Analysis and design of individual information systems to support health behavior change

As a wide-ranging socio-technical transformation, the digitalization has significantly influenced the world, bringing opportunities and challenges to our lives. Despite numerous benefits like the possibility to stay connected with people around the world, the increasing dispersion and use of digital technologies and media (DTM) pose risks to individuals’ well-being and health. Rising demands emerging from the digital world have been linked to digital stress, that is, stress directly or indirectly resulting from DTM (Ayyagari et al. 2011; Ragu-Nathan et al. 2008; Tarafdar et al. 2019; Weil and Rosen 1997), potentially intensifying individuals’ overall exposure to stress. Individuals experiencing this adverse consequence of digitalization are at elevated risk of developing severe mental health impairments (Alhassan et al. 2018; Haidt and Allen 2020; Scott et al. 2017), which is why various scholars emphasize that research should place a stronger focus on analyzing and shaping the role of the individual in a digital world, pursuing instrumental as well as humanistic objectives (Ameen et al. 2021; Baskerville 2011b). Information Systems (IS) research has long placed emphasis on the use of information and communication technology (ICT) in organizations, viewing an information system as the socio-technical system that emerges from individuals’ interaction with DTM in organizations. However, socio-technical information systems, as the essence of the IS discipline (Lee 2004; Sarker et al. 2019), are also present in different social contexts from private life. Acknowledging the increasing private use of DTM, such as smartphones and social networks, IS scholars have recently intensified their efforts to understand the human factor of IS (Avison and Fitzgerald 1991; Turel et al. 2021). A framework recently proposed by Matt et al. (2019) suggests three research angles: analyzing individuals’ behavior associated with their DTM use, analyzing what consequences arise from their DTM use behavior, and designing new technologies that promote positive or mitigate negative effects of individuals’ DTM use. Various recent studies suggest that individuals’ behavior seems to be an important lever influencing the outcomes of their DTM use (Salo et al. 2017; Salo et al. 2020; Weinstein et al. 2016). Therefore, this dissertation aims to contribute to IS research targeting the facilitation of a healthy DTM use behavior. It explores the use behavior, consequences, and design of DTM for individuals' use with the objective to deliver humanistic value by increasing individuals' health through supporting a behavior change related to their DTM use. The dissertation combines behavioral science and design science perspectives and applies pluralistic methodological approaches from qualitative (e.g., interviews, prototyping) and quantitative research (e.g., survey research, field studies), including mixed-methods approaches mixing both. Following the framework from Matt et al. (2019), the dissertation takes three perspectives therein: analyzing individuals’ behavior, analyzing individuals’ responses to consequences of DTM use, and designing information systems assisting DTM users. First, the dissertation presents new descriptive knowledge on individuals’ behavior related to their use of DTM. Specifically, it investigates how individuals behave when interacting with DTM, why they behave the way they do, and how their behavior can be influenced. Today, a variety of digital workplace technologies offer employees different ways of pursuing their goals or performing their tasks (Köffer 2015). As a result, individuals exhibit different behaviors when interacting with these technologies. The dissertation analyzes what interactional roles DTM users can take at the digital workplace and what may influence their behavior. It uses a mixed-methods approach and combines a quantitative study building on trace data from a popular digital workplace suite and qualitative interviews with users of this digital workplace suite. The empirical analysis yields eight user roles that advance the understanding of users’ behavior at the digital workplace and first insights into what factors may influence this behavior. A second study adds another perspective and investigates how habitual behavior can be changed by means of DTM design elements. Real-time feedback has been discussed as a promising way to do so (Schibuola et al. 2016; Weinmann et al. 2016). In a field experiment, employees working at the digital workplace are provided with an external display that presents real-time feedback on their office’s indoor environmental quality. The experiment examines if and to what extent the feedback influences their ventilation behavior to understand the effect of feedback as a means of influencing individuals’ behavior. The results suggest that real-time feedback can effectively alter individuals’ behavior, yet the feedback’s effectiveness reduces over time, possibly as a result of habituation to the feedback. Second, the dissertation presents new descriptive and prescriptive knowledge on individuals’ ways to mitigate adverse consequences arising from the digitalization of individuals. A frequently discussed consequence that digitalization has on individuals is digital stress. Although research efforts strive to determine what measures individuals can take to effectively cope with digital stress (Salo et al. 2017; Salo et al. 2020; Weinert 2018), further understanding of individuals’ coping behavior is needed (Weinert 2018). A group at high risk of suffering from the adverse effects of digital stress is adolescents because they grow up using DTM daily and are still developing their identity, acquiring mental strength, and adopting essential social skills. To facilitate a healthy DTM use, the dissertation explores what strategies adolescents use to cope with the demands of their DTM use. Combining a qualitative and a quantitative study, it presents 30 coping responses used by adolescents, develops five factors underlying adolescents’ activation of coping responses, and identifies gender- and age-related differences in their coping behavior. Third, the dissertation presents new prescriptive knowledge on the design of individual information systems supporting individuals in understanding and mitigating their perceived stress. Facilitated by the sensing capabilities of modern mobile devices, it explores the design and development of mobile systems that assess stress and support individuals in coping with stress by initiating a change of stress-related behavior. Since there is currently limited understanding of how to develop such systems, this dissertation explores various facets of their design and development. As a first step, it presents the development of a prototype aiming for life-integrated stress assessment, that is, the mobile sensor-based assessment of an individual’s stress without interfering with their daily routines. Data collected with the prototype yields a stress model relating sensor data to individuals’ perception of stress. To deliver a more generalized perspective on mobile stress assessment, the dissertation further presents a literature- and experience-based design theory comprising a design blueprint, design requirements, design principles, design features, and a discussion of potentially required trade-offs. Mobile stress assessment may be used for the development of mobile coping assistants. Aiming to assist individuals in effectively coping with stress and preventing future stress, a mobile coping assistant should recommend adequate coping strategies to the stressed individual in real-time or execute targeted actions within a defined scope of action automatically. While the implementation of a mobile coping assistant is yet up to future research, the dissertation presents an abstract design and algorithm for selecting appropriate coping strategies. To sum up, this dissertation contributes new knowledge on the digitalization of individuals to the IS knowledge bases, expanding both descriptive and prescriptive knowledge. Through the combination of diverse methodological approaches, it delivers knowledge on individuals’ behavior when using DTM, on the mitigation of consequences that may arise from individuals’ use of DTM, and on the design of individual information systems with the goal of facilitating a behavior change, specifically, regarding individuals’ coping with stress. Overall, the research contained in this dissertation may promote the development of digital assistants that support individuals’ in adopting a healthy DTM use behavior and thereby contribute to shaping a socio-technical environment that creates more benefit than harm for all individuals

