Equipment provision after stroke: A scoping review of the use of personal care and mobility aids in rehabilitation

Abstract

Introduction

The aim of this scoping review was to examine and synthesise literature on adaptive equipment use for personal care and mobility after stroke.

Method

We searched databases including Medline, EMBASE, AMED, CINAHL and Scopus to February 2016. Two authors independently screened 789 titles, identifying 28 studies for inclusion in the review.

Results

Findings were grouped into four themes: (1) stroke-specific impairments and consequences for equipment use and training; (2) meaning of equipment for people with stroke; (3) cost of equipment after stroke; and (4) conflicts between equipment provision and models of stroke rehabilitation.

Conclusion

The wide range of impairments after stroke increases complexity of how people use equipment. Nonetheless, training needs and the relationship between social context, identity and equipment use are increasingly better understood,. The findings highlight a tension between practice that seeks to re-train function by ‘normal’ movement without equipment and restoration of function by using compensation strategies involving use of equipment. However, there is no evidence that compensation strategies impede recovery of physical abilities. High-quality evidence about costs of equipment after stroke, which could inform policy decisions, is urgently needed.

Keywords

Adaptive equipment assistive technology stroke disability services

Introduction

The number of people who survive a stroke is growing, and improving quality of life for this group is an increasingly urgent issue, alongside reducing the financial burden of stroke on healthcare systems (Feigin et al., 2014). In the United Kingdom (UK), the cost of stroke per year is estimated at over UK£7b (Wolfe et al., 2014). In New Zealand, the country of origin for this paper, annual costs due to stroke are now estimated to be NZ$700m (Stroke Foundation of New Zealand, 2010).

Providing adaptive equipment for people after stroke can be an effective means of reducing the burden of stroke. Adaptive equipment is defined as ‘equipment that enables an individual, who requires assistance, to perform the daily activities essential to maintain health and autonomy and to live as full a life as possible’ (World Health Organization (WHO), 2004: 10). Equipment provision is often a substantial component of occupational therapy practice for people with stroke, and fits with the objective of achieving client-centred occupational-focused goals, such as being able to have a shower or move around one's house (Gelderblom and de Witte, 2002). Equipment provision can be expensive. Consequently, public health services have established systems to manage costs, such as criteria for funding particular equipment and therapists specialising in certain types of equipment assessment. The administration of equipment provision policies and processes can be time-consuming, requiring the completion of extensive paperwork, and potentially lead to challenging interactions for therapists with clients, their family or health service funder. The time spent on these activities can itself lead to additional cost to the health service.

People who use equipment after stroke present with unique challenges, with many being discharged from rehabilitation with ongoing impairments and an expectation from family and healthcare staff that the abilities of the person with the stroke will continue to improve following community-based rehabilitation interventions (Pollock et al., 2014). As a result, the equipment needs of people with stroke can be expected to change over time, and the risk of adaptive equipment use inhibiting opportunities for further recovery of unaided physical function could be queried.

Furthermore, whether or not equipment will be used as a health professional intended, or used at all, is an important consideration when prescribing it. Equipment use after stroke has been associated with personal factors (Scherer et al., 2011) and the timing of the introduction of equipment. For instance, three distinct stages of equipment use have been proposed in relation to the optimal timing of powered mobility aids: reluctant use, strategic use and essential use (Mortenson et al., 2015). It has also been suggested that the relationship between how someone with a disability views themselves and their abilities, as well as their equipment, impacts on equipment use (Lund and Nygard, 2003).

There is increasing demand on occupational therapists to justify how they spend their time with people in stroke rehabilitation (Whitehead et al., 2014). Concurrently, clients’ loss of access to social interaction and life roles – areas that can be enabled by equipment provision – remain substantial issues for stroke rehabilitation services (Woodman et al., 2014). It is timely therefore to explore what research exists on optimising use of adaptive equipment by people who have experienced stroke. To address this, we conducted a scoping review to identify and synthesise research on the provision and use of adaptive equipment after stroke. A scoping review is a type of critical review that involves mapping key concepts underpinning an area in order to identify where gaps exist and to summarise findings (Arksey and O’Malley, 2005; Levac et al., 2010). Scoping reviews are more focal than general literature reviews, and are suited when the aim is to address broad research questions, where the work involves synthesis of studies of differing methodological design, or where key concepts of an area need to be clarified (Joanna Briggs Institute, 2015). In this review, we chose to focus solely on equipment for mobility or personal care after stroke, as research and reviews on equipment use have been criticised in the past for lack of attention to the clinical characteristics and needs of specific user groups (Auger et al., 2008). The key question addressed by this review was ‘what is known about the uptake and use of equipment for mobility and personal care by people after stroke?’

Method

Selection of studies

To be included in this review, articles needed to describe the findings from a study on equipment use involving people 16 years or older who had experienced a stroke, and be published in an English-language peer-reviewed journal. Included studies also needed to focus on adaptive equipment used for activities of daily living in the home (such as making a meal, using the toilet or bathing) or for mobility in either the home or community, and needed to report on the effectiveness or utility of this equipment from the perspectives of either equipment users or providers.

Articles were excluded if they focused primarily on equipment that was deemed highly unlikely to be routinely funded by public health systems in New Zealand for personal use. Decisions regarding what equipment a public health system might not fund was based on the authors' combined experiences of working in healthcare systems in New Zealand, Australia, the UK and Ireland. We excluded studies on robotics, housing modifications, communication devices (such as iPad and speech-enhancing devices), virtual reality technology, functional electrical stimulation, orthotics and prostheses, hearing aids or glasses, personal electronic devices, personal alarms and computers. We also excluded studies that focused primarily on the engineering, product design or the biomechanics of adaptive equipment. Finally, we excluded studies involving people who experienced transient ischaemic attacks without stroke. Year of publication, study methodology or study quality were not used to exclude articles.

Search strategy and article selection

We devised search strategies to identify relevant literature, and applied these to electronic databases including Medline, EMBASE and AMED in OVID, CINAHL in Ebsco, and Scopus. We also searched VISTA-Rehab (an archive dedicated to stroke-specific rehabilitation trials), the Cochrane Database of Systematic Reviews and TRIP. These databases were selected as they cover the majority of peer-reviewed allied health literature. Boolean terms were used to combine terms associated with the population, topic and outcomes of interest where appropriate (Table 1). The initial list of terms was subsequently added to in an iterative fashion as new search terms were identified (see Appendix 1 for an example of the electronic search strategies used). All databases were searched from inception to 5 February 2016.

Table 1.

Overview of search terms.

Terms related to population of interest (combined with the Boolean ‘OR’)	Terms related to equipment (combined with the Boolean ‘OR’)

Stroke CVA Cerebral vascular disease Cerebral infarct Cerebral haemorrhage	Assistive technology Adaptive equipment Assistive equipment Self-help devices Disability aids Assistive technology devices Special equipment Community equipment Quality-of-life technology Home aids Durable medical equipment Wheelchair/s

CVA, cerebral vascular accident.

