http://informahealthcare.com/dre ISSN 0963-8288 print/ISSN 1464-5165 online Disabil Rehabil, Early Online: 1–5 ! 2015 Informa UK Ltd. DOI: 10.3109/09638288.2015.1035460
RESEARCH PAPER
Factors associated with community ambulation in chronic stroke Sarah Durcan1, Evelyn Flavin1, and Frances Horgan2 Stroke Rehabilitation Team, Baggot Street Community Hospital, Dublin, Ireland and 2School of Physiotherapy, Royal College of Surgeons in Ireland, Dublin, Ireland
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Abstract
Keywords
Purpose: Loss of independent community ambulation is one of the most disabling consequences of stroke. The aim of this study was to investigate the association of multiple personal and post-stroke factors with community ambulation in persons between 1- and 3-year post-stroke. Methods: This was a cross-sectional study of 40 community-dwelling stroke patients, 418 years, between 1- and 3-year post-stroke. The main outcome measures used were self-report community ambulation questionnaire, demographic information, 10-M Walk Test, Timed Up and Go test, Activities-Specific Balance Confidence Scale, Fatigue Severity Scale, Hospital Anxiety and Depression Scale, Trail-Making Test-Part B, Single Letter Cancellation Test. Results: Age, number of medications and use of a walking aid were found to be significantly associated with community ambulation (p 0.05). Gait speed, walking balance and balance self-efficacy were also found to be significantly associated with community ambulation (p 0.05). Balance self-efficacy was the only factor independently associated with community ambulation post-stroke (p 0.05). Conclusion: Balance self-efficacy may be a significant determinant in the attainment of independent community ambulation post-stroke. This suggests that physical aspects such as gait speed and walking balance should not be considered in isolation when addressing community ambulation post-stroke.
Balance self-efficacy, community ambulation, gait, stroke History Received 9 October 2014 Revised 10 March 2015 Accepted 25 March 2015 Published online 9 April 2015
ä Implications for Rehabilitation
Balance self-efficacy may play a significant role in the attainment of independent community ambulation in a chronic stroke population. Physiotherapy interventions addressing community ambulation post-stroke should consider methods for improving balance self-efficacy in chronic stroke, such as self management programmes.
Introduction Community ambulation has been defined as independent mobility outside the home, which includes the ability to confidently negotiate uneven terrain, private venues, shopping centres and other public venues [1]. It has been reported that 80% of patients regain independent gait following a stroke [1,2], however only a smaller proportion manage to walk independently in the community again [1]. Loss of independent community ambulation is one of the most disabling consequences of stroke. It has been found to be associated with poor quality of life, decreased satisfaction and mood disorders in stroke patients [3]. Lord et al. [1] found that the ability ‘‘to get out and about’’ in the community was considered to be either essential or very important to 75% of stroke patients. Considering the importance of community ambulation to quality of life post-stroke, it is necessary for clinicians to gain a better understanding of the factors associated Address for correspondence: Sarah Durcan, Stroke Rehabilitation Team, Baggot Street Community Hospital, Dublin 4, Ireland. Tel: +35316699389. E-mail: [email protected]
with community ambulation, so they can develop more specific rehabilitation programs to maximise patient outcome. The attainment of independent community ambulation following stroke has not been well researched in the literature to date, therefore it is unclear what factors play a significant role in the ability to walk independently in the community. In the absence of a validated outcome measure to assess community ambulation post-stroke, many studies have focussed on gait speed as a proxy measure for community ambulation [1,4,5]. Gait speed has been found to be a useful and discriminate measure of different ambulation levels [5]. Walking distance has also been reported as a useful predictor of community walking activity in high functioning people with stroke [6]. However, physical ability does not always predict the ability to walk in the community following stroke. Lord et al. [1] found that although the majority of patients regained independent gait and scored highly on mobility outcomes, nearly one-third were unable to walk unsupervised in their own community. It has been suggested that other physical [7,8], personal [8,9] and psychosocial factors [9] may also play a significant role in return to community ambulation after stroke.
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S. Durcan et al.
Only a few studies to date have examined what factors are significantly associated with community ambulation following stroke. Balance self-efficacy and depression have been found to be associated with participation in community walking in chronic stroke patients [9]. Similarly, the ability to walk in the community following stroke has been shown to be determined by several underlying factors such as balance, motor function, endurance and use of an assistive device [8]. There is currently no consensus on what factors are most important in predicting those who will return to independent community ambulation, particularly in a chronic stroke population. The current study aimed to investigate the association of personal and post-stroke factors, with the ability to ambulate independently in the community following stroke. These factors included physical ability, as well as psychological and cognitive factors such as fatigue, executive function and visual neglect of extrapersonal space, which have not been explored in previous research. It also examined whether any of these factors were independently associated with community ambulation post-stroke.
