External Task Demands Research Articles

Towards enhanced performance: an integrated framework of emotional valence, arousal, and task demand

Extensive evaluations exist concerning the linkage between objective task demands and subsequent effects on user performance. However, the human user also experiences a range of emotions related to external task demands. Problematically, little is known about the associations between emotional valence, and arousal associated with the task demand–performance axis. In this paper, we advance a theoretical model concerning such interactive influences using three dimensions: (1) emotional valence, (2) arousal, and (3) task demand. The model evaluates the impact of these dimensions on user performance. It also identifies critical emotional user states, particularly those resulting in negative performance effects, as well as non-critical emotional states that can positively impact performance. Finally, we discuss the implications for affect-adaptive systems that can mitigate the impact of critical emotional states while leveraging the benefits of non-critical ones.

Test-retest reliability and validity of vagally-mediated heart rate variability to monitor internal training load in older adults: a within-subjects (repeated-measures) randomized study

BackgroundVagally-mediated heart rate variability (vm-HRV) shows promise as a biomarker of internal training load (ITL) during exergame-based training or motor-cognitive training in general. This study evaluated the test-retest reliability of vm-HRV during exergaming in healthy older adults (HOA) and its validity to monitor ITL.MethodsA within-subjects (repeated-measures) randomized study was conducted that included baseline assessments and 4 measurement sessions. Participants played 5 exergames at 3 standardized levels of external task demands (i.e., “easy”, “challenging”, and “excessive”) in random order for 90 s. Test-retest reliability was assessed on the basis of repeated-measures analyses of variance (ANOVA), intraclass correlation coefficients (ICC3,1), standard errors of measurement (SEM), and smallest detectable differences (SDD). Validity was determined by examining the effect of game level on vm-HRV in the ANOVA.ResultsFourty-three HOA (67.0 ± 7.0 years; 58.1% females (25 females, 18 males); body mass index = 23.7 ± 3.0 kg·m−2) were included. Mean R-R time intervals (mRR) and parasympathetic nervous system tone index (PNS-Index) exhibited mostly good to excellent relative test-retest reliability with no systematic error. Mean SEM% and SDD% were 36.4% and 100.7% for mRR, and 44.6% and 123.7% for PNS-Index, respectively. Significant differences in mRR and PNS-Index were observed between standardized levels of external task demands, with mostly large effect sizes (mean r = 0.847). These results persisted irrespective of the type of neurocognitive domain trained and when only motoric and cognitive demands were manipulated while physical intensity was kept constant. The remaining vm-HRV parameters showed inconsistent or poor reliability and validity.ConclusionOnly mRR and PNS-Index demonstrated reliable measurement and served as valid biomarkers for ITL during exergaming at a group level. Nonetheless, the presence of large SEMs hampers the detection of individual changes over time and suggests insufficient precision of these measurements at the individual level. Future research should further investigate the reliability and validity of vm-HRV with a specific focus on comparing different measurement methodologies and exercise conditions, particularly focusing on ultra-short-term HRV measurements, and investigate the potential implications (i.e., superiority to other markers of ITL or monitoring strategies?) of using vm-HRV as a biomarker of ITL.

Mental Workload Classification and Tasks Detection in Multitasking: Deep Learning Insights from EEG Study.

While the term task load (TL) refers to external task demands, the amount of work, or the number of tasks to be performed, mental workload (MWL) refers to the individual's effort, mental capacity, or cognitive resources utilized while performing a task. MWL in multitasking scenarios is often closely linked with the quantity of tasks a person is handling within a given timeframe. In this study, we challenge this hypothesis from the perspective of electroencephalography (EEG) using a deep learning approach. We conducted an EEG experiment with 50 participants performing NASA Multi-Attribute Task Battery II (MATB-II) under 4 different task load levels. We designed a convolutional neural network (CNN) to help with two distinct classification tasks. In one setting, the CNN was used to classify EEG segments based on their task load level. In another setting, the same CNN architecture was trained again to detect the presence of individual MATB-II subtasks. Results show that, while the model successfully learns to detect whether a particular subtask is active in a given segment (i.e., to differentiate between different subtasks-related EEG patterns), it struggles to differentiate between the two highest levels of task load (i.e., to distinguish MWL-related EEG patterns). We speculate that the challenge comes from two factors: first, the experiment was designed in a way that these two highest levels differed only in the quantity of work within a given timeframe; and second, the participants' effective adaptation to increased task demands, as evidenced by low error rates. Consequently, this indicates that under such conditions in multitasking, EEG may not reflect distinct enough patterns to differentiate higher levels of task load.

