamt Themen, die im modernen Büro eine Rolle spielen. Um die ökologische Validität zu erhöhen, haben wir drei der Studien im Feld durchgeführt, darunter eine groß angelegte Längsschnittstudie. Diese Untersuchungen geben Aufschluss darüber, wie die Technologie die Nutzer bei der Überwindung der Diskrepanz zwischen Absicht und Verhalten unterstützen kann, um ihre eigenen Verhaltensziele in der realen Welt zu erreichen.
Auf der Grundlage unserer Untersuchungen schlagen wir einen Gestaltungsrahmen für Technologien zur Verhaltensänderung vor, die einen gesunden Arbeitsplatz fördern. Der Rahmen basiert auf verwandten Arbeiten und umfasst theoretische Konzepte aus der Physiologie und der Nudge-Theorie. Wir haben den Rahmen so gestaltet, dass er Forschern und Technologieentwicklern bei der Entwicklung von Technologien zur Verhaltensänderung von Nutzen ist.
Insgesamt leistet diese Arbeit folgende Beiträge: (1) prototypische Systeme zur Verbesserung der körperlichen Aktivität, des achtsamen Umgangs mit Bildschirmen und der sozialen Interaktion, (2) Feldevaluierungen von Technologien zur Verhaltensänderung am Arbeitsplatz, (3) einen umsetzbaren Gestaltungsrahmen, der wichtige Gestaltungsdimensionen hervorhebt und die Literatur für künftige Entwickler von Technologien zur ethischen Verhaltensänderung kategorisiert, und (4) eine Reflexion über ethische Verhaltensänderung. Abschließend diskutieren wir offene Herausforderungen für das Feld und die Umsetzung der Forschung in die Praxis. Diese Arbeit zeigt das Potenzial von Technologien zur Unterstützung gesünderer Arbeitsplätze ohne Produktivitätseinbußen auf, indem sie konkrete Lösungen und ökologisch validierte Feldbewertungen liefert. Indem wir für die Integration von Prinzipien des Wohlbefindens in die Arbeitsplatzgestaltung eintreten und nutzerzentrierte Ansätze für Technologien zur Verhaltensänderung betonen, legt unsere Arbeit den Grundstein für die Schaffung gesünderer und produktiverer Arbeitsplätze in der Zukunft
Azobenzene photoswitches for near-infrared modulation of bioactivity and high-performance imaging applications
Get PDFFunctional insights of ZYX and LY96 sequence variants identified in patients with Inflammatory Bowel Disease
Get PDFAdvancements in remote sensing of the thermodynamic cloud phase using Meteosat satellites
Get PDFClouds can consist entirely of liquid droplets, ice crystals or a mixture of both, called mixed-phase. Knowledge of the thermodynamic cloud phase is crucial for understanding the Earth’s radiation budget, cloud and atmospheric processes, and the water cycle. However, the microphysical processes governing cloud phase and phase transitions are not well understood, leading to large uncertainties in climate predictions. Especially mixed phase clouds still pose a challenge. To date, the most reliable methods for cloud phase determination from satellites are synergistic lidar-radar techniques, such as the DARDAR (liDAR-raDAR) product. But active remote sensing is limited by its narrow field of view and low temporal resolution. These missing pieces can be provided by geostationary passive sensors. However, passive remote sensing of cloud phase is challenging and remote sensing of the more complex mixed-phase in particular is rarely done. This study addresses these challenges and provides a comprehensive analysis of the phase detection capabilities of the SEVIRI instrument aboard the geostationary Meteosat Second Generation satellite. First, an analysis of the geographic and temporal distribution of cloud phases on the SEVIRI disc using the reliable DARDAR data as "ground truth" shows that all cloud phases are relevant for SEVIRI, including the mixed-phase. Second, the information content of infrared-window brightness temperature differences (BTDs) of SEVIRI is investigated. Sensitivities of the BTDs to all radiatively relevant cloud parameters are assessed using radiative transfer calculations and reveal a complex phase dependence of the BTDs, where the dominant link between BTDs and phase is through the cloud top temperature. This analysis helps to understand the potential and limitations of BTDs in phase retrievals. Using these findings, the new PRObabilistic cloud top Phase retrieval for SEVIRI (ProPS) is developed. It employs a probabilistic Bayesian approach for cloud and phase detection based on collocated DARDAR-SEVIRI data. ProPS distinguishes between clear sky, optically thin ice, optically thick ice, mixed-phase, supercooled, and warm liquid clouds. The retrieval has a high (>80%) probability of detection for liquid and ice pixels and classifies more than half of the challenging mixed-phase and supercooled clouds correctly. The new method enables the study of the temporal evolution of cloud phases, in particular also mixed-phase and supercooled clouds, which have so far been rarely studied from geostationary satellites. This thesis contributes to the global effort to observe and understand cloud phases in order to improve their representation in numerical models and to constrain the large uncertainties in climate projections
Advancing the discovery of predictive biomarkers in drug high-throughput screens and clinical trials for precision oncology
Get PDFDiscovering a universal cure for all cancers, known as the one-drug-fits-them-all approach, is challenging due to the diverse and complex nature of the disease. Precision oncology is a paradigm in modern medicine which ought to overcome this approach by tailoring cancer treatments to tumour and patient characteristics for increased safety and efficacy. Carcinogenesis is driven by genetic alterations, which established themselves as suitable drug targets and predictive biomarkers in clinical practice. While these discoveries were previously limited to studying a few key cancer pathways or cancer genes, the contemporary accumulation of biomedical data, including molecularly profiled drug high-throughput screens and clinical trials, facilitates the discovery of biomarkers for predicting treatment success. Several computational models using data-driven methods were able to successfully predict responses to drugs in both preclinical and clinical settings based on molecular characteristics; however, the translation of the predicted biomarkers towards clinical utility has remained limited. In order to address this, this thesis presents a range of methods and analysis strategies that make sparse, interpretable and robust predictions of potential biomarkers for treatment efficacy.
