Combining cognitive and physical work tasks

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DOCTORAL THESIS NO. 22

Susanna Mixter

Gävle University Press

Combining cognitive and physical work tasks

Short-term effects on fatigue, stress, performance and recovery

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Dissertation for the Degree of Doctor of Medicine in Occupational Health Science to be publicly defended on Friday 4^th June 2021 at 9.00-12.00 in Lilla Jadwigasalen, University of Gävle.

External reviewer: Paul Jarle Mork, Norwegian University of Science and Technology

Cover illustration: https://www.wordclouds.com Gävle University Press

ISBN 978-91-88145-71-0 ISBN 978-91-88145-72-7 (pdf) urn:nbn:se:hig:diva-35467

Distribution:

University of Gävle

Faculty of Health and Occupational Studies

Department of Occupational Health Sciences and Psychology SE-801 76 Gävle, Sweden

+46 26 64 85 00 www.hig.se

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To my beloved children, Anja and Konrad.

“Every age has its turn

Every branch of the tree has to learn Learn to grow, find its way,

Make the best of this short-lived stay Take this seed, take this spade Take this dream of a better day Take your time, build a home

Build a place where we all can belong Some things change, some remain Some will pass us unnoticed by What to focus on, to improve upon In the face of our ancient tribes Feels so clear, feels so obvious To each one on their own But we are here, together

Reaping what time and what we have sown We don't choose where we're born

We don't choose in what pocket or form But we can learn to know

Ourselves on this globe in the void Take this mind, take this pen Take this dream of a better land Take your time, build a home

Build a place where we all... can belong”

José González

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Abstract

Background: Although combinations of physical and cognitive work tasks occurs in working life (both concurrent and alternating), no one has summarized the research regarding such combinations. Very few studies have investigated the effects of alternating physical and cognitive tasks, which have been suggested as an alternative to classic job rotation. The aim with this thesis was to investigate the effects of concurrent and alternating cognitive and physical work tasks on fatigue, stress, recovery, and performance and whether the cognitive task difficulty and the temporal pattern is important in this respect.

Methods: In study I, 48 controlled studies comprising combinations of physi- cal and cognitive work tasks was summarized in a systematic review. In two controlled experiments (study II, III and IV), participants performed alterna- tions of a physical and a cognitive task. In study II and III, the difficulty levels of the cognitive task were varied between conditions, and in study IV, the tem- poral patterns and cognitive task difficulty was varied between conditions.

During work, indicators of fatigue (study II and IV), stress (study III and IV) and performance (study II and IV) was assessed.

Results: Concurrent physical and cognitive work tasks have a negative impact on biomechanical indicators, fatigue and performance, while the effect on stress seems mixed. Alternating physical and cognitive work tasks leads to some accumulated fatigue over time, with physical recovery taking place during the cognitive task. Indicators of stress did not increase over time, and nei- ther fatigue nor stress was influenced by cognitive task difficulty.

Conclusions: Concurrent physical and cognitive work should be avoided in working life and if they must be performed, employers should decrease task demands. Alternations on the other hand, could be carried out without exces- sive fatigue or stress, and with maintained performance. This thesis provides a basis for recommendations on how to properly organize job-rotation schemes.

Keywords: physical, repetitive, cognitive, mental, load, variation, job rotation, restoration, allostatic load

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Sammanfattning

Bakgrund: Kombinationer av fysiska och kognitiva arbetsuppgifter förekom- mer i många yrken (både samtidiga och alternerande), men ännu har ingen sammanfattat forskningen gällande effekterna av sådana kombinationer. Väl- digt få studier har undersökt effekterna av alternerande fysiska och kognitiva uppgifter, vilket har föreslagits som ett alternativ till klassisk jobbrotation. Syf- tet med denna avhandling var att undersöka effekten av samtidiga och alternerande fysiska och kognitiva arbetsuppgifter på trötthet, stress, återhämtning och prestation, och i vilken utsträckning som den kognitiva arbetsuppgiftens svårighetsgrad och tidsmönstret av alterneringarna har betydelse för utfallen.

Metod: I studie I sammanfattades 48 studier bestående av kombinationer av fysiska och kognitiva uppgifter i en systematisk litteraturöversikt. I två kon- trollerade experiment (Studie II, III och IV), utförde deltagare alterneringar av en fysisk och en kognitiv uppgift. I studie II och III varierades svårighetsgraden av den kognitiva uppgiften mellan betingelserna, och i studie IV varierades både svårighetsgraden och tidsmönstret av alterneringar mellan betingelserna.

Under arbetet mättes indikatorer på trötthet (studie II och IV), stress (studie III och IV) och prestation (studie II och IV).

Resultat: Samtidiga fysiska och kognitiva arbetsuppgifter har en negativ in- verkan på biomekaniska indikatorer, trötthet och prestation, medan effekten på stress är mer oklar. Alternerande fysiskt och kognitivt arbete leder till viss ack- umulerad trötthet över tid, men med fysisk återhämtning under den kognitiva uppgiften. Indikatorer på stress ökade inte över tid, och varken trötthet eller stress påverkades av den kognitiva uppgiftens svårighetsgrad.

Slutsatser: Samtidiga fysiska kognitiva uppgifter bör undvikas i arbetslivet och om de måste utföras, bör arbetsgivaren minska arbetsuppgiftens krav. Al- terneringar verkar å andra sidan kunna utföras utan större påverkan på trötthet och stress, och med bibehållen prestation. Resultaten från den här avhand- lingen kan utgöra en bas för rekommendationer om hur arbetsrotationer ska organiseras.

Nyckelord: fysisk, repetitiv, kognitiv, mental, belastning, variation, arbetsro- tation, återhämtning, allostatisk belastning

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Acknowledgements

When I started my PhD-studies, I had absolutely no idea what I was getting into. Honestly, for the first year, I was just confused. After a while, I felt a little bit less confused. Nearly six years later, I am still confused, but on a higher level. I would like to express my deepest and sincerest gratitude towards all of you who have helped me feel confused on a higher level. First, I would like to thank my main supervisor Svend Erik Mathiassen for his excellent academic leadership and emotional support in times of both success and failure. His vast knowledge in the field fascinates me every day. I also appreciate your honest ways, which have taught me to separate critique of my work from critique of myself. I am very lucky to have had one of the “rock star of Ergonomics” as my main supervisor. To my co-supervisors David Hallman and Petra Lindfors, thank you for your endless patience in supporting me along this journey. To David, you have taught me everything that is possibly worth knowing about HRV-analysis, and always supported me at times when I just wanted to give up. To Petra, for always giving me superb input on stress theory, statistical analysis and for always being ready to receive a phone call. I also wish to give a special thanks to Helena Jahncke, who was my co-supervisor during the first half of my PhD-studies. I will always consider you a professional mentor as well as a good friend.

