Abstract
Introduction:
While it is well known that regular physical activity provides significant physical and psychosocial health benefits, people with disabilities have disproportionately lower rates of exercise compared to the able-bodied population. Reduced levels of physical activity can put this population at an increased risk of chronic health conditions, highlighting the importance of ensuring that our communities have accessible adaptive fitness opportunities.
Objectives:
To evaluate the demographic and disability characteristics in individuals who regularly attend a specialized urban adaptive fitness center, to provide foundational understanding about the population that uses such resources.
Design:
Cross-sectional study SETTING: Specialized urban adaptive fitness center PARTICIPANTS: Sixty-three (n = 63) participants who regularly attend an urban Adaptive Sports and Fitness Center INTERVENTION: Not applicable MAIN OUTCOME MEASURE: World Health Organization (WHO) Disability Assessment Schedule (WHODAS) 2.0, evaluating disability in six domains: cognition, mobility, self-care, getting along, life activities, and participation. Results were converted into scores ranging from 0 (no disability) to 100 (total disability) and compared to WHO published norms for the general population and a demographics intake form.
Results:
Participants with mean age of 52.9 ±14.3 years were grouped into three diagnostic categories: spinal cord injury (30.2%), traumatic brain injury/stroke (36.5%), and other neurologic disease/chronic medical disease (33.3%). A total of 45.9% live alone, 96.8% exercise at least twice/week, and 43.5% participate in adaptive sports. Participants travel 8.0 miles on average for attendance. WHODAS disability summary score was 26.48 (86th percentile).
Conclusions:
Although adaptive fitness center participants had a higher level of disability than 80% to 90% of the general population, regular participation was realistic and feasible. Further understanding of the barriers in those who do not engage in such facilities is needed.
INTRODUCTION
The 2018 Physical Activity Guidelines for Americans recommend at least 150 to 300 minutes a week of moderate-intensity physical activity, 75 to 150 minutes a week of vigorous-intensity aerobic physical activity, or an equivalent combination of moderate- and vigorous-intensity aerobic activity per week.1 When compared to the general population, people with disabilities generally have lower rates of physical activity.2 For example, according to the Healthy People 2010 report, only one third of people with disabilities reported participation in leisure-time physical activity, in comparison to half of the general population.3 A greater propensity toward a sedentary lifestyle puts this population at risk for a number of preventable chronic health conditions.2, 3 Therefore, engagement of these individuals in lifelong fitness is of critical importance.4, 5
Although the benefits of exercise for individuals with disabilities are clear, research on community-based exercise interventions is limited.3 As the average lengths of stay in acute inpatient rehabilitation have decreased, there is an increased need to smoothly transition from hospital-based rehabilitation to accessible community-based physical activity.1, 6 However, access for these individuals to traditional fitness centers can be limited. One study found that beyond the Americans with Disabilities Act (ADA) mandated requirements for physical accessibility, accommodations for individuals using wheelchairs for mobility was insufficient, with only 20% providing suitable adaptive equipment and none of the facilities employing staff who were trained for the specific needs of people with disabilities.3 Another study showed that patients with neurologic disabilities found gyms unwelcoming and that the standard training of a physical trainer may not be sufficient to care for these individuals.5 In support of those findings, managers of these fitness centers perceived the hiring of specially trained staff to be the largest barrier to access for people with neurologic disabilities.3 Furthermore, although specialized adaptive equipment such as upper-body ergometers, dynamic standers, and functional electrical stimulation cycles are present in rehabilitation centers and therapy clinics, access to such equipment is rare in community fitness centers.3, 6
Prior research has evaluated barriers and facilitators of participation in adaptive sports. Barriers included self-esteem, poor finances, transportation, problems accessing information, lack of role models, and safety concerns.7, 8 Facilitators of sustained participation included social support, self-efficacy, improved fitness, and increased positive affect.7, 8 Another study found that individuals living in proximity to the program site and having moderate functional impairment, such as using assistive device for ambulating, were more likely to have sustained participation in community-based adaptive sports.4
Although it is well-established that there are barriers to community participation in physical activity in people with disabilities, the literature does not characterize the demographics and level of disability in those who do regularly attend adaptive fitness facilities. This foundational information is important to better understand the characteristics of people with disabilities who use adaptive fitness centers. Therefore, the primary objectives of this exploratory study were to assess the characteristics of individuals who regularly attend a specialized urban adaptive fitness center, and to evaluate the degree of disability in these individuals in various domains of living. Our primary hypothesis was that individuals regularly attending an urban adaptive fitness center will have significant differences in domains of function across disability diagnoses. Our overall goal is that the baseline knowledge obtained from this study will help delineate the factors influencing participation in adaptive fitness centers, which will be helpful in developing future strategies to increase use of adaptive fitness centers.