Future bathroom: A study of user-centred design principles affecting usability, safety and satisfaction in bathrooms for people living with disabilities

Research and development work relating to assistive technology 2010-11 (Department of Health) Presented to Parliament pursuant to Section 22 of the Chronically Sick and Disabled Persons Act 197

Human experience in the natural and built environment : implications for research policy and practice

22nd IAPS conference. Edited book of abstracts. 427 pp. University of Strathclyde, Sheffield and West of Scotland Publication. ISBN: 978-0-94-764988-3

Sviluppo di un metodo innovativo per la misura del comfort termico attraverso il monitoraggio di parametri fisiologici e ambientali in ambienti indoor

openLa misura del comfort termico in ambienti indoor è un argomento di interesse per la comunità scientifica, poiché il comfort termico incide profondamente sul benessere degli utenti ed inoltre, per garantire condizioni di comfort ottimali, gli edifici devono affrontare costi energetici elevati. Anche se esistono norme nel campo dell'ergonomia del comfort che forniscono linee guida per la valutazione del comfort termico, può succedere che in contesti reali sia molto difficile ottenere una misurazione accurata. Pertanto, per migliorare la misura del comfort termico negli edifici, la ricerca si sta concentrando sulla valutazione dei parametri personali e fisiologici legati al comfort termico, per creare ambienti su misura per l’utente. Questa tesi presenta diversi contributi riguardo questo argomento. Infatti, in questo lavoro di ricerca, sono stati implementati una serie di studi per sviluppare e testare procedure di misurazione in grado di valutare quantitativamente il comfort termico umano, tramite parametri ambientali e fisiologici, per catturare le peculiarità che esistono tra i diversi utenti. In primo luogo, è stato condotto uno studio in una camera climatica controllata, con un set di sensori invasivi utilizzati per la misurazione dei parametri fisiologici. L'esito di questa ricerca è stato utile per ottenere una prima accuratezza nella misurazione del comfort termico dell'82%, ottenuta mediante algoritmi di machine learning (ML) che forniscono la sensazione termica (TSV) utilizzando la variabilità della frequenza cardiaca (HRV) , parametro che la letteratura ha spesso riportato legato sia al comfort termico dell'utenza che alle grandezze ambientali. Questa ricerca ha dato origine a uno studio successivo in cui la valutazione del comfort termico è stata effettuata utilizzando uno smartwatch minimamente invasivo per la raccolta dell’HRV. Questo secondo studio consisteva nel variare le condizioni ambientali di una stanza semi-controllata, mentre i partecipanti potevano svolgere attività di ufficio ma in modo limitato, ovvero evitando il più possibile i movimenti della mano su cui era indossato lo smartwatch. Con questa configurazione, è stato possibile stabilire che l'uso di algoritmi di intelligenza artificiale (AI) e il set di dati eterogeneo creato aggregando parametri ambientali e fisiologici, può fornire una misura di TSV con un errore medio assoluto (MAE) di 1.2 e un errore percentuale medio assoluto (MAPE) del 20%. Inoltre, tramite il Metodo Monte Carlo (MCM) è stato possibile calcolare l'impatto delle grandezze in ingresso sul calcolo del TSV. L'incertezza più alta è stata raggiunta a causa dell'incertezza nella misura della temperatura dell'aria (U = 14%) e dell'umidità relativa (U = 10,5%). L'ultimo contributo rilevante ottenuto con questa ricerca riguarda la misura del comfort termico in ambiente reale, semi controllato, in cui il partecipante non è stato costretto a limitare i propri movimenti. La temperatura della pelle è stata inclusa nel set-up sperimentale, per migliorare la misurazione del TSV. I risultati hanno mostrato che l'inclusione della temperatura della pelle per la creazione di modelli personalizzati, realizzati utilizzando i dati provenienti dal singolo partecipante, porta a risultati soddisfacenti (MAE = 0,001±0,0003 e MAPE = 0,02%±0,09%). L'approccio più generalizzato, invece, che