Bulletin

Bulletin vol. 34 no. 1 | 7 incorrectly. However, validity indicators, online video surveillance, and anthropometric identifiers can be included to minimize these concerns (Bilder, 2011). For example, algorithms can be implemented that allow for item-level response monitoring and automated consistency checks. Further, neuroinformatics algorithms are available that will allow for detection of outlying response patterns of uncertain validity (Feenstra et al., 2017; Jagaroo, 2009; Parsons, 2016). Potential of function-led assessments Burgess and colleagues (2006) suggest that neuropsychological assessments be developed to represent real-world "functions" and proffer results that are "generalizable" for prediction of the functional performance across a range of situations. This "function-led approach" to creating neuropsychological assessments would include neuropsychological models that proceed from directly observable everyday behaviors backward to examine the ways in which a sequence of actions leads to a given behavior in normal functioning; and the ways in which that behavior might become disrupted. A new generation of neuropsychological tests should be developed that are "function led" rather than purely "construct driven." These neuropsychological assessments should meet the usual standards of reliability, but discussions of validity should include both sensitivity to brain dysfunction and generalizability to real-world function. Virtual environments offer a potential approach to developing function-led measures (Parsons et al., 2017). Virtual environments (VE) are increasingly considered as potential aids in enhancing the ecological validity of neuropsychological assessments (Parsey and Schmitter-Edgecombe, 2013; Parsons, 2015). VEs represent a special case of computerized neuropsychological assessment devices as they have enhanced computational capacities for administration efficiency, stimulus presentation, automated logging of responses, and data analytic processing. Since VEs allow for precise presentation and control of dynamic perceptual stimuli, they can provide ecologically valid assessments that combine the veridical control and rigor of laboratory measures with a verisimilitude that reflects real life situations (Bohil et al., 2011). Additionally, the enhanced computation power allows for increased accuracy in the recording of neurobehavioral responses in a perceptual environmental that systematically presents complex stimuli. Such simulation technology appears to be distinctively suited for the development of ecologically valid environments, in which three-dimensional objects are presented in a consistent and precise manner. VE-based assessments can provide a balance between naturalistic observation (e.g., capturing behaviors in a virtual classroom during testing) and the need for exacting control over key variables (i.e., systematically manipulating the classroom demands). These immersive virtual environments offer enhanced measures because traditional neuropsychological tests are limited by sterile testing environments that fail to replicate the distractions, stressors, and/or demands found in the real world. Virtual environments allow for precise control over stimulus parameters and the ability to adjust the potency or frequency of stimuli. With traditional assessments (paper-and-pencil and computer automated), the clinical neuropsychologist may not receive a clear picture of the client's ability to perform everyday activities. While many cognitive tests do give some insight into the client's everyday performance, they do not provide direct knowledge about shortcomings in the functional capabilities of the client, which limits the accuracy and utility of the clinical neuropsychologist's recommendations (Chaytor & Schmitter- Edgecombe, 2003). Virtual environments offer a platform for shifting from tests that lack criterion validity to direct observation of behavior in real world scenarios that will offer clinical neuropsychologists enhanced information for determining categorical, sequential, and hierarchical performance indicators. Speech (and language) recognition Improvements in the ability of automated systems to recognize spoken language will dramatically affect the ways in which technology may be integrated into cognitive and behavioral assessment. At present, the process approach requires a human examiner to assess speech fluency, prosody, rate, verbally expressed thought content and thought process, etc. Advances in speech and language recognition will eventually make it possible to assess a full range of cognitive and affective functions using

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