Table 2.

Summary of study characteristics, analysis and results organised according to theme: stroke-specific impairments predicting use and related assessment and training considerations.

Reference(s)	Country	Research question	Sample	Study design	Analysis	Core finding
Lennon (1991)	UK	Explore the difference in cueing technique when training someone with stroke to transfer into a wheelchair.	1 person.	Single case comparing verbal prompting with patient self-cueing to complete an eight-step transfer to a wheelchair.	Mann Whitney U test.	Participant improved over time using both approaches, however his performance was marginally better using verbal self-cueing strategy (p < .01).
Mann et al. (1995)	USA	Describe the satisfaction and rates of ownership of equipment after stroke.	35 people.	Observational cohort study	Mean, SD and changes on key measures.	People were satisfied with 80% of their devices. Rate of device ownership rose over a two-year period (from mean = 14 items to mean = 16.7 items).
Prangrat et al. (2000)	USA	What is the difference between people with and without neglect using everyday objects after stroke?	12 people.	Descriptive mixed methods.	Mann-Whitney U test. Chi- square test on four case studies.	People with neglect used their equipment less than those without neglect (group without neglect used 87.5% of total devices they owned, group with unilateral neglect used 71.64% of devices).
Dawson and Thornton (2003)	UK	What difference does neglect make during a wheelchair obstacle training course?	2 people.	ABA single-subject experimental.	Mann-Whitney U test.	People with unilateral neglect reduced left-sided collisions when using their chair over the two weeks (p = .0001).
Laufer (2003)	Israel	What is the effect of mobility equipment on postural sway in people with stroke?	30 people with stroke.	Observational study about postural sway and mobility equipment.	Means and SD. ANOVA. Adjusted Tukey-Kramer tests.	Postural sway was reduced in all positions only with the quad cane.
Sorensen et al. (2003)	Denmark	What equipment is issued to people with stroke and how long they use equipment for?	155 people with stroke.	Two-year longitudinal cohort study.	Chi-squared analysis. Gamma analysis. t-test. SDs. ANOVA.	75% received equipment at discharge and 80% were still using equipment or had received more six months after discharge. Statistically significant difference in the number of equipment items issued where people had a home visit pre-discharge (p = .003).
Chiu and Man (2004)	Hong Kong	Does home-based training on equipment make a difference to functional ability, satisfaction with equipment and use of equipment?	53 people (n = 30 intervention; n = 23 control).	RCT with no concealed allocation to groups or blinding of assessors.	Descriptive statistics. t-test.	Intervention group showed improved function (t = 3.89; df = 51; p = .01) and satisfaction with equipment (t = 69.8; df = 29; p = .01) after intervention and they had a higher rate of using bathing equipment (96.7% compared to 56.5%).
Jutai et al. (2007)	Canada	What effect do clinical and functional variables have on equipment use?	316 people.	Longitudinal study estimating if clinical and functional features relate to equipment use.	Chi-squared tests. Spearman correlations. Logistic regression analyses.	Equipment use was significantly associated with mobility (OR = .97; 95% CI, .96–.98), functional independence (OR = .96; 95% CI, .95–.98), and cognitive status (OR = 1.46; 95% CI, 1.03–2.07).
Turton et al (2009)	UK	What effect does neglect have on collision rate when people are mobilising with equipment after stroke?	14 people with stroke and neglect. (n = 9 people with stroke but no neglect as control).	Observational study comparing mobility and collisions of people with stroke with and without neglect.	Mean deviations. One-sample t-tests. Repeated measures ANOVA.	Wheelchair users with neglect deviated to the left-of-centre while those walking deviated to the right. Collisions were more frequent in participants who were driving wheelchairs.
Punt et al. (2008)	UK	Does side of stroke lesion affect wheelchair navigation?	6 people.	Observational cohort study on navigation performance on wheelchair assessment course and doorway accuracy test.	Paired t-tests. Mean number of errors.	Errors were characterised by a strong asymmetrical bias. Mean of 3.35 for contra-lesional errors and only 0.4 for ipsi-lesional errors (F (1, 5) = 4.8; p < .05). Mean of errors = 3.75.
Mountain et al. (2010a)	USA	What difference does wheelchair training make on people achieving wheelchair skills after stroke?	10 people, 6 of whom had visuospatial neglect.	Prospective, uncontrolled, within-participant repeated-measures design on effect of wheelchair skills training.	2-sided paired signed-rank test.	25.5% of wheelchair skills were passed at baseline compared to 71.5% post-training (p = .002). Though people with neglect scored lower pre and post training, their scores improved with training to the same extent as those without neglect.
Mountain et al. (2010b)	USA	Examine the factors affecting the likelihood of being issued a wheelchair for a group of veterans with stroke.	100 people.	Retrospective cohort study of health records.	Nonparametric Wilcoxon rank-sum test.. Chi-squared analysis. Multivariate analyses. Fisher exact test. Logistic regression.	Adjusted odds ratios of using a wheelchair were 3.33 (95% CI, 1.33–8.33) for those with left-hemisphere versus right-hemisphere strokes (p = .010). 40% of people with stroke were using manual wheelchairs at discharge and 1% powered wheelchairs.
Punt et al. (2011)	UK	What effect does the position of the joystick have on navigational performance for people with stroke?	6 people (n = 4 in experiment 1 and n = 2 in experiment 2).	Observational study, two experiments on the effect of joystick position on navigational performance.	Standard error. Descriptive statistics. ANOVA in experiment 2.	A relatively simple intervention (for example, position of the joystick) can lead to improved navigational performance in patients with spatial neglect. (p < .025, F(1, 3) = 6.1).
Mountain et al. (2014)	USA	Does formal power wheelchair skills training increase wheelchair skills in people after stroke?	17 people with stroke (n = 9 intervention group n = 7 control).	Single blind RCT exploring effect of training on wheelchair users' skills.	Analysis of co-variance. Wilcoxon's rank-sum tests. χ² test. Fisher's exact tests.	People with stroke who receive formal powered wheelchair skills training improve their powered wheelchair skills to a significantly greater extent (30%) than participants who do not (0%).
Skolarus et al. (2014)	USA	What type of equipment and personal care do people receive after stroke, including unmet needs?	892 stroke survivors and n = 6709 as control group.	Cross-sectional study sampled from National Health and Aging Trends Study (2011).	Multinomial logistic regression models predicting type of accommodation and logistic regression models predicting unmet need.	Stroke survivors used more equipment and received more personal assistance and had greater unmet need than stroke-free controls. Measures of physical and cognitive capacity (both p < .01) were most important in predicting accommodations.
Kim and Kim (2015)	Korea	Investigate the relationship between fall efficacy, balance and use of assistive devices in people with stroke.	105 people with > 19 on Mini Mental State Examination.	Mixed methods: self-report questionnaire and face-to-face interviews.	Chi-squared. Fisher's exact tests. t-tests.	No significant difference between patients' fall experiences according to their use of assistive devices (χ² = 2.722, p = .099). Participants who used assistive devices had less balance ability and fall efficacy.* (t = 3.088, p = .003).