METHODS
The institutional review board at Northwestern University approved this study.
Study design, setting, and sample size
This was a cross-sectional study surveying participants who regularly attend an urban Adaptive Sports and Fitness Center, affiliated with the Shirley Ryan AbilityLab in Chicago, IL. This particular fitness center is open only to people with a primary physical disability. Enrollment involves a membership application completed by both the individual as well as his/her medical provider documenting a history of a primary physical disability, a one-time initiation fee of $35, and a yearly maintenance fee of $60. The inclusion criteria for participants in the study included active members enrolled at the fitness center, those with a self-reported disability, and those who were at least 18 years old (a fitness center requirement). The exclusion criteria included those without a physical impairment/disability and those for whom English was not a primary language. Recruitment of participants occurred in the adaptive fitness center over a 3-month period (3/19/19 – 6/13/19) based on recruiter availability. This cross-sectional study did not have a comparison group.
All individuals who fit inclusion criteria completed a survey that assessed three domains:
Demographics – this included age, height, weight, educational level, home zip code, and employment status. We used each participant’s self-reported height and weight to calculate estimated body mass index (BMI). We used home zip code to derive information about each participant’s neighborhood median household income as a measure of socioeconomic status (SES). The median household income was assessed by geocoding each participant’s reported zip code to the U.S. Census Bureau 2011–2015 American Community Survey 5-year estimate of median family income and then dividing by 10,000. The use of this metric as a surrogate marker of SES has been documented in other studies.9, 10
Medical history – this included primary disability and frequency of primary care physician visits. Based on survey responses for primary disability, participants were grouped into three diagnostic categories: spinal cord injury (SCI), traumatic brain injury (TBI)/stroke, and other neurologic disease/chronic medical disease. “Other neurologic disease” included survey responses such as Parkinson disease and other movement disorders, multiple sclerosis, cerebral palsy, and nonspecific neurologic impairments such as “hemiplegia” or “ataxia.” “Chronic medical disease” included survey responses such as cancer, transplant, cardiovascular disease, pulmonary disease, amputation, lymphedema, and rheumatologic diagnoses. Of note, in five cases where survey participants selected multiple diagnoses, categories were redefined to group participants in the diagnosis group that was likely causing them the most mobility limitations (for example: dual TBI/SCI patients were grouped in SCI given likely mobility impairments from SCI). Survey responses for whether or not each participant had a primary care physician (PCP) and whether or not he/she saw his/her PCP annually were used as markers of health maintenance.
Fitness Center/Sports Participation - including distance traveled to the fitness center, frequency of physical activity engagement in the fitness center, and participation in adaptive sports.
World Health Organization Disability Assessment Schedule 2.0 (WHODAS) 2.0
The WHODAS 2.0 is an internationally validated generic assessment instrument developed by the World Health Organization (WHO) to provide a standardized method for measuring health and disability. It was developed from a comprehensive set of International Classification of Functioning, Disability and Health (ICF) items that are sufficiently reliable and sensitive to measure the difference made by a given intervention.11 The WHODAS 2.0 aims to evaluate disability in six domains: cognition, mobility, self-care, getting along, life activities, and participation.
Survey results were inputted into a computer program available on the WHO website. The tool evaluates each item response (i.e., “none,” “mild,” “moderate,” “severe,” “extreme or cannot do”) separately and uses complex item response scoring to determine a summary score by differentially weighting the items and levels of severity.12 Scoring takes into account multiple levels of difficulty for each WHODAS 2.0 item. The program summates recorded item scores within each disability domain, creates a summation of all six domain scores, and then converts the summary score into a metric ranging from 0 to 100 (where 0 = no disability and 100 = full disability). Results were compared to WHO published normalized values in the general population.11
Survey administration
The survey and WHODAS were administered digitally in person to consented participants via a REDCap survey on an iPad. A member of the research team was available at the time of completing the survey to address any questions and/or concerns.