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walk outside, (Level 2) the patient can walk outside as far as the front of the house without physical assistance or supervision, (Level 3-limited community walkers) – the patient can walk in the immediate environment (e.g. down the road) without physical assistance or supervision, (Level 4-independent community walkers) – the patient can walk to shops, friends’ houses or activities in the vicinity without physical assistance or supervision. Other outcome measures 10 Metre Walk Test (10MWT) This was administered as a measure of gait speed. In this test, the individual walks without assistance for 10 m and the time is measured for the intermediate 6 m, allowing for acceleration and deceleration. Three trials of the test were carried out and the average of the three was calculated. This has been found to be a reliable measure of gait speed after stroke [12]. Timed-Up and Go (TUG)
Methods Design and participants This was a cross-sectional observational study, with participants recruited from the database of an out-patient community stroke rehabilitation service. The inclusion criteria for the study were: (1) diagnosis of a stroke as defined by the World Health Organisation definition [10] (2) 418 years of age, communitydwelling, (3) between 1- and 3-year post-stroke, (4) able to walk at least 10 m with/without a walking aid and independently and (5) able to give informed written consent. Participants were excluded if they had (1) other neurological conditions, significant orthopaedic condition affecting mobility and uncontrolled cardiac conditions, (2) recent lower limb fracture within the previous 6 months, (3) severe communication difficulties (inability to complete the pen and paper tasks and questionnaires) and (4) cognitive impairment (a score of six or less on the Abbreviated Mental Test Score [11]). One hundred participants were randomly selected from the database and invited to participate in the study. All the participants who volunteered to participate in the study and met the study criteria, attended the out-patient unit on one occasion to complete a battery of outcome measures and questionnaires. Measurements All the outcome measures were completed by the principal investigator, who has 47 years experience working in a stroke rehabilitation setting. A pilot study with 4 participants was completed prior to commencement of the study, to inform the length of time of the assessments and any difficulties with their administration. The data from the pilot study were not included in the final analyses. Demographic information Basic demographic information and data on stroke characteristics were collected during an interview with the participants. Participant’s score on the Modified Rankin Scale and falls history within the previous 6 months were also recorded. Primary outcome measure
This was used to assess walking balance. Subjects were asked to stand up from a chair with arms, walk up to a line on the floor 3 m away, turn around and walk back to the chair and sit down. The time taken to complete the test was recorded. It is a reliable measure in chronic stroke patients [13] and strongly associated with the Berg Balance Scale (BBS) in community-dwelling stroke survivors [14]. Activities-Specific Balance Confidence Scale (ABC Scale) This was administered to assess balance confidence in carrying out everyday activities [15]. Participants were asked to rate on a scale from 0% (no confidence) to 100% (completely confident) how confident they were that they would not lose their balance or become unsteady carrying out a range of 16 functional activities. It has been found to be a reliable measure for use with stroke patients [16]. Fatigue Severity Scale (FSS) This was used to assess the impact of fatigue. It is a 9-item selfreport scale, which measures the severity of fatigue and how much it affects the person’s activities and lifestyle [17]. It contains nine questions with scores ranging from 1 (strongly disagree) to 7 (strongly agree). It has been shown to be a reliable and valid measure of fatigue in a stroke population [18] and has been previously used in studies to assess fatigue in stroke patients [19]. Hospital Anxiety and Depression Scale (HADS) This was used as a measure of anxiety and depression. It contains two 7-item scales, one for anxiety and one for depression. It has been shown to be reliable, valid and sensitive to change in the screening for depression [20]. Trail-Making Test-Part B (TMT-B) This was used as a measure of executive function. It evaluates the components of executive function that represent complex visual scanning, speed, attention and ability to shift sets [21]. It has been previously used in studies examining associations between gait and executive function [22]. It has been shown to have excellent test–retest reliability in patients with stroke [23].
Community Ambulation Questionnaire This is a short, self-administered questionnaire that was developed by Lord et al. [1]. It categorises patients into four categories of community ambulation: (Level 1) the patient is unable to
Single Letter Cancellation Test (SLCT) This was used to measure unilateral spatial neglect. It has been found to have strong psychometric properties,
Community ambulation in chronic stroke
DOI: 10.3109/09638288.2015.1035460
(including reliability and validity), in identifying unilateral spatial neglect in the near extrapersonal space [24]. Data analysis Data were analyzed using SPSS software (Version 18.0; SPSS Inc, Chicago, IL). Descriptive statistics were used to describe the characteristics of the participants and their levels of community ambulation. Participants were dichotomised into two groups, independent community walkers and non-independent community walkers. Binary logistic regression analysis was then carried out to examine for associations between community ambulation and the personal and post-stroke factors. Multivariate logistic regression was used to examine whether any of the factors were independently associated with community ambulation post-stroke. Ethical approval was received for this study and informed written consent was obtained from each study participant.