consiste nell'addestrare gli algoritmi sull'intero gruppo di partecipanti tranne uno, e utilizzare quello tralasciato per il test, fornisce prestazioni leggermente inferiori (MAE = 1±0.2 e MAPE = 25% ±6%). Questo risultato evidenzia come in condizioni semi-controllate, la previsione di TSV utilizzando la temperatura della pelle e l'HRV possa essere eseguita con un certo grado di incertezza.Measuring human thermal comfort in indoor environments is a topic of interest in the scientific community, since thermal comfort deeply affects the well-being of occupants and furthermore, to guarantee optimal comfort conditions, buildings must face high energy costs. Even if there are standards in the field of the ergonomics of the thermal environment that provide guidelines for thermal comfort assessment, it can happen that in real-world settings it is very difficult to obtain an accurate measurement. Therefore, to improve the measurement of thermal comfort of occupants in buildings, research is focusing on the assessment of personal and physiological parameters related to thermal comfort, to create environments carefully tailored to the occupant that lives in it. This thesis presents several contributions to this topic. In fact, in the following research work, a set of studies were implemented to develop and test measurement procedures capable of quantitatively assessing human thermal comfort, by means of environmental and physiological parameters, to capture peculiarities among different occupants. Firstly, it was conducted a study in a controlled climatic chamber with an invasive set of sensors used for measuring physiological parameters. The outcome of this research was helpful to achieve a first accuracy in the measurement of thermal comfort of 82%, obtained by training machine learning (ML) algorithms that provide the thermal sensation vote (TSV) by means of environmental quantities and heart rate variability (HRV), a parameter that literature has often reported being related to both users' thermal comfort. This research gives rise to a subsequent study in which thermal comfort assessment was made by using a minimally invasive smartwatch for collecting HRV. This second study consisted in varying the environmental conditions of a semi-controlled test-room, while participants could carry out light-office activities but in a limited way, i.e. avoiding the movements of the hand on which the smartwatch was worn as much as possible. With this experimental setup, it was possible to establish that the use of artificial intelligence (AI) algorithms (such as random forest or convolutional neural networks) and the heterogeneous dataset created by aggregating environmental and physiological parameters, can provide a measure of TSV with a mean absolute error (MAE) of 1.2 and a mean absolute percentage error (MAPE) of 20%. In addition, by using of Monte Carlo Method (MCM), it was possible to compute the impact of the uncertainty of the input quantities on the computation of the TSV. The highest uncertainty was reached due to the air temperature uncertainty (U = 14%) and relative humidity (U = 10.5%). The last relevant contribution obtained with this research work concerns the measurement of thermal comfort in a real-life setting, semi-controlled environment, in which the participant was not forced to limit its movements. Skin temperature was included in the experimental set-up, to improve the measurement of TSV. The results showed that the inclusion of skin temperature for the creation of personalized models, made by using data coming from the single participant brings satisfactory results (MAE = 0.001±0.0003 and MAPE = 0.02%±0.09%). On the other hand, the more generalized approach, which consists in training the algorithms on the whole bunch of participants except one, and using the one left out for the test, provides slightly lower performances (MAE = 1±0.2 and MAPE = 25%±6%). This result highlights how in semi-controlled conditions, the prediction of TSV using skin temperature and HRV can be performed with acceptable accuracy.INGEGNERIA INDUSTRIALEembargoed_20220321Morresi, Nicol