Statistical analyses
All statistical analyses were performed using R (version 3.6.2). Demographic and clinical characteristics among the three diagnosis groups were compared using either chi-square tests (for categorical variables) or one-way analysis of variance (ANOVA) tests (for continuous variables), to evaluate for significant differences in WHODAS scores between each diagnosis group for each of the six domains. Statistical significance was set at p < .05.
RESULTS
Demographics
A total of 63 (n = 63) surveys were completed from the Adaptive Sports and Fitness Center and there were no participants who were approached who declined completion of the questionnaire. All individuals who were approached for recruitment for the study agreed to participate and there was no study drop out. The average age of participants was 52.9 ± 14.25 years old. A total of 45.9% of participants lived alone and 83.6% of participants were either unemployed or on disability. The estimated median household income for participants’ zip codes was $54,500 ± $22,000. Survey participants were grouped into three diagnostic categories with the following frequencies: SCI (30.2%), TBI/stroke (36.5%), and other neurologic disease/chronic medical disease (33.3%). There was a significant difference between groups in average age (p = .020), with individuals with SCI being younger. The estimated average income between groups also approached statistical significance (p = .053), with individuals with TBI having the lowest income. There were no between-group differences in employment status or living situation of survey participants. Of note, 82.3% of participants had a PCP, with 92.1% of these visiting their PCP at least annually. Detailed breakdown of participant demographics can be found in Table 1.
TABLE 1.
Key demographic characteristics by diagnosis
| All participants | Spinal cord injury | Traumatic brain injury/stroke | Other neurologic disease/chronic medical disease | p | |
|---|---|---|---|---|---|
| N | 63 | 19 | 23 | 21 | |
| Age, mean (SD) | 52.92 (14.25) | 46.63 (16.28) | 52.65 (11.45) | 59.20 (12.96) | .020* |
| BMI, mean (SD) | 29.35 (9.04) | 27.89 (8.93) | 31.19 (9.31) | 28.87 (9.03) | .511 |
| Income (10k), mean (SD) | 5.45 (2.20) | 5.38 (1.78) | 4.71 (2.12) | 6.37 (2.44) | .053 |
| Distance traveled to fitness center, mean (SD) | 9.62 (9.77) | 9.45 (4.81) | 8.88 (4.87) | 10.62 (16.14) | .922 |
| Unemployed/on disability (%) | 51 (83.6) | 15 (78.9) | 19 (86.4) | 17 (85.0) | .830 |
| Living alone (%) | 28 (45.9) | 8 (42.1) | 11 (52.4) | 9 (42.9) | .762 |
| Engage in physical activity at least two times a week (%) | 60 (96.8) | 19 (100) | 22 (100) | 19 (90.5) | .733 |
| Participation in adaptive sports (%) | 27 (43.5) | 8 (42.1) | 11 (43.5) | 9 (45.0) | .983 |
| Have a primary care provider (%) | 51 (80.9) | 15 (78.9) | 17 (73.9) | 19 (90.5) | .407 |
| See primary care provider at least yearly (%) | 47 (74.6) | 13 (68.4) | 17 (73.9) | 17 (81.0) | .585 |
p < .05.
Abbreviation: BMI, body mass index.
Sports/fitness participants
There were no between group differences in distance traveled to the fitness center for exercise participation. The average distance traveled to attend the fitness center was 8.0 (interquartile range [IQR] 4.80–12.25) miles, with 96.8% of participants engaging in moderate intensity physical activity at least two times a week at the fitness center. Of note, 43.5% of those surveyed participated in organized adaptive sports through the fitness center. There was no significant difference in frequency of attending the fitness center between the different diagnostic groups.
WHODAS
The mean summary score for all participants across all diagnoses was 26.48. This placed the participants in the 86th percentile of the general population, meaning, they were more disabled than 86% of the general population. Separating the WHODAS disability summary score by diagnosis placed SCI participants in the 87th percentile, TBI/stroke participants in the 87th percentile, and other neurologic diagnoses/chronic medical disease participants in the 84th percentile of the general population, respectively. There were no significant differences in disability scores between diagnostic groups (SCI, TBI, or other neurological disease/chronic medical disease). A detailed breakdown of WHODAS survey results can be found in Table 2.
TABLE 2.