Context independent reductions in external processing during self-generated episodic social cognition.

Ongoing cognition supports behavioral flexibility by facilitating behavior in the moment, and through the consideration of future actions. These different modes of cognition are hypothesized to vary with the correlation between brain activity and external input, since evoked responses are reduced when cognition switches to topics unrelated to the current task. This study examined whether these reduced evoked responses change as a consequence of the task environment in which the experience emerges. We combined electroencephalography (EEG) recording with multidimensional experience sampling (MDES) to assess the electrophysiological correlates of ongoing thought in task contexts which vary on their need to maintain continuous representations of task information for satisfactory performance. We focused on an event-related potential (ERP) known as the parietal P3 that had a greater amplitude in our tasks relying on greater external attention. A principal component analysis (PCA) of the MDES data revealed four patterns of ongoing thought: off-task episodic social cognition, deliberate on-task thought, imagery, and emotion. Participants reported more off-task episodic social cognition and mental imagery under low external demands and more deliberate on-task thought under high external task demands. Importantly, the occurrence of off-task episodic social cognition was linked to similar reductions in the amplitude of the P3 regardless of external task. These data suggest the amplitude of the P3 may often be a general feature of external task-related content and suggest attentional decoupling from sensory inputs are necessary for certain types of perceptually-decoupled, self-generated thoughts.

Multitask brain network reconfiguration is inversely associated with human intelligence.

Intelligence describes the general cognitive ability level of a person. It is one of the most fundamental concepts in psychological science and is crucial for the effective adaption of behavior to varying environmental demands. Changing external task demands have been shown to induce reconfiguration of functional brain networks. However, whether neural reconfiguration between different tasks is associated with intelligence has not yet been investigated. We used functional magnetic resonance imaging data from 812 subjects to show that higher scores of general intelligence are related to less brain network reconfiguration between resting state and seven different task states as well as to network reconfiguration between tasks. This association holds for all functional brain networks except the motor system and replicates in two independent samples (n = 138 and n = 184). Our findings suggest that the intrinsic network architecture of individuals with higher intelligence scores is closer to the network architecture as required by various cognitive demands. Multitask brain network reconfiguration may, therefore, represent a neural reflection of the behavioral positive manifold - the essence of the concept of general intelligence. Finally, our results support neural efficiency theories of cognitive ability and reveal insights into human intelligence as an emergent property from a distributed multitask brain network.

Catching wandering minds with tapping fingers: neural and behavioral insights into task-unrelated cognition.

When the human mind wanders, it engages in episodes during which attention is focused on self-generated thoughts rather than on external task demands. Although the sustained attention to response task is commonly used to examine relationships between mind wandering and executive functions, limited executive resources are required for optimal task performance. In the current study, we aimed to investigate the relationship between mind wandering and executive functions more closely by employing a recently developed finger-tapping task to monitor fluctuations in attention and executive control through task performance and periodical experience sampling during concurrent functional magnetic resonance imaging (fMRI) and pupillometry. Our results show that mind wandering was preceded by increases in finger-tapping variability, which was correlated with activity in dorsal and ventral attention networks. The entropy of random finger-tapping sequences was related to activity in frontoparietal regions associated with executive control, demonstrating the suitability of this paradigm for studying executive functioning. The neural correlates of behavioral performance, pupillary dynamics, and self-reported attentional state diverged, thus indicating a dissociation between direct and indirect markers of mind wandering. Together, the investigation of these relationships at both the behavioral and neural level provided novel insights into the identification of underlying mechanisms of mind wandering.

Identification of community structure-based brain states and transitions using functional MRI

Brain function relies on a precisely coordinated and dynamic balance between the functional integration and segregation of distinct networks. Characterizing the way in which brain regions reconfigure their interactions to give rise to distinct but hidden brain states remains an open challenge. In this paper, we propose a Bayesian method for characterizing community structure-based latent brain states and showcase a novel strategy based on posterior predictive discrepancy using the latent block model to detect transitions between community structures in blood oxygen level-dependent (BOLD) time series. The set of estimated parameters in the model includes a latent label vector that assigns network nodes to communities, and also block model parameters that reflect the weighted connectivity within and between communities. Besides extensive in-silico model evaluation, we also provide empirical validation (and replication) using the Human Connectome Project (HCP) dataset of 100 healthy adults. Our results obtained through an analysis of task-fMRI data during working memory performance show appropriate lags between external task demands and change-points between brain states, with distinctive community patterns distinguishing fixation, low-demand and high-demand task conditions.