Fall Efficacy Scale is a self-report questionnaire that measures the perceived confidence of participants in task performance.

Table 3.

Summary of study characteristics, analysis and results organised according to theme: meaning and acceptance of equipment.

Reference(s)	Country	Research question	Stroke population	Study design	Analysis	Core finding
Hass et al. (1996)	Sweden	Explore the device selection process from a user perspective.	38 people with stroke.	Qualitative.	Descriptive qualitative analysis.	People with stroke reported little choice of equipment items and variable follow up, but did use their equipment as intended.
Gitlin (1998)	USA	Describe the early interpretation of devices by older people with stroke.	103 people in rehabilitation.	Qualitative.	Structured qualitative approach, using ethnographic and interpretative philosophy.	Dimensions identified were the operation and utility of equipment, social contexts and consequences, and attributions of cultural meanings of use.
Reid et al. (2001)	Canada	Identify the priorities and barriers to occupational performance for people using wheelchairs after stroke.	16 people with stroke.	Observational study on occupational performance when people with stroke used wheelchairs.	Mean, SD and frequency counts. Mann-Whitney U test. Wilcoxon signed-rank test.	Self-care was rated as a priority for both people with stroke and their caregiver's mobility difficulties inability to walk was reported to be a significant barrier to occupational performance.
Garber et al. (2002)	USA	Investigate the extent to which wheelchairs are used after stroke and how much they meet an individual's functional, psychological and social needs.	49 veterans.	Cross-sectional descriptive study.	Means, SDs and ranges. t-tests. Chi-squared analysis.	Fifteen people (31%) stopped using their wheelchairs due to improved function or using other aids, and had used them on average 13 weeks. Participants who kept using a wheelchair were satisfied with these items.
Barker et al. (2004)	Canada	Describe the lived experience of people with stroke who are prescribed wheelchairs.	10 people.	Qualitative descriptive study.	Constant comparative inductive method.	Three categories of acceptance of wheelchair use: reluctant, grateful and internal. Increased mobility, varied social response and loss of valued roles common to all categories.
Rudman et al. (2006)	Canada	Explore the experience of stroke survivors who use wheelchairs.	16 people with 15 caregivers.	Qualitative.	Inductive analysis with semi-structured in-depth interviews grounded theory principles.	Relationship exists between equipment use and one's identity, occupation, and having a sense of control.
Barker et al. (2006)	Canada	Explore the lived experience of people with stroke who have wheelchairs, mapping findings onto ICF*.	10 people.	Qualitative.	Re-interpretation of original data collected by Barker et al. (2004), mapping concepts onto the ICF* categories.	Wheelchairs were enablers of community participation among the participants but also created difficulties, such as restricting destinations and creating increased dependence on others.
Pettersson et al. (2006)	Sweden	Compare activity limitations and participation restrictions on a group with stroke before and after them receiving a power wheelchair.	32 people who used power wheelchairs.	Pre- and post-design comparing limitations and participation restrictions after receiving a powered wheelchair.	Effect size calculated per individual participant and per activity and participation domain in the ICF*.	Powered wheelchairs have a positive effect on activity and participation (ES = 2.6). Most problems categorised ‘Community, social and civic life’ according to the ICF, and the effect size in this domain was large (ES = 2.4).
Pettersson et al. (2007a)	Sweden	Evaluate the impact receiving a power wheelchair has on the quality of life of someone after stroke.	32 people who used power wheelchairs.	Pre- and post-design to investigate QoL and psychosocial impact of wheelchair.	Wilcoxon signed-rank test. within-group effect size. Mann- Whitney U test. Kruskal-Wallis test.	Improved quality of life was observed with respect to the items competence, independence, capability, quality of life, wellbeing, happiness, and self-esteem as well as usual activity dimension.
Pettersson et al. (2007b)	Sweden	Explore personal meaning associated with using equipment after stroke.	22 people.	Qualitative study using conversational interviews.	Hermeneutic-phenomenological approach.	Equipment use that was complex and contradictory. Equipment was seen as necessary but could evoke negative emotions because of restrictions implied by its use.

ICF, International Classification of Function.

Table 4.

Summary of study characteristics, analysis and results organised according to theme: cost of equipment.

Reference(s)	Country	Research question	Stroke population	Study design	Analysis	Core finding
Hass et al. (1995)	Sweden	Investigate the cost and impact of equipment after stroke.	38 people.	Prospective, observational study.	Regression analysis. Descriptive analysis.	Average cost per patient for was 204,409 Swedish kronor (SEK). Costs for accommodation were 70% of total. Equipment cost was 1% of the total.
Hesse et al. (1996)	Germany	Document what equipment is prescribed to people after stroke.	121 people.	Retrospective cross-sectional study.	Descriptive analysis.	194 (42%) received at least one item of equipment, mean of 2.1 items per person, totalling ECU* 690 per person. 85% reported over 50% satisfaction with services.
Gosman-Hedstrom et al. (2002a)	Sweden	Investigate differences in the type and cost of equipment supplied to people on a general ward and a stroke specialist unit.	249 people aged over 70 years.	Randomised uncontrolled comparison of equipment prescription on a stroke unit and a general ward	Frequency differences. Mann–Whitney U. Chi-square test.	Statistically significant difference (p = .05) in prescribing inexpensive equipment items between wards within the first three months, however, no significant difference in cost at later stages. Low cost items had a high impact on people's life.
Gosman-Hedstrom et al. (2002b).	Sweden	Question identical to Gosman-Hedstrom et al. (2002a).	249 people aged over 70 years.	Identical to design in Gosman-Hedstrom et al. (2002a).	Identical to analysis in Gosman-Hedstrom et al. (2002a).	Identical to results in Gosman-Hedstrom et al. (2002a).
Gosman-Hedstrom and Blomstrand (2003)	Sweden	Describe dependence and health related quality of life of people who used equipment after stroke.	121 who used equipment compared to 30 without.	Longitudinal cohort study.	Mann-Whitney U test. χ² test.	Many people who used equipment relied on others for personal care (63%) and this group reported significantly lower health-related quality of life (p ≤ .01).
Hubbard et al. (2006)	USA	Analysis of variance in wheelchair provision to veterans after stroke. Factors included sex, age and ethnicity/race.	52,309 veterans.	Cross-sectional, retrospective study, using three years of data from Veteran Health Affairs (VHA) database and Medicare.	Descriptive methods, ANOVA. Chi-square analyses. Logistic regression.	Hispanics (OR = 1.864), American Indians/Asians (OR = 1.585) and African Americans (OR = 1.360) were more likely than Caucasians to receive manual wheelchairs and Caucasians more likely to receive power wheelchairs and scooters.
Hubbard Winkler et al. (2010a)	USA	Investigate if provision of wheelchairs varied by regional administrative factors and client-related factors.	12,046 veterans.	Cross-sectional retrospective study examining regional variation in equipment	z scores. Logistic regression models were run for 8 of the 11 equipment categories.	Significant variation was observed in equipment provision, where patient characteristics accounted for only 6.2% of the variation. Local administrative region and disability severity accounted for equivalent amounts of the variation.
Hubbard Winkler et al. (2010b)	USA	Compare differences in cost and type of equipment between VHA and Medicare.	12,046 veterans.	Retrospective study to on equipment provision policy by comparing Medicare and VHA^†	Descriptive comparison of outcomes in two services frequency counts, mean, median and percentages.	Most equipment was for activities of daily living, followed by walkers/canes/crutches. VHA costs were lower than Medicare.
Hubbard Winkler et al. (2011)	USA	Describe the utilisation rates and related costs to veterans who receive equipment after stroke.	12,046 veterans.	Retrospective study using records at VHA to determine how provision of equipment relates to utilisation and costs of services post-stroke.	Bivariate (t-test) Multivariate analyses.	Receiving a manual wheelchair was associated with increased inpatient days and costs (both p < .001) and a power wheelchair with more inpatient (p = .03) and outpatient costs (p < .001). Getting a scooter was associated with more outpatient visits and costs (both p < .001).