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Results There were 40 patients who volunteered to participate in the study and who met the inclusion criteria. The baseline demographics of the participants are presented in Table 1. Based on the responses to the Community Ambulation Questionnaire, participants were classified into different levels of community ambulation. About 57.5% were independent community walkers (Level 4), 35% were limited community walkers (Level 3) and 7.5% could only walk as far as the front of their house (Level 2). The study participants were dichotomised into two groups as has been done in previous studies [8,25]. Participants in Level 4 were classified as independent community walkers (n ¼ 23), while those in Level 2 and Level 3 were classified as noncommunity walkers (n ¼ 17). The descriptive statistics for the outcome measures according to group assignment is provided in Table 2. Binary logistic regression Binary logistic regression analysis was used to examine the association between level of community ambulation and both the personal factors and the outcome measures. A two-tailed significance level of 0.05 was used for all the tests. For the personal factors, there was a significant association between community ambulation and age (p ¼ 0.04), use of a walking aid (p ¼ 0.001) and number of medications (p ¼ 0.02). Patients who were older and with polypharmacy were less likely to be community walkers, while those who used a walking aid were more likely to be
Table 1. Baseline characteristics of study population (n ¼ 40). Variable Age (years), mean (SD) Gender, n (%) male Use of walking aid, n (%), yes No. of medications, median (IQR) No. of co-morbidities, median (IQR) Time since stroke (months), mean (SD) Lesion side, n (%) Right Left MRS, n (%) 2 42 No. of falls, n (%) None 1
3
community walkers. All the results of the analyses are presented in Table 3. For the outcome measures, a significant association was found between community ambulation and gait speed (p ¼ 0.001), the TUG (p ¼ 0.004) and the ABC scale (0.001). The results of all the analyses are presented in Table 3. Patients with higher scores for gait speed and balance self-efficacy were more likely to be community walkers. Also, patients who took less time to complete the TUG were more likely to be community walkers. Multivariate logistic regression Multivariate logistic regression examined which post-stroke variables were independently associated with community ambulation post-stroke. Age was entered into the analysis as a biological factor. Gait speed, TUG and the ABC scale were also included in the analysis, as they had been shown to be significantly associated with community ambulation in the binary logistic regression analysis (p 0.05). A two-tailed significance level of 0.05 was used for all the tests. The ABC Scale was the only variable found to be independently associated with community ambulation. The results of this analysis are presented in Table 4.
Discussion The main finding of this study was that balance self-efficacy was the only factor independently associated with community ambulation, with those with higher levels of balance self-efficacy more likely to be independent community walkers. Previous research has demonstrated that balance-self efficacy is independently associated with post-stroke activity and participation in chronic stroke patients [26]. Balance self-efficacy has also been found to be an independent predictor of community reintegration in older adults with chronic stroke [27]. In relation to community ambulation post-stroke, Robinson et al. [9] found that balance self-efficacy was the only personal factor which was strongly associated with both subjective and objective measures of participation in community walking. Balance self-efficacy refers to a person’s belief in their ability to undertake activities of daily living without losing their balance [28]. Considering the complex nature of community ambulation and the skills and attributes required, it is understandable that stroke patients with low levels of balance confidence may be less likely to attain independent community ambulation. It is possible that in a chronic stroke population, patients may have learned to manage their physical limitations, however the fear of having a fall may prevail. This may result in limitations in activity and participation in everyday activities, including community ambulation. Also, physiotherapy intervention following stroke tends to focus on the recovery of the physical aspects such as gait
Measurement 66 22 12 5 2 22.3
(13.4) (55) (30) (4) (2) (6.9)
25 (62.5) 15 (37.5) 33 (82.5) 7 (17.5) 29 (72.5) 11 (27.5)
Table 2. Summary statistics for outcome measures.
Outcome measure Gait speed (m/s), mean (SD) TUG (seconds), median (IQR) ABC Scale, median (IQR) FSS, mean (SD) HADS-A, mean (SD) HADS-D, mean (SD) TMT-B (s), median (IQR) SLCT, median (IQR)
Independent community walkers (n ¼ 23) 1.33 9.43 86.25 32.87 6.39 4.09 106 104
(0.2) (1.8) (15) (14) (4.4) (2.7) (114) (1)
Non-community walkers (n ¼ 17) 0.76 15.3 56.25 36.35 6.24 5.41 165 102
(0.3) (14.1) (14.1) (10.2) (3.4) (2.7) (187) (5)
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Table 3. Binary logistic regression analyses for relationship between community ambulation and personal and post-stroke factors. Variable
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Age Gender Use of walking aid Time since stroke No. of medications No. of co-morbidities MRS Falls History Gait Speed TUG ABC Scale FSS HADS-A HADS-D TMT-B SLCT
Regression coefficient
SE
p Value
EXP (B)
0.06 0.56 3.70 0.02 0.39 0.46 22.04 0.17 9.27 1.04 0.13 0.02 0.01 0.18 0.01 0.112
0.03 0.65 1.14 0.05 0.16 0.24 15 192 0.71 2.91 0.36 0.04 0.02 0.08 0.12 0.003 0.08
0.04* 0.39 0.001* 0.62 0.02* 0.06 0.99 0.82 0.001* 0.004* 0.001* 0.38 0.90 0.14 0.06 0.16
0.94 0.57 40.33 1.02 0.68 0.63 0.00 0.85 10 596 0.35 1.15 0.98 1.01 0.834 0.99 1.12
SE, standard error; p value, significance value; EXP(B), odds ratio. *p 0.05. Table 4. Multivariate logistic regression for community ambulation. Variable Age Gait speed TUG ABC Constant
B
SE
Wald
df
Sig
EXP (B)
0.13 13.06 0.03 0.17 15.98
0.10 9.56 0.48 0.09 17.80
1.64 1.87 0.004 3.90 0.80
1 1 1 1 1
0.20 0.17 0.95 0.05* 0.40
0.87 470 017 0.97 0.05 0.00
B, regression coefficient; df, degrees of freedom; SE, standard error; Sig, significance level; Wald, Wald statistic; EXP (B), odds ratio. *p 0.05.
