Research in Gerontological Nursing

Research Brief 

Physio-Feedback and Exercise Program (PEER) Improves Balance, Muscle Strength, and Fall Risk in Older Adults

Ladda Thiamwong, PhD, RN; Jeffrey R. Stout, PhD; Mary Lou Sole, PhD, RN, CCNS, CNL, FAAN, FCCM; Boon Peng Ng, PhD; Xin Yan, PhD; Steven Talbert, PhD, RN

Abstract

A one-group pre/posttest study was conducted to examine the feasibility and effect size of an 8-week physio-feedback and exercise program (PEER) on improving balance, muscle strength, and fall risk. Nineteen participants (mean age = 76 years) received the intervention, which included visual physio-feedback by the BTrackS™ Assess Balance System, cognitive reframing, and a combined group- and home-based exercise program by a trained peer coach. Pre- and post-measurement outcomes were evaluated for balance, handgrip strength, and fall risk. Feasibility was assessed by dropout rate, safety, and adherence to exercise. Significant improvements were noted in dynamic balance (Sit-to-Stand, Timed Up & Go tests), handgrip strength, and fall risk. Participants' attendance was 87.5%, with no fall incidence. The physio-feedback, cognitive reframing, and peer coaching facilitate older adults to align their perceived fall risk with physiological fall risk and motivate them to stay active. PEER intervention is feasible; safe; improves balance, muscle strength, and fall risk; and may enhance activity engagement.

Targets:

Community-dwelling older adults.

Intervention Description:

Provide visual physio-feedback and cognitive reframing based on the fall risk appraisal matrix and participate in combined group- and home-based exercises by a trained peer coach.

Mechanism of Action:

Align perceived and physiological fall risk, peer coaching to exercise.

Outcomes:

Balance, handgrip strength, fall risk, and activity engagement.

[Research in Gerontological Nursing, 13(6), 289–296.]

Abstract

A one-group pre/posttest study was conducted to examine the feasibility and effect size of an 8-week physio-feedback and exercise program (PEER) on improving balance, muscle strength, and fall risk. Nineteen participants (mean age = 76 years) received the intervention, which included visual physio-feedback by the BTrackS™ Assess Balance System, cognitive reframing, and a combined group- and home-based exercise program by a trained peer coach. Pre- and post-measurement outcomes were evaluated for balance, handgrip strength, and fall risk. Feasibility was assessed by dropout rate, safety, and adherence to exercise. Significant improvements were noted in dynamic balance (Sit-to-Stand, Timed Up & Go tests), handgrip strength, and fall risk. Participants' attendance was 87.5%, with no fall incidence. The physio-feedback, cognitive reframing, and peer coaching facilitate older adults to align their perceived fall risk with physiological fall risk and motivate them to stay active. PEER intervention is feasible; safe; improves balance, muscle strength, and fall risk; and may enhance activity engagement.

Targets:

Community-dwelling older adults.

Intervention Description:

Provide visual physio-feedback and cognitive reframing based on the fall risk appraisal matrix and participate in combined group- and home-based exercises by a trained peer coach.

Mechanism of Action:

Align perceived and physiological fall risk, peer coaching to exercise.

Outcomes:

Balance, handgrip strength, fall risk, and activity engagement.

[Research in Gerontological Nursing, 13(6), 289–296.]

Falls in older adults are the most significant cause of injury leading to hospitalization, disability, and fatality. Fall prevention interventions have received considerable attention, but fall rates are still rising. Without effective fall prevention strategies, the number of injuries and associated direct and indirect costs caused by falls are projected to be higher and create a global burden. In 2015, the direct costs of fatal falls were more than $637 million, whereas Medicare costs for non-fatal falls were more than $31 billion (Burns et al., 2016). Indirect costs associated with falls remain a critical burden to family and household economies (Kelly, 2017).

Extensive systematic reviews confirm that a multifactorial approach, which includes a customized exercise program and enhanced self-management, has high effectiveness to prevent falls (Guirguis-Blake et al., 2018; Hopewell et al., 2018; McInnes et al., 2011). A recent systematic review also confirmed that exercise programs reduce the rate of falls by 23% and reduce the number of community-dwelling older adults experiencing falls by 18% (Sherrington et al., 2019). Several studies have also shown that older adults benefit from either supervised group- or home-based exercise, and both are cost-effective (El-Khoury et al., 2013). Little is known regarding the impact of combined group- and home-based exercise programs on maintaining activity engagement. In addition, older adults are more receptive to assistance and have increased attendance rates when someone from a similar background administers the fall prevention intervention (French et al., 2014). Therefore, the current authors proposed a peer coaching approach to providing exercise programs in this pilot study.

