Spatial and temporal task characteristics as stress: A test of the dynamic adaptability theory of stress, workload, and performance

Abstract

The goal for this study was to test assertions of the dynamic adaptability theory of stress, which proposes two fundamental task dimensions, information rate (temporal properties of a task) and information structure (spatial properties of a task). The theory predicts adaptive stability across stress magnitudes, with progressive and precipitous changes in adaptive response manifesting first as increases in perceived workload and stress and then as performance failure. Information structure was manipulated by varying the number of displays to be monitored (1, 2, 4 or 8 displays). Information rate was manipulated by varying stimulus presentation rate (8, 12, 16, or 20 events/min). A signal detection task was used in which critical signals were pairs of digits that differed by 0 or 1. Performance accuracy declined and workload and stress increased as a function of increased task demand, with a precipitous decline in accuracy at the highest demand levels. However, the form of performance change as well as the pattern of relationships between speed and accuracy and between performance and workload/stress indicates that some aspects of the theory need revision. Implications of the results for the theory and for future research are discussed.

Introduction

Task induced stress is a ubiquitous phenomenon that can substantially impair an individual's performance, safety, and well-being. Theory and research on human performance under stress have tended to emphasize either the stimulus properties (e.g., temperature, vibration, noise; for recent meta-analytic reviews, see Conway et al., 2007, Hancock et al., 2007, Szalma and Hancock, 2011) or physiological mechanisms of response such as the general adaptation syndrome (Selye, 1976) or unitary arousal (Hebb, 1955). However, these single mechanism approaches proved to be insufficient to account for the relationship between stress and performance (Hockey, 1984, Hockey and Hamilton, 1983). The failure of unitary arousal theory in particular led to the development of an energetic resource perspective (Hockey, 1984, Hockey, 1997, Hockey et al., 1986) in which stress effects result from a person–environment relation that is appraised by an individual as potentially or actually exceeding his/her resources to effectively adapt to the event (Lazarus, 1999, Lazarus and Folkman, 1984).

One of these theories, the Dynamic Adaptability Theory (DAT; Hancock & Warm, 1989), was developed specifically for understanding the mechanisms underlying the effects of stress and workload on adaptive response as it relates to task performance. This theory incorporates both the stimulus and response elements of stress into a single framework, the trinity of stress (see Fig. 1). The environmental demands are represented as the input, which are the deterministic properties of the task and the immediate physical and social environment that can be specified independent of an individual's response. As most environments impose multiple demands, the input may be viewed as an external demand profile or ‘signature’ (c.f., Hockey & Hamilton, 1983). Note that for DAT ‘input’ refers to the demands imposed by the environment (including the task itself), and not only the sensory/perceptual input that is an element of most information processing theories (e.g., Wickens & Hollands, 2000). That is, ‘input’ in this model reflects each step of the information processing stream (i.e., sensory/perceptual input, the processing requirements of the task, and response options; Wickens & Hollands, 2000). In addition, use of the term ‘stress’ in Fig. 1 refers to environmental demand rather than the response of the organism (the latter is represented in the other two elements described below). The second component is adaptation, which consists of a general (nomothetic) response of the organism to the input. These responses are common to members of the species (e.g., release of stress hormones, mechanisms of arousal, appraisal and coping). Finally, the output is the response of the organism that is dependent upon the characteristics of the individual and is thus idiographic¹ (e.g., coping strategy selected, appraisal content, levels of arousal or stress hormones). Note that psychomotor response can be either adaptation (e.g., stereotypical responses) or ‘idiographic’ output (e.g., dependent on skill level).

A fundamental tenet of the dynamic adaptability model is that across a relatively wide range of stress magnitude individuals successfully adapt to the demands imposed upon them (see Fig. 2). The theory specifies three general modes of adaptive function: dynamic stability (successful adaptation to demands), dynamic instability (vulnerability to failure to effectively adapt to demands), and the transition between these two states (the dotted lines in Fig. 2). Note that the model incorporates both increases (hyperstress) and decreases (hypostress) in environmental stimulation. Inclusion of the latter accounts for the stress associated with the relative absence of stimulation or environmental demand, although to date direct evidence for such effects in non-sensory, cognitively complex tasks has been lacking.

