Effects of Attentional Focus on Dual-Task Walking Performance in Older and Young Adults

Autor(es)

Campolina, Alice Brochado ; Machado, Nathalia Laisa Rodrigues ; Mazoni, Alysson Fernandes ; Andrade, Valeria ; Vaz, Daniela Virginia

• Tipo de documento: Artigo Científico
• Fonte: JOURNAL OF MOTOR BEHAVIOR; v. N/A, p. 9-pg., 2025-03-05.

Resumo

Walking, often performed automatically, allows for concurrent tasks like carrying objects, but dual-tasks can be challenging for the older adults. As previous search supports the benefits of external focus (EF) over internal focus (IF) of attention in motor tasks, this study investigated attentional effects on dual-task walking performance in young and older adults. A total of 84 healthy participants (42 young adults, 23.02 +/- 2.91 years; 42 older adults, 23.02 +/- 2.91 years) were instructed to walk while carrying a filled cup without spilling. Walking speed (comfortable, fast) and attentional focus (internal, external, none) were systematically varied. Inertial sensors captured gait speed, cadence, step duration, step length, and pelvis acceleration variability, while spillage was measured in grams. A generalized linear model with bootstrap resampling (alpha = 0.05) examined the effects of focus, walking speed, and group. Results indicated that young adults walked faster than older adults (p < 0.001), and speed decreased from single-task to dual-task (p = 0.003) and from fast walking to comfortable walking (p < 0.001). No significant effect of attentional focus was found (p >= 0.056). The interaction between focus and speed was significant only for spillage (p = 0.041), showing an unimportant difference in spillage between fast walking without focus instructions (398.85 g) and with external focus instructions (399.76 g) (p = 0.030). The interaction between focus and group was not significant (p >= 0.531). Overall, this suggests that dual task walking may not be significantly affected by attentional focus instructions. (AU)

• Processo FAPESP: 21/05823-1 - Análise avançada de dados em grande volume aplicada a políticas de Ciência e inovação
• Beneficiário: Alysson Fernandes Mazoni
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado