Perspectives, satisfaction, self-efficacy, and barriers to aerobic exercise reported by individuals with chronic stroke in a developing country

Aguiar, Larissa Tavares; Nadeau, Sylvie; Teixeira-Salmela, Luci Fuscaldi; Reis, Maria Teresa; Peniche, Paula da Cruz; Faria, Christina Danielli Coelho de Morais

doi:10.1080/09638288.2020.1855260

Cited by 8 publications

(6 citation statements)

References 23 publications

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“…Fear of falling in acute stroke was associated with physical inactivity 1 year after stroke. This is in line with a recent publication ( 31 ), in which fear of falling was considered to be a barrier to aerobic exercise in individuals with chronic stroke in a developing country ( 31 ). Previous studies have shown a difference between women and men with regard to fear of falling, and how fear of falling associates with the risk of falling ( 14 , 32 , 33 ).…”

Section: Discussionsupporting

confidence: 91%

Physical inactivity after stroke: Incidence and early predictors based on 190 individuals in a 1-year follow-up of the Fall Study of Gothenburg

Botö¹,

Buvarp²,

Hansson³

et al. 2021

J Rehabil Med

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Objective To determine the incidence of physical inactivity and factors prior to stroke and in acute stroke that are associated with physical inactivity 1 year after stroke Design Prospective longitudinal cohort Patients A total of 190 consecutively included individuals with acute stroke Methods A follow-up questionnaire, relating to physical activity level using the Saltin-Grimby Physical Activity Scale, was sent to participants in the Fall Study of Gothenburg 1 year after stroke. Predictors of physical inactivity at baseline were identified using univariable and multivariable logistic regression analyses. Results Physical inactivity 1 year after stroke was reported by 70 (37%) of the 190 patients who answered the questionnaire and was associated with physical inactivity before the stroke, odds ratio (OR) 4.07 (95% confidence interval (95% CI) 1.69–9.80, p = 0.002); stroke severity (assessed by National Institutes of Health Stroke Scale (NIHSS), score 1–4), OR 2.65 (95% CI) 1.04–6.80, p = 0.042) and fear of falling in acute stroke, OR 2.37 (95% CI 1.01–5.60, p = 0.048). Conclusion Almost 4 in 10 participants reported physical inactivity 1 year after stroke. Physical inactivity before the stroke, stroke severity and fear of falling in acute stroke are the 3 main factors that predict physical inactivity 1 year after stroke. LAY ABSTRACT After a stroke, there is a risk of becoming physically inactive, which could affect one’s health. In order to create a rehabilitation plan with individualized preventive actions and interventions against physical inactivity, it is important, early after stroke onset, to identify patients who are at risk of becoming physically inactive. Previous studies of the early prediction of physical inactivity are few in number, with small sample sizes. This research on 190 individuals describes which factors prior to and in acute stroke (which is the first week after stroke) are associated with physical inactivity 1 year after stroke. The results showed that physical inactivity before stroke, stroke severity, and a fear of falling in acute stroke are associated with physical inactivity 1 year after stroke.

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Section: Discussionsupporting

confidence: 91%

Physical inactivity after stroke: Incidence and early predictors based on 190 individuals in a 1-year follow-up of the Fall Study of Gothenburg

Botö¹,

Buvarp²,

Hansson³

et al. 2021

J Rehabil Med

View full text Add to dashboard Cite

show abstract

“…These results reinforce the recent literature that indicated that barriers to PA are likely to be critical factors in the regular practice of PA and its maintenance over time [37]. Several authors have focused on the presence of perceived barriers to PA [8,49,50] or to exercise [51][52][53] in post-stroke participants. However, none of them studied their association with objectively measured PA and SB.…”

Section: Discussionsupporting

confidence: 87%

Association of Barriers, Fear of Falling and Fatigue with Objectively Measured Physical Activity and Sedentary Behavior in Chronic Stroke

Sánchez-Sánchez

Arnal‐Gómez

Cortés‐Amador

et al. 2021

JCM

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Understanding the fostering factors of physical activity (PA) and sedentary behavior (SB) in post-stroke chronic survivors is critical to address preventive and health interventions. This cross-sectional study aimed to analyze the association of barriers to PA, fear of falling and severity of fatigue encountered by stroke chronic survivors with device-measured PA and SB. Ambulatory community-dwelling post-stroke subjects (≥six months from stroke onset) were evaluated and answered the Barriers to Physical Activity after Stroke Scale (BAPAS), Short Falls Efficacy Scale-International (Short FES-I) and Fatigue Severity Scale (FSS). SB and PA were measured with an Actigraph GT3X+ accelerometer for ≥seven consecutive days. Stepwise multiple linear regression analysis was employed to identify factors associated with PA and SB. Fifty-seven participants (58.2 ± 11.1 years, 37 men) met the accelerometer wear–time criteria (three days, ≥eight h/day). The physical BAPAS score explained 28.7% of the variance of the prolonged sedentary time (β = 0.547; p < 0.001). Additionally, the walking speed (β = 0.452) together with physical BAPAS (β = −0.319) explained 37.9% of the moderate-to-vigorous PA time (p < 0.001). In chronic post-stroke survivors, not only the walking speed but, also, the perceived physical barriers to PA are accounted for the SB and PA. Interventions to reverse SB and to involve subjects post-stroke in higher levels of PA should consider these factors.

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“…Relevant studies have pointed out that when the body mass index reaches or exceeds 25 kg/rrf, the body shape is generally obese, and the problems and diseases caused by obesity may be significantly improved [ 27 ]. As can be seen from Table 6 , there was no significant difference in BMI between normal weight, overweight, and obese people after aerobic exercise or exercise [ 28 ]. P =0.05.…”

Section: Results and Analysismentioning

confidence: 99%

Comparative Study on the Effect of Various Aerobic Exercises on College Students’ Weight Loss Based on Deep Learning Analysis

Huang

Luo

et al. 2022

Computational Intelligence and Neuroscience

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In order to solve the problem of higher obesity rate of college students and meet the needs of college students to lose weight effectively, a comparative study on the effect of various aerobic exercises on college students’ weight loss based on in-depth learning analysis is proposed. The experiment shows that 30 subjects who voluntarily participated in the weight loss experiment and research were selected from a university, including 16 men and 14 women. It shows that aerobic exercise plays an important role in improving people’s energy metabolism. Based on the deep unsupervised learning algorithm, this paper studies the effect of a variety of aerobic exercises on college students’ weight loss. It is found that visceral fat obese people are easier to lose weight than outer skin fat obese people. With the help of aerobic exercise to lose weight, we should choose the aerobic exercise items significantly increased in EPOC during exercise recovery according to the obesity characteristics and types of different college students so that the effect of exercise weight loss is more effective.

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Perspectives, satisfaction, self-efficacy, and barriers to aerobic exercise reported by individuals with chronic stroke in a developing country

Cited by 8 publications

References 23 publications

Physical inactivity after stroke: Incidence and early predictors based on 190 individuals in a 1-year follow-up of the Fall Study of Gothenburg

Physical inactivity after stroke: Incidence and early predictors based on 190 individuals in a 1-year follow-up of the Fall Study of Gothenburg

Association of Barriers, Fear of Falling and Fatigue with Objectively Measured Physical Activity and Sedentary Behavior in Chronic Stroke

Comparative Study on the Effect of Various Aerobic Exercises on College Students’ Weight Loss Based on Deep Learning Analysis

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