and balance, with little input addressing balance self-efficacy. Future interventions addressing return to community ambulation post-stroke should consider methods of improving balance selfefficacy in the chronic stroke population. One example is the use of self-management programmes following stroke, which can promote changes in behaviour and self management skills, which in turn have a positive effect on self-efficacy [29]. Another key finding was that gait speed was not an independent predictor of community ambulation post-stroke. Similarly, walking balance was also found not to be independently associated with community ambulation on the multivariate analysis. This suggests that the task of community walking requires more complex attributes than physical ability alone. This is in keeping with the findings of the study by Lord et al. [1], who reported that while 80% of patients had regained independent gait and scored highly on mobility outcomes, nearly one-third were not able to walk unsupervised in their own community after their stroke. This finding has implications for the development of future outcome measures for community ambulation post-stroke. It supports the need to consider other factors such as balance selfefficacy, in conjunction with the physical factors, when developing new assessment tools, given the multi-factorial nature of community ambulation. In relation to the other factors explored in this study, no significant association was identified between community ambulation and fatigue, depression, executive function and visual neglect. This cohort of stroke patients were relatively high functioning (82.5% scoring 2 or less on MRS), with both the independent community walker group and the non-community walker group scoring below the threshold for impairment on the measures of fatigue, depression, executive function and visual neglect. These low scores would have affected the likelihood of finding an association with community ambulation.
There were several limitations of this current study. Firstly, the cross-sectional study design meant causal relationships between the factors and community ambulation could not be established. Secondly, the small sample size limits the generalisability of the study findings and did not allow for a greater number of variables to be included in the multiple logistic regression analysis. The study population were relatively young (mean age 66 years), with mild to moderate levels of disability, therefore may not be representative of the wider stroke population. Also, as they were all recruited from the one out-patient community Stroke Rehabilitation service and had the same service providers, this could potentially limit the wider generalisability of the results. Thirdly, the use of a self-administered questionnaire to measure community ambulation may have resulted in reporting bias. Finally, other factors which may influence community ambulation such as walking endurance, lower limb strength, dual task ability, patient motivation and environmental factors were not considered in this study. In conclusion, the findings of this study suggest that balance self-efficacy may be a stronger predictor than physical factors, such as gait speed and balance, in return to independent community ambulation in chronic stroke patients. However, community ambulation is a complex, multifactorial task and continued research is required to further establish the significant determinants of community ambulation post-stroke. This in turn will enable a more specific outcome measure to developed and validated, as well as the development of more effective interventions to address community ambulation post-stroke.
Acknowledgements The authors would like to thank the patients that participated in this study.
DOI: 10.3109/09638288.2015.1035460
Declaration of interest The authors report no declaration of interests.
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References 1. Lord S, McPherson K, McNaughton H, et al. Community ambulation after stroke: how important and obtainable is it and what measures appear predictive? Arch Phys Med Rehabil 2004;85:234–9. 2. Veerbeek J, Kwakkel G, van Wegan E, et al. Early prediction of outcome of activities of daily living after stroke: a systematic review. Stroke 2011;42:1482–8. 3. Pound P, Gompertz P, Ebrahim S. A patient-centred study of the consequences of stroke. Clin Rehabil 1998;12:338–47. 4. Hill K, Ellis P, Bernhardt J, et al. Balance and mobility outcomes for stroke patients: a comprehensive audit. Aust J Physiother 1997;43: 173–80. 5. Perry J, Garrett M, Gronley J, Mulroy S. Classification of walking handicap in the stroke population. Stroke 1995;26:982–9. 6. Fulk G, Reynolds C, Mondal S, Deutsch J. Predicting home and community walking activity in people with stroke. Arch Phys Med Rehabil 2010;91:1582–6. 7. Robinson C, Shumway-Cook A, Noritake Matsuda P, Ciol M. Understanding physical factors associated with participation in community ambulation following stroke. Disabil Rehabil 2011;33: 1033–42. 8. Van de Port I, Kwakkel G, Lindeman E. Community ambulation in patients with chronic stroke: how is it related to gait speed? J Rehabil Med 2008;40:23–7. 9. Robinson C, Shumway-Cook A, Ciol M, Kartin D. Participation in community walking following stroke: subjective versus objective measures and the impact of personal factors. Phys Ther 2011;91: 1865–76. 10. Hatano S. Experience from a multicentre stroke register: a preliminary report. B World Health Organ 1976;54:541–53. 11. Hodkinson H. Evaluation of a mental test score for assessment of mental impairment in the elderly. Age and Ageing 1972;1:233–8. 12. Collen F, Wade D, Bradshaw C. Mobility after stroke: reliability of measures of impairment and disability. Int Disabil Stud 1990;12:6–9. 13. Flansbjer U, Holmback A, Downham D, et al. Reliability of gait performance tests in men and women with hemiparesis after stroke. J Rehabil Med 2005;37:75–82. 14. Knorr S, Brouwer B, Garland S. Validity of the Community Balance and Mobility Scale in community-dwelling persons after stroke. Arch Phys Med Rehabil 2010;91:890–6.