*European Currency Unit – used as the unit of account of the European Community before being replaced by the Euro on 1 January 1999. ^†VHA does not limit provision of equipment to in-home use only whereas Medicare has this restriction.

The titles and abstracts of all articles from these database searches were screened independently by two authors. The first author screened all articles, while the co-authors provided a second independent opinion on the inclusion or exclusion of articles by screening a third of all articles each. Differences of opinion regarding inclusion of articles were resolved by discussion. Full text articles were sought when further information was required to make a selection decision.

Data extraction and synthesis

The full text of each included article was read and key messages were noted. Descriptive data from included studies were tabulated to compare content. Data were extracted on the research question(s), country of origin, methodology, population, key findings and how the results related to the scope of this review. As formal assessment of methodological quality is not performed in a scoping review (Joanna Briggs Institute, 2015), this process was not included as part of the selection or synthesis of literature. Similarities in the aims and results of studies were noted and grouped together to form themes, and a narrative synthesis of this literature arranged around these themes was completed to summarise the review findings.

Results

Study characteristics

Our search resulted in the identification of 789 potentially relevant articles after removing duplicate citations. On screening titles and abstracts, we excluded 724 papers, identifying 65 papers for full text retrieval. On review of these full text papers, we excluded another 27 articles, leaving 38 for inclusion in the review. Most studies were excluded because the equipment being studied was not specific to mobility or personal care. No studies were excluded at the screening stage because the technology was deemed unlikely to be funded by a public health system. A flow diagram for the selection of articles for inclusion is present in Figure 1 based on PRISMA guidelines (Moher et al., 2009). These 38 articles presented findings from 28 discrete research projects, with data from seven individual studies being presented across more than one publication.

Figure 1.

PRISMA flow diagram (Moher et al., 2009).

Of the included studies, 10 were conducted in the United States (USA) (Garber et al., 2002; Gitlin, 1998; Hubbard et al., 2006; Hubbard Winkler et al., 2010a, 2010b, 2011; Mann et al., 1995; Mountain et al., 2010a, 2010b, 2014; Prangrat et al., 2000; Skolarus et al., 2014), five in the UK (Barrett et al., 2001; Lennon, 1991; Punt et al., 2008, 2011; Turton et al., 2009; Tyson and Rogerson, 2009), three in Sweden (Gosman-Hedstrom and Blomstrand, 2003; Gosman-Hedstrom et al., 2002a, 2002b; Pettersson et al., 2006, 2007b, 2007a), three in Canada (Barker et al., 2004, 2006; Jutai et al., 2007; Reid et al., 2001; Rudman et al., 2006), and one each in Hong Kong (Chiu and Man, 2004), Switzerland (Allet et al., 2009), Germany (Hesse et al., 1996), Denmark (Sorensen et al., 2003), Israel (Laufer, 2003) and Korea (Kim and Kim, 2015). Four studies were randomised control led trials (RCTs) (Barrett et al., 2001; Chiu and Man, 2004; Mountain et al., 2014; Tyson and Rogerson, 2009), while others primarily used either descriptive designs such as cross-sectional or cohort frameworks, at times in combination with economic evaluations, or they consisted of qualitative research. No systematic reviews specific to adaptive equipment use for people after stroke were found.

Overview of review findings

We organised the findings related to equipment use after stroke from the studies into four key areas: (1) stroke-specific impairments and consequences for equipment use and training; (2) meaning of equipment for people with stroke; (3) cost of equipment after stroke; and (4) conflicts between equipment provision and models of stroke rehabilitation (see Tables 2 –5).

Table 5.

Summary of study characteristics, analysis and results organised according to theme: equipment use conflicting with stroke rehabilitation approaches.

Reference(s)	Country	Research question	Sample	Study design	Analysis	Core finding
Barrett (2001)	UK	What effect does encouraging early propulsion after stroke have on function, quality of life, tone and length of stay?	40 people (n = 21 intervention group, n = 19 control).	Pilot randomised trial.	Descriptive comparison of being encouraged or discouraged to self-propel during early rehabilitation.	Both groups had similar results for mood and for tone as well as QoL, satisfaction with discharge and care needs.
Tyson and Rogerson (2009)	UK	What effect do walking devices have on functional mobility, walking impairments and patients' perspectives?	20 people.	Randomised crossover trial.	Friedman test. 1-way ANOVA. Mann-Whitney U tests. Paired t-tests.	Functional mobility improved with all equipment (p < .0001–.005; effect sizes 1.68–0.52; number needed to treat = 2–5). Walking impairments were unchanged (p < .800–.988). People reported that equipment improved their walking, confidence and safety, preferring to walk with equipment than delay walking to achieve a normative gait pattern.
Allet et al. (2009)	Switzerland	What effect do three different walking aids have on walking capacity, gait and patient satisfaction?	25 people in early stages of mobility rehabilitation.	Cohort study.	Regression modelling for repeated measures. Spearman's correlation.	Walking distance was greatest with simple cane with ergonomic handgrip (mean walking distance, 115.48 m), followed by the four-point cane (mean walking distance, 101.40 m; p = .021). Gait velocity was higher with ergonomic hand grip cane than four-point cane (mean difference, 3.58 cm/s; p = .018). Simple cane with ergonomic handgrip was patients' preferred aid.

Stroke-specific impairments and consequences for equipment use and training

The impairments that result from stroke are complex and broadly influence the extent and type of equipment used (Garber et al., 2002). Many who use equipment have poor balance and are at high risk of injury from falls (Kim and Kim, 2015); and people with stroke who need equipment can have difficulties getting out of their house (12.4%), as well as moving around inside their house (11.9%) (Skolarus et al., 2014). People often experience cognitive difficulties after stroke though one longitudinal study reported that having better cognition after stroke was reliably associated with equipment use (OR = 1.46; 95% CI, 1.03–2.07) (Jutai et al., 2007). From this literature, it appears that the wide range of impairments that can be associated with having a stroke increase the complexity of how people interact with equipment.

