Movement specific reinvestment and allocation of attention by older adults during walking

L. Uiga (Corresponding Author), C. M. Capio, T. W.L. Wong, M. R. Wilson, R. S.W. Masters

Research output: Journal article publicationJournal articleAcademic researchpeer-review

14 Citations (Scopus)


Older repeat fallers have previously been shown to have a higher propensity to consciously monitor and control their movements (i.e. reinvestment) than non-fallers, yet to direct their attention equally between their limb movements and the external environment during locomotion (Wong et al. in J Am Geriatr Soc 57: 920–922, 2009). Whether increased attention to their movements is a result of falling or originates from a prior inclination to reinvest remains unclear. In order to better understand the interaction between reinvestment and attention during locomotion, this study examined the allocation of attention by older adults who had not fallen but displayed a high or low inclination for reinvestment. Twenty-eight low and twenty-eight high reinvestors were required to perform 30 walking trials. Their allocation of attention during walking was evaluated by asking tone-related attentional focus questions shortly after finishing each walking trial. High reinvestors were found to be more aware of their limb movements and less aware of the external environment. Low reinvestors, on the contrary, were more aware of the surrounding environment and less aware of their movement mechanics. Given that focusing internally to body movements has been proposed to utilise working memory capacity, the ability of high reinvestors to pick up all the environmental information necessary for successful locomotion might be compromised and requires further examination.

Original languageEnglish
Pages (from-to)421-424
Number of pages4
JournalCognitive Processing
Publication statusPublished - 1 Sep 2015
Externally publishedYes


  • Attentional focus
  • Locomotion
  • Older adults
  • Reinvestment

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Cognitive Neuroscience
  • Artificial Intelligence

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