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15. Powell L, Myers A. The Activities-specific Balance Confidence (ABC) Scale. J Gerontol Med Sci 1995;50:M28–34. 16. Botner E, Miller W. Measurement properties of the ActivitiesSpecific Balance Confidence Scale among individuals with stroke. Disabil Rehabil 2005;27:156–63. 17. Krupp L, LaRocca N, Muir-Nash J, Steinberg A. The Fatigue Severity Scale: application to patients with multiple sclerosis and systemic lupus erythematosus. Arch Neurol 1989;46:1121–3. 18. Lerdal A, Kottorp A. Psychometric properties of the Fatigue Severity Scale-Rasch analyses of individual responses in a Norwegian stroke cohort. Int J Nurs Stud 2011;48:1258–65. 19. Choi-Kwon S, Han S, Kwon S, Kim J. Post stroke fatigue: characteristics and related factors. Cerebrovasc Dis 2005;19:84–90. 20. Zigmond A, Snaith R. The Hospital Anxiety and Depression Scale. Acta Psychiat Scand 1983;67:361–70. 21. Greenlief C, Margolis R, Erker G. Application of the Trail Making Test in differentiating neuropsychological impairment of elderly persons. Percept Motor Skill 1985;61:1283–9. 22. Ble A, Volpato S, Zuliani G, et al. Executive function correlates with walking speed in older persons: the InCHIANTI Study. J Am Geriatr Soc 2005;53:410–15. 23. Goldstein G, Watson J. Test-retest reliability of the Halstead–Reitan battery and the WAIS in a neuropsychiatric population. Clin Neuropsychol 1989;3:265–72. 24. Menon A, Korner-Bitensky N. Evaluating unilateral spatial neglect post stroke: working your way through a maze of assessment choices. Top Stroke Rehabil 2004;11:41–66. 25. Bijleveld-Uitman M, van de Port I, Kwakkel G. Is gait speed or walking distance a better predictor for community walking after stroke? J Rehabil Med 2013;45:535–40. 26. Schmid A, van Puymbroeck M, Altenburger P, et al. Balance and balance self-efficacy are associated with activity and participation after stroke: a cross sectional study in people with chronic stroke. Arch Phys Med Rehabil 2012;93:1101–7. 27. Pang M, Eng J, Miller W. Determinants of satisfaction with community reintegration in older adults with chronic stroke: role of balance self-efficacy. Phys Ther 2007;87:282–91. 28. Salbach N, Mayo N, Robichaud-Ekstrand S, et al. The effect of a task-orientated walking intervention on improving balance selfefficacy poststroke: a randomised, controlled trial. J Am Geriatr Soc 2005;53:576–82. 29. Jones F, Riazi A. Self-efficacy and self-management after stroke: a systematic review. Disabil Rehabil 2011;33: 797–810.
RESEARCH PAPER
Factors associated with community ambulation in chronic stroke Sarah Durcan1, Evelyn Flavin1, and Frances Horgan2 Stroke Rehabilitation Team, Baggot Street Community Hospital, Dublin, Ireland and 2School of Physiotherapy, Royal College of Surgeons in Ireland, Dublin, Ireland
Disabil Rehabil Downloaded from informahealthcare.com by Kainan University on 04/15/15 For personal use only.
1
Abstract
Keywords
Purpose: Loss of independent community ambulation is one of the most disabling consequences of stroke. The aim of this study was to investigate the association of multiple personal and post-stroke factors with community ambulation in persons between 1- and 3-year post-stroke. Methods: This was a cross-sectional study of 40 community-dwelling stroke patients, 418 years, between 1- and 3-year post-stroke. The main outcome measures used were self-report community ambulation questionnaire, demographic information, 10-M Walk Test, Timed Up and Go test, Activities-Specific Balance Confidence Scale, Fatigue Severity Scale, Hospital Anxiety and Depression Scale, Trail-Making Test-Part B, Single Letter Cancellation Test. Results: Age, number of medications and use of a walking aid were found to be significantly associated with community ambulation (p 0.05). Gait speed, walking balance and balance self-efficacy were also found to be significantly associated with community ambulation (p 0.05). Balance self-efficacy was the only factor independently associated with community ambulation post-stroke (p 0.05). Conclusion: Balance self-efficacy may be a significant determinant in the attainment of independent community ambulation post-stroke. This suggests that physical aspects such as gait speed and walking balance should not be considered in isolation when addressing community ambulation post-stroke.
Balance self-efficacy, community ambulation, gait, stroke History Received 9 October 2014 Revised 10 March 2015 Accepted 25 March 2015 Published online 9 April 2015
ä Implications for Rehabilitation
Balance self-efficacy may play a significant role in the attainment of independent community ambulation in a chronic stroke population. Physiotherapy interventions addressing community ambulation post-stroke should consider methods for improving balance self-efficacy in chronic stroke, such as self management programmes.