The theory predicts adaptive stability across a wide range of environmental demand, represented as the plateau in Fig. 2. However, increase or decrease in environmental demand to more extreme levels results in instability in adaptation. As can be seen in Fig. 2, this instability is progressive, such that declines in subjective comfort (e.g., perceived stress and workload; the regions bounded by points A_C and A_Ψ in Fig. 2) begin to occur at levels of stress exposure that are lower than the levels at which performance decrements are observed (the regions bounded by points A_Ψ and A_P in Fig. 2). When the level of stress exceeds the capacity of an adaptive response (i.e., comfort, performance) the resulting range of stress input is a zone of dynamic instability in which the form of adaptation becomes unstable and less effective. For comfort these are manifested as increased perceived workload and stress, compensatory physiological response (e.g., autonomic arousal, stress hormone release) and compensatory effort (c.f. Hockey, 1997).

Note that in their original conception, Hancock and Warm (1989) regarded hyperstress as an excessive amount of stimulation (too much of something) and hypostress as an insufficient magnitude of environmental stimulation or demand. For instance, they noted that thermal stress occurs at both very high temperatures (hyperstress) and very low temperatures (hypostress). Performance impairment occurs at both extremes (Hancock et al., 2007). In contrast, they identified acoustic noise as exerting its negative effects only in the hyperstress region, as low levels of acoustic noise weakly impacts performance, although recently it has been established that this depends on duration of exposure (Szalma & Hancock, 2011).

Transition from stable to unstable psychological adaptation (A_Ψ) results in a zone of dynamic instability that manifests as a performance decrement. The outermost region is failure of physiological adaptation (A_P) which can manifest as unconsciousness (Harris, Hancock, & Harris, 2005) or the failure of the bodily mechanisms for physical adaptation, as occurs in conditions of prolonged thermal stress above 85 °F effective temperature (Hancock et al., 2007) or when there is sufficient noise intensity to cause sensory damage. The model explicitly defines psychological adaptation in terms of the individual's attentional resource capacity, and physiological adaptation is considered a homeostatic regulation mechanism. The boundaries or transition modes between the zones of adaptability may be continuous, in which case the functions shown in Fig. 2 represent thresholds of adaptive stability. However, Hancock and Warm (1989) argued that the boundaries may instead represent discontinuities or ‘catastrophe cusps’ in the transition between states of adaptation. This contrasts with the argument by Hockey, 1997, Hockey, 2003 that task-induced stress induces graceful performance degradation rather than precipitous decline.

It may seem counterintuitive to consider increases in perceived workload and stress as ‘instability’ of adaptation. Although stress and high workload are often subjectively unpleasant, they include compensatory responses that preserve behavioral and physiological adaptation (c.f., Selye, 1976). Such outcomes do not indicate manifest instability in response and they are not if the sole criterion for effective adaptation is overt performance. However, from the energetic resources perspective the effectiveness of adaptation includes its costs in terms of psychological and physiological energy (e.g., compensatory effort; Hockey, 1997). This cost is based on the assumption that biological systems seek equilibrium states of minimal energy expenditure. An increase in workload or stress therefore represents an adaptive ‘instability’ even when performance is preserved because the maintenance of the latter increases the energetic costs to the organism, and these costs can render the individual more vulnerable to performance failure as a result of depleted energetic resources. Thus, ranges of task load in which performance is maintained at the cost of compensatory effort (manifested in measures of workload and stress) are considered ‘latent performance decrements’ (Hockey, 1997).

A unique feature of the dynamic adaptability theory is that it explicitly identifies the task a person is performing as the dominant source of environmental demand, and it specifies two basic dimensions of information that constitute the task component of the broader demand signature. These dimensions are shown in Fig. 3, which is derived by rotation of Fig. 2 around the ordinate and partitioning the stress axis into its component vectors. Information structure refers to the spatial organization of a task (and its resultant meaning for the individual), and information rate refers to the temporal properties of a task. Note that each of the two task dimensions is itself composed of multiple components. For instance, the change in performance with time on task manifests as a task duration component of information rate, while the rate of events represents the pacing aspect, and stimulus duration a third component. Hence, better labels for these information components may be ‘spatial’ and ‘temporal’ dimensions (c.f., Hancock & Szalma, 2008).

