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Aging, Neuropsychology, and Cognition
A Journal on Normal and Dysfunctional Development
Volume 16, 2009 - Issue 4
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Original Articles

Can Computer Familiarity Regulate the Benefits of Computer-based Memory Training in Normal Aging? A Study with an Italian Sample of Older Adults

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Pages 401-418 | Received 13 Dec 2007, Accepted 12 Dec 2008, Published online: 21 Jun 2009
 

ABSTRACT

In this study, we investigated whether computer familiarity could regulate the efficacy of a computer-based memory training intervention in an Italian sample of older adults. Participants were randomly assigned to either the training or the waiting-list control group and were tested on four computerized neuropsychological memory tasks and one paper-pencil task. Computer familiarity measures included a computer questionnaire, reaction times in a pointing task and mouse use ability. Only the training group was taught and practised two memory strategies on three computerized neuropsychological tasks during three training sessions. Compared to the waiting-list control group, participants in the training condition showed significant benefits after the intervention in the practiced tasks and they generalized training effects to the transfer tasks. Furthermore, no link resulted between computer familiarity and memory benefits. These findings support the application of the computer-based memory training with older adults, independently of them being computer users or not.

Notes

1Note that we used exercises taken from the TNP but we modified the items: figures and words. Indeed we selected new figures and we proceed presenting them to two independent judges in order to exclude that them were unclear and difficult to distinguish. Regarding the new words, they were taken from CitationPaivio, Yuille, and Madigan's (1968) word norms, balancing imagery, concreteness and frequency of use. The Pearson's correlation coefficient among practiced tasks was .87 between the recognition of words-list and the recognition of figures-list, .83 between the recognition of words-list and the face-name learning and .84 between the recognition of figures-list and face-name learning, respectively, whereas it was .29 between the two transfer tasks. Furthermore, the Cronbach α coefficient among practiced tasks was .94, whereas between transfer tasks it was .40.

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