The majority of older people have sedentary behavior, which increases their risk of illness and falls. One in 10 community-dwelling older adults had low actual fall risk, but high fear of falling, and one in three older adults sustained falls (Delbaere et al., 2010). Falls may decrease in older adults who have an accurate appraisal of their physical abilities. Older adults with better-perceived physical health may experience less fear of falling (Kumar et al., 2014). Fall prevention is best approached from a participant-centered perspective (Kuhlenschmidt et al., 2016), and older adults prefer to adapt to realistic fall risk by taking self-control and implementing self-management strategies (McInnes et al., 2011).

Limited fall interventions were found that were tailored to older adults who have a mismatch between perceived fall risk and physiological fall risk. The Center for Disease Control and Prevention's (CDC; 2017) Stopping Elderly Accidents, Deaths, and Injuries (STEADI) program illuminated vital elements of fall prevention for health care providers and older adults. However, the STEADI program was not designed to impact older adults' fall risk appraisal realistically. In addition, several types of interventions focused on reducing fear of falling (Robinson & Wetherell, 2018; Whipple et al., 2018); however, some degree of fear of falling can increase conscious awareness and reduce fall risk by encouraging individuals to avoid exposure to unnecessary risk (Litwin et al., 2018).

A paucity of tailored interventions exists that use physio-feedback to challenge balance and muscle capacity, combine group and individual activities, and are led by a trained peer coach. Therefore, the current authors developed an individualized, in-home physio-feedback exercise program (PEER) (Thiamwong et al., 2019) using three key components, including visual physio-feedback on balance (Alhasan et al., 2017), cognitive reframing (Lachman et al., 1992), and a peer coaching approach (Matz-Costa et al., 2019). It was hypothesized that visual physio-feedback and cognitive reframing help align perceived fall risk with physiological fall risk and direct participants toward adaptive behaviors in a safe manner with peer coaching enhancing exercise and activity engagement. To the best of the authors' knowledge, this pilot study is the first to examine the feasibility and effect size of the fall prevention program for older adults who live at home and regularly visit a community center.

Method

Study Design

The one-group pre/posttest study design sought to (a) examine the feasibility of the PEER; and (b) estimate the effect size of the PEER on static balance, dynamic balance, muscle strength, and fall risk. Data were collected at two time points (pretest, posttest) to test the hypotheses and generate the effect size to power a larger trial.

This study was part of a two-group pre/posttest study (Thiamwong et al., 2019). Due to resource issues, the dynamic balance and muscle strength could only be measured for the PEER intervention group, not the control group. Therefore, participants from the control group were excluded from data analysis. Data from participants in the PEER group were included in the analysis and are reported in the Results section.

Participants and Setting

Participants were recruited from senior communities in central Florida using flyers. The assessment and intervention procedures were performed at a community center and participants' homes. Fifty participants were approached, and 41 participants who met inclusion criteria were enrolled. Participants were assigned to two groups: PEER intervention (n = 19) and control (n = 22). Participants who met the following inclusion criteria were enrolled: (a) age ≥65; (b) no marked cognitive impairment (Mini-Mental State Examination [MMSE] score ≥24 [Folstein et al., 1975]); and (c) live in their own homes. Exclusion criteria were: (a) a medical condition precluding exercise, such as uncontrolled cardiac disease (shortness of breath and/or experience pressure, squeezing, burning, or tightness when doing a physical activity); and (b) currently receiving treatment from a rehabilitation facility. The University of Central Florida Institutional Review Board approved the study protocol, and all participants consented to participate.

Intervention Components and Procedures

The PEER intervention comprised two components: (a) visual physio-feedback and cognitive reframing by a researcher, and (b) combined group- and home-based exercise by a trained peer coach (Thiamwong et al., 2019).

Visual Physio-Feedback and Cognitive Reframing. Visual physio-feedback is considered an assessment and treatment method and offers participants visual information about their static balance performance. Cognitive reframing is a method that is used to identify maladaptive thoughts and reframe older adults' perceptions to more closely align with reality (Lachman et al., 1992). Visual physio-feedback and cognitive reframing comprised three steps.