Introduction Community ambulation has been defined as independent mobility outside the home, which includes the ability to confidently negotiate uneven terrain, private venues, shopping centres and other public venues [1]. It has been reported that 80% of patients regain independent gait following a stroke [1,2], however only a smaller proportion manage to walk independently in the community again [1]. Loss of independent community ambulation is one of the most disabling consequences of stroke. It has been found to be associated with poor quality of life, decreased satisfaction and mood disorders in stroke patients [3]. Lord et al. [1] found that the ability ‘‘to get out and about’’ in the community was considered to be either essential or very important to 75% of stroke patients. Considering the importance of community ambulation to quality of life post-stroke, it is necessary for clinicians to gain a better understanding of the factors associated Address for correspondence: Sarah Durcan, Stroke Rehabilitation Team, Baggot Street Community Hospital, Dublin 4, Ireland. Tel: +35316699389. E-mail: [email protected]
with community ambulation, so they can develop more specific rehabilitation programs to maximise patient outcome. The attainment of independent community ambulation following stroke has not been well researched in the literature to date, therefore it is unclear what factors play a significant role in the ability to walk independently in the community. In the absence of a validated outcome measure to assess community ambulation post-stroke, many studies have focussed on gait speed as a proxy measure for community ambulation [1,4,5]. Gait speed has been found to be a useful and discriminate measure of different ambulation levels [5]. Walking distance has also been reported as a useful predictor of community walking activity in high functioning people with stroke [6]. However, physical ability does not always predict the ability to walk in the community following stroke. Lord et al. [1] found that although the majority of patients regained independent gait and scored highly on mobility outcomes, nearly one-third were unable to walk unsupervised in their own community. It has been suggested that other physical [7,8], personal [8,9] and psychosocial factors [9] may also play a significant role in return to community ambulation after stroke.
Disabil Rehabil Downloaded from informahealthcare.com by Kainan University on 04/15/15 For personal use only.
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S. Durcan et al.
Only a few studies to date have examined what factors are significantly associated with community ambulation following stroke. Balance self-efficacy and depression have been found to be associated with participation in community walking in chronic stroke patients [9]. Similarly, the ability to walk in the community following stroke has been shown to be determined by several underlying factors such as balance, motor function, endurance and use of an assistive device [8]. There is currently no consensus on what factors are most important in predicting those who will return to independent community ambulation, particularly in a chronic stroke population. The current study aimed to investigate the association of personal and post-stroke factors, with the ability to ambulate independently in the community following stroke. These factors included physical ability, as well as psychological and cognitive factors such as fatigue, executive function and visual neglect of extrapersonal space, which have not been explored in previous research. It also examined whether any of these factors were independently associated with community ambulation post-stroke.
Disabil Rehabil, Early Online: 1–5
walk outside, (Level 2) the patient can walk outside as far as the front of the house without physical assistance or supervision, (Level 3-limited community walkers) – the patient can walk in the immediate environment (e.g. down the road) without physical assistance or supervision, (Level 4-independent community walkers) – the patient can walk to shops, friends’ houses or activities in the vicinity without physical assistance or supervision. Other outcome measures 10 Metre Walk Test (10MWT) This was administered as a measure of gait speed. In this test, the individual walks without assistance for 10 m and the time is measured for the intermediate 6 m, allowing for acceleration and deceleration. Three trials of the test were carried out and the average of the three was calculated. This has been found to be a reliable measure of gait speed after stroke [12]. Timed-Up and Go (TUG)
Methods Design and participants This was a cross-sectional observational study, with participants recruited from the database of an out-patient community stroke rehabilitation service. The inclusion criteria for the study were: (1) diagnosis of a stroke as defined by the World Health Organisation definition [10] (2) 418 years of age, communitydwelling, (3) between 1- and 3-year post-stroke, (4) able to walk at least 10 m with/without a walking aid and independently and (5) able to give informed written consent. Participants were excluded if they had (1) other neurological conditions, significant orthopaedic condition affecting mobility and uncontrolled cardiac conditions, (2) recent lower limb fracture within the previous 6 months, (3) severe communication difficulties (inability to complete the pen and paper tasks and questionnaires) and (4) cognitive impairment (a score of six or less on the Abbreviated Mental Test Score [11]). One hundred participants were randomly selected from the database and invited to participate in the study. All the participants who volunteered to participate in the study and met the study criteria, attended the out-patient unit on one occasion to complete a battery of outcome measures and questionnaires. Measurements All the outcome measures were completed by the principal investigator, who has 47 years experience working in a stroke rehabilitation setting. A pilot study with 4 participants was completed prior to commencement of the study, to inform the length of time of the assessments and any difficulties with their administration. The data from the pilot study were not included in the final analyses. Demographic information Basic demographic information and data on stroke characteristics were collected during an interview with the participants. Participant’s score on the Modified Rankin Scale and falls history within the previous 6 months were also recorded. Primary outcome measure
This was used to assess walking balance. Subjects were asked to stand up from a chair with arms, walk up to a line on the floor 3 m away, turn around and walk back to the chair and sit down. The time taken to complete the test was recorded. It is a reliable measure in chronic stroke patients [13] and strongly associated with the Berg Balance Scale (BBS) in community-dwelling stroke survivors [14]. Activities-Specific Balance Confidence Scale (ABC Scale) This was administered to assess balance confidence in carrying out everyday activities [15]. Participants were asked to rate on a scale from 0% (no confidence) to 100% (completely confident) how confident they were that they would not lose their balance or become unsteady carrying out a range of 16 functional activities. It has been found to be a reliable measure for use with stroke patients [16]. Fatigue Severity Scale (FSS) This was used to assess the impact of fatigue. It is a 9-item selfreport scale, which measures the severity of fatigue and how much it affects the person’s activities and lifestyle [17]. It contains nine questions with scores ranging from 1 (strongly disagree) to 7 (strongly agree). It has been shown to be a reliable and valid measure of fatigue in a stroke population [18] and has been previously used in studies to assess fatigue in stroke patients [19]. Hospital Anxiety and Depression Scale (HADS) This was used as a measure of anxiety and depression. It contains two 7-item scales, one for anxiety and one for depression. It has been shown to be reliable, valid and sensitive to change in the screening for depression [20]. Trail-Making Test-Part B (TMT-B) This was used as a measure of executive function. It evaluates the components of executive function that represent complex visual scanning, speed, attention and ability to shift sets [21]. It has been previously used in studies examining associations between gait and executive function [22]. It has been shown to have excellent test–retest reliability in patients with stroke [23].