Socio-technical analysis and design of digital workplaces to foster employee health

Recent socio-technical developments caused by ongoing digitalization (e.g., robotic process automation, artificial intelligence, anthropomorphic systems) or the COVID-19 pandemic (e.g., an increasing number of remote working employees and hence, increasing number of virtual collaboration) change the work environment and culture. Digital and smart workplace technol-ogies facilitate business processes and provide tools for efficient communication and (virtual) collaboration, “increasing the productivity of the workforce in the information age” (Attaran et al. 2019, p. 1). Especially in times of the COVID-19 pandemic, digital technologies play a crucial role in keeping us socially close, connected, and collaborative while increasing the phys-ical distance between humans. However, this development affects the health of employees (Tarafdar et al. 2013). In research, for example, it has long been known that the increased usage of digital technologies and media (DTM) may cause stress, leading to potentially harmful reac-tions in individuals. Research has noted this specific form of stress as technostress (Ayyagari et al. 2011; Tarafdar et al. 2007; Tarafdar et al. 2011; Tarafdar et al. 2019), which is an umbrella term for causes, negative organizational outcomes, and negative humanistic outcomes resulting from the use of DTM at work. The simultaneous consideration of humanistic (e.g., well-being, equality) and organizational outcomes (e.g., efficiency, productivity) is an integral part of a socio-technical system (Beath et al. 2013; Mumford 2006), which is at the core of the IS discipline (Bostrom et al. 2009; Chiasson and Davidson 2005). However, a review from Sarker et al. (2019) regarding published research articles in one of the top journals within the IS community revealed that most reviewed studies (91%) had focused exclusively on instrumental goals. They conclude that “many IS researchers have forgotten or ignored the premise that technologies need to benefit humankind overall (Majchrzak et al. 2016), not just their economic condition” (Sarker et al. 2019, p. 705). Especially as humanistic outcomes can lead to even more positive instrumental outcomes. Hence, Sarker et al. (2019) call for focusing on the connection between humanistic and instru-mental outcomes, enabling a positive synergy resulting from this interplay. For this reason, this dissertation adopts a socio-technical perspective. It aims to conduct re-search that links instrumental outcomes with humanistic objectives to ultimately achieve a healthier use of DTMs at the digital workplace. It is important to note that the socio-technical perspective considers both the technical component and the social component privileging nei-ther one of them and sees outcomes resulting from the reciprocal interaction between those two.Therefore, the dissertation focuses on the interaction while applying pluralistic methodological approaches from qualitative (e.g., semi-structured interviews, focus group discussions) and quantitative research (e.g., collection from a field study or survey research). It provides a theo-retical contribution applying both behavioral research (i.e., analysis of cause-and-effect rela-tionships) and design-oriented research (i.e., instructions for designing socio-technical information systems). Overall, this work addresses four different areas within the reciprocal interaction between the social and technical components: the role of the technical component, the role of the social component, DTMs fostering a fit between the technical and social compo-nents, and the imminent misfit between these two due to ongoing digitalization. First, to contribute to an understanding of the technical component’s role, this thesis presents new knowledge on the characteristics and features of DTM and their influence on employee health and productivity. Research on the design of digital workplaces examined different design approaches, in which information exchange and sharing documents or project support were regarded (Williams and Schubert 2018). However, the characteristics of DTM also play an es-sential role in the emergence of technostress (Dardas and Ahmad 2015). This thesis presents ten characteristics of DTM that affect technostress at an individual’s workplace, including a measurement scale and analysis on how these characteristics affect technostress. Besides, also, the provision of functional features by DTMs can affect instrumental outcomes or humanistic