Step 1. Instructed participants to complete the short Falls Efficacy Scale-International (FES-I) as a perceived fall risk and BTrackS™ Balance Test (BBT) as a physiological fall risk. The short FES-I is a self-report Likert-type questionnaire and consists of seven items, which focus on the concern about falls when performing daily activities (Kempen et al., 2008). Participants were asked to rate their concerns about falling when performing seven daily activities, such as getting in and out of a chair.

The BTrackS Assess Balance System consists of the portable BTrackS Balance Plate (BBP), BTrackS Balance Test (BBT), and the BTrackS Assess Balance Software. The BBT comprises four 20-second trials, and the participant needs to stand as still as possible on the BBP with eyes closed and hands-on-hips (Goble & Baweja, 2018).

Step 2. Created participants' fall risk appraisal matrix as a tool to reframe participants' thoughts. The fall risk appraisal matrix categorized participants into four groups (congruent, incongruent, rational, and irrational) based on the perceived fall risk (short FES-I score) and physiological fall risk (BBT score). The fall risk appraisal matrix, which is a graphical grid categorizing older adults' perceived fall risk and physiological fall risk, was divided into four quadrants. The following criteria and cut points were used (Thiamwong et al., 2020):

  • Irrational: High perceived fall risk (short FES-I >10) but low physiological fall risk (BBT ≤30).
  • Incongruent: Low perceived fall risk (short FES-I ≤10) despite high physiological fall risk (BBT >30).
  • Rational: Low perceived fall risk (short FES-I ≤10) aligned with low physiological fall risk (BBT ≤30).
  • Congruent: High perceived fall risk (short FES-I >10) aligned with high physiological fall risk (BBT >30).

Step 3. Met with each participant to present the matrix of fall risk appraisal with the BTrackS software displaying the participant's static balance capacity, created a personal goal, and tailored an action plan based on the fall risk appraisal matrix. For example, participants with incongruent fall risk appraisal need to focus on increasing fall risk awareness and participating in the exercise, as presented below.

Group- and Home-Based Exercise Program. The exercise program comprised simple balance and strength training, combined with group-based exercise 60 minutes once per week, and home-based exercise 30 minutes twice per week. The training incorporated four sets of exercise: (a) warm-up (seated), (b) strength for upper and lower body (seated and standing), (c) balance (standing and moving), and (d) stretching of the lower and upper body.

A peer coaching approach was used to assist and encourage older adults to engage in the exercise. The group-based exercises were led by a trained peer coach for 60 minutes per week in a room at the community center (four to six persons per group). The trained peer coach demonstrated exercises as a group. Training sessions were designed according to the frequency, intensity, time, and type guidelines recommended by the American College of Sports Medicine (Chodzko-Zajko et al., 2009) and standardized levels of progression: beginner, intermediate, and advanced. Based on these guidelines, a total duration of 91 to 120 minutes of exercise per week is most effective in improving overall balance performance (Lesinski et al., 2015). Therefore, the PEER group was required to exercise 120 minutes (60 minutes per week for group-based exercise and 30 minutes twice per week for individual exercise) for 8 weeks. The home-based exercise comprises the same set of exercises as the group-based exercise, and participants received an exercise booklet with illustrations. The booklet serves as a guide for remembering the exercises learned during group and provides several types of exercises that participants can integrate into their daily activities (e.g., walking around the house).

Outcome Measures

Pre- and post-measurement outcomes were evaluated for dynamic balance, static balance, handgrip strength, and fall risk. All outcomes, except an exercise log, were measured before and after the PEER intervention by the first author (L.T.). Feasibility was assessed by the number of sessions attended, retention, and adherence to record a weekly exercise log.

Dynamic Balance and Static Balance. Dynamic balance was assessed by the Timed Up & Go (TUG) and Sit-to-Stand tests. The TUG test has been widely used to assess functional mobility and predict fall risk (Ory et al., 2015; Shumway-Cook et al., 2007) and has been validated among community-dwelling older adults (Bohannon, 2006). The TUG has an acceptable sensitivity (87%) and specificity (87%) for assessing older adults who are prone to falls (Shumway-Cook et al., 2000). The TUG test measured the time in seconds for a participant to stand up from a standard armchair, walk at a normal pace on the floor 3 meters, return, and sit down (Podsiadlo & Richardson, 1991). Participants who completed the TUG test in <12 seconds were classified as having low fall risk (Bischoff et al., 2003). The Sit-to-Stand test was suggested by the CDC's (2017) STEADI program, with results scored based on participant age and gender. The Sit-to-Stand test has been shown to be reliable in a variety of populations (Bohannon & Crouch, 2019; Jones et al., 1999). Participants completed this test by fully standing up from a chair as many times as possible within 30 seconds.