To my fellow co-authors not mentioned above; Staffan Hygge, Charlotte Lewis, Eugene Lyskov, Kent Dimberg and Sofie Bjärntoft; thank you for your professional collaboration, input and all the work spent on revising the manu- scripts.

A special thanks to Sofie Bjärntoft who took on the job to collect data for the second experiment. Thanks to Kent Dimberg for thorough analysis of amylase- and cortisol samples. I would also like to give a special thanks to Nisse Larson for setting up the experiments, and Per Gandal for technical support during the experiments and data analysis. I could never have done this without your help! I also want to thank Patrik Sörqvist and Staffan Hygge for your valuable discussions and input on the study design regarding the cognitive task.

A special thanks to Johan Willander for helping me navigate in the cognitive- psychology field.

To research librarian Malin Almstedt Jansson – I am very grateful for your support in the planning and searching phase of the systematic literature review.

Thanks to Ylva Trolle Lagerros, my supervisor during my master thesis – you are the reason I decided to go for the PhD-track in the first place. Thank you for believing in me. I would also like to thank Emma Mårtensson. I would never have guessed that a class reunion with only three participants could have led me to this!

To my fellow PhD-colleagues, and especially those who have followed me (almost) during the entire journey; Sofie, Johanna, Monica, Linda, Mamunur, Tina, Elena and Ola. Thank you for all the emotional support! A special thanks to Monica, Sofie and Johanna for putting up with me as a roommate.

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To my other colleagues at CBF; I am very happy to be a part of a group of teacher and researchers where people genuinely care about each other. A special thanks to Jennie Jackson who has taught me so much about EMG-measurements. I also want to send a special thanks to my colleagues at the public- health department. You are truly one of the best groups of people I have ever worked with.

Of course, I would also like to thank my family and friends. To my Mom (May she rest in peace), my Dad and bonus Mom, for always encouraging me to reach for the stars. To my sisters, thank you for always being there for me.

We don’t get to choose our family members, but I would choose you a thousand times over. To my best friends Ylva, Lena, Emma, Emily, Mari and Ma- ria. Whatever you do, please don’t stop being who you are; such true friends with kind spirits and unique “quirkiness” is rare to find. You bring colors to my life.

To my husband Henrik, thank you for supporting me all the way through this journey. We have spent the last 15 years together, and I could not imagine spending the rest of my life with anyone else. You are warm, kind, smart and fun, and what I love the most about you, is that you challenge me to new ways of thinking, every day.

To my children, Anja and Konrad, thank you for reminding me of that there are things in life a thousand times more important than work. There is no greater love than the one I have for you.

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List of Papers

This thesis is based on the following papers, which are referred to in the text by Roman numerals.

Paper I

Mixter, S., Mathiassen, S E., Jahncke, H., Hygge S., Lyskov, E., Hallman, D., Lewis, C. Effects of combining physical and cognitive work tasks – a sys- tematic review. Manuscript

Paper II

Mixter, S., Mathiassen, S E., & Hallman, D.M. (2019) Alternations between physical and cognitive tasks in repetitive work – effect of cognitive task diffi- culty on fatigue development in women. Ergonomics, 62:8, 1008-1022. doi:

10.1080/00140139.2019.1614229 Paper III

Mixter, S., Mathiassen, S E., Lindfors, P., Dimberg, K., Jahncke, H., Lyskov, E. & Hallman, D.M. (2020) Stress-related responses to alternations between repetitive physical work and cognitive tasks of different difficulties. Interna- tional Journal of Environmental Research and Public Health, 17, 8509. doi:

10.3390/ijerph17228509 Paper IV

Mixter, S., Mathiassen, S E., Bjärntoft, S., Lindfors, P., Lyskov, E. & Hallman, D. Fatigue, stress and performance during alternating physical and cognitive tasks – effects of the temporal pattern of alternations. Under review

Reprints were made with permission from each publisher.

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Author contributions

Paper I: The study was designed by Svend Erik Mathiassen (SEM), Helena Jahncke (HJ), Staffan Hygge (SH), Charlotte Lewis (CL), and David Hallman (DH). HJ was mainly responsible for the electronic search. CL performed the initial screening and Eugene Lyskov (EL) and SH performed the quality screening. Susanna Mixter (SM) was mainly responsible for drafting the manuscript and all authors participated in critical revision. All authors approved the final manuscript.

Paper II: The study was designed by SEM, DH, and SM. Data was collected by SM, supervised by SEM. Statistical analysis was planned by SEM, DH, and SM. Data was analyzed by SM supervised by DH. SM was mainly responsible for drafting the manuscript and all authors participated in critical revision. All authors approved the final manuscript.

Paper III: The study was designed by SEM, DH, SM, EL, HJ, and Kent Dim- berg (KD). Data was collected by SM, supervised by SEM. Statistical analysis was planned by SEM, DH, SM, KD, and Petra Lindfors (PL). Data was analyzed by SM, and saliva samples were analyzed by KD. SM was mainly responsible for drafting the manuscript and all authors participated in critical revision. All authors approved the final manuscript.

Paper IV: The study was designed by SEM, DH, SM, and EL. Data was collected by Sofie Bjärntoft (SB). Statistical analysis was planned by SEM, SM, PL, and EL. Data were analyzed by SM, and saliva samples were analyzed by KD. SM was mainly responsible for drafting the manuscript and all authors participated in critical revision. All authors approved the final manuscript.

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Abbreviations

ANS BP CT ECG EMG HF HPA HRV MSD MVC PPT RMSSD RVC RVE sAA

Autonomic Nervous System Blood Pressure

Cognitive Task Electrocardiography Electromyography High Frequency

Hypothalamic- pituitary-adrenal Heart Rate Variability

Musculoskeletal Disorders Maximal Voluntary Contraction Pressure Pain Threshold

Root Mean Square of Successive Differences between R-R intervals

Reference Voluntary Contraction Reference Voluntary Exertion Salivary Alpha Amylase

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Introduction

In the midst of the Covid-19 pandemic, one profession that has attracted increased attention due to the heavily increased demand for testing is biomedical analysts. Biomedical analyst is a profession characterized by repetitive, low- intensive physical work tasks (i.e. pipetting) but also mental task demands (Björksten, Almby and Jansson, 1994; Fredriksson, 1995; Lintula and Nevala, 2006; Sadeghian et al., 2014; Yung and Wells, 2017). According to The Swedish Work Environment Authority (2012), such repetitive and closely controlled work should be avoided, and prevention should lead to increased variation.

Combinations of physical and mental work tasks are also common in other occupations, such as in retail, health care, and industry work (Mozrall and Drury, 1996; Sluiter et al., 2000; Thorvald, Lindblom and Andreasson, 2019).