Uncovering hidden brain state dynamics that regulate performance and decision-making during cognition

Human cognition is influenced not only by external task demands but also latent mental processes and brain states that change over time. Here, we use novel Bayesian switching dynamical systems algorithm to identify hidden brain states and determine that these states are only weakly aligned with external task conditions. We compute state transition probabilities and demonstrate how dynamic transitions between hidden states allow flexible reconfiguration of functional brain circuits. Crucially, we identify latent transient brain states and dynamic functional circuits that are optimal for cognition and show that failure to engage these states in a timely manner is associated with poorer task performance and weaker decision-making dynamics. We replicate findings in a large sample (N = 122) and reveal a robust link between cognition and flexible latent brain state dynamics. Our study demonstrates the power of switching dynamical systems models for investigating hidden dynamic brain states and functional interactions underlying human cognition.

Engagement of the motor system in position monitoring: reduced distractor suppression and effects of internal representation quality on motor kinematics

The position monitoring task is a measure of divided spatial attention in which participants track the changing positions of one or more objects, attempting to represent positions with as much precision as possible. Typically precision of representations declines with each target object added to participants’ attention load. Since the motor system requires precise representations of changing target positions, we investigated whether position monitoring would be facilitated by increasing engagement of the motor system. Using motion capture, we recorded the positions of participants’ index finger during pointing responses. Participants attempted to monitor the changing positions of between one and four target discs as they moved randomly around a large projected display. After a period of disc motion, all discs disappeared and participants were prompted to report the final position of one of the targets, either by mouse click or by pointing to the final perceived position on the screen. For mouse click responses, precision declined with attentional load. For pointing responses, precision declined only up to three targets and remained at the same level for four targets, suggesting obligatory attention to all four objects for loads above two targets. Kinematic profiles for pointing responses for highest and lowest loads showed greater motor adjustments during the point, demonstrating that, like external environmental task demands, the quality of internal representations affects motor kinematics. Specifically, these adjustments reflect the difficulty of both pointing to very precisely represented locations as well as keeping representations distinct from one another.

The CEO as a key microfoundation of global strategy: Task demands, CEO origin, and the CEO's international background

Research SummaryWe explore the selection of new CEOs with international backgrounds as a key microfoundation of global strategy. Building on executive succession, upper echelons, and international business research, we argue that firms choose CEOs with international backgrounds to match their task demands. We further argue that depending on the CEO's origin from inside or outside the firm, different task demands matter. Specifically, we propose that the relationship between internal (firm‐level) task demands and the new CEO's international background is more pronounced for inside successions, whereas the relationship between external (industry‐level) task demands and the new CEO's international background is more pronounced for outside successions. An analysis of a sample of 363 CEO successions in S&P 500 firms supports our reasoning.Managerial SummaryChoosing a CEO with the “right” experience is a crucial concern for many large firms. While firms increasing seem to select new CEOs with international backgrounds, not all firms do so. In this article, we explore several factors that might influence this choice. Our results reveal that the predecessor's international background, the firm's level of internationalization, and the level of internationalization of the firm's industry influence whether a CEO with an international background is selected. Moreover, while for inside successions, the firm's level of internationalization is particularly important, for outside successions, the level of internationalization of the firm's industry is particularly important. Our findings inform those who search, select, and appoint new CEOs, including boards of directors and (executive search) consultants.

Identifying interactive effects of task demands in lifting on estimates of in vivo low back joint loads

This investigation examined interactions between the magnitude of external load, movement speed and (a)symmetry of load placement on estimates of in vivo joint loading in the lumbar spine during simulated occupational lifting. Thirty-two participants with manual materials handling experience were included in the study. Three-dimensional motion data, ground reaction forces, and activation of six bilateral trunk muscle groups were captured while participants performed lifts with two loads at two movement speeds and using two load locations. L4-L5 joint compression and shear force-time histories were estimated using an EMG-assisted musculoskeletal model of the lumbar spine. Results from this investigation provide strong evidence that known mechanical low back injury risk factors should not be viewed in isolation. Rather, injury prevention efforts need to consider the complex interactions that exist between external task demands and their combined influence on internal joint loading.