Community Ambulation Questionnaire This is a short, self-administered questionnaire that was developed by Lord et al. [1]. It categorises patients into four categories of community ambulation: (Level 1) the patient is unable to
Single Letter Cancellation Test (SLCT) This was used to measure unilateral spatial neglect. It has been found to have strong psychometric properties,
Community ambulation in chronic stroke
DOI: 10.3109/09638288.2015.1035460
(including reliability and validity), in identifying unilateral spatial neglect in the near extrapersonal space [24]. Data analysis Data were analyzed using SPSS software (Version 18.0; SPSS Inc, Chicago, IL). Descriptive statistics were used to describe the characteristics of the participants and their levels of community ambulation. Participants were dichotomised into two groups, independent community walkers and non-independent community walkers. Binary logistic regression analysis was then carried out to examine for associations between community ambulation and the personal and post-stroke factors. Multivariate logistic regression was used to examine whether any of the factors were independently associated with community ambulation post-stroke. Ethical approval was received for this study and informed written consent was obtained from each study participant.
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Results There were 40 patients who volunteered to participate in the study and who met the inclusion criteria. The baseline demographics of the participants are presented in Table 1. Based on the responses to the Community Ambulation Questionnaire, participants were classified into different levels of community ambulation. About 57.5% were independent community walkers (Level 4), 35% were limited community walkers (Level 3) and 7.5% could only walk as far as the front of their house (Level 2). The study participants were dichotomised into two groups as has been done in previous studies [8,25]. Participants in Level 4 were classified as independent community walkers (n ¼ 23), while those in Level 2 and Level 3 were classified as noncommunity walkers (n ¼ 17). The descriptive statistics for the outcome measures according to group assignment is provided in Table 2. Binary logistic regression Binary logistic regression analysis was used to examine the association between level of community ambulation and both the personal factors and the outcome measures. A two-tailed significance level of 0.05 was used for all the tests. For the personal factors, there was a significant association between community ambulation and age (p ¼ 0.04), use of a walking aid (p ¼ 0.001) and number of medications (p ¼ 0.02). Patients who were older and with polypharmacy were less likely to be community walkers, while those who used a walking aid were more likely to be
Table 1. Baseline characteristics of study population (n ¼ 40). Variable Age (years), mean (SD) Gender, n (%) male Use of walking aid, n (%), yes No. of medications, median (IQR) No. of co-morbidities, median (IQR) Time since stroke (months), mean (SD) Lesion side, n (%) Right Left MRS, n (%) 2 42 No. of falls, n (%) None 1
3
community walkers. All the results of the analyses are presented in Table 3. For the outcome measures, a significant association was found between community ambulation and gait speed (p ¼ 0.001), the TUG (p ¼ 0.004) and the ABC scale (0.001). The results of all the analyses are presented in Table 3. Patients with higher scores for gait speed and balance self-efficacy were more likely to be community walkers. Also, patients who took less time to complete the TUG were more likely to be community walkers. Multivariate logistic regression Multivariate logistic regression examined which post-stroke variables were independently associated with community ambulation post-stroke. Age was entered into the analysis as a biological factor. Gait speed, TUG and the ABC scale were also included in the analysis, as they had been shown to be significantly associated with community ambulation in the binary logistic regression analysis (p 0.05). A two-tailed significance level of 0.05 was used for all the tests. The ABC Scale was the only variable found to be independently associated with community ambulation. The results of this analysis are presented in Table 4.
Discussion The main finding of this study was that balance self-efficacy was the only factor independently associated with community ambulation, with those with higher levels of balance self-efficacy more likely to be independent community walkers. Previous research has demonstrated that balance-self efficacy is independently associated with post-stroke activity and participation in chronic stroke patients [26]. Balance self-efficacy has also been found to be an independent predictor of community reintegration in older adults with chronic stroke [27]. In relation to community ambulation post-stroke, Robinson et al. [9] found that balance self-efficacy was the only personal factor which was strongly associated with both subjective and objective measures of participation in community walking. Balance self-efficacy refers to a person’s belief in their ability to undertake activities of daily living without losing their balance [28]. Considering the complex nature of community ambulation and the skills and attributes required, it is understandable that stroke patients with low levels of balance confidence may be less likely to attain independent community ambulation. It is possible that in a chronic stroke population, patients may have learned to manage their physical limitations, however the fear of having a fall may prevail. This may result in limitations in activity and participation in everyday activities, including community ambulation. Also, physiotherapy intervention following stroke tends to focus on the recovery of the physical aspects such as gait
Measurement 66 22 12 5 2 22.3
(13.4) (55) (30) (4) (2) (6.9)
25 (62.5) 15 (37.5) 33 (82.5) 7 (17.5) 29 (72.5) 11 (27.5)
Table 2. Summary statistics for outcome measures.