In one of the few longitudinal studies of equipment use after stroke, Sorensen et al. (2003) reported that 75% of 155 consecutive clients discharged from a Danish hospital with stroke had received equipment. Almost all of those followed up at 6 months and between 3 and 5 years were using assistive equipment or environmental modifications (93%; 71/76). The mean number of items of equipment provided was 4.4 (SD = 2.39). A total of 83% (96/116) were prescribed mobility aids, and 63% (73/116) rated bathing and mobility aids as their most valued items, though many (37.9%; 44/116) had equipment prior to stroke. These researchers also noted, similarly to others (Mann et al., 1995), that the amount of adaptive equipment owned can increase in the years post stroke.

Perceptual impairments that result in visual–spatial neglect commonly occur when people have a right hemisphere stroke, and introduce a significant and often poorly understood challenge when it comes to equipment provision (Prangrat et al., 2000). People with neglect tend to use the equipment they are issued less (Prangrat et al., 2000), have more wheelchair collisions (Turton et al., 2009), and have more difficulties navigating obstacles when using their mobility equipment, than those without neglect (Punt et al., 2008; Punt et al., 2011). People with left-hemisphere stroke are more likely to receive a wheelchair at discharge from hospital than those with right-hemisphere stroke (OR = 3.33; 95% CI, 1.33–8.33) (Mountain et al., 2010b). The presence of neglect, therefore, may impact on the provision and uptake of equipment.

Several studies have examined the training needs of people with neglect after stroke to establish how to maximise benefits from equipment for this group. In a small cohort study exploring the outcome of a wheelchair skills training programme for 10 people with stroke, Mountain et al. (2010a) found that even though people with neglect scored lower on a powered wheelchair skills test before and after training compared to the group without neglect, the scores of both groups improved – and improved to the same extent. Similarly, Dawson and Thornton (2003) found that driving accuracy improved for two people with stroke after practice navigating a wheelchair obstacle course over 2 weeks, while Punt et al. (2011) demonstrated that simply changing the position of a power chair joystick from one side to the other had a significantly positive effect for four people with neglect in terms of their ability to navigate with their wheelchair (p < .025).

Home-based training also appears to improve ability and satisfaction with equipment use. In a RCT in Hong Kong, Chiu and Man (2004) compared additional (2–3 visits) home-based training in equipment use (n = 30) to hospital-based training only (n = 27) for people after stroke. A significant increase in both the users' functional abilities (t = 3.89; df = 51; p = .01) and their satisfaction with the equipment (t = 69.8; df = 29; p = .01) was observed. Similarly, other studies also found that more in-home training, in the form of pre-discharge visits, increased the uptake of equipment use by people with stroke (Hesse et al., 1996; Sorensen et al., 2003). Finally, people with stroke who receive formal powered wheelchair skills training appear to improve their wheelchair skills to a greater extent than those who do not (Mountain et al., 2014). Other suggested strategies have included encouraging self-cueing rather than therapist-led prompting when practising transfers to and from a wheelchair (Lennon, 1991) and provision of a four-point cane to reduce postural sway in people mobilising (Laufer, 2003).

Meaning of equipment for people with stroke

Since the mid-1990s, researchers began including data on the experiences of users of equipment, often as an adjunct to other study objectives such as exploring perceptions of life after stroke (Hass et al., 1996; Mann et al., 1995). Later, the question of experiences of equipment users after stroke became a more central concern. In one of the first qualitative studies to explore the meaning of equipment use for people after stroke (n = 103), Gitlin (1998) identified six dimensions of client concerns, namely: (1) the operation of devices; (2) the utility of devices; (3) transitional perspective (equipment offering an adapted way of doing a task); (4) the learning curve associated with device use; (5) the emotional response to using a device; and (6) value dilemmas evoked by equipment. This study also suggested that perceptions of equipment could be culturally related.

Exploration of the relationship between social context and consequences of equipment use have since been expanded upon, particularly in the area of wheelchair use after stroke (Barker et al., 2004; Pettersson et al., 2007b; Rudman et al., 2006). A key finding is that people with stroke appear to rank the value and use of a piece of equipment more highly when the equipment is explicitly linked to a social interaction or occupational performance goal (Pettersson et al., 2007a; Reid et al., 2001). Ongoing use and development of measures such as the Canadian Occupational Performance Measure (Reid et al., 2001) and the Psychosocial Impact of Assistive Devices Scale (Pettersson et al., 2007a) have been discussed in the publications in this review as being useful to evaluate the personal meaningfulness of adaptive equipment.

Cost of equipment after stroke

There is little published information on the actual cost of providing adaptive equipment to people after stroke and no research was found on cost-effectiveness of equipment for people with stroke specifically. While we identified some studies that reported on the cost of equipment after stroke in individual countries, it was difficult to generalise from these studies because of differences in the value of currency between countries and over time, differences in the relative value of costs compared to local economies, and differences in the cost of this equipment compared to overall healthcare or rehabilitation costs. However, one Swedish study indicated that equipment contributed approximately 1% of total healthcare cost following stroke, with an average of 2,307 Swedish kronor (being spent per person on adaptive equipment in the first year of stroke recovery (Hass et al., 1995)). Higher costs of equipment were associated with greater disability. In a retrospective study of people discharged with equipment from a stroke unit in Germany, Hesse et al. (1996) reported that 690 European Currency Units¹ were spent per person with stroke receiving equipment. In another Swedish study, no difference was found between the cost of equipment issued on a specialist stroke ward compared to a general medical ward, and the overall cost of equipment was reported as low compared to other stroke-related costs (Gosman-Hedstrom et al., 2002a). The authors of this study concluded that health-related quality of life was lower for people who used equipment, however this was attributed to having increased dependency on others, rather than being caused by the presence of equipment (Gosman-Hedstrom and Blomstrand, 2003).

One large cross-sectional cohort study explored the cost and funding policies regarding assistive devices for 12,046 people entitled to support from Veteran's Affairs and/or Medicare in the USA (Hubbard Winkler et al., 2010a). Equipment provision varied significantly by administrative region and by disability severity (Hubbard Winkler et al., 2010b), and funding for in-home equipment alone (as opposed to funding for equipment for outside the house) did not necessarily lead to decreased costs (Hubbard Winkler et al., 2010b). This variation in equipment provision suggests that administration policies and processes have influence over provision of equipment at a clinical level. Earlier research by Hubbard et al. (2006) strongly indicated that there was inequity with wheelchair provision attributable to ethnic background, where Hispanics (OR = 1.864), African Americans (OR = 1.360) and American Indians/Asians (OR = 1.585) were more likely than Caucasians to receive standard wheelchairs, rather than powered wheelchairs or scooters. With the exception of research conducted by Hubbard Winkler et al. (2011) in recent years, the lack of high-quality evidence about the cost of equipment after stroke makes policy decisions in this area challenging, and means it is difficult to quantify the degree of unmet need (Skolarus et al., 2014).