While a substantial amount of studies have investigated to what extent simul- taneous physical and cognitive demands influence biomechanical exposure, stress, fatigue, recovery and performance; (Finsen, Søgaard and Christensen, 2001; Tomporowski, 2003; Hjortskov et al., 2004; MacDonell and Keir, 2005;

Mehta, Nussbaum and Agnew, 2012; Srinivasan, Mathiassen, et al., 2015), very few have investigated the effects of alternating physical and cognitive demands (Asmussen and Mazin, 1978; Davis et al., 2002; Stock, Beck and DeFreitas, 2011; Mathiassen et al., 2014). Alternations between physical and cognitive work tasks have been put forth as an alternative to classic job rotation, in giving more time for physical recovery and increasing variation in physical exposure (Mathiassen et al., 2014).

No previous study has aimed to systematically review studies comprising combinations of occupationally relevant physical and cognitive tasks. Further- more, it is still unknown how alternations between repetitive physical work tasks and cognitive work tasks of occupational relevance influence short-term health-related indicators.

Investigating the effects of alternations between low-intensive and physical repetitive work and mental tasks in an experimental setting has the potential to form a basis for recommendations on how to properly organize job rotations.

In a wider perspective, striving for designing jobs with a more optimal combination of physical and cognitive load, by facilitating a healthy pattern of load and recovery, is a health-promoting perspective – rather than just preventing risks.

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Background

Physical and cognitive workload

Physiological and cognitive processes inevitably interact to influence physical capabilities and performance, and therefore, these factors should be considered together when considering the work situation (Mehta, 2016).

Physical workload has been defined as “biomechanical events occurring in the body” (Winkel and Mathiassen, 1994). While the external exposure is the same for all workers with the same work tasks, for instance lifting a 10 kg box from the floor, the internal exposure differs between individuals and comprises the impact of the external load on the body (Winkel and Mathiassen, 1994).

Mental demands may for example constitute time pressure and task complex- ity, while strain refers to the resources available to cope with the mental de- mand (Young et al., 2014).

Combinations of physical and cognitive work tasks exist in a range of oc- cupations, both concurrently (performed at the same time) and alternating.

While a large body of research has investigated the acute effects of concurrent and physical load on fatigue, stress, recovery and performance (Finsen, Søgaard and Christensen, 2001; Hjortskov et al., 2004; Au and Keir, 2007;

Mehta and Agnew, 2011; Mehta, Nussbaum and Agnew, 2012; Srinivasan, Mathiassen, et al., 2015, 2016), very few have studied the effects of alternating physical and cognitive work (Asmussen and Mazin, 1978; Davis et al., 2002;

Stock, Beck and DeFreitas, 2011; Mathiassen et al., 2014). Concurrent physi- cal and cognitive load have been suggested to result in significantly altered muscle activity (Finsen, Søgaard and Christensen, 2001; Au and Keir, 2007;

Mehta, Nussbaum and Agnew, 2012), elevated stress response (Ekberg et al., 1995; Taelman et al., 2011; Wang, Szeto and Chan, 2011), and decreased per- formance (Ekberg et al., 1995; Kolish and Schaefer, 1996; Hughes, Babski- Reeves and Smith-Jackson, 2007; Mehta, Nussbaum and Agnew, 2012) than during a reference task with single physical or cognitive load.

Although combinations of physical and cognitive work tasks occur in working life, no one has systematically reviewed the effects of such combinations from an occupational relevance perspective. Earlier reviews aiming to describe the effects of such combinations have focused on the effects of acute bouts of physical exercise on cognition only, the effects of mental fatigue on physical performance, or used high-intensity tasks (Etnier et al., 1997; Tomporowski, 2003; Van Cutsem et al., 2017), which may lack occupational relevance.

Repetitive work

Although a small decrease in exposure to physical risk factors has been reported by European workers during the last 10 years, 61% of workers in the EU still perform repetitive hand and arm movements (Eurofound, 2017). Fur- thermore, in 2018, about a quarter of the Swedish working population experi- encing discomfort and pain as a result of the working conditions stated repetitive work tasks as the main reason (The Swedish Work Environment

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Authority, 2018). Repetitive and low-intensity manual work occurs in a range of occupations; including assembly work (Bosch, de Looze and van Dieën, 2007), laboratory work (Fredriksson, 1995; Buczek et al., 2013; Yung and Wells, 2017), and retail (Bonfiglioli et al., 2007).

Repetitive work has been defined as short and repeated work cycles with a small cycle-to-cycle variability often involving the upper extremity (Kilbom, 1994) and as work repeated “over and over again” (The Swedish Work Environment Authority, 2012). Repetitive work, even when performed at low levels of maximal voluntary contractions (MVC) at ˂15% has been associated with objective and subjective indicators of fatigue (Jensen et al., 1993;

Blangsted et al., 2005; Bosch, de Looze and van Dieën, 2007; de Looze, Bosch and van Dieën, 2009), and the development of musculoskeletal disorders (MSD) (van der Windt et al., 2000; C Nordander et al., 2009; de Kok et al., 2019). Although an explicit cause- and effect- relationship between low-intensive, repetitive work and MSD has not been established, several studies have suggested the “Cinderella- hypothesis” as an explanation as to why such work may result in MSD (Visser et al., 2006). Like the fairy-tale, studies show that motor unit recruitment during repetitive work will behave stereotypically, with the same low-threshold motor units being recruited at the start of work, as the last ones being “shut off” at the end (Kadefors, 1999; Lundberg et al., 1999;

Takala, 2002). Consequently, repetitive low force work sustained over a long period of time may lead to accumulated fatigue by small yet repeated tissue trauma, causing a chronic load injury over time (Cote, 2013).

Fatigue and assessment of short-term muscle fatigue In everyday language, the term fatigue commonly refers to various sensations and physiological processes such as “exhaustion” or “strain”. In occupational settings, fatigue is a common term to describe the negative effects of sustained physical and mental exposures at work (Åhsberg, 2000). From a scientific viewpoint, fatigue can refer to various aspects, such as mental or physical fatigue (Boksem and Tops, 2008; Marcora, Staiano and Manning, 2009; Enoka, 2012; Finsterer and Mahjoub, 2013).

Muscle fatigue has been defined as “a reduction in the ability of a muscle to produce force or power whether or not the task can be sustained” (Bigland- Ritchie, 1984), and its origin may be located in the working muscle, also known as peripheral fatigue, or be a function of altered supraspinal or spinal output or input, also known as central fatigue (Kent-Braun, 1999; Gandevia, 2001; Hunter, Duchateau and Enoka, 2004). Enoka and Duchateau (2008) em- phasize that the definition described by Bigland-Ritchie (1984) does not mean that muscle fatigue is the point of task failure, but rather a decrease in the force or power that develops at the start of the physical activity.

Fatigue has been pointed out as a precursor to MSD, in that yet small but repeated tissue trauma will accumulate over time and eventually cause perma- nent damage (Cote, 2013). Surface electromyography (EMG) is a common method to objectively assess local muscle fatigue during both isometric (static) and dynamic work, both in controlled, experimental studies and in real-time

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work (Cifrek et al., 2009). EMG records the myoelectric signals from the mus- cle contractions near the measurement site and provides a non-invasive, real- time method to monitor fatigue development. In recordings of EMG, a shift towards a decreased frequency and a rise in amplitude, despite constant external load, is considered a sign of fatigue (Öberg, 1995; Hägg, Luttmann and Jäger, 2000; McDonald, Mulla and Keir, 2019). Perceived fatigue is commonly assessed with ratings of fatigue, for example with Visual analog scales (VAS), or category ratio scales such as BORG CR 10 (Borg, 1998).