objectives. For example, affording users with certain kinds of autonomy regarding the config-uration of DTM while they work towards their goals could have a tremendous effect on pursu-ing goals and well-being (Patall et al. 2008; Ryan and Deci 2000). Therefore, this thesis presents knowledge regarding the design of DTM on the benefits of affording users with autonomy. Furthermore, it shows that merely affording more autonomy can have positive effects above and beyond the positive effects of the actualization of affordance. Second, to contribute to an understanding of the social component’s role, this thesis presents new knowledge on contextual and individual factors of social circumstances and their influence on employee health and productivity. In this context, the influence of the COVID-19 pandemic on the intensity of technostress among employees is considered, as work became more digital almost overnight. Therefore, this thesis provides empirical insights into digital work and its context in times of the COVID-19 pandemic and its effect on employees’ well-being, health, and productivity. Furthermore, measures to steer the identified effects if the situation in the course of the COVID-19 pandemic persists or comparable disruptive situations should re-occur are discussed. On the other hand, this research takes a closer look at the effect of an individual preference regarding coping styles in dealing with upcoming technostress. A distinction is made between the effects of two different coping styles, namely active-functional and dysfunctional, on strain as a humanistic outcome and productivity as an instrumental outcome. In the course of this, evidence is provided that coping moderates the relationship between the misfit within the socio-technical system and strain as proposed by the psychological theory of job demands-resources model (Demerouti et al. 2001). Third, to contribute to a successful fit between the technical and social components, this thesis presents frameworks and guidelines on the design of DTM, which understand the social com-ponent (here the user and her/his environment) and adjust accordingly to the needs of their users. Therefore, the thesis provides knowledge on the design of DTMs that support users in applying stress management techniques and build the foundation for stress-sensitive systems (i.e., systems that aim to mitigate stress by applying intervention measures on the social and technical component (Adam et al. 2017)). As a matter of fact, a framework for collecting and storing data (e.g., on the user and her/his environment) is developed and experiences with im-plementing a prototype for life-integrated stress assessment are reported. The experiences from this and the existing knowledge in the literature will finally be aggregated to a mid-range design theory for mobile stress assessment. To contribute to the fourth and last aspect, the imminent misfit within the socio-technical sys-tem due to ongoing digitalization, this thesis presents new knowledge regarding digital work demands that potentially affect both employees’ health and instrumental outcomes. The current version of technostress’s theoretical foundation was introduced more than ten years ago by Tarafdar et al. (2007). However, the interaction with and use of DTM has considerably changed along with the societal and individual expectations. Therefore, this thesis puts the current con-cept of technostress to test. As a result, a new theory of digital stress, as an extension of the concept of technostress, is proposed with twelve dimensions – instead of five dimensions within the concept of Tarafdar et al. (2007) – that could be hierarchically structured in four higher-order factors. This theory holistically addresses the current challenges that employees have to deal with digitalization. To sum up, this dissertation contributes to the IS community’s knowledge base by providing knowledge regarding the interaction between employees and their digital workplace to foster the achievement of humanistic and instrumental outcomes. It provides both behavioral research and design-oriented research while using pluralistic methodological approaches. For this pur-pose, this thesis presents knowledge about the different components within the socio-technical system, design knowledge on DTMs fostering the fit between these components, and an under-standing of an upcoming misfit due to the ongoing digitalization. Overall, this research aims to support the successful change towards a healthy digital workplace in the face of digitalization