WHODAS 2.0 survey results by domain/diagnosis
| All participants | Spinal cord injury | Traumatic brain injury/stroke | Other neurologic disease/chronic medical disease | p | |
|---|---|---|---|---|---|
| N | 63 | 19 | 23 | 21 | |
| Domain 1 score: cognition, mean (SD) | 16.27 (17.29) | 11.62 (12.47) | 20.83 (20.22) | 15.48 (17.08) | .224 |
| Domain 2 score: mobility, mean (SD) | 43.25 (22.99) | 56.58 (17.08) | 36.30 (24.08) | 38.81 (22.19) | .008* |
| Domain 3 score: self-care, mean (SD) | 21.92 (23.25) | 23.36 (25.33) | 25.82 (22.79) | 16.37 (21.78) | .390 |
| Domain 4 score: getting along, mean (SD) | 17.30 (19.09) | 13.42 (14.15) | 18.26 (18.44) | 19.76 (23.53) | .559 |
| Domain 5 score: life activities, mean (SD) | 28.04 (20.77) | 32.73 (23.81) | 29.07 (18.80) | 22.68 (19.66) | .302 |
| Domain 6 score: participation, mean (SD) | 32.10 (14.82) | 34.54 (16.75) | 32.62 (15.01) | 29.32 (12.90) | .534 |
| Summary score, mean (SD) | 26.48 (13.32) | 28.72 (11.16) | 27.15 (14.70) | 23.74 (13.69) | .484 |
p < .05.
Chi-square and one-way ANOVA testing was done to evaluate for significant differences in WHODAS scores for each of the six domains between each diagnostic category, as well as linear regression models to assess for significant associations between demographics and WHODAS scores. As expected, individuals with SCI had lower mobility scores on the WHODAS (p = .005), although this was not associated with frequency of attending the fitness center.
DISCUSSION
This exploratory study evaluated the demographics and characterized the degree of disability in those regularly attending an urban adaptive fitness center. Our hypotheses were that in individuals regularly attending an urban adaptive fitness center, the WHODAS 2.0 will have significant differences in domains of function across disability diagnoses, and second, that the level of disability on the WHODAS 2.0 would not be associated with frequency of attendance to the fitness center. As expected, this study found significant between-group differences for the domain of mobility. However, although there were cohorts in the study who had significantly more mobility impairment than others, our results show they were still attending the fitness center, which suggests that mobility impairments are not the sole barrier to active participation at the fitness center.
Of particular importance, adults with disabilities who attended the adaptive fitness center had a higher level of disability compared to the general population, but a very high proportion (96.8%) were still regularly participating in physical activity (at least twice weekly) at the fitness center or in adaptive sports. The majority of these individuals were also living alone and had annual evaluations by a primary care physician. This suggests that this cohort of individuals regularly exercised and led independent lives in which they are taking care of their own health maintenance. We are unable to confirm how much of this is attributable to enrollment in the fitness center, but more broadly, these findings may represent a healthy lifestyle choice that these participants with disabilities engage in that could be beneficial to them. In addition, the participants were not living in the immediate vicinity of the fitness center, traveling a mean distance of 8 miles to get to the urban location. Our study did not specifically investigate whether distance from the fitness center was a barrier to participation, as we did not include a “non-participating cohort.” However a prior study found that those who live within 24.4 miles from an adaptive fitness program site had significantly higher odds of sustained participation at a fitness center than those who lived more than 24.4 miles from the program site.5
A previous study found that those with a moderate level of functional impairment, such as requiring an assistive device for ambulating, were more likely to have sustained participation in community-based adaptive sports as compared to independent ambulators.5 For these individuals, participation in regular fitness centers or exercising outside of a fitness center may be more realistic compared to our cohort with more severe impairments. This study found that despite our participants having a higher level of disability than the general population, they were regularly engaging in physical activity.8
Although it is well known that engagement in regular physical activity has numerous physical health benefits that reduce morbidity and mortality from chronic medical issues, there are several psychosocial benefits as well.13 Prior studies have shown the positive influence of adaptive fitness and adaptive sports participation on self-esteem, body image, self-perceived quality of life, self-efficacy, community reintegration, employment, and motivation.14, 15 Active participation in adaptive fitness can result in better life satisfaction, improved mood, empowerment, resilience, and development of positive athletic identity.14–17 There have also been studies that show the impact of adaptive fitness on positive behavioral changes including forming healthy habits.13 In addition, group fitness can also aid in the establishment of peer groups and social support systems, which can serve as yet another integral factor in participating in physical activity.18 Such positive psychological benefits can in turn increase motivation for sustained physical activity levels and participation in adaptive fitness and sports, just as we see in our study results.6, 13, 14, 19–22 Therefore, regular physical activity has the potential to provide psychological and social benefits significant enough for individuals to be willing to travel to the urban environment to attend the fitness center, despite their level of disability.