Work-related stress and assessment of stress

Stress can refer to a general physiological response to any demand placed on the individual (Selye, 1973; McEwen and Stellar, 1993), but according to more contemporary conceptualizations, the relationship between the type of stressor and the individual experience (e.g. appraisal of the stressor) greatly influences the stress response (Folkman et al., 1986; Goldstein and McEwen, 2002;

Goldstein, 2003).

Work-related stress is common in occupations with a combination of high work demands and a low decision latitude (i.e. “strained” work) according to the job-demands resource model (Bakker and Demerouti, 2007). In 2017, 25%

of working women and 19% of working men in Sweden reported having a job classified as “strained” (The Swedish Work Environment Authority, 2018).

Furthermore, work stress has been associated with changes in psychophysio- logical functioning (Chandola, Heraclides and Kumari, 2010), MSD (Swedish Agency for Health Technology Assessment and Assessment of Social Services., 2012), and cardiovascular disease (Chandola et al., 2008).

The term allostasis or allostatic load refers to the ability to “maintain sta- bility through change”(McEwen and Stellar, 1993). In the case of too frequent activation with limited recovery, or an inability to shut down or activate the stress response to a recurring stressor, allostatic overload will occur (McEwen, 2007). This may over time result in a maladaptive pattern of activation and recovery, resulting in “hyperactivity” of the stress regulatory systems (an inability to shut off) or “hypoactivity” (an inability to respond adequately to everyday stressors) (McEwen, 1998; McEwen and Seeman, 1999). In the experimental study in this thesis, the focus was to investigate short-term activation in regulatory systems, being relevant to stress responses occurring over a working day.

Stress can be measured using various indicators of the allostatic systems, (e.g. cardiovascular, autonomic, and Hypothalamic–pituitary–adrenal axis;

HPA-axis). Autonomic activation can be measured non-invasively using blood pressure (BP), heart rate variability (HRV)-analysis (mainly parasympathetic influences), and salivary alpha-amylase (sAA, mainly sympathetic activity).

HPA-axis activity can be measured with cortisol (Kirschbaum and Hellhammer, 1989, 1994). While cortisol has a time lag from stress exposure to reactivity, HRV and sAA change almost instantly (Nater and Rohleder, 2009; Togo and Takahashi, 2009). In addition to these biomarkers, perceived stress is an important component of the stress response that can be measured

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using ratings (e.g. Borg scales; Borg, 1998). Although there exist various other markers related to central, immune, and inflammatory systems, this was not within the scope of this study.

According to the allostatic load model, an adaptive stress response, which is necessary for adjusting to everyday stressors, is characterized by periods of both activation and adequate recovery (McEwen, 1998).

Recovery

The effort recovery-model emphasizes the role of recovery in the transition between acute load and chronic load reactions (Geurts and Sonnetag, 2006).

Accordingly, repeated exposure to physical or cognitive demands exceeding workers' capabilities, resulting in muscle fatigue or a marked increase in stress regulatory systems, could develop to more chronic load reactions if recovery is insufficient. Linden et al. (1997) defined recovery as a “post-stress rest pe- riod that provides information about the degree to which the elevation (i.e.

reactivity) in the physiological and psychological parameters being measured persists after the stressor has ended”. Hence, this theory suggests that recov- ery consists of two processes; recovery or restoration to a state of health and strength, and the result of that process (Schwarz, 2008). However, the view of recovery as a static construct, in which recovery has a clear start and end, and where the individual is either fully recovered or not, has been questioned.

Zijlstra, Cropley and Rydstedt (2014) instead conceptualized recovery as a dy- namic construct, in which the individual aims to continuously “harmonize the actual state with the required state”. With that conceptualization, recovery at work might not just be seen as an absence of load (complete passive rest), but also something which can be provided by a variety of tasks at work.

This thesis addresses recovery-related aspects occurring within the time frame of a working day, and not for longer periods. In the experimental studies in this thesis, recovery from fatigue and stress is assumed to take place during the alternations between physical and cognitive tasks, with different activation patterns taking place throughout the work bouts.

Variation in work

To avoid discomfort and MSD:s, recovery from potentially harmful exposures is seen as a crucial part. For instance, this can be done by moving activity from one part of the body to another, to achieve increased variation in biomechanical exposure. Exposure variation has been defined as “the change in exposure across time”(Mathiassen, 2006), and refers to how much and how fast expo- sure changes within a defined time frame. However, the concept does not take similarity in exposure between different work tasks into consideration, and thus, Mathiassen (2006) suggests that the term “diversity” is better suited to describe the difference in exposure variation between tasks.

In an occupational context, the problem with creating increased variation is to identify what aspects of work tasks should vary, or how much different work tasks should differ between one another to offer adequate recovery (Mathiassen, 2006; Luger et al., 2014; Santos et al., 2014; Mathiassen and

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Lewis, 2016). To increase variation in biomechanical exposure, three main strategies have been suggested; 1) to change the work station or to change the content of a single work task 2) to change the temporal time pattern of the work tasks, or 3) to enlarge the work by incorporating new work tasks, for example by job rotation (Mathiassen & Lewis 2016).

Regarding the first strategy (i.e. changes in a single work task or work sta- tion) the number of studies is scarce, and few have assessed the effects on variation in physical exposure (Mathiassen and Lewis, 2016).

Changing the temporal time pattern of the work, i.e. to add or restructure break pattern or to manipulate work cycle time, has been investigated both in controlled experimental studies (Mathiassen, 1993; Iridiastadi and Nussbaum, 2006), as well as in field studies (Dababneh, Swanson and Shell, 2001; Mclean et al., 2001; Balci and Aghazadeh, 2003). Regarding rest breaks, it has been shown that isometric (static) contractions can be sustained longer when interspersed with breaks than without breaks in controlled experimental studies (Bjorksten and Jonsson, 1977; Mathiassen, 1993).

Restructuring work breaks or manipulating work/cycle time without chang- ing the total work time has been reviewed by Luger et al. (2014) and effects regarding fatigue-related indicators seem inconclusive. However, some evidence was found to support the notion that more frequent interruptions in re- petitive work could be beneficial (Luger et al., 2014).

However, there are some issues in applying results from experimental studies aiming to change temporal variation to real-life occupational settings.

