Relationship Between Walking Capacity, Biopsychosocial Factors, Self-efficacy, and Walking Activity in Persons Poststroke

被引:85
作者
Danks, Kelly A. [1 ]
Pohlig, Ryan T. [3 ]
Roos, Margie [4 ]
Wright, Tamara R. [1 ]
Reisman, Darcy S. [1 ,2 ]
机构
[1] Univ Delaware, Dept Phys Therapy, Newark, DE USA
[2] Univ Delaware, Biomech & Movement Sci Program, Newark, DE USA
[3] Univ Delaware, Biostat Core Facil, Newark, DE USA
[4] Univ Sci Philadelphia, Dept Phys Therapy, Philadelphia, PA USA
来源
JOURNAL OF NEUROLOGIC PHYSICAL THERAPY | 2016年 / 40卷 / 04期
关键词
human movement system; physical activity; stroke; walking; FATIGUE SEVERITY SCALE; QUALITY-OF-LIFE; PARKINSONS-DISEASE; STROKE SURVIVORS; GERIATRIC DEPRESSION; PHYSICAL-ACTIVITY; BALANCE; VALIDITY; RELIABILITY; GAIT;
D O I
10.1097/NPT.0000000000000143
中图分类号
R74 [神经病学与精神病学];
学科分类号
100204 [神经病学];
摘要
Background/Purpose: Many factors appear to be related to physical activity after stroke, yet it is unclear how these factors interact and which ones might be the best predictors. Therefore, the purpose of this study was twofold: (1) to examine the relationship between walking capacity and walking activity, and (2) to investigate how biopsychosocial factors and self-efficacy relate to walking activity, above and beyond walking capacity impairment poststroke. Methods: Individuals greater than 3 months poststroke (n = 55) completed the Yesavage Geriatric Depression Scale (GDS), Fatigue Severity Scale (FSS), Modified Cumulative Illness Rating (MCIR) Scale, Walk 12, Activities-Specific Balance Confidence (ABC) Scale, Functional GaitAssessment (FGA), and oxygen consumption testing. Walking activity data were collected via a StepWatch Activity Monitor. Predictors were grouped into 3 constructs: (1) walking capacity: oxygen consumption and FGA; (2) biopsychosocial: GDS, FSS, and MCIR; (3) self-efficacy: Walk 12 and ABC. Moderated sequential regression models were used to examine what factors best predicted walking activity. Results: Walking capacity explained 35.9% (P < 0.001) of the variance in walking activity. Self-efficacy (Delta R-2 = 0.15, P < 0.001) and the interaction between the FGAxABC (Delta R-2 = 0.047, P < 0.001) significantly increased the variability explained. The FGA (beta = 0.37, P = 0.01), MCIR (Delta= -0.26, P = 0.01), and Walk 12 (beta = -0.45, P = 0.00) were each individually significantly associated with walking activity. Discussion and Conclusion: Although measures of walking capacity and self-efficacy significantly contributed to "real-world" walking activity, balance self-efficacy moderated the relationship between walking capacity and walking activity. Improving balance self-efficacy may augment walking capacity and translate to improved walking activity poststroke. Video Abstract available for more insights from the authors (see Supplemental Digital Content 1, http://links.lww.com/JNPT/A139).
引用
收藏
页码:232 / 238
页数:7
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