Outcome measure Gait speed (m/s), mean (SD) TUG (seconds), median (IQR) ABC Scale, median (IQR) FSS, mean (SD) HADS-A, mean (SD) HADS-D, mean (SD) TMT-B (s), median (IQR) SLCT, median (IQR)
Independent community walkers (n ¼ 23) 1.33 9.43 86.25 32.87 6.39 4.09 106 104
(0.2) (1.8) (15) (14) (4.4) (2.7) (114) (1)
Non-community walkers (n ¼ 17) 0.76 15.3 56.25 36.35 6.24 5.41 165 102
(0.3) (14.1) (14.1) (10.2) (3.4) (2.7) (187) (5)
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Table 3. Binary logistic regression analyses for relationship between community ambulation and personal and post-stroke factors. Variable
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Age Gender Use of walking aid Time since stroke No. of medications No. of co-morbidities MRS Falls History Gait Speed TUG ABC Scale FSS HADS-A HADS-D TMT-B SLCT
Regression coefficient
SE
p Value
EXP (B)
0.06 0.56 3.70 0.02 0.39 0.46 22.04 0.17 9.27 1.04 0.13 0.02 0.01 0.18 0.01 0.112
0.03 0.65 1.14 0.05 0.16 0.24 15 192 0.71 2.91 0.36 0.04 0.02 0.08 0.12 0.003 0.08
0.04* 0.39 0.001* 0.62 0.02* 0.06 0.99 0.82 0.001* 0.004* 0.001* 0.38 0.90 0.14 0.06 0.16
0.94 0.57 40.33 1.02 0.68 0.63 0.00 0.85 10 596 0.35 1.15 0.98 1.01 0.834 0.99 1.12
SE, standard error; p value, significance value; EXP(B), odds ratio. *p 0.05. Table 4. Multivariate logistic regression for community ambulation. Variable Age Gait speed TUG ABC Constant
B
SE
Wald
df
Sig
EXP (B)
0.13 13.06 0.03 0.17 15.98
0.10 9.56 0.48 0.09 17.80
1.64 1.87 0.004 3.90 0.80
1 1 1 1 1
0.20 0.17 0.95 0.05* 0.40
0.87 470 017 0.97 0.05 0.00
B, regression coefficient; df, degrees of freedom; SE, standard error; Sig, significance level; Wald, Wald statistic; EXP (B), odds ratio. *p 0.05.
and balance, with little input addressing balance self-efficacy. Future interventions addressing return to community ambulation post-stroke should consider methods of improving balance selfefficacy in the chronic stroke population. One example is the use of self-management programmes following stroke, which can promote changes in behaviour and self management skills, which in turn have a positive effect on self-efficacy [29]. Another key finding was that gait speed was not an independent predictor of community ambulation post-stroke. Similarly, walking balance was also found not to be independently associated with community ambulation on the multivariate analysis. This suggests that the task of community walking requires more complex attributes than physical ability alone. This is in keeping with the findings of the study by Lord et al. [1], who reported that while 80% of patients had regained independent gait and scored highly on mobility outcomes, nearly one-third were not able to walk unsupervised in their own community after their stroke. This finding has implications for the development of future outcome measures for community ambulation post-stroke. It supports the need to consider other factors such as balance selfefficacy, in conjunction with the physical factors, when developing new assessment tools, given the multi-factorial nature of community ambulation. In relation to the other factors explored in this study, no significant association was identified between community ambulation and fatigue, depression, executive function and visual neglect. This cohort of stroke patients were relatively high functioning (82.5% scoring 2 or less on MRS), with both the independent community walker group and the non-community walker group scoring below the threshold for impairment on the measures of fatigue, depression, executive function and visual neglect. These low scores would have affected the likelihood of finding an association with community ambulation.
There were several limitations of this current study. Firstly, the cross-sectional study design meant causal relationships between the factors and community ambulation could not be established. Secondly, the small sample size limits the generalisability of the study findings and did not allow for a greater number of variables to be included in the multiple logistic regression analysis. The study population were relatively young (mean age 66 years), with mild to moderate levels of disability, therefore may not be representative of the wider stroke population. Also, as they were all recruited from the one out-patient community Stroke Rehabilitation service and had the same service providers, this could potentially limit the wider generalisability of the results. Thirdly, the use of a self-administered questionnaire to measure community ambulation may have resulted in reporting bias. Finally, other factors which may influence community ambulation such as walking endurance, lower limb strength, dual task ability, patient motivation and environmental factors were not considered in this study. In conclusion, the findings of this study suggest that balance self-efficacy may be a stronger predictor than physical factors, such as gait speed and balance, in return to independent community ambulation in chronic stroke patients. However, community ambulation is a complex, multifactorial task and continued research is required to further establish the significant determinants of community ambulation post-stroke. This in turn will enable a more specific outcome measure to developed and validated, as well as the development of more effective interventions to address community ambulation post-stroke.
Acknowledgements The authors would like to thank the patients that participated in this study.
DOI: 10.3109/09638288.2015.1035460
Declaration of interest The authors report no declaration of interests.
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