Firstly, studies have suggested that the work/rest ratio changes as the duration of work increases, in that longer work bouts needs to be followed by longer rest breaks to achieve the same recovery compared to shorter work bouts (Rohmert, 1973; Mathiassen, 1993). Konz (1998) also suggested that fatigue recovery decreases exponentially with time. Secondly, passive rest is essen- tially non-productive time, and from the employer’s viewpoint, increasing the duration of rest breaks will not be beneficial (Konz, 1998). Field studies investigating the effect of rest break patterns generally show that shorter but more frequent rest breaks might lead to a lower fatigue-response than longer but more infrequent breaks (Mclean et al., 2001; Balci and Aghazadeh, 2003, 2004), but the evidence is more scarce with regards to stress-related outcomes (Boucsein and Thum, 1997).

Job rotation

The third main strategy to increase biomechanical exposure variation is through job rotation, which involves rotating between different work tasks at regular intervals during a defined time, such as a work shift or a workweek.

Regarding studies assessing the effects of job-rotation interventions, the find- ings are ambiguous. Two recently conducted systematic reviews (Leider et al., 2015; Padula et al., 2017) investigated the effects of such programs on MSD- occurrence, MSD-risk factors, psychosocial factors, perceived job control, and work satisfaction. Padula et al. (2017) did not find that job rotation had an impact on MSD-development or factors related to it and did not reduce the exposure of risk factors, however, in some studies the job-rotation seemed to

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result in higher work satisfaction. Leider et al. (2015) also found mixed results, where one field study found positive results and one field study found negative results for MSD- complaints. In another study with the aim to reorganize work within an industry company, the intervention resulted in decreased productivity and worsened symptoms of MSD:s after the rearrangement (Christmansson, Fridén and Sollerman, 1999). Also, an introduction of job-rotation may cause increased overall biomechanical load when distributing the heavier work tasks among a larger proportion of workers (Frazer et al., 2003).

One issue with creating task diversity in real occupational settings by intro- ducing job rotation schemes is that tasks within the same workplace might be too similar, as the tasks may activate muscles in the same functional group (Wells, McFall and Dickerson, 2010). This leads back to the question of how much tasks should differ between each other to provide working rest for an- other work task. Regarding this, Wells, McFall and Dickerson (2010) empha- size a distinction between the variation in work tasks and motor variation. For instance, in a job characterized by mostly low-intensive assembly tasks, it might be difficult to combine work tasks that load different parts of the body.

Thus, the inconclusive results concerning the effects of job-rotation schemes on fatigue, MSD-complaints and well-being might not mean that increased variation in itself is a bad thing, but rather that the tasks included are not diverse enough (Mathiassen and Lewis, 2016).

Adding cognitive tasks- an alternative to classic job-rotation?

As previously mentioned, one of the issues with designing job rotation schemes to increase physical exposure variation is that the tasks included in the intervention might be too similar. One alternative to classic job rotation constitutes the alternative of alternating between a productive cognitive task and physical tasks in an otherwise (predominantly) physical work, potentially giving more time for physical recovery and providing value-added activities with the same effect as a passive break (recovery). This idea has for instance been studied by Christmansson, Fridén and Sollerman (1999), where adminis- trative work was incorporated in a job-rotation scheme for assembly workers.

Although alternations between physical and cognitive work tasks occur nat- urally in many occupational settings, surprisingly few studies have described such occupations. In one field study (Jahncke et al. 2017) with the aim to describe the occurrence of alternations between physical and mental tasks among blue-collar workers, the results showed that workers, in general, preferred to perform a mental task after a physical task, and vice versa. Of the few controlled experimental studies investigating the effects of alternating physical and cognitive tasks, a majority used high-intensity physical tasks (Asmussen and Mazin, 1978; Stock, Beck and DeFreitas, 2011). From an occupational perspective, this may not be relevant since physical work tasks in occupational settings are seldom performed to exhaustion. In contrast to concurrent physical and cognitive work, alternating physical and cognitive work has the potential to offer physical recovery. Some studies even suggest that a cognitive task in-

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terspersed between bouts of physical tasks has a more positive effect on physical recovery than if the work had been interspersed by a passive break (Asmussen and Mazin, 1978; Stock, Beck and DeFreitas, 2011).

Mathiassen et al. (2014) further tested these notions by taking the intensity of the physical task and the difficulty level of the cognitive task into consideration. In an experimental study, the aim was to determine to what extent the difficulty level of a cognitive task interspersed in between bouts of a repetitive, physical task influenced recovery from physical and psychophysical indicators of fatigue and stress. The result suggested a greater recovery during the hardest cognitive task, where Heart Rate variability (HRV) and heart rate recovered more during the breaks with the hardest cognitive task, while the other indicators of fatigue, such as electromyography (EMG) and ratings of fatigue and pain did not differ between study conditions.

In conclusion, combinations of physical and cognitive work tasks occur in many occupations, both concurrently and alternating. However, it is not fully known how these combinations, in terms of physical and cognitive task type, duration, and intensity-level influence health-related responses such as fatigue, stress, performance, and recovery. Moreover, only one previous study has investigated the influence of a cognitive task performed in between repeated bouts of an occupationally relevant physical task (Mathiassen et al., 2014).

Also, women are more often than men assigned work tasks that are characterized as more monotonous, constrained, and repetitive (Lewis and Mathiassen, 2013) and some studies also suggest that women have lower motor variability, e.g. a lack of natural variation in postures and movements while performing a repetitive task (Johansen et al., 2013; Srinivasan, Sinden, et al., 2016). There- fore, more studies of women are needed.

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Rationale for the thesis

Work characterized by physical low-intensity, repetitive work is a prevailing issue in today’s work life, leading to fatigue and chronic load injuries. In many of these occupations, cognitive task demands occur concurrently with physical demands. Swedish laws and regulations clearly state that strictly controlled and repetitive work should be avoided and that interventions should aim to increase variation, for example by job rotation. However, one problem with creating increased variation is to identify what aspects of work tasks should vary and how much they should vary to create recovery from potentially harmful physical exposures. In earlier studies addressing this issue, alternating physical and cognitive work has been suggested as a feasible alternative to classic job rotation, in providing recovery from fatigue and stress while at the same time main- taining productivity.

Although both alternating and concurrent physical and cognitive load occur in a range of occupations, it is not fully understood how these combinations of work tasks affect acute health-related outcomes such as biomechanical exposure, stress, fatigue and recovery of workers. Therefore, this thesis will be de- voted to investigating to what extent combinations of cognitive and physical work tasks affect such outcomes. In line with the allostatic load model, recovery from physical fatigue and stress is hypothesized to take place during alternations, in creating work characterized by a healthy pattern of activation and recovery.

In a longer perspective, this thesis can contribute to understanding how work tasks could be combined to not only prevent risks but also to promote worker's overall health.

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Overall and specific aims

Overall aims

The overall aim of this doctoral thesis is to investigate the effects of concurrent and alternating cognitive and physical load on fatigue, stress, recovery, and performance and whether the task difficulty and the temporal pattern is important in this respect. In a wider perspective, the purpose is to gain a better understanding of if, and how physical and cognitive work can be alternated in a way that ensures sufficient or improved recovery, and that performance in the work tasks remains or improves.