Magnitudes of information structure and rate that are too low or too high induce instability in adaptation. In principle, if these dimensions could be quantified accurately then the collective demands could be represented as a vector that determines the adaptive state of the individual. Such a representation would also permit inclusion of other environmental stimuli (e.g., noise, temperature). Although the vector approach is potentially useful, it is premature to specify a general vector function for performance under stress because of the limited understanding of interactive effects of multiple sources of stress (Hancock & Szalma, 2008) and the difficulty in quantifying information processing (McBride & Schmorrow, 2005). For instance, Hancock and Warm (1989) explicitly represented the two task dimensions as non-orthogonal, but it is not yet clear how this interactivity should be represented within a vector model, or how task dimensions interact with other sources of stress and how these should be represented mathematically. These theoretical refinements require research in which these inter-relationships can be examined empirically. The present study represents one such effort.

One way in which the zones of dynamic instability may manifest in the context of task-induced stress is in the relationship between performance (behavioral response–psychological adaptation, A_Ψ) and perceived workload (comfort, A_C). Yeh and Wickens (1988) and Hancock (1996) argued that the pattern of relationships of task manipulations to performance and to perceived workload can reveal the effects of task characteristics on resource supply and demand, and the strategic allocation of resources. Yeh and Wickens (1988) defined cases in which a manipulation impairs performance and increases workload as associations, because both measures indicate an increase in resource demand. All other cases are dissociations, because only one measure indicates increased resource demand. However, Hancock differentiated between performance–workload dissociation, in which one measure indicated greater consumption of resources (lower performance or higher workload) but the other measured indicated fewer resource demands (improved performance or lower workload). Manipulations in which one measure increased or decreased while the other remained stable are insensitivities.²

Hancock (1996; see also Parasuraman & Hancock, 2001) argued that these patterns were diagnostic of different adaptive responses to demands. Hence, performance insensitivity indicates either a compensatory response (when workload increases), such that stability in performance is maintained only at the expense of greater effort; or the development of task-related skills (when workload decreases) that allow the performer to reduce resource allocation to a task while maintaining a stable level of performance. Workload insensitivities reflect either insensitivity of the performer to the quality of his/her behavioral output (when performance declines) or to a floor/ceiling effect with respect to perceived workload. When performance improves workload insensitivity may indicate that the performer has developed task-related skills so that performance requires fewer resources, but the individual has chosen to maintain his/her level of resource investment, thereby improving performance. Note that when task-related skills develop, a strategic decision by the performer determines whether there is performance insensitivity (i.e., the performer chooses to not allocate excess resources to the task) or workload insensitivity (resources are allocated to the task). Dissociations occur either because the person ‘gives up’ because they do not believe that can achieve task goals (workload and performance both decline), or because the demands are growing but the person is responding successfully so that performance is enhanced at the cost of greater workload (both measures increase).

The patterns of performance–workload relationships can be mapped to the zones of the dynamic instability shown in Fig. 2 (for a more detailed treatment see Oron-Gilad et al., 2008). Region A_N in the Figure represents the normative zone within which an individual is in their normal equilibrium state. Fluctuations of external demands within this region do not require adaptive response and therefore no change in performance or workload is observed; the self-regulation of behavior and information processing is experienced as relatively effortless and automatic. The threshold at point A_N represents the point at which changes in the magnitude of the stressor require compensatory response (at both the physiological and psychological level of analysis) to maintain stable adaptation to changing demands by allocating effort to preserve performance. However, in region A_N–A_C the individual remains within their comfort zone, so engagement of resources in response to increased demand is not appraised as stressful. In this region one would expect that increased task load would increase engagement in the task and energetic arousal (but not tense arousal; Helton et al., 2010, Matthews et al., 2002). Regions A_N and A_N–A_C correspond to the engaged mode of stress response described by Hockey, 1997, Hockey, 2003, and in region A_N–A_C this can manifest as a dissociation in which performance improves with greater allocation of effort. The individual is engaging in ‘effort without distress’ (Hockey, 1997, Hockey, 2003).