Changes in Dimensionality and Fractal Scaling Suggest Soft-Assembled Dynamics in Human EEG.

Humans are high-dimensional, complex systems consisting of many components that must coordinate in order to perform even the simplest of activities. Many behavioral studies, especially in the movement sciences, have advanced the notion of soft-assembly to describe how systems with many components coordinate to perform specific functions while also exhibiting the potential to re-structure and then perform other functions as task demands change. Consistent with this notion, within cognitive neuroscience it is increasingly accepted that the brain flexibly coordinates the networks needed to cope with changing task demands. However, evaluation of various indices of soft-assembly has so far been absent from neurophysiological research. To begin addressing this gap, we investigated task-related changes in two distinct indices of soft-assembly using the established phenomenon of EEG repetition suppression. In a repetition priming task, we assessed evidence for changes in the correlation dimension and fractal scaling exponents during stimulus-locked event-related potentials, as a function of stimulus onset and familiarity, and relative to spontaneous non-task-related activity. Consistent with predictions derived from soft-assembly, results indicated decreases in dimensionality and increases in fractal scaling exponents from resting to pre-stimulus states and following stimulus onset. However, contrary to predictions, familiarity tended to increase dimensionality estimates. Overall, the findings support the view from soft-assembly that neural dynamics should become increasingly ordered as external task demands increase, and support the broader application of soft-assembly logic in understanding human behavior and electrophysiology.

Effects of aging on prefrontal brain activation during challenging walking conditions

BackgroundDeficits in cognitive domains, in particular, those related to the prefrontal cortex, contribute to diminished walking performance in complex conditions in older age. Studies using functional near infra-red spectroscopy (fNIRS) reported inconsistent findings of brain activation age-related changes in response to increased task demands. We aimed to study the effects of aging on gait and prefrontal activation in complex walking tasks with internal and external task demands. MethodsTwenty-three healthy young adults (30.9±3.7yrs) and 20 healthy older adults (69.7±5.8yrs) participated in this study. Gait and prefrontal activation were assessed during three walking conditions: (1) usual walking, (2) dual tasking (internal task demands) and, (3) obstacle negotiation (external task demands). fNIRS measured changes in oxygenated hemoglobin concentrations in the prefrontal cortex. ResultsSeveral gait measures were worse in older compared to younger adults under all walking conditions (p<0.005). Even at the lowest level of challenge, older adults had significant increases in HbO2 levels during usual walking, relative to standing (p=0.006). Both groups showed increased activation during dual-task (p<0.002) and during obstacle negotiation (p<0.003). ConclusionsPrefrontal activation during walking is dependent on age and task properties and that older adults apparently rely more on cognitive resources even during usual walking task.

The flexible brain.

This scientific commentary refers to ‘Neural, electrophysiological and anatomical basis of brain-network variability and its characteristic changes in mental disorders’ by Zhang et al. (doi:10.1093/aww143). The vastness of the brain’s dynamic repertoire is one of the remarkable features of brain function, making it possible to adapt rapidly and efficiently to external task demands, implement novel behaviours, and switch from one task to another. Variability in the neural dynamics is, nonetheless, constrained and displays heterogeneous topography—specific regions appear more or less variable over time, both in terms of their activity time courses (Garrett et al. , 2011) and also in terms of their interactions with other brain regions (their functional connectivity). In this issue of Brain , Zhang and co-workers present a novel method for characterizing the temporal variability of a region’s functional connectivity profile [estimated from blood oxygen level-dependent (BOLD) functional MRI], relating this variability to the region’s electrophysiology (measured with electroencephalography; EEG) and to its macroscale structural connectivity (white-matter pathways), and further demonstrating its potential utility as a neural marker for mental disorders (Zhang et al. , 2016). The past decade has witnessed a burgeoning interest in the functional network architecture of the human brain. Most of these earlier studies have adopted a ‘static’ point of view, wherein functional connections between regions are characterized over long time scales, obscuring faster dynamics. More recently, however, it has become apparent that over the course of seconds to minutes, the human brain displays network-wide reconfigurations both at rest (Zalesky et al. , 2014) and during task performance (Braun et al. , 2015). These findings …

A Functional Cartography of Cognitive Systems.