Conflicts between equipment provision and models of stroke rehabilitation

This theme was identified in just three of the articles reviewed, but was significant in that these studies used experimental designs and include two of the four RCTs identified and included in this review. Barrett et al. (2001) examined whether encouraging people to self-propel a wheelchair in the acute phase (generally within the first month) of stroke rehabilitation risked worsening their spasticity. In their pilot RCT (n = 21 intervention group, n = 19 control group), they found that there was no evidence that early self-propelling increased spasticity. In an observational study with 25 participants, Allet et al. (2009) found that use of a standard walking stick resulted in greater walking distance on a 6 minute walking test compared to the same patient walking with a Nordic walking pole or a four-point cane.

Relatedly, in a multi-site crossover RCT with 20 non-ambulant clients undergoing mobility retraining after stroke, Tyson and Rogerson (2009) found that participants preferred to walk as soon as possible rather than work on what might be considered normal gait patterns, irrespective of the walking device used. Significant improvement in mobility was observed with all assistive devices (p > .0001–.005; effect sizes: 1.68–0.52). This finding supported the idea that the benefits of providing adaptive equipment early after stroke to increase a person's function outweighs potential disadvantages that may or may not actually exist related to impeding recovery of ‘normal’ movement patterns.

Discussion

This scoping review examined and synthesised concepts from published research on equipment provision for personal care and mobility when people have had a stroke. Broadly speaking, research to the present day has focused on estimating the frequency of equipment use and non-use (Gosman-Hedstrom et al., 2002b; Hass et al., 1995; Sorensen et al., 2003), and on exploring patient experiences of equipment provision and use (Barker et al., 2006; Gitlin, 1998; Pettersson et al., 2006), contributing to better understanding of the utility of equipment after stroke. The methods used to address research questions in this field have become ever more sophisticated, including analysis of large datasets to develop models to predict equipment use according to demographic characteristics (Hubbard Winkler et al., 2011) and the importance of the perspective of equipment users has been increasingly explored (Barker et al., 2004; Pettersson et al., 2007b; Rudman et al., 2006). An indication of the development of interest in this area is the emergence over the last 15 years of academic journals dedicated to the design and implementation of assistive technology.

Visual–spatial neglect, in particular, increases the complexity of how people interact with equipment; however, studies on this topic demonstrate that even in the presence of neglect people can learn to use adaptive equipment with adequate training. Home visits with the purpose of training in equipment use were particularly highlighted as valuable, enhancing users' understanding of equipment and improving the fit of equipment for users' needs (Chiu and Man, 2004; Skolarus et al., 2014). Learning happens best in an ecologically meaningful environment such as one's home and neighbourhood (Jones et al., 2013; Logan et al., 2004). However, findings from this scoping review indicate that most training on equipment use (reported empirically) tends to occur in hospital settings (Mountain et al., 2014; Punt et al., 2011). Although an economic analysis on the efficacy of home visits in relation to equipment provision is warranted, current research suggests that home visits (Sorensen et al., 2003) or home-based training on equipment after discharge (Chiu and Man, 2004) are beneficial.

The relationship between social context and consequences of equipment use have been a major focus of research, particularly in the area of wheelchair use after stroke. The findings of this review suggest that it may be important to relate equipment use to personally meaningful roles and occupations, which can only occur when therapists have a clear understanding of what these are from clients' perspectives. When a goal is established regarding social interaction or occupational performance, people are more likely to overcome initial negative feelings towards equipment (Pettersson et al., 2007a; Reid et al., 2001). The ambivalence that people can go through about accepting or using equipment is nuanced. Nevertheless, when health professionals pay attention to social and occupational contexts in order to recommend equipment best suited to client goals, consider the timeliness of introducing equipment, and are aware of the connection between equipment and valued social and cultural activities, use and satisfaction with equipment is likely to be enhanced.

Research findings identified in this review add clarity to the long-running debate on whether to introduce equipment early in stroke rehabilitation. Several studies have concluded that providing equipment for mobility early after stroke and during the impairment reduction phase of rehabilitation, at a minimum, does no harm (Barrett et al., 2001) and possibly improves functional gain during rehabilitation (Allet et al., 2009; Tyson and Rogerson, 2009), a position endorsed by other research (Pollock et al., 2014; Zorowitz, 2011). These findings challenge the assertion that recovery of ‘normal’ movement after stroke is preferable over achievement of functional outcomes such as speed and distance when walking, which is promoted in some approaches to rehabilitation for stroke (Pollock et al., 2014). Such approaches can explicitly advocate minimal use of equipment, based on the assumption that it may limit recovery of normal movement (Lennon et al., 2001). A tension for all rehabilitation professionals has been the issue of whether to focus therapy on retraining of physical abilities after stroke or on pursuit of functional outcomes by providing compensatory strategies, with the concern that the compensatory strategy may impede physical recovery (Ferrarello et al., 2011). Findings from this review highlight the small but growing body of evidence supporting the view that early mobilisation with equipment does not appear to be detrimental to physical recovery, and may even facilitate it. This finding suggests that therapists can have confidence using rehabilitation and compensatory strategies alongside each other in practice.

Scoping reviews are subject to the limitations of all reviews, where pertinent research may be missed during the search process, and where the conclusions of the review are dependent on the relevance and usefulness of the underlying research studies. Furthermore, as no rating of quality or risk of bias occurs in a scoping review, recommendations for practice cannot be graded (Joanna Briggs Institute, 2015). The heterogeneity of the literature in this area was unsurprising, though this feature did make comparisons difficult, meaning that decisions on synthesis were therefore narrative and pragmatic. Some populations received greater attention across studies, such as veterans (Garber et al., 2002; Hubbard Winkler et al., 2011), which may impact on the generalizability of these findings to other populations. Our review process also did not involve consultation with end-users of equipment – a recommended step to further enhance the value of review findings (Levac et al., 2010). Most research studies in this review excluded people with moderate and severe cognitive and communication difficulties, meaning that the findings may not apply to this group.

The purpose of a scoping review is to map a body of literature on a topic (Pham et al., 2014) and this review achieved that purpose. The search terms, search strategy and data extraction were conducted using an iterative and team approach, and findings have been related to policy and further research, as advocated by Levac et al. (2010). The search terms were tested and changed to ensure breadth and accuracy in the search strategy. No other review specific to equipment use and stroke was identified, and the findings, particularly about tailored training enhancing recovery after stroke and taking a pragmatic approach to when and how equipment is introduced to people, appear to be congruent with current literature on stroke rehabilitation approaches (Pollock et al., 2014).

Experimental studies are required to test emerging ideas about the best approaches to equipment prescription and use after stroke. Questions that could be addressed by such studies include assessing the impact of the preference of users on uptake of equipment and testing the extent to which contextualised training with equipment affects functional outcomes. Large, population-based surveys are also required to gather basic information on the current state of play regarding who uses adaptive equipment after stroke, at what cost and to what ends. Alongside this type of evidence, information on the environmental and occupational factors affecting equipment use is required. Based on findings from this scoping review the current research in this area would not be compatible with a systematic review approach to research synthesis at this point as there are not enough studies involving sufficiently similar and precise research questions to enable such a review. There would also be inadequate data to conduct a meta-analysis on any topic related to equipment use after stroke.

