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Effect of cognitive task complexity on dual task postural stability: a systematic review and meta-analysis.

Abubakar Tijjani SalihuChrianna BharatShapour Jaberzadeh
Published in: Experimental brain research (2022)
The dual task experimental paradigm is used to probe the attentional requirements of postural control. However, findings of dual task postural studies have been inconsistent with many studies even reporting improvement in postural stability during dual tasking and thus raising questions about cognitive involvement in postural control. A U-shaped non-linear relationship has been hypothesized between cognitive task complexity and dual task postural stability suggesting that the inconsistent results might have arisen from the use of cognitive tasks of varying complexities. To systematically review experimental studies that compared the effect of simple and complex cognitive tasks on postural stability during dual tasking, we searched seven electronic databases for relevant studies published between 1980 to September 2020. 33 studies involving a total of 1068 participants met the review's inclusion criteria, 17 of which were included in meta-analysis (healthy young adults: 15 studies, 281 participants; Stroke patients: 2 studies, 52 participants). Narrative synthesis of the findings in studies involving healthy old adults was carried out. Our result suggests that in healthy population, cognitive task complexity may not determine whether postural stability increases or decreases during dual tasking (effect of cognitive task complexity was not statistically significant; P > 0.1), and thus the U-shaped non-linear hypothesis is not supported. Rather, differential effect of dual tasking on postural stability was observed mainly based on the age of the participants and postural task challenge, implying that the involvement of cognitive resources or higher cortical functions in the control of postural stability may largely depends on these two factors.
Keyphrases
  • case control
  • young adults
  • systematic review
  • working memory
  • randomized controlled trial
  • machine learning
  • artificial intelligence
  • big data
  • adverse drug