Static balance was assessed with the BBT, as described above. The BBT has excellent validity (Pearson correlation, r > 0.90) and test–retest reliability (intraclass correlation coefficient [ICC] = 0.83) (Levy et al., 2018). BBT scores range from 1 to 100, with scores of 0 to 30 indicating low fall risk (Balance Tracking Systems, 2018; Goble, 2015), and scores ≥31 indicating moderate to high fall risk.

Muscle Strength. The handgrip strength test was used to assess muscle strength. The dynamometer is a reliable screening tool with an ICC between 0.941 and 0.981 (Schaubert & Bohannon, 2005). Participants were instructed to squeeze a handgrip dynamometer as hard as possible with the dominant hand for three attempts. For each trial, the handgrip dynamometer shows maximum strength performance produced by the participant after it is released, and is recorded as weak, normal, or strong based on the participant's age and gender.

Fall Risk. Fall risk was assessed by the CDC STEADI fall risk checklist, which comprises 12 statements with yes or no answers. Total score ≥4 points indicates fall risk (CDC, 2017).

Feasibility of the PEER Intervention

Feasibility was assessed by dropout rate, safety, and adherence to record a weekly exercise log. A weekly exercise log was designed to record activity, including types and duration of exercises that participants performed at home and handed to the peer coach the following week. The trained peer coach called participants once per week to ask about any adverse consequences from the home-based exercise and to remind participants to complete the weekly exercise log.

Data Analysis

Paired sample t tests and effect sizes (Cohen's d) were calculated to assess changes for normally distributed data (Kolmogorov-Smirnov test), whereas the Wilcoxon signed-rank test was used to examine non-normally distributed data. Alpha level was set a priori at p < 0.05. ICC was calculated for the BBT to determine the reliability coefficients (based on a 95% confidence interval), where ICC <0.5 was poor, ICC 0.5 to 07 was moderate, ICC 0.75 to 0.90 was good, and ICC >0.9 was excellent reliability (Koo & Li, 2016). Standard error of measurement (SEM) was computed to measure absolute reliability. The SEM represents the stability or variability of response and defines score ranges, which can be expected in repeat tests (Serbetar, 2015). Data were analyzed using SPSS for Windows® version 25.

Results

Demographics

The majority of participants (74%) were women, mean age was 75.5 (SD = 5.4, range = 66 to 84 years), 21% lived alone, 42% identified as having good general health, and 47% had a history of falls in the past 1 year. Racial/ethnicity makeup was 79% non-Hispanic White and 21% Hispanic. The majority (58%) of participants reported that fear of falling limited their daily activities; however, 11% had no concerns about falling (Table 1).

Participants' Baseline Descriptive Characteristics (N = 19)Participants' Baseline Descriptive Characteristics (N = 19)

Table 1:

Participants' Baseline Descriptive Characteristics (N = 19)

Balance Performance, Muscle Strength, and Fall Risk

Table 2 presents significant and meaningful improvement for dynamic balance Sit-to-Stand test (p < 0.001; d = 0.95) and fall risk (p = 0.016; d = 0.61) scores. Although mean BBT score decreased from 29.79 (SD = 15.74) to 26.84 (SD = 12.21), the decrease was not statistically significant (p = 0.056). Nonparametric analyses for the dynamic balance TUG test and handgrip strength test both illustrated significant improvements of 13.1% and 17.7%, respectively. The relative reliability for the BBT for pre/post change scores over 8 weeks measured in a similar cohort of participants (N = 20; mean age = 77.6 [SD = 9.33] years) showed excellent reliability (ICC = 0.91, SEM ±3.3 cm).

Changes in Balance, Muscle Strength, and Fall Risk Measures From Baseline to 8 Weeks (N = 19)

Table 2:

Changes in Balance, Muscle Strength, and Fall Risk Measures From Baseline to 8 Weeks (N = 19)

Feasibility of the PEER Intervention

Participants' attendance ranged from six to eight sessions, with an overall attendance rate of 87.5%. Reasons for not attending were scheduled medical appointments and sick family members. No fall incidence was reported during the study. The exercise logs showed that 84.2% of participants performed the home-based exercise and other activities (e.g., walking, walking the dog, cleaning the floor) at least 30 minutes twice per week.