Adaptive equipment prescription can be meaningfully modelled with clinical and socio-demographic variables (such as income and ethnicity) to predict provision and use of equipment (Hubbard Winkler et al., 2010a; Jutai et al., 2007; Skolarus et al., 2014) and this approach to identifying inequities and addressing gaps is likely to continue to evolve, with electronic data management processes increasingly providing greater opportunities for this to happen. The lack of high-quality evidence about cost of equipment after stroke means that policy decisions in this area tend to be based on ideology rather than evidence. Thus, further economic analyses are recommended. Future research on how to optimise the timing and conditions for training on equipment use after stroke is also warranted, and use of outcome measures that focus on the meaning of equipment to the user may also help with furthering clinical knowledge and establishing the impact of equipment use after stroke.

Conclusion

Providing adaptive equipment early in stroke rehabilitation appears to have more advantages than disadvantages, and there are some specific techniques being developed to maximise how people with stroke receive training to use equipment. Receiving support in one's own home environment appears to encourage uptake of equipment, possibly as therapists' assessing in the home setting enables them to have a greater understanding of a client's valued roles and routines. Having a positive self-image of themselves using equipment and awareness of the social context and occupational goals of their clients were indicated in this review as possibly important influences on whether people will use equipment after stroke. It appears that providing equipment provides more opportunities during rehabilitation than not and, finally, the cost of equipment in relation to stroke care remains unclear, making it difficult to address important questions about cost-effectiveness of supplying equipment in a public health system.

Key findings

Equipment after stroke may be most useful and used when tailored to people's participation or occupational goals;

More work is required to understand the best conditions to optimise equipment training;

Equipment in stroke rehabilitation probably provides more advantages for recovery than disadvantages.

What the study has added

Equipment appears to promote quality of life for people after stroke when linked to participation or occupational goals. Lack of information on how equipment affects people's occupational performance, as well as cost to the health service, makes evidence based recommendations challenging.

Footnotes

Research ethics

No ethical approval was required for this study

Declaration of conflicting interests

The authors confirm that there is no conflict of interest.

Funding

This work was supported by a Publishing Bursary from the University of Otago, Postgraduate services and a University of Otago PhD scholarship grant.

Note

Appendix 1: Search strategy example

References

Allet

Leemann

Guyen

(2009) Effect of different walking aids on walking capacity of patients with poststroke hemiparesis. Archives of Physical Medicine and Rehabilitation 90: 1408–1413.

Arksey

O'Malley

(2005) Scoping studies: Towards a methodological framework. International Journal of Social Research Methodology 8: 19–32.

Auger

Demers

Gélinas

(2008) Powered mobility for middle-aged and older adults: Systematic review of outcomes and appraisal of published evidence. American Journal of Physical Medicine and Rehabilitation 87: 666–680.

Barker

Reid

Cott

(2004) Acceptance and meanings of wheelchair use in senior stroke survivors. American Journal of Occupational Therapy 58: 221–230.

Barker

Reid

Cott

(2006) The experience of senior stroke survivors: Factors in community participation among wheelchair users. Canadian Journal of Occupational Therapy 73: 18–25.

Barrett

Watkins

Plant

(2001) The COSTAR wheelchair study: A two-centre pilot study of self-propulsion in a wheelchair in early stroke rehabilitation. Collaborative stroke audit and research. Clinical Rehabilitation 15: 32–41.

Chiu

CWY

Man

DWK

(2004) The effect of training older adults with stroke to use home-based assistive devices. OTJR: Occupation, Participation and Health 24: 113–120.

Dawson

Thornton

(2003) Can patients with unilateral neglect following stroke drive electrically powered wheelchairs? The British Journal of Occupational Therapy 66: 496–504.

Feigin

Forouzanfar

Krishnamurthi

(2014) Global and regional burden of stroke during 1990–2010: Findings from the Global Burden of Disease Study 2010. The Lancet 383: 245–255.

10.

Ferrarello

Baccini

Rinaldi

(2011) Efficacy of physiotherapy interventions late after stroke: A meta-analysis. Journal of Neurology, Neurosurgery and Psychiatry 82: 136–143.

11.

Garber

Bunzel

Monga

(2002) Wheelchair utilization and satisfaction following cerebral vascular accident. Journal of Rehabilitation Research and Development 39: 521–534.

12.

Gelderblom

de Witte

(2002) The assessment of assistive technology outcomes, effects and costs. Technology & Disability 14: 91–94.

13.

Gitlin

(1998) Emerging concerns of older stroke patients about assistive device use. The Gerontologist 38: 169–180.

14.

Gosman-Hedstrom

Blomstrand

(2003) Dependence and health-related quality of life in elderly people using assistive devices after acute stroke: The Gopteborg 70+ Stroke Study. Technology & Disability 15: 247–257.

15.

Gosman-Hedstrom

Claesson

Blomstrand

(2002a) Assistive devices in elderly people after stroke: A longitudinal, randomized study—The Göteborg 70+ Stroke Study. Scandinavian Journal of Occupational Therapy 9: 109–118.

16.

Gosman-Hedstrom

Claesson

Blomstrand

(2002b) Use and cost of assistive technology the first year after stroke. International Journal of Technology Assessment in Health Care 18: 520–527.

17.

Hass

Freden-Karlsson

Persson

(1996) Assistive technologies in stroke rehabilitation from a user perspective. Scandinavian Journal of Caring Sciences 10: 75–80.

18.

Hass

Persson

Brodin

(1995) Assessment of rehabilitation technologies in stroke: Outcomes and costs. International Journal of Technology Assessment in Health Care 11: 245–261.

19.

Hesse

Gahein-Sama

Mauritz

(1996) Technical aids in hemiparetic patients: Prescription, costs and usage. Clinical Rehabilitation 10: 328–333.

20.

Hubbard

Fitzgerald

Reker

(2006) Demographic characteristics of veterans who received wheelchairs and scooters from Veterans Health Administration. Journal of Rehabilitation Research and Development 43: 831–844.

21.

Hubbard Winkler

Cowper Ripley

(2010a) Demographic and clinical variation in veterans health administration provision of assistive technology devices to veterans poststroke. Archives of Physical Medicine and Rehabilitation 91: 369–377.

22.

Hubbard Winkler

Vogel

Hoenig

(2010b) Cost, utilization, and policy of provision of assistive technology devices to veterans poststroke by Medicare and VA. Medical Care 48: 558–562.

23.

Hubbard Winkler

Cowper Ripley

(2011) Medical utilization and cost outcomes for poststroke veterans who receive assistive technology devices from the Veterans Health Administration. Journal of Rehabilitation Research and Development 48: 125–132.

24.

