Academic journal article Human Factors

Malleable Attentional Resources Theory: A New Explanation for the Effects of Mental Underload on Performance

Academic journal article Human Factors

Malleable Attentional Resources Theory: A New Explanation for the Effects of Mental Underload on Performance

Article excerpt


With the new millennium upon us, major motor manufacturers are offering new vehicle automation devices. Adaptive cruise control (ACC) has already been released, offering total longitudinal control of the vehicle (see Richardson, Barber, King, Hoare, & Cooper, 1997). Soon, lateral control devices such as active steering (AS) will take to the roads. Although automation is usually implemented with the intention of reducing workload and thereby improving performance, current evidence suggests that excessively low mental demands are actually detrimental to performance. Rather than being a consequence of out-of-the-loop behavior (Ephrath & Young, 1981; Kessel & Wickens, 1982), some believe that mental underload is in itself responsible for performance decrements (e.g., Brookhuis, 1993; Hancock & Caird, 1993). Indeed, underload is possibly of greater concern than overload, as the former is more difficult to detect (Hancock & Parasuraman, 1992; Hancock & Verwey, 1997).

Although widespread concern about mental underload exists, relatively few researchers seem to be actively involved in exploring the issue in the context of vehicle automation. However, a handful of experiments have found degraded performance when using vehicle automation, mostly in recovery from automation failure. The explanations for such results vary around expectations about the automation (Nilsson, 1995), mobilization of effort (Desmond, Hancock, & Monette, 1998), complacency (de Waard, van der Hulst, Hoedemaeker, & Brookhuis, 1999), and mental workload (Stanton, Young, & McCaulder, 1997).

Despite these few studies, the literature has so far failed to produce a coherent and parsimonious explanation of why mental under-load should be detrimental to performance. This paper uses the currently pertinent subject of vehicle automation as an applied focus for a significant theoretical proposition.

Malleable Attentional Resources Theory

The breadth of the underload problem in the literature suggests it is not limited to situations involving automation. An example is recent research at the University of Michigan's Transportation Research Institute. Participants were sometimes slower to complete in-car tasks when stationary than when driving (O. Tsimhoni, personal communication, September 14, 1999). It seemed that participants were not as efficient without the additional driving workload, even though they were trying to complete the task as quickly as they could. Thus there appears to be an underlying cognitive problem, which has not yet been satisfactorily identified, associated with underload. In an attempt to fill this gap in the literature, the current paper offers a new theory based on attentional resource theory.

Attentional resource theories make a common basic assumption about performance: If demands exceed resource capacity, performance degrades. In the original capacity model of attention, Kahneman (1973) suggested that attentional capacity was positively associated with physiological arousal. Further work since then has found that resource size may change with long-term fluctuations in mood or age (Hasher & Zacks, 1979; Humphreys & Revelle, 1984). However, most applied research on attention has implicitly assumed that the size of resource pools is fixed (see Wickens, 1984, 1992). It is posited here, though, that this limit may change in the relatively short term, depending on task circumstances. This introduces the concept of malleable attentional resource pools.

Evidence is accumulating that simply reducing demand is not necessarily a key to improving performance. It has been proposed (e.g., Young & Stanton, 1997a, 1997b, 1999a, 1999b, 2001b, 2002) that resources may actually shrink to accommodate any demand reduction, a converse of the tenet that "work expands to fill the time available. …

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