Specific aims

In paper I, the aim was to investigate how combinations of occupationally relevant physical and cognitive load affect indicators of biomechanical, physiological, and cognitive demands.

In paper II, the aim was to investigate to what extent the difficulty level of a cognitive task interspersed in between repeated bouts of a repetitive physical work task had an effected the recovery from fatigue.

In paper III, the aim was to investigate to what extent the difficulty level of a cognitive task interspersed in between bouts of a repetitive physical task effected subjective and objective indicators of stress.

In paper IV, the aim was to investigate the extent to which the time pattern of alternations between a repetitive physical task and a cognitive task has an impact on recovery from fatigue and subjective and objective indicators of stress, and whether the difficulty level of the cognitive task is important in this respect.

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Materials and Methods

Design and experimental setup

Within the scope of this doctoral thesis, one systematic literature review (Paper I) and two experimental studies have been carried out. In this document, they are referred to as Experiment I and Experiment II. Data from Experiment I form the basis of both Paper II and Paper III and data from Experiment II form the basis of Paper IV. Table 1 provides an overview of the studies included in this thesis. The two experimental studies had a full within-subject design, in which participants were exposed to different study conditions.

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Table 1. Overview of the studies included in the thesis.

*Six of the participants from Experiment I also participated in Experiment II.

Study design

Study participants

Independent variables

Dependent variables

Data collection methods Study I Systematic

literature review

Men and women in working age (between 18 and 70)

Occupationally relevant physical and cognitive work tasks.

Indicators of:

Biomechan- ics Stress Fatigue Performance Well-being

e.g. muscle activity, force, kinemat- ics, HR, HRV, ratings of fatigue and stress, endur- ance time, ratings of mood

Study II Controlled experiment

W=15 Mean age=

26.5 (4.7) Mean BMI=

23.7 (1.9)

Recruited on University Campus

Alternating pipetting and n-back with a time pattern of 7+3 min (repeated 10 times. Three difficulty levels of n-back.

Fatigue Performance

- EMG amplitude, RVC% during work -Pressure pain threshold - Perceived fatigue and pain - Pre-and post- differences in MVC - Correct and false positive answers in cognitive task Study

III

Controlled experiment

Same as study II

Alternating pipetting and n-back with a time pattern of 7+3 min (repeated 10 times. Three difficulty levels of n-back.

Stress

- ECG, HR and HRV-indices during work

- Systolic and diastolic BP - Salivary alpha- amylase (sAA) and cortisol

Study IV

Controlled experiment

*W= 15 Mean age=

24.8 (4.0) Mean BMI=

23.1 (2.9)

Recruited on University Campus

Alternating pipetting and n-back with a time pattern of 7+3 min or 14 + 6 min (repeated 10 or 5 times). Two difficulty levels of n-back.

Fatigue Stress Performance

- EMG amplitude, RVC% during work - Pre-and post- differences in MVC - ECG, HR and HRV-indices during work

- Systolic and diastolic BP - Salivary alpha- amylase (sAA) - Perceived fatigue, pain and stress - Correct and false positive answers in cognitive task

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Study Setup; Experiment I

In experiment I, the participants visited the lab on four occasions; a one-hour practice session on a separate day, and three experiment sessions, each interspersed by 3 to 7 days (to minimize carry-over effects from fatigue). Each experiment session consisted of a pre-test battery, a work period, and a post-test battery (see figure 1 for details). The work period consisted of a physical task (pipetting) (see section “physical task”) alternated with a cognitive task (CT) (see section “cognitive task”) in either of three different difficulty levels; easy, moderate or difficult. In all three difficulty levels, participants performed pipetting for 7 minutes, followed by a 3-minute CT. The work bouts of pipetting and CT were repeated 10 times, giving a total of approximately 110 minutes, including breaks for fatigue- and pain ratings. The order of the CT difficulty levels was randomized across participants, and each participant (with two ex- ceptions) visited the lab in either the morning or the afternoon, according to their preference.

Study setup; Experiment II

In Experiment II, the participants visited the lab on five occasions; a one-hour practice session on a separate day, and four experiment sessions, each interspersed by 3 to 7 days (to minimize carry-over effects from fatigue). In study condition I and II, the work period consisted of pipetting alternated with a CT in either of two difficulty levels: easy or difficult. Participants performed pipetting for 14 minutes followed by a CT for 6 minutes, repeated 5 times. In study condition III and IV participants performed pipetting for 7 minutes followed by a CT for 3 minutes, with either of two CT difficulty levels: easy or difficult. The total time of physical and cognitive work was the same across all study conditions (approximately 110 minutes including RPE-ratings). For details, see figure 2. As in experiment I, the order of the study conditions was randomized across participants.

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Figure 1. Figure illustrates time chart in Experiment I.

Figure 2. Figure 2 illustrates the time chart in Experiment II.

Physical task

The physical task was the same across both experiments and all study conditions. At a simulated workstation (figure 3), participants performed pipetting, a task previously used in studies assessing motor variability during repetitive work tasks (Srinivasan, Mathiassen, et al., 2015; Sandlund et al., 2017) as a

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model for repetitive and submaximal work tasks. The physical pipetting task consisted of repeatedly aspiring liquid from a pickup tube (Ø 20 mm) and de- livering it to one of four target tubes (Ø 6 mm) in an array of 10x10 tubes at a cycle time of 2.8 s paced by a metronome (see figure 3). The pace corresponds to 100MTM (Methods-Time Measurement; (Maynard, Stegemerten and Schwab, 1948), a standard work pace in industry. Led lamps signaled where the liquid was to be dispensed in a standardized clockwise sequence, moving between the four tubes.

Participants were seated in a rigid chair with a knee angle of 90 degrees, and with the table height fixed at elbow height. The distance between the table and the chair was set by instructing the participant to hold their right arm out, and the chair was then fixed in position when the participant’s ulna styloid process was above the pickup tube. To prevent the participant from leaning forward, their torso was strapped to the chair.

Figure 3. The array of target- and pickup tubes. The liquid was aspired from tube A and dispensed in one of the small tubes (B).

Cognitive task

A standardized cognitive task engaging the working memory, the n-back task (Kane et al., 2007) was used in both experiments. Participants were seated in front of a computer screen and were presented with individual letters (one of seven consonants) in black font for 2000 ms, followed by a white screen for 500 ms, after which a new letter was shown. There were three difficulty levels:

easy (1-back, CT1) moderate (2-back, CT2), and difficult (3-back, CT3), of which all three were included in experiment I, and the easy and difficult levels were included in experiment II. CT1 was used as a control condition, thought to be very easy to accomplish, yet requiring focus. The participants were instructed to press a button when the presented consonant was the same as the one presented one step back (1-back), two steps back (2-back), or three steps back (CT3), respectively. To avoid biomechanical strain on the right body side, the participant pressed the button with her left hand. Performance was assessed

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by the number of correct positive answers, false positive answers (if the button was pressed when there was, in fact, no match), and response time.