Joanna Briggs Institute (2015) Methodology for JBI Scoping Reviews, University of Adelaide, South Australia: The Joanna Briggs Institute.

25.

Jones

Riazi

Norris

(2013) Self-management after stroke: Time for some more questions? Disability and Rehabilitation 35: 257–264.

26.

Jutai

Coulson

Teasell

(2007) Mobility assistive device utilization in a prospective study of patients with first-ever stroke. Archives of Physical Medicine and Rehabilitation 88: 1268–1275.

27.

Kim

(2015) Falls and use of assistive devices in stroke patients with hemiparesis: Association with balance ability and fall efficacy. Rehabilitation Nursing 40: 267–274.

28.

Laufer

(2003) The effect of walking aids on balance and weight-bearing patterns of patients with hemiparesis in various stance positions. Physical Therapy 83: 112–122.

29.

Lennon

(1991) Wheelchair transfer training in a stroke patient with neglect: A single case study design. Physiotherapy Theory & Practice 7: 51–55.

30.

Lennon

Baxter

Ashburn

(2001) Physiotherapy based on the Bobath concept in stroke rehabilitation: A survey within the UK. Disability and Rehabilitation 23: 254–262.

31.

Levac

Colquhoun

O'Brien

(2010) Scoping studies: Advancing the methodology. Implementation Science 5: 1–9.

32.

Logan

Gladman

Avery

(2004) Randomised controlled trial of an occupational therapy intervention to increase outdoor mobility after stroke. BMJ 329: 1372.

33.

Lund

Nygard

(2003) Incorporating or resisting assistive devices: Different approaches to achieving a desired occupational self-image. Occupational Therapy Journal of Research: Occupation, Participation and Health 23: 67–75.

34.

Mann

Hurren

Tomita

(1995) A follow-up study of older stroke survivors living at home. Topics in Geriatric Rehabilitation 11: 52–66.

35.

Moher

Liberati

Tetzlaff

(2009) Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Med 6(7): e1000097, .

36.

Mortenson

Hammell

Luts

(2015) The power of power wheelchairs: Mobility choices of community-dwelling, older adults. Scandinavian Journal of Occupational Therapy 22: 394–401.

37.

Mountain

Kirby

Eskes

(2010a) Ability of people with stroke to learn powered wheelchair skills: A pilot study. Archives of Physical Medicine and Rehabilitation 91: 596–601.

38.

Mountain

Kirby

MacLeod

(2010b) Rates and predictors of manual and powered wheelchair use for persons with stroke: A retrospective study in a Canadian rehabilitation center. Archives of Physical Medicine and Rehabilitation 91: 639–643.

39.

Mountain

Kirby

Smith

(2014) Powered wheelchair skills training for persons with stroke: A randomized controlled trial. American Journal of Physical Medicine and Rehabilitation 93: 1031–1043.

40.

National Health and Aging Trends Study (2016) National Health and Aging Trends Study. Available at: http://www.nhats.org/ (accessed 20 August 2016).

41.

Pettersson

Ahlstrom

Tornquist

(2007a) The value of an outdoor powered wheelchair with regard to the quality of life of persons with stroke: A follow-up study. Assistive Technology 19: 143–153.

42.

Pettersson

Appelrosi

Ahlstrom

(2007b) Lifeworld perspectives utilizing assistive devices: Individuals, lived experience following a stroke. Canadian Journal of Occupational Therapy 74: 15–26.

43.

Pettersson

Tornquist

Ahlstrom

(2006) The effect of an outdoor powered wheelchair on activity and participation in users with stroke. Disability & Rehabilitation: Assistive Technology 1: 235–243.

44.

Pham

Rajic

Greig

(2014) A scoping review of scoping reviews: Advancing the approach and enhancing the consistency. Research Synthesis Methods 5: 371–385.

45.

Pollock A, Baer G, Campbell P, et al. (2014) Physical rehabilitation approaches for the recovery of function and mobility following stroke. Cochrane Database of Systematic Reviews: Art. No. CD001920. DOI 10.1002/14651858.CD001920.pub3.

46.

Prangrat

Mann

Tomita

(2000) Impact of unilateral neglect on assistive device use. Technology & Disability 12: 53–69.

47.

Punt

Kitadono

Hulleman

(2008) From both sides now: Crossover effects influence navigation in patients with unilateral neglect. Journal of Neurology, Neurosurgery and Psychiatry 79: 464–466.

48.

Punt

Kitadono

Hulleman

(2011) Modulating wheelchair navigation in patients with spatial neglect. Neuropsychological Rehabilitation 21: 367–382.

49.

Reid

Hebert

Rudman

(2001) Occupational performance in older stroke wheelchair users living at home. Occupational Therapy International 8: 273–286.

50.

Rudman

Hebert

Reid

(2006) Living in a restricted occupational world: The occupational experiences of stroke survivors who are wheelchair users and their caregivers. Canadian Journal of Occupational Therapy 73: 141–152.

51.

Scherer

Craddock

Mackeogh

(2011) The relationship of personal factors and subjective well-being to the use of assistive technology devices. Disability and Rehabilitation 33: 811–817.

52.

Skolarus

Burke

Freedman

(2014) The role of accommodations in poststroke disability management. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences 69: S26–S34.

53.

Sorensen

Lendal

Schultz-Larsen

(2003) Stroke rehabilitation: Assistive technology devices and environmental modifications following primary rehabilitation in hospital - a therapeutic perspective. Assistive Technology 15: 39–48.

54.

Stroke Foundation of New Zealand and New Zealand Guidelines Group (2010) New Zealand Clinical Guidelines for Stroke Management 2010, Wellington, New Zealand: Stroke Foundation of New Zealand.

55.

Turton

Dewar

Lievesley

(2009) Walking and wheelchair navigation in patients with left visual neglect. Neuropsychological Rehabilitation 19: 274–290.

56.

Tyson

Rogerson

(2009) Assistive walking devices in nonambulant patients undergoing rehabilitation after stroke: The effects on functional mobility, walking impairments, and patients' opinion. Archives of Physical Medicine and Rehabilitation 90: 475–479.

57.

Whitehead

Fellows

Sprigg

(2014) Who should have a pre-discharge home assessment visit after a stroke? A qualitative study of occupational therapists' views. British Journal of Occupational Therapy 77: 384–391.

58.

World Health Organization (2004) Ageing and health technical report: A glossary of terms for community health care and services for older persons. Report no. WHO/WKC/Tech.Ser./04.2. Geneva: World Health Organization.

59.

Wolfe

Rudd

McKevitt

(2014) Modelling, evaluating and implementing cost-effective services to reduce the impact of stroke. Programme Grants for Applied Research 2(2): 1–18.

60.

Woodman

Riazi

Pereira

(2014) Social participation post stroke: A meta-ethnographic review of the experiences and views of community-dwelling stroke survivors. Disability and Rehabilitation 36: 2031–2043.

61.

Zorowitz

(2011) Stroke rehabilitation: An overview of existing guidelines and standards of care. European Neurological Review 6: 170–174.