State of the art of audio- and video based solutions for AAL

Working Group 3. Audio- and Video-based AAL ApplicationsIt is a matter of fact that Europe is facing more and more crucial challenges regarding health and social care due to the demographic change and the current economic context. The recent COVID-19 pandemic has stressed this situation even further, thus highlighting the need for taking action. Active and Assisted Living (AAL) technologies come as a viable approach to help facing these challenges, thanks to the high potential they have in enabling remote care and support. Broadly speaking, AAL can be referred to as the use of innovative and advanced Information and Communication Technologies to create supportive, inclusive and empowering applications and environments that enable older, impaired or frail people to live independently and stay active longer in society. AAL capitalizes on the growing pervasiveness and effectiveness of sensing and computing facilities to supply the persons in need with smart assistance, by responding to their necessities of autonomy, independence, comfort, security and safety. The application scenarios addressed by AAL are complex, due to the inherent heterogeneity of the end-user population, their living arrangements, and their physical conditions or impairment. Despite aiming at diverse goals, AAL systems should share some common characteristics. They are designed to provide support in daily life in an invisible, unobtrusive and user-friendly manner. Moreover, they are conceived to be intelligent, to be able to learn and adapt to the requirements and requests of the assisted people, and to synchronise with their specific needs. Nevertheless, to ensure the uptake of AAL in society, potential users must be willing to use AAL applications and to integrate them in their daily environments and lives. In this respect, video- and audio-based AAL applications have several advantages, in terms of unobtrusiveness and information richness. Indeed, cameras and microphones are far less obtrusive with respect to the hindrance other wearable sensors may cause to one’s activities. In addition, a single camera placed in a room can record most of the activities performed in the room, thus replacing many other non-visual sensors. Currently, video-based applications are effective in recognising and monitoring the activities, the movements, and the overall conditions of the assisted individuals as well as to assess their vital parameters (e.g., heart rate, respiratory rate). Similarly, audio sensors have the potential to become one of the most important modalities for interaction with AAL systems, as they can have a large range of sensing, do not require physical presence at a particular location and are physically intangible. Moreover, relevant information about individuals’ activities and health status can derive from processing audio signals (e.g., speech recordings). Nevertheless, as the other side of the coin, cameras and microphones are often perceived as the most intrusive technologies from the viewpoint of the privacy of the monitored individuals. This is due to the richness of the information these technologies convey and the intimate setting where they may be deployed. Solutions able to ensure privacy preservation by context and by design, as well as to ensure high legal and ethical standards are in high demand. After the review of the current state of play and the discussion in GoodBrother, we may claim that the first solutions in this direction are starting to appear in the literature. A multidisciplinary 4 debate among experts and stakeholders is paving the way towards AAL ensuring ergonomics, usability, acceptance and privacy preservation. The DIANA, PAAL, and VisuAAL projects are examples of this fresh approach. This report provides the reader with a review of the most recent advances in audio- and video-based monitoring technologies for AAL. It has been drafted as a collective effort of WG3 to supply an introduction to AAL, its evolution over time and its main functional and technological underpinnings. In this respect, the report contributes to the field with the outline of a new generation of ethical-aware AAL technologies and a proposal for a novel comprehensive taxonomy of AAL systems and applications. Moreover, the report allows non-technical readers to gather an overview of the main components of an AAL system and how these function and interact with the end-users. The report illustrates the state of the art of the most successful AAL applications and functions based on audio and video data, namely (i) lifelogging and self-monitoring, (ii) remote monitoring of vital signs, (iii) emotional state recognition, (iv) food intake monitoring, activity and behaviour recognition, (v) activity and personal assistance, (vi) gesture recognition, (vii) fall detection and prevention, (viii) mobility assessment and frailty recognition, and (ix) cognitive and motor rehabilitation. For these application scenarios, the report illustrates the state of play in terms of scientific advances, available products and research project. The open challenges are also highlighted. The report ends with an overview of the challenges, the hindrances and the opportunities posed by the uptake in real world settings of AAL technologies. In this respect, the report illustrates the current procedural and technological approaches to cope with acceptability, usability and trust in the AAL technology, by surveying strategies and approaches to co-design, to privacy preservation in video and audio data, to transparency and explainability in data processing, and to data transmission and communication. User acceptance and ethical considerations are also debated. Finally, the potentials coming from the silver economy are overviewed.publishedVersio

Pilot workload and fatigue: A critical survey of concepts and assessment techniques

The principal unresolved issues in conceptualizing and measuring pilot workload and fatigue are discussed. These issues are seen as limiting the development of more useful working concepts and techniques and their application to systems engineering and management activities. A conceptual analysis of pilot workload and fatigue, an overview and critique of approaches to the assessment of these phenomena, and a discussion of current trends in the management of unwanted workload and fatigue effects are presented. Refinements and innovations in assessment methods are recommended for enhancing the practical significance of workload and fatigue studies

Space Station Habitability Recommendations Based on a Systematic Comparative Analysis of Analogous Conditions

Conditions analogous to the proposed NASA Space Station are systematically analyzed in order to extrapolate design guidelines and recommendations concerning habitability and crew productivity. Analogous environments studied included Skylab, Sealab, Tektite, submarines, Antarctic stations and oil drilling platforms, among others. These analogues were compared and rated for size and composition of group, social organization, preparedness for mission, duration of tour, types of tasks, physical and psychological isolation, personal motivation, perceived risk, and quality of habitat and life support conditions. One-hundred design recommendations concerning, sleep, clothing, exercise, medical support, personal hygiene, food preparation, group interaction, habitat aesthetics, outside communications, recreational opportunities, privacy and personal space, waste disposal, onboard training, simulation and task preparation, and behavioral and physiological requirements associated with a microgravity environment, are provided