A major strength of our study was the use of the WHODAS 2.0, an internationally validated generic assessment tool to measure the level of disability across several domains of living in our participants.11 The published WHO normalized values in the general population, allowed comparison to our cohort in terms of level of disability and functional difficulties experienced in each domain.
Our study is limited by the small sample size, which is due primarily to the uniqueness of the type of facility and in turn the participants available for recruitment. The study findings, therefore, are primarily exploratory in nature. Our recruitment included only individuals who were regularly participating in the fitness center, and who attended during the period of recruitment. A comparison group of individuals who did not participate in the fitness center were not included, and therefore our study was biased toward those who were engaged. However, the present study provides important information on the type of individuals who do attend and suggests that in this specific cohort that distance and level of disability are not barriers to participation. Further clarification of barriers in individuals who may be enrolled but do not attend would be beneficial. Although having a comparison group would have strengthened the findings of this study, accessing and recruiting a match-controlled cohort not enrolled in the fitness center at all would be logistically challenging due to the fitness center’s affiliation with our own health care institution. We did not examine sex differences between study participants; however, of all members enrolled in the adaptive fitness center, 51% were female and 49% were male. Race/ethnicity was also not included on our demographic intake form, and this will need to be further explored in future studies. Our participants’ heights and weights were self-reported and used for calculation of BMI. Although this can be considered a limitation, it was determined to be an acceptable measure of BMI for the purposes of this study. Finally, our study’s assessment of physical activity level was primarily through frequency of attending the adaptive fitness center and whether or not participants engaged in adaptive sports; we did not gather specific information on average duration of physical activity per week, as highlighted in the 2018 Physical Activity Guidelines for Americans. In addition, future studies assessing the impact of adaptive fitness centers on community integration and social interaction should be performed. The COVID-19 pandemic has also impacted individuals with disabilities to a greater extent compared to able-bodied individuals both in terms of the disease process and associated mitigation strategies. Future studies should therefore evaluate the impact of tele-exercise platforms in maintaining physical activity engagement in people with disabilities.
CONCLUSION
Our study shows that although participants at this urban adaptive fitness center had a higher level of disability than 80% to 90% of the general population, active participation in the fitness center was realistic and feasible. Individuals with disabilities have long experienced health disparities, including limited access to adaptive fitness opportunities, which have impacted their wellness, empowerment, and ability to successfully integrate into their communities.17, 19 Our findings provide understanding of the demographic and disability characteristics of individuals who regularly attend an urban adaptive fitness center, and serve as a foundation for future studies to assess the impact of these facilities on the health and quality of life of individuals with disabilities.
ACKNOWLEDGMENTS
We would like to thank the Shirley Ryan AbilityLab Adaptive Sports and Fitness Center for their assistance and support in conducting this research study at their facility.
Footnotes
DISCLOSURE
All authors declare they have no competing interests.
REFERENCES
- 1.Piercy KL, Troiano RP, Ballard RM, et al. The physical activity guidelines for Americans. JAMA 2018;320(19):2020–2028. doi: 10.1001/jama.2018.14854 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Sahlin K, Lexell J. Impact of organized sports on activity, participation, and quality of life in people with neurologic disabilities. PM R 2015;7(10):1081–1088. [DOI] [PubMed] [Google Scholar]
- 3.Dolbow D, Figoni S. Accommodation of wheelchair-reliant individuals by community fitness facilities. Spinal Cord 2015;53(7): 515–519. [DOI] [PubMed] [Google Scholar]
