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Fall Prevention in Post-stroke Patients: The Power of Social Interactions

Fall Prevention in Post-stroke Patients: The Power of Social Interactions
Introduction:
Stroke is a health priority in New Zealand (NZ) as it is the most common cause of disability and affects approximately 8000-9000 individuals per year. Currently, around 50,000 individuals live with the ramifications of stroke in NZ and costs approximately $700 million per annum (Ranta, 2018). Disabilities due to stroke include poor balance, mobility, and increased fall risks. In 2010, the financial consequence of falls in NZ was $1,855.8 million (Robertson & Campbell, 2012). Furthermore, falls are commonly experienced by post-stroke patients where 40-73% of such population fall most frequently within the first 6-12 months period of recovery and have an increased likelihood to fall again (Weerdesteyn, Niet, van Duijnhoven, & Geurts, 2008). During such period, patients actively re-integrate into the community and are likely to experience unexpected perturbations that challenge their stability (Sherrington & Tiedemann, 2015). Falls have severe physical and psychosocial consequences. Physical injuries range from bruises to hip fractures, with only 38% of individuals experiencing a hip fracture regaining independent mobility, leading to increased disability and risk of morbidity and mortality (Weerdesteyn et al., 2008). Moreover, there are psychosocial consequences of falls as 88% of individuals who fell develop a fear of falling (Weerdesteyn et al., 2008). Consequently, individuals isolate themselves and undergo social deprivation leading to a vicious cycle of inactivity and deconditioning (Sherrington & Tiedemann, 2015). Social participation is inversely related to fall rates. Therefore, providing social support for stroke patients may reduce their fall rates (World Health Organization, 2008). Exercises in fall prevention programs are useful in decreasing fall rates (Dean et al., 2009). However, there little research on the effect of social interactions on fall rates. Therefore, it is of interest to investigate if group community-based classes, targeting both psychosocial and physical factors, will reduce fall rates more than an independent physical exercise program.
Aim and Hypotheses:
This study aims to compare the effect of functional home exercise programme to community-based exercise classes on fall rates in older, community dwelling, post-ischaemic stroke patients of 6 to 12 months. The null hypothesis is that there will be no significant difference in fall rates between participants of home exercise programme and community-based exercise classes. The alternative hypothesis states fall rates will be significantly lower in participants of community-based exercise than home exercise programme.
Design:
This study employs a randomised controlled trial with single blinding of assessors. This is implemented by appointing another individual to obtain outcome measures, ensuring the assessors do not impose bias on the results intentionally or subconsciously. Due to the nature of the study, blinding of participants is not possible as participants know they are undertaking exercise in groups or independently.
Participants:
Referencing a similar study conducted by Olaleye, Hamzat, and Owolabi (2014), 50 participants were recruited through advertisement to the stroke foundation and eligible patients were advised to contact the researchers. Inclusion criteria includes participants must have had a stroke in the past 6 to 12 months and fallen in the last 3 months. Participants must also be community dwelling older adults (60 years) as there is an increased falling frequency after the age of 60 (Ugur, 2000). Exclusion criteria includes inability to ambulate independently and have contraindications to exercise. Consented participants were screened for safety.
Intervention:
Treatment intervention consists of 90 minutes of group, community-based class directed by a physiotherapist for 3 times per week for 12 weeks. The exercise program include, strengthening, coordination, balance such as passing ball in multiple directions, and functional exercises such as sit to stand or walking (Dean et al., 2009). Contrastingly, the active control intervention includes 90 minutes of the same exercise program as the treatment group, but completed independently at home with physiotherapist supervision.
Non-experimental variables require control to prevent them from influencing the dependent variable. Therefore, control for treatment time or time spent with physiotherapist is established by both groups having the same treatment time of 90 minutes, 3 times per week for 12 weeks. Furthermore, to control the amount of physical activity participants engage in outside the exercise program, they are advised to maintain the normal amount of physical activity they have conducted in the past 3 months. If they increase their normal amount of physical activity, they must record it to factor such variable into the analysis.
Outcome Measures:
Outcome measures are used to measure the effect of independent variables of intervention (treatment group and control group) and time (pre-training and post-training) on the dependent variable of number of falls.
The primary outcome measure is the direct measurement of fall rates, represented as a number, using fall diaries. Participants are instructed to record all incidences of falls with the date and location in a diary immediately after they occur. Fall diaries provide direct documentation of falls rates recorded over a period of time rather than momentary recall which relies on memory. This minimises recall error hence, increasing inter-rater reliability (ICC = 0.94) in the chronic disease population and has strong validity (r = 0.77-0.80) when correlating with self-observation report technique (Carp & Carp, 1981; Quittner, Modi, Lemanek, Ievers-Landis, & Rapoff, 2008)
As falls rates are difficult to improve in just 12 weeks, a secondary outcome measure is balance. Balance impairments in post-stroke population is a powerful risk factor of falling. Hence, reduction in balance problems may reduce fall rates (Weerdesteyn et al., 2008). The Balance Evaluation Systems Test (BESTest) is a measure of balance by testing the 6 systems constituting to balance. The BESTest demonstrates excellent validity (r = 0.96) when correlating with the Bergs Balance Scale and interrater reliability (ICC = 0.99) in the stroke population with no observed floor or ceiling effects (Chinsongkram et al., 2014).
Procedure:
After recruitment of participants, an online randomiser program designed by Urbaniak and Plous (2013) was used to assign eligible participants to either the home exercise group (control group) or community-based exercise group (treatment group) using a 1:1 ratio in a simple randomised sequence to ensure balance in numbers. Initially, participants are asked the number of falls they had in the last 3 months and complete the BESTest as a baseline measure before commencement of intervention. Following the baseline measure, participants will partake in the intervention for 12 weeks. By 12 weeks, patients will have completed the intervention and undertaken the second measurement of outcome measures. Lastly, 3 months after the cessation of intervention, a post-intervention measure is taken. The procedure appears in Figure 1.
Clinical Significance:
If the findings from this study is significant, fall prevention programs should include group community-based exercise classes as this will be more cost, time, and resource efficient for both physiotherapists and patients. Overall, group community-based exercise classes will improve patient’s quality of life whilst reducing fall rates by alleviating the social consequences of stroke. Moreover, by reducing fall incidence, it will ease the financial burden of falls in NZ.

