Background: Cognitively straining conditions such as disruptions, interruptions, and information overload are related to impaired task performance and diminished well-being at work. It is therefore essential that we reduce their harmful consequences to individual employees and organizations. Our intervention study implements practices for managing the cognitive strain typical to office work tasks and working conditions in offices. We will examine the effects of a cognitive ergonomics intervention on working conditions, workflow, well-being, and productivity. Methods/design: The study is a stratified cluster randomized trial. The clusters are work units, for example, teams or offices. The four participating organizations entered a total of 36 clusters, and we invited all 1169 knowledge employees of these units to participate. We randomly allocated the clusters into an intervention group (cognitive ergonomics) or an active control group (recovery supporting). We invited an additional 471 participants to join a passive control group only for baseline and follow-up measurements, with no intervention. The study consists of a baseline survey and interviews and observations at the workplace, followed by an intervention. It starts with a workshop defining the specific actions for the intervention implementation stage, during which we send task reminder questionnaires to all employees to support behaviour change at the individual and team levels. The primary outcome measure is perceived frequency of cognitive strain from working conditions; the secondary outcome measures include subjective cognitive load, well-being, workflow/productivity, and cognitive stress symptoms. Process evaluation uses the quantitative and qualitative data obtained during the implementation and evaluation phases. The baseline measurements, intervention phase, and end-of-treatment measurements are now complete, and follow-up will continue until November 2019. Discussion: There is a need to expand the research of cognitive strain, which poses a considerable risk to work performance and employee well-being in cognitively demanding tasks. Our study will provide new information about factors that contribute to such strain. Most importantly, the results will show which evidence-based cognitive ergonomic practices support work performance in knowledge work, and the project will provide concrete examples of how to improve at work.

Digital monitoring of physiological signals can allow computer systems to adapt unobtrusively to users, so as to enhance personalised 'smart' interactions. In recent years, physiological computing has grown as a research field, and it is increasingly considered in diverse applications, ranging from specialised work contexts to consumer electronics. Working in this emerging field requires comprehension of several physiological signals, psychophysiological states or 'indices', and analysis techniques. The resulting literature encompasses a complex array of knowledge and techniques, presenting a clear challenge to the practitioner.We provide a foundational review of the field of psychophysiology to serve as a primer for the novice, enabling rapid familiarisation with the core concepts, or as a quick-reference resource for advanced readers. We place special emphasis on everyday human-computer interface applications, drawing a distinction from clinical or sports applications, which are more commonplace. The review provides a framework of commonly understood terms associated with experiential constructs and physiological signals. Then, 12 short and precisely focused review chapters describe 10 individual signals or signal sources and present two technical discussions of online data fusion and processing. A systematic review of multimodal studies is provided in the form of a reference table. We conclude with a general discussion of the application of psychophysiology to human-computer interaction, including guidelines and challenges.

The use of psychophysiologic signals in human-computer interaction is a growing field with significant potential for future smart personalised systems. Working in this emerging field requires comprehension of different physiological signals and analysis techniques. Cardiovascular signals such as heart rate variability and blood pressure variability are commonly used in psychophysiology in order to investigate phenomena such as mental workload. In this paper we present a short review of different cardiovascular metrics useful in the context of humancomputer interaction. This paper aims to serve as a primer for the novice, enabling rapid familiarisation with the latest core concepts. We emphasise everyday humancomputer interface applications to distinguish from the more common clinical or sports uses of psychophysiology. This paper is an extract from a comprehensive review of the entire field of ambulatory psychophysiology, with 12 similar chapters, plus application guidelines and systematic review.

Cognitive functioning is a relevant work and health related topic, however, validated methods to assess subjective cognitive complaints (SCC) at work are lacking. We introduce the Cognitive Function at Work Questionnaire (CFWQ) for measuring SCCs in occupational settings. 1-year follow-up data of 418 employees from a Finnish public media service company was analyzed. Participants completed web-based CFWQ, cognitive tests and a broad set of questionnaires for evaluating depression, anxiety, insomnia, daytime sleepiness, burnout, stress, mental job burden, work ability, cognitive errors, and perceived health. The factor analysis yielded a model with the CFWQ subdomains: Memory, Language, Executive Function, Speed of Processing, Cognitive Control and Name Memory. The internal consistency (Cronbach's alpha = .87) and the test-retest constancy (ICC = .84) reflected good reliability. Correlation between the CFWQ and cognitive errors at work ranged from.25 to .64 indicating adequate concurrent validity. Employees with depression, insomnia and burnout symptoms had higher (p < .001) CFWQ scores than participants without these symptoms. Depression and burnout symptom severity as well as accumulation of mood, sleep, and psychosocial stressors were associated with higher CFWQ scores (p < .001 in all). The CFWQ appears psychometrically sound measure for the assessment of SCC in occupational population.

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