At higher magnitudes of demand more resources must be allocated to the task if performance is to be maintained. If the person is operating at or near capacity they may enter region A_C–A_Ψ, in which adaptation in terms of subjective state (comfort) becomes unstable (i.e., perceived workload and stress increase) but the person can maintain performance. This corresponds to what Hockey, 1997, Hockey, 2003 described as strain mode (‘effort with distress’) and manifests as performance insensitivity (workload and stress increase but performance is maintained). Further increase in demand leads to performance failure, as the demands exceed the resource capacity of the person to maintain performance even with increased effort (region A_Ψ–A_P). This can reflect either a strain mode with performance–workload association in which performance declines and workload increases, or to what Hockey, 1997, Hockey, 2003 referred to as a disengaged mode in which both performance and workload decrease (a dissociation) due to disengagement from the task (‘no effort with no distress’). Note that whichever of the two possible outcomes in region A_N–A_C and A_Ψ–A_P occurs is determined by whether the individual chooses to allocate more effort to task performance (Hockey, 1997).

There have been limited attempts to directly test the predictions of the Dynamic Adaptability Theory regarding changes in performance–workload relationships as a function of variation in information structure and rate. In one early attempt, Hancock and Caird (1993) adapted the theory to test a model of mental workload in which they proposed that workload increases occur when the person's perceived distance from goal achievement increases and/or when the time available for action decreases. If the former is considered a form of information structure and the latter a form of information rate, their model of workload can be viewed as a special application of the more general Dynamic Adaptability Theory. Hancock and Caird (1993) tested their model using a computer-based task in which a grid of circles was presented and participants were to mouse click on a specific sequence of circles that were decreasing in size. Goal distance was manipulated by varying the number of movements required to navigate a sequence of circles (i.e., the number of steps in the sequence), and time for action was manipulated by modulating the rate at which the circles became smaller (shrink rate). They found that increases in task demand impaired performance and increased workload in a manner consistent with their model. However, Hancock and Caird (1993) did not analyze their results in terms of the relationship between performance and mental workload to evaluate the more general Dynamic Adaptability Theory, nor did they use a multidimensional appraisal-based measure of perceived stress that includes task engagement as a component.

More recently, Oron-Gilad et al. (2008) reported performance workload relationships in a field study of police officers engaged in firearms training tasks. However, in that study the task dimensions identified in the Dynamic Adaptability Model could not be manipulated, which limited the strength of inferences regarding the pattern of effects. The goal for the present study was to evaluate the Dynamic Adaptability Theory by manipulating the task structure and rate and examining the resultant performance–workload and performance–stress relationships. Based on the model, the form of adaptation (i.e., comfort, performance) and the level of information demand should determine the adaptive state of the individual (i.e., the degree to which the person can effectively maintain comfort, performance, etc.). Stable adaptation is expected at lower levels of demand with precipitous declines in stability at higher levels of task load. Further, as explicitly noted by Hancock and Warm (1989), the two task dimensions will likely interact in influencing response as a function of demand (i.e., the two dimensions will not be orthogonal). The specific hypotheses are summarized below.

• Higher levels of information demand will be associated with instability in effective adaptation as measured by perceived workload, cognitive state (i.e., stress), and performance.

• These changes will occur progressively. Based on the nested structure shown in Fig. 2, workload and stress are expected to increase at a level of demand lower than that associated with performance change, although task engagement may also increase if the person engages compensatory resources.

• The two information dimensions will have interactive effects, such that the magnitude of changes in performance, workload, and stress as a function of information rate will be larger as the demands on the information structure dimension are increased.

• The relation of outcome measures (adaptive responses) to task demand will be curvilinear, with a precipitous change at the thresholds of adaptation. An alternative hypothesis, based on Hockey, 1997, Hockey, 2003 is that graceful degradation will be observed (i.e., a shallower slope for the degradation function).

These hypotheses were tested by manipulating the two dimensions specified by the Dynamic Adaptability Theory, and evaluating their effects on the different forms of adaptation defined in terms of outcome measures. Information structure was manipulated by varying source complexity (i.e., the number of displays to be monitored; Davies & Parasuraman, 1982), and information rate was manipulated by varying the rate of stimulus presentation. Subjective comfort was measured in terms of perceived workload and stress, and psychological adaptation was measured in terms of performance, per Hancock and Warm's (1989) original interpretation. A short duration (12 min) signal detection task was employed, in which critical signals were pairs of digits that differed by 0 or 1.