Participants

A total of 24 women were recruited to participate in the two experimental studies (table 1). Six of the participants participated in both Experiment I and II, giving a total of 15 participants in each study. Inclusion criteria for participat- ing was to be a woman in the age range of 20-50 years, right-handed, and to have previous experience in pipetting. Exclusion criteria were as follows: preg- nancy: previous trauma to the neck or back: chronic diseases or pain. Partici- pants were recruited by announcements on Gävle University Campus and the criteria for inclusion was checked during telephone contact. All of the included women had a BMI ≤30, which has previously been shown as a factor affecting the measurement of muscle activity with surface EMG (Nordander et al., 2003).

Methods

Paper I (Systematic literature review)

For the systematic literature review, two electronic database searches in Sco- pus, Cinahl, PsychInfo and PubMed were conducted, the first in early 2016 and the second one in August 2019. In close collaboration with an information search specialist, a search string was developed to fit the inclusion and exclusion criteria. After pilot searches, Scopus was chosen as the main database.

The inclusion criteria for screening of titles and abstracts included all controlled studies with controlled combinations of physical and/or cognitive tasks, with no restrictions as to if the physical or the cognitive task is primary, and to include both studies that address alternations between and those who address combinations of physical and cognitive tasks. Exclusion criteria was studies of animals, children (≤18), and people of older age (≥70) since these groups are not represented in working life. Studies with an obvious non-healthy popula- tion, studies with extreme working conditions or tasks (e.g. heat or cold stress), studies with maximum or near to maximum exertions, and non-defined cognitive work tasks were also excluded.

In step I, records were screened for the inclusion criteria. This step was conducted by the same researcher (CL) in both 2016 and 2019. In step II, two other researchers in the team (SH and EL) screened the remaining articles for quality. In parallel with, but independent of this process, full texts articles were relevance screened by two other researchers (SM and SEM) in the team in both waves.

Experiment I and II; Practice session

During the one-hour practice session, participants received verbal and written information about the study and signed an informed consent. The participants

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answered the following questionnaires: Edinburgh inventory (hand domi- nance) (Oldfield, 1971), a standardized Nordic questionnaire for the analysis of musculoskeletal symptoms (Kuorinka et al., 1987), and the stress-energy questionnaire (Arbetslivsinstitutet, 2002).

To demonstrate sufficient pipetting proficiency, the participant had to perform at least 70 cycles of pipetting without mistakes (about half of a 7-minute work bout), a criterion also used in previous studies (Srinivasan, Mathiassen, et al., 2016). All participants met this requirement for pipetting skills. Partici- pants also performed a 10-minute practice session at each of the three n-back difficulty levels. Also, participants performed practice sessions of the maximal voluntary contractions (MVC) appearing during the experimental sessions.

The same procedure for practice sessions was used in both experiments.

Experiment I and II; Pre- and post-test battery

To assess baseline levels of stress before each experimental session, participants were asked to rate their stress- and energy levels during the last 10 minutes with the stress-energy questionnaire (Arbetslivsinstitutet, 2002). Par- ticipants also rated fatigue, pain, and stress according to the Borg CR-10 scale (Borg 1998) and different dimensions of fatigue with the Swedish Occupa- tional Fatigue Inventory (SOFI) (Ahsberg 2000). For detailed time points of ratings, see figure 1 and 2).

After electrodes had been applied, participants started with a 5-minute baseline rest. Participants was instructed to rest quietly in their chair for five minutes. After the baseline rest, participants performed a 5-minute practice session of the cognitive task. After the baseline rest, participants performed Reference Voluntary Contractions (RVC) and Maximal Voluntary Contrac- tions (MVC) for the right and left trapezius and the right forearm extensors.

For the trapezius RVC, participants were instructed to hold their arms straight at the frontal plane in 90 degrees abduction with palms facing down and to do so with a time pattern of 2 ×15 sec interspersed by 30-sec rest, and then one RVC for 60 sec. For the trapezius MVC, participants were seated in a rigid chair with handles on each side, which were connected to chains at- tached to a dynamometer. The participants was instructed to grab the handles with straight arms and torso, and thereafter perform a maximal vertical lift. The time pattern of the MVC was 3×5 sec, each interspersed by a 60-sec break.

For the right forearm extensors MVC, the participants were instructed to grab a handgrip placed at the table at elbow height, and to exert a maximal force with the same time pattern as for the trapezius MVC. For the right forearm extensors RVC, the participants was instructed to grab the handgrip and to exert a force corresponding to 15% of the MVC (the value that was obtained during the MVC for the forearm extensors). The participants received visual feedback from a computer screen during the RVC. The time pattern was similar to the trapezius RVC.

Pressure pain threshold (PPT) for the upper trapezius muscle was obtained by an algometer (Somedic Production AB, Sollentuna, Sweden). The examiner applied pressure on the upper trapezius muscle 3 times at each side, alternating between right and left. The pressure was increased from zero by app

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50 kPa/sec, and the participants were instructed to press a button when the pressure turned into a pain sensation. The PPT-value was expressed as the mean for each side (right and left trapezius).

Systolic and diastolic arterial blood pressure was measured at time points given in figure1 and 2 with a non-invasive, automatic blood pressure monitor (Boso Medicus, Sohn Gmbh, Germany).

After the 10 work bouts, ratings on the Borg CR10-scale and the SOFI- scale, BP-measurements, MVC, and PPT-measurements were repeated. Only the long RVC (60 sec) was repeated during the post-test battery.

The pre-and post-test battery included the same measures in both experiments, with one exception; PPT was not measured in experiment II.

Experiment I and II; Work bouts of physical and cognitive task Electromyography (EMG)

Throughout experiments I & II, electromyography (EMG) was used to assess objective fatigue-development. Surface- EMG was measured in the right upper trapezius muscle and the forearm extensors on the right arm, both of which are muscle sites commonly associated with occupationally-related musculoskeletal pain and discomfort (Swedish Agency for Health Technology Assessment and Assessment of Social Services., 2012). Before electrodes were applied, the skin area was prepared by shaving, gentle rubbing with abrasive paper, and applying of alcohol. On the upper trapezius muscle, a pair of self-adhesive electrodes were placed lateral to the midpoint between vertebrae C7 and acro- mion with a 20 mm inter-electrode distance (Mathiassen, Winkel and Hägg, 1995). For the forearm extensors, an electrode pair was placed at a 20 mm inter-electrode distance on the muscle belly, at 1/3 of the distance between the elbow and the hand (Nordander et al., 2004).

