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Predicting competency in automated machine use in an acquired brain injury population using neuropsychological measures
Author(s) -
Simon F. Crowe
Publication year - 2003
Publication title -
archives of clinical neuropsychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.909
H-Index - 98
eISSN - 1873-5843
pISSN - 0887-6177
DOI - 10.1016/j.acn.2003.09.002
Subject(s) - neuropsychology , neuropsychological assessment , population , psychology , acquired brain injury , machine learning , physical medicine and rehabilitation , computer science , medicine , cognition , psychiatry , physical therapy , rehabilitation , environmental health
The purpose of the current study was to explore whether performance on standardised neuropsychological measures could predict functional ability with automated machines and services among people with an acquired brain injury (ABI). Participants were 45 individuals who met the criteria for mild, moderate or severe ABI and 15 control participants matched on demographic variables including age- and education. Each participant was required to complete a battery of neuropsychological tests, as well as performing three automated service delivery tasks: a transport automated ticketing machine, an automated teller machine (ATM) and an automated telephone service. The results showed consistently high relationship between the neuropsychological measures, both as single predictors and in combination, and level of competency with the automated machines. Automated machines are part of a relatively new phenomena in service delivery and offer an ecologically valid functional measure of performance that represents a true indication of functional disability.

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