Discussion

The current study provides preliminary support that the PEER intervention improved outcomes for older adults in terms of balance performance, muscle strength, and fall risk. Recruitment and retention rates were successful, and no drop out occurred. The authors hypothesize that participants valued receiving individual pre/post visual physio-feedback from the researcher and the group exercise with the trained peer coach, and the $25 gift card after completion may have contributed to the high retention rate.

Visual feedback delivery and cognitive reframing in the PEER intervention were integral in enhancing accurate appraisal of participants' balance performance and aligning perceived fall risk and physiological fall risk. Visual physio-feedback regarding balance has a positive effect on balance confidence and task selection in older adults and provides individuals with information about their body functions with the purpose of developing changes in behavior (Alhasan et al., 2017). In addition, the feedback should motivate participants to exercise and stay active. This is the first study to use the BTrackS Assess Balance System to provide visual balance performance feedback to older adults. This system is a novel physio-feedback technology, which is portable and easy to use and could support a community-based fall prevention approach. Furthermore, the current study demonstrated excellent reliability (ICC = 0.91, SEM ±3.3 cm) in this cohort of community-dwelling older adults for the BBT. The current data agree with the findings of Levy et al. (2018), who reported ICC of 0.83 and SEM of 3.47 cm in a similar group of older men and women.

The adoption of the BTrackS Assess Balance System for a primary care clinic or health care center is feasible, as the technology is relatively inexpensive (<$1,800 for a device and lifetime software), compared to other balance plates, which cost approximately $5,000 to $20,000 and have poor portability (Goble, 2018). The BTrackS Assess Balance System has proved reliable and useful for estimating fall risk and examining whether an intervention is effectively improving balance performance (Levy et al., 2018). The system is also useful for the estimation of fall risk conditions and targeting, training (Dueñas et al., 2016; Levy et al., 2018), and possibly quantifying whether an intervention is effectively improving balance.

The improvements of dynamic balance and muscle strength are consistent with previous studies that have shown balance and muscle strength have high effectiveness in preventing falls in older adults (Granacher et al., 2013; Guirguis-Blake et al., 2018). A meta-analysis found that fall interventions with multiple components were effective in preventing falls and reduced injurious falls in older adults by 40% (Stein et al., 2014). Furthermore, a systematic review suggested that exercise programs that challenge balance can prevent falls in community-dwelling older adults (Sherrington et al., 2017).

The combination of a group-based exercise program with tailored home-based exercise and support from the trained peer coach is a vital component of the PEER intervention. Peer coaching was a fundamental component in motivating older adults to engage in activity and has the potential to enhance long-term adherence. This finding is consistent with a previous study that found a peer-delivered intervention is as effective in improving physical activity as professionally delivered interventions, and is low-cost, increases accessibility, and compensates for the shortage of health professionals caring for older adults (van de Vijver et al., 2018). Older adults who received positive feedback reported higher levels of balance confidence, whereas those who received negative feedback demonstrated task selection evident of reduced risk taking (Lamarche et al., 2014).

Limitations

The study had some limitations. First, the sample was small; therefore, findings must be interpreted with caution. However, significant improvements were identified in dynamic balance, handgrip strength, and fall risk, even with a limited sample size. Second, functional status, chronic conditions, and medication regimens were not accounted for in this study, which could have affected exercise and activity engagement. Third, the one-group, pre/posttest design cannot infer causality. Finally, the TUG test, Sit-to-Stand test, and handgrip strength were not assessed in the control group due to limited resources. Therefore, only data from the PEER intervention group were able to be presented.

Conclusion

The current study contributes to the growing literature, as it is one of only a few to focus on fall interventions tailored to older adults who have a mismatch between perceived fall risk and physiological fall risk. The findings illustrate the importance of incorporating visual physio-feedback, cognitive reframing, and peer coaching into a combined group- and home-based exercise program.

The direct physio-feedback and cognitive reframing allow older adults to align their perceived and physiological fall risk, potentially providing them with the opportunity to take responsibility to prevent falls. Combined group-and home-based exercise, delivered by a peer coach, was vital in motivating older adults to stay active. This self-sustainable, peer-coaching intervention has the potential to be scaled to the community level. Future research should include an attentio n control group, a larger sample size, cost evaluation, and follow up, in addition to other outcomes such as physical activity and quality of life, as peer coaching is used to help older adults sustain and increase daily activity, socialization, and well-being (van de Vijver et al., 2018). Finally, group-based exercises with peer support may provide the motivation to persevere and maintain a healthier lifestyle.