The EMG signal was sampled at 2000 Hz using customary software (Platon version 8.1), amplified (Noraxon MyoSystem 1400A), and band-pass filtered at 10-1000 Hz. Post-sampling, the data file was imported to Spike (Spike 2, Cambridge Electronic Design, Cambridge, UK, 2015), filtered using a Finite Impulse Response (FIR) high pass filter with a cutoff frequency at 35 Hz to remove contamination from electrocardiographic signals, and visually in- spected for obvious artefacts. Thereafter, the signal was root mean square (RMS) converted in consecutive 250 ms windows. The EMG RMS value was then normalized by the mean EMG amplitude during the RVC in the pre-test battery and expressed in percent of this reference voluntary contraction, i.e.

%RVC.

Electrocardiography (ECG)

Throughout experiment I & II, Electrocardiography (ECG) was used to assess the development of heart rate and Heart rate variability (HRV). ECG was rec- orded from the thorax derivation (midaxillary sixth left rib – distal end of ster- num) using a 0.5-200 Hz bandpass filter and a 2000 Hz sampling rate. ECG- data were sampled with Platon (in-house developed software) and amplified

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with Noraxon (MyoSystem 1400A). After sampling, each data file was imported to Spike (Spike 2, Cambridge Electronics 2015) for further data analysis. After visual inspection of the signal, obvious artefacts were removed and R-R intervals were identified by using a custom script.

According to previous recommendations, (Malik et al., 1996), R-R interva- lograms were further analyzed in the time and frequency domain. The HRV- indices RMSSD (root mean square of the successive differences between R-R intervals) and HF (high-frequency spectral power, 0.15-0.4 Hz) was deter- mined in the time and frequency domain, respectively.

The Fast Fourier Transform was used to assess the power spectral density of HRV, and consecutive, overlapping 2-min windows were used to obtain R- R intervals and HRV-indices.

Salivary A-amylase (sAA) and Cortisol

To assess objective indicators of stress-related physiological activity, saliva samples were collected and analyzed for concentrations of cortisol and sAA in both waves of experiments. Both cortisol and sAA were used since they repre- sent different aspects of stress responses (Skoluda et al., 2015). While cortisol has been extensively used for decades as a marker of HPA-axis activity (Kirschbaum & Hellhammer 1994; Kirschbaum & Hellhammer 1989), sAA has later emerged as a reliable marker of sympathetic nervous activation (Nater and Rohleder, 2009; Rohleder and Nater, 2009).

To minimize measurement errors in saliva sampling, participants were instructed to avoid intensive physical activity 24 hours prior to each experiment and to avoid intake of food and fluids (including water) up to 30 minutes prior to each experiment session.

In experiment I, saliva samples were collected on 5 occasions in each study session (figure 1) and on one occasion during the training day. The study participant was instructed to chew on a cotton swab (Salivette®, Sarstedt Landskrona) for 60 seconds, a procedure used in previous studies (Rohleder &

Nater 2009; Wilde et al. 2013; Kirschbaum & Hellhammer 1994). Since the saliva glands are located at several areas in the mouth, the participant was instructed to move the swab around in the mouth while chewing. For the study participants’ comfort, they were offered water to drink immediately after each saliva sample. Thereafter, the cotton swabs were frozen at a temperature of - 18 ºC.

Determination of sAA activity in saliva was performed using the method by Pointe Scientific, Inc. (Liquid Amylase, CNPG3 reagent set) developed for the determination of s-amylase activity in human serum. Thawed saliva samples was centrifuged for 2 min at 1000 x g at room temperature. The superna- tant was diluted 1:50 in distilled water and ten microliters sample was used for duplicate analyses. Enzyme activity was measured by following the increase in absorbance in the assay medium at 405 nm for 3 min at 37 ºC. Blank reaction was measured by using distilled water (10 µl) as sample. sAA- activity was calculated according to the method by Pointe Scientific Inc. and expressed as units per ml saliva (U/ml saliva).

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For cortisol analyses, 40 µl of centrifuged saliva from the same sample for alpha-amylase determination was used for duplicate measurements. Free salivary cortisol was analyzed by using an enzyme immunoassay kit (Cortisol Sa- liva ELISA, SE 120038) manufactured by Sigma-Aldrich. Concentration of cortisol was expressed as ng cortisol/ml saliva.

In experiment II, saliva samples were collected at three occasions in each study session (figure 1 and 2) and on one occasion during the training day.

Saliva samples during experiment II were collected with a passive drooling technique (Rohleder & Nater 2009; Nagy et al. 2015). This technique has several advantages as compared to absorbent device technique since the saliva production is not stimulated and the whole content of saliva that pools on the floor of the mouth rather than localized produced saliva is collected. (Nagy et al., 2015). Also, it generates a reference value for whole saliva produced during one minute and takes the degree of saliva-dilution into account (Rohleder and Nater, 2009). The participant was instructed to swallow, and then to allow the saliva to pool passively in their mouth for one minute. There- after, they spit in a plastic cup and repeated the process to pool for one minute and spit once again. The plastic cup was weighed without and with saliva and the volume of saliva was calculated. The examiner used a disposable pipette to mix and collect the saliva, which was dispensed into small plastic tubes. Im- mediately after each study session, the saliva samples were frozen at a temperature of -18 ºC.

Determination of alpha-amylase activity in saliva was performed using the method by Pointe Scientific, Inc. (Liquid Amylase, CNPG3 reagent set) developed for determination of amylase activity in human serum. Thawed saliva samples was centrifuged for 2 min at 1000 x g at room temperature. The su- pernatant was diluted 1:50 in distilled water and ten microliters sample was used for duplicate analyses. Enzyme activity was measured by following the increase in absorbance in the assay medium at 405 nm for 3 min at 37 ºC.

Blank reaction was measured by using distilled water (10 µl) as sample. sAA- activity was calculated according to the method by Pointe Scientific Inc. and expressed as units per ml saliva (U/ml saliva). Two other values were also calculated for further use: saliva/minute and alpha-amylase U/min.

For cortisol analyses, 25 µl of centrifuged saliva from the same sample for alpha-amylase determination was used for duplicate measurements. Free salivary cortisol was analyzed by using an enzyme immunoassay kit (Cortisol Sa- liva ELISA, SE 120038) manufactured by Salimetrics. Concentration of cortisol was expressed as ng cortisol/ml saliva. One other value, ng cortisol U/min, was also calculated for further use.

Fatigue- and pain ratings

During the last minute of pipetting work bouts and after each CT-work bout, participants were asked to rate the following on the Borg CR-10 scale (Borg, 1990, 1998); mental fatigue, fatigue in right shoulder, pain in right shoulder, fatigue in right lower arm, pain in right lower arm, stress and perceived men- tal effort (mental effort was only rated after the CT- work bouts). The partici- pant expressed the rating verbally and the value was noted by the examiner.

Combining cognitive and physical work tasks

Susanna Mixter

Combining cognitive and physical work tasks

Short-term effects on fatigue, stress, performance and recovery

Abstract

Sammanfattning

Acknowledgements

List of Papers

Author contributions

Abbreviations

Table of Contents

Introduction

Background

Rationale for the thesis

Overall and specific aims

Materials and Methods