One of the most remarkable features of the human brain is its ability to adapt rapidly and efficiently to external task demands. Novel and non-routine tasks, for example, are implemented faster than structural connections can be formed. The neural underpinnings of these dynamics are far from understood. Here we develop and apply novel methods in network science to quantify how patterns of functional connectivity between brain regions reconfigure as human subjects perform 64 different tasks. By applying dynamic community detection algorithms, we identify groups of brain regions that form putative functional communities, and we uncover changes in these groups across the 64-task battery. We summarize these reconfiguration patterns by quantifying the probability that two brain regions engage in the same network community (or putative functional module) across tasks. These tools enable us to demonstrate that classically defined cognitive systems—including visual, sensorimotor, auditory, default mode, fronto-parietal, cingulo-opercular and salience systems—engage dynamically in cohesive network communities across tasks. We define the network role that a cognitive system plays in these dynamics along the following two dimensions: (i) stability vs. flexibility and (ii) connected vs. isolated. The role of each system is therefore summarized by how stably that system is recruited over the 64 tasks, and how consistently that system interacts with other systems. Using this cartography, classically defined cognitive systems can be categorized as ephemeral integrators, stable loners, and anything in between. Our results provide a new conceptual framework for understanding the dynamic integration and recruitment of cognitive systems in enabling behavioral adaptability across both task and rest conditions. This work has important implications for understanding cognitive network reconfiguration during different task sets and its relationship to cognitive effort, individual variation in cognitive performance, and fatigue.

Local dynamic stability of spine muscle activation and stiffness patterns during repetitive lifting.

To facilitate stable trunk kinematics, humans must generate appropriate motor patterns to effectively control muscle force and stiffness and respond to biomechanical perturbations and/or neuromuscular control errors. Thus, it is important to understand physiological variables such as muscle force and stiffness, and how these relate to the downstream production of stable spine and trunk movements. This study was designed to assess the local dynamic stability of spine muscle activation and rotational stiffness patterns using Lyapunov analyses, and relationships to the local dynamic stability of resulting spine kinematics, during repetitive lifting and lowering at varying combinations of lifting load and rate. With an increase in the load lifted at a constant rate there was a trend for decreased local dynamic stability of spine muscle activations and the muscular contributions to spine rotational stiffness; although the only significant change was for the full state space muscle activation stability (p < 0.05). With an increase in lifting rate with a constant load there was a significant decrease in the local dynamic stability of spine muscle activations and the muscular contributions to spine rotational stiffness (p ≤ 0.001 for all measures). These novel findings suggest that the stability of motor inputs and the muscular contributions to spine rotational stiffness can be altered by external task demands (load and lifting rate), and therefore are important variables to consider when assessing the stability of the resulting kinematics.

The Neural Representation of Voluntary Task-Set Selection in Dynamic Environments.

When choosing actions, humans have to balance carefully between different task demands. On the one hand, they should perform tasks repeatedly to avoid frequent and effortful switching between different tasks. On the other hand, subjects have to retain their flexibility to adapt to changes in external task demands such as switching away from an increasingly difficult task. Here, we developed a difficulty-based choice task to investigate how subjects voluntarily select task-sets in predictably changing environments. Subjects were free to choose 1 of the 3 task-sets on a trial-by-trial basis, while the task difficulty changed dynamically over time. Subjects self-sequenced their behavior in this environment while we measured brain responses with functional magnetic resonance imaging (fMRI). Using multivariate decoding, we found that task choices were encoded in the medial prefrontal cortex (dorso-medial prefrontal cortex, dmPFC, and dorsal anterior cingulate cortex, dACC). The same regions were found to encode task difficulty, a major factor influencing choices. Importantly, the present paradigm allowed us to disentangle the neural code for task choices and task difficulty, ensuring that activation patterns in dmPFC/dACC independently encode these 2 factors. This finding provides new evidence for the importance of the dmPFC/dACC for task-selection and motivational functions in highly dynamic environments.