- 4.Anderson C, Grant R, Hurley M. Exercise facilities for neurologically disabled populations – perceptions from the fitness industry. Disabil Health J 2017;10(1):157–162. [DOI] [PubMed] [Google Scholar]
- 5.Blauwet C, Yang H, Cruz S, et al. Functional and environmental factors are associated with sustained participation in adaptive sports. PM R 2017;9(7):668–675. [DOI] [PubMed] [Google Scholar]
- 6.Lape E, Katz J, Losina E, Kerman H, Gedman M, Blauwet C. Participant-reported benefits of involvement in an adaptive sports program: a qualitative study. PM R 2018;10(5):507–515. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Lastuka A, Cottingham M. The effect of adaptive sports on employment among people with disabilities. Disabil Rehabil 2016;38(8):742–748. [DOI] [PubMed] [Google Scholar]
- 8.Adam S, Morgan K. Meaningful components of a community-based exercise program for individuals with disabilities: a qualitative study. Disabil Health J 2018;11(2):301–305. [DOI] [PubMed] [Google Scholar]
- 9.Jin J, Sandoval V, Lawless ME, Sehgal AR, McHenry CR. Disparity in the management of Graves’ disease observed at an urban county hospital: a decade-long experience. Am J Surg 2012;204(2):199–202. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Jolly M, Mikolaitis RA, Shakoor N, Fogg LF, Block JA. Education, zip code-based annualized household income, and health outcomes in patients with systemic lupus erythematosus. J Rheumatol 2010;37(6):1150–1157. [DOI] [PubMed] [Google Scholar]
- 11.WHO Disability Assessment Schedule 2.0 (WHODAS 2.0) (2018, June 14). https://www.who.int/classifications/icf/whodasii/en/
- 12.Üstün TB, Chatterji S, Kostanjsek N, et al. Developing the World Health Organization Disability Assessment Schedule 2.0. Bull World Health Organ 2010;88(11):815–823. doi: 10.2471/blt.09.067231 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Bonda’r R, Fronso S, Bortoli L, Robazza C, Metsios G, Bertollo M. The effects of physical activity or sport-based interventions on psychological factors in adults with intellectual disabilities: a systematic review. J Intellect Disabil Res 2019;64(2): 69–92. [DOI] [PubMed] [Google Scholar]
- 14.Diaz R, Miller E, Kraus E, Fredericson M. Impact of adaptive sports participation on quality of life. Sports Med Arthrosc Rev 2019;27(2):73–82. doi: 10.1097/JSA.0000000000000242 [DOI] [PubMed] [Google Scholar]
- 15.Hutzler Y, Sherrill C. Disability, physical activity, psychological well-being, and empowerment: a life-span perspective. In: Lidor R, Bar-Eli, eds. Sport Psychology: Linking Theory and Practice Morgantown Morgantown, WV: Fitness Information Technology, Inc; 1999:281–300. [Google Scholar]
- 16.Tow S, Gober J, Nelson M. Adaptive sports, arts, recreation, and community engagement. Phys Med Rehabil Clin N Am 2020;31(1):143–158. [DOI] [PubMed] [Google Scholar]
- 17.Laferrier J, Teodorski E, Cooper R. Investigation of the impact of sports, exercise, and recreation participation on psychosocial outcomes in a population of veterans with disabilities: a cross-sectional study. Am J Phys Med Rehabil 2015;94(12): 1026–1034. doi: 10.1097/PHM.0000000000000263 [DOI] [PubMed] [Google Scholar]
- 18.Lundberg NR, Taniguchi S, McCormick BP, Tibbs C. Identity negotiating: Redefining stigmatized identities through adaptive sports and recreation participation among individuals with a disability. J Leisure Res 2011;43(2):205–225. http://turing.library.northwestern.edu/login?url=https://www-proquest-com.ezproxy.galter.northwestern.edu/docview/925792283?accountid=12861. doi: 10.1080/00222216.2011.11950233 [DOI] [Google Scholar]
- 19.Groff DG, Lundberg NR, Zabriskie RB. Influence of adapted sport on quality of life: Perceptions of athletes with cerebral palsy. Disabil Rehabil 2009;31(4):318–326. doi: 10.1080/09638280801976233 [DOI] [PubMed] [Google Scholar]
- 20.Malone LA, Barfield J, Brasher JD. Perceived benefits and barriers to exercise among persons with physical disabilities or chronic health conditions within action or maintenance stages of exercise. Disabil Health J 2012;5(4):254–260. doi: 10.1016/j.dhjo.2012.05.004 [DOI] [PubMed] [Google Scholar]
- 21.Declerck L, Kaux JF, Vanderthommen M, Lejeune T, Stoquart G. The effect of adaptive sports on individuals with acquired neurological disabilities and its role in rehabilitation: a systematic review. Curr Sports Med Rep 2019;18(12):458–473. doi: 10.1249/JSR.0000000000000662 [DOI] [PubMed] [Google Scholar]
- 22.Macko R Adaptive physical activity improves mobility function and quality of life in chronic hemiparesis. J Rehabil Res Dev 2008;45(2):323–328. [DOI] [PubMed] [Google Scholar]