Recruitment

Assessed for eligibility (n= 50)
Randomized
Figure 1.: Method of Recruitment, Randomisation, Interventions, and Assessment of Outcome Measures


Bibliography:

Baseline measures (Initial)
Allocated to intervention group (n= 25)
Allocated to control group (n= 25)
Primary outcome measure of number of falls in the past 3 months and secondary measure of balance are assessed initially in both groups
Control group:
90 minutes of independently exercise program completed at home with physiotherapist supervision. The exercise program is the same as the treatment intervention group.
Treatment group:
90 minutes of group, community-based class directed by a physiotherapist for 3 times per week for 12 weeks.
Intervention (12-weeks)
First Follow-up measures (week 12)
Analysis of Treatment Group:
Analysis of Control Group:
Number of falls in the past 3 months and balance are assessed in both groups at the end of intervention. This measurement demonstrates the effect of the intervention and time on fall rates.
Second Follow-up measures (week 24)
Analysis of Treatment Group:
Analysis of Control Group:
Number of falls in the past 3 months and balance are assessed at 3 months after the intervention.

Carp, F. M., & Carp, A. (1981). The validity, reliability and generalizability of diary data. Experimental Aging Research7(3), 281–296. https://doi.org/10.1080/03610738108259811
Chinsongkram, B., Chaikeeree, N., Saengsirisuwan, V., Viriyatharakij, N., Horak, F. B., & Boonsinsukh, R. (2014). Reliability and Validity of the Balance Evaluation Systems Test (BESTest) in People With Subacute Stroke. Physical Therapy94(11), 1632–1643. https://doi.org/10.2522/ptj.20130558
Dean, C. M., Rissel, C., Sharkey, M., Sherrington, C., Cumming, R. G., Barker, R. N., … Kirkham, C. (2009). Exercise intervention to prevent falls and enhance mobility in community dwellers after stroke: a protocol for a randomised controlled trial. BMC Neurology9, 38. https://doi.org/10.1186/1471-2377-9-38
Olaleye, O. A., Hamzat, T. K., & Owolabi, M. O. (2014). Stroke rehabilitation: should physiotherapy intervention be provided at a primary health care centre or the patients’ place of domicile? Disability and Rehabilitation36(1), 49–54. https://doi.org/10.3109/09638288.2013.777804
Quittner, A. L., Modi, A. C., Lemanek, K. L., Ievers-Landis, C. E., & Rapoff, M. A. (2008). Evidence-based Assessment of Adherence to Medical Treatments in Pediatric Psychology. Journal of Pediatric Psychology33(9), 916–936. https://doi.org/10.1093/jpepsy/jsm064
Ranta, A. (2018). Projected stroke volumes to provide a 10-year direction for New Zealand stroke services. The New Zealand Medical Journal131, 15–28.
Robertson, M., & Campbell, A. (2012). Falling costs: the case for investment. Retrieved from https://www.hqsc.govt.nz/our-programmes/reducing-harm-from-falls/publications-and-resources/
Sherrington, C., & Tiedemann, A. (2015). Physiotherapy in the prevention of falls in older people. Journal of Physiotherapy61(2), 54–60. https://doi.org/10.1016/j.jphys.2015.02.011
Ugur, C. (2000). Characteristics of falling in patients with stroke. Journal of Neurology, Neurosurgery & Psychiatry69(5), 649–651. https://doi.org/10.1136/jnnp.69.5.649
Weerdesteyn, V., Niet, M. de, van Duijnhoven, H. J. R., & Geurts, A. C. H. (2008). Falls in Individuals with Stroke. The Journal of Rehabilitation Research and Development45(8), 1195. https://doi.org/10.1682/JRRD.2007.09.0145
World Health Organization (Ed.). (2008). WHO global report on falls prevention in older age. Geneva, Switzerland: World Health Organization.



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