RSAP is pleased to announce the winning author for its Annual Best Paper Award among articles published in 2013, Stephen Carter et al, for their paper titled “Consumers' willingness to use a medication management service: The effect of medication-related worry and the social influence of the general practitioner” appearing in Volume 9, Issue 4 of the journal. The following is

Workload has been described both objectively (e.g., number of prescriptions dispensed per pharmacist) as well as subjectively (e.g., pharmacist's perception of busyness). These approaches might be missing important characteristics of pharmacist workload that have not been previously identified and measured.To measure the association of community pharmacists' workload perceptions at three levels (organization, job, and task) with job satisfaction, burnout, and perceived performance of two tasks in the medication dispensing process.A secondary data analysis was performed using cross-sectional survey data collected from Wisconsin (US) community pharmacists. Organization–related workload was measured as staffing adequacy; job-related workload was measured as general and specific job demands; task-related workload was measured as internal and external mental demands. Pharmacists' perceived task performance was assessed for patient profile review and patient consultation. The survey was administered to a random sample of 500 pharmacists who were asked to opt in if they were a community pharmacist. Descriptive statistics and correlations of study variables were determined. Two structural equation models were estimated to examine relationships between the study variables and perceived task performance.From the 224 eligible community pharmacists that agreed to participate, 165 (73.7%) usable surveys were completed and returned. Job satisfaction and job-related monitoring demands had direct positive associations with both dispensing tasks. External task demands were negatively related to perceived patient consultation performance. Indirect effects on both tasks were primarily mediated through job satisfaction, which was positively related to staffing adequacy and cognitive job demands and negatively related to volume job demands. External task demands had an additional indirect effect on perceived patient consultation performance, as it was associated with lower levels of job satisfaction and higher levels of burnout.Allowing community pharmacists to concentrate on tasks and limiting interruptions while performing these tasks are important factors in improving quality of patient care and pharmacist work life. The results have implications for strategies to improve patient safety and pharmacist performance.

Batman and Robin or Superman: How CEO/COO Duos Impact Firm Performance

The chief operating officer (COO) often represents the second in command of an organization to the CEO. Past research on the impact of CEO/COO duos on firm performance offers conflicting results both theoretically and empirically. Some suggest that duos enhance performance through information processing and TMT coordination (Hambrick & Cannella, 2004; Marcel, 2009). Others however suggest that separating the CEO from operations can be detrimental for firm outcomes (Charan & Colvin, 1999). In our paper we use the attention based view (Ocasio, 1997) to suggest that it is not so much a matter of if but when CEO/COO duos enhance performance. We argue that increased external task demands benefit from CEO/COO duos whereas increased internal task demands lead to lower outcomes from CEO/COO duos. Using data from Execucomp and Compustat we test our hypothesis and find general support for our theory.

The association of subjective workload dimensions on quality of care and pharmacist quality of work life

Workload has been described both objectively (e.g., number of prescriptions dispensed per pharmacist) as well as subjectively (e.g., pharmacist's perception of busyness). These approaches might be missing important characteristics of pharmacist workload that have not been previously identified and measured. To measure the association of community pharmacists' workload perceptions at three levels (organization, job, and task) with job satisfaction, burnout, and perceived performance of two tasks in the medication dispensing process. A secondary data analysis was performed using cross-sectional survey data collected from Wisconsin (US) community pharmacists. Organization-related workload was measured as staffing adequacy; job-related workload was measured as general and specific job demands; task-related workload was measured as internal and external mental demands. Pharmacists' perceived task performance was assessed for patient profile review and patient consultation. The survey was administered to a random sample of 500 pharmacists who were asked to opt in if they were a community pharmacist. Descriptive statistics and correlations of study variables were determined. Two structural equation models were estimated to examine relationships between the study variables and perceived task performance. From the 224 eligible community pharmacists that agreed to participate, 165 (73.7%) usable surveys were completed and returned. Job satisfaction and job-related monitoring demands had direct positive associations with both dispensing tasks. External task demands were negatively related to perceived patient consultation performance. Indirect effects on both tasks were primarily mediated through job satisfaction, which was positively related to staffing adequacy and cognitive job demands and negatively related to volume job demands. External task demands had an additional indirect effect on perceived patient consultation performance, as it was associated with lower levels of job satisfaction and higher levels of burnout. Allowing community pharmacists to concentrate on tasks and limiting interruptions while performing these tasks are important factors in improving quality of patient care and pharmacist work life. The results have implications for strategies to improve patient safety and pharmacist performance.