The chapters of this thesis include (1) an integrative method for identifying DNA methylation biomarkers associated with drug susceptibility using drug high-throughput screens and multi-omics characterisations in cancer cell lines, (2) an assessment of the epithelial-mesenchymal transition in cancer cell lines and its causal impact on drug susceptibility and (3) a framework for the exploration and identification of the molecular and biomarker landscapes of randomised controlled clinical trials in oncology.
In summary, the presented work facilitates the discovery of predictive biomarkers by incorporating molecular data modalities into tailored modelling strategies to reflect cancer mechanisms in high-throughput screens and clinical trials. In future, these methods may become an indispensable part of a more integrated and data-driven drug discovery and development process to design more targeted and effective cancer treatment strategies
Investigating the precision of dynamic DNA origami platforms with multi-color single-molecule FRET methods and using them to benchmark deep-neural networks analysis approaches
Get PDFMany fundamental biological processes and interactions can be successfully explored by applying Förster resonance energy transfer (FRET) techniques which have become crucial tools in molecular biology and biophysics. By strategically incorporating suitable dye pairs into different positions of biomolecules, we can resolve both inter- and intra-molecular distances, as well as dynamic interactions with sub-nanometer resolution. Such level of detail is essential for understanding the molecular machinery of life, as it allows us to observe interactions and conformational changes that are often invisible when using traditional methods. FRET is particularly powerful due to its extreme sensitivity to the distance between the centers of molecules since it is related to the 6th power of the distance, so it is one of the most effective tools for detecting small changes. Unlike conventional ensemble measurements, which average out molecular behaviors across an ensemble, single-molecule FRET (smFRET) enables the detection of subtle variations such as conformational and functional heterogeneities within a sample. These underlying variations provide critical insights into the complex behaviors of biomolecular systems. The ability to observe such differences with the appropriate statistics, can uncover hidden states, transient interactions and rare events that play key roles in biological functions.
Traditionally, FRET experiments were focused on two-color systems, where a donor and acceptor dye pair report on a single distance. However, recent advancements have pushed the boundaries of FRET applications by introducing three-color FRET assays. Incorporating three labels into the system allows for the simultaneous measurement of multiple distances, creating a more comprehensive three-dimensional vision of the molecular interactions and structures. This multi-color approach not only helps track individual distances between each dye pair but also reveals correlations between them, offering a richer understanding of the molecular dynamics under study. Although three-color FRET assays can complicate both the experimental design and data analysis, these challenges have been addressed. Thanks to significant advancements in instrumentation and the development of sophisticated analysis software, the once intimidating task of analyzing three-color FRET data has become more manageable. The technological innovations in detection sensitivity, data processing and automation have transformed what was once a time-consuming and user-prone process into a streamlined, reliable workflow. As a result, researchers can now perform complex three-color FRET experiments with reduced analysis times, removing barriers that previously might have discouraged the widespread adoption of such techniques.
The combination of solution-based and surface-based smFRET assays offers a versatile approach for studying biomolecular systems. Solution-based assays are ideal for capturing the fast dynamic behavior of molecules in their native states and not bound to the surface, while surface-immobilization assays allow for long-term observations of molecular kinetics by fixing molecules on a chamber surface area. By employing both techniques, we can gain a comprehensive understanding of the sample, taking advantage of the different time scales and environmental conditions each method provides. This dual approach enables the examination of individual biomolecules behavior in ways that might be impossible using just one of the techniques.
A particularly exciting development in the field of smFRET is its combination with DNA origami nanotechnology. DNA origami structures allow for the precise design and construction of nanoscale samples, and have revolutionized many areas of single-molecule biophysics. When complemented with smFRET, DNA origami provides a versatile platform for positioning fluorophores with sub-nanometer precision, enabling extreme control over the spatial arrangement of dyes. This level of control facilitates the study of a wide range of fundamental questions, from unraveling the structural features and distances, and molecular functions to probing the single fluorophores behavior in dynamic molecular changes and interactions.
In this thesis, both two- and three-color smFRET assays were employed to benchmark a powerful and versatile analysis tool based on deep learning. The primary goal was to significantly shorten the data analysis time and eliminate user bias during the analysis process, which is a common issue in manual data interpretation. The development of this tool has reduced the time required for analysis from weeks to minutes, revolutionizing how data is processed and visualized, and open a whole new world of possible experiments. Moreover, the experiments conducted on various L-shaped DNA origami nanostructures, which were integral to the development of these smFRET assays, uncovered a number of interesting characteristics related to the behavior of fluorophores and labeling strategies. These findings have prompted us to further investigate the precise control and manipulation of fluorophore positioning and transient binding kinetics of single-stranded DNA in the context of the DNA origami structure. A comprehensive set of experiments was executed to explore how accurately and consistently one can arrange and control the transient binding kinetics of DNA single strands. These studies revealed a number of factors that can interfere with the behavior and kinetics of the system, including the type of fluorophores used and the specific labeling or binding positions. By understanding and characterizing such factors, we can now predict and control the performance of FRET-based assays more reliably