References

  • Alhasan, H., Hood, V. & Mainwaring, F. (2017). The effect of visual biofeedback on balance in elderly population: A systematic review. Clinical Interventions in Aging, 12, 487–497 doi:10.2147/CIA.S127023 [CrossRef] PMID:28293105
  • Balance Tracking Systems. (2018). BTrackS™ assess balance. https://balancetrackingsystems.com/assess-balance
  • Bischoff, H. A., Stähelin, H. B., Monsch, A. U., Iversen, M. D., Weyh, A., von Dechend, M., Akos, R., Conzelmann, M., Dick, W. & Theiler, R. (2003). Identifying a cut-off point for normal mobility: A comparison of the timed 'up and go' test in community-dwelling and institutionalised elderly women. Age and Ageing, 32(3), 315–320 doi:10.1093/ageing/32.3.315 [CrossRef] PMID:12720619
  • Bohannon, R. W. (2006). Reference values for the timed up and go test: A descriptive meta-analysis. Journal of Geriatric Physical Therapy (2001), 29(2), 64–68 doi:10.1519/00139143-200608000-00004 [CrossRef] PMID:16914068
  • Bohannon, R. W. & Crouch, R. (2019). 1-minute sit-to-stand test: Systematic review of procedures, performance, and clinimetric properties. Journal of Cardiopulmonary Rehabilitation and Prevention, 39(1), 2–8 doi:10.1097/HCR.0000000000000336 [CrossRef] PMID:30489442
  • Burns, E. R., Stevens, J. A. & Lee, R. (2016). The direct costs of fatal and non-fatal falls among older adults - United States. Journal of Safety Research, 58, 99–103 doi:10.1016/j.jsr.2016.05.001 [CrossRef] PMID:27620939
  • Centers for Disease Control and Prevention. (2017). STEADI—Older adult fall prevention. https://www.cdc.gov/steadi
  • Chodzko-Zajko, W. J., Proctor, D. N., Fiatarone Singh, M. A., Minson, C. T., Nigg, C. R., Salem, G. J. & Skinner, J. S. (2009). American College of Sports Medicine position stand. Exercise and physical activity for older adults. Medicine and Science in Sports and Exercise, 41(7), 1510–1530 doi:10.1249/MSS.0b013e3181a0c95c [CrossRef] PMID:19516148
  • Delbaere, K., Close, J. C., Brodaty, H., Sachdev, P. & Lord, S. R. (2010). Determinants of disparities between perceived and physiological risk of falling among elderly people: Cohort study. BMJ (Clinical Research Ed.), 341, c4165 doi:10.1136/bmj.c4165 [CrossRef] PMID:20724399
  • Dueñas, L., Balasch i Bernat, M., Mena del Horno, S., Aguilar-Rodríguez, M. & Alcántara, E. (2016). Development of predictive models for the estimation of the probability of suffering fear of falling and other fall risk factors based on posturography parameters in community-dwelling older adults. International Journal of Industrial Ergonomics, 54, 131–138 doi:10.1016/j.ergon.2016.05.009 [CrossRef]
  • El-Khoury, F., Cassou, B., Charles, M.-A. & Dargent-Molina, P. (2013). The effect of fall prevention exercise programmes on fall induced injuries in community dwelling older adults: Systematic review and meta-analysis of randomised controlled trials. BMJ (Clinical Research Ed.), 347, f6234 doi:10.1136/bmj.f6234 [CrossRef] PMID:24169944
  • Folstein, M. F., Folstein, S. E. & McHugh, P. R. (1975). “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12(3), 189–198 doi:10.1016/0022-3956(75)90026-6 [CrossRef] PMID:1202204
  • French, D. P., Olander, E. K., Chisholm, A. & McSharry, J. (2014). Which behaviour change techniques are most effective at increasing older adults' self-efficacy and physical activity behaviour? A systematic review. Annals of Behavioral Medicine, 48(2), 225–234 doi:10.1007/s12160-014-9593-z [CrossRef] PMID:24648017
  • Goble, D. J. (2015). Validating BTrackS to measure balance. http://balancetrackingsystems.com/wp-content/uploads/2015/03/ValidatingBTrackS-Final-Feb2015.pdf
  • Goble, D. J. (2018). The BTrackS™ balance test is a valid predictor of older adult falling. https://balancetrackingsystems.com/wp-content/uploads/2019/05/Validating-BTrackS-FRA.pdf
  • Goble, D. J. & Baweja, H. S. (2018). Postural sway normative data across the adult lifespan: Results from 6280 individuals on the Balance Tracking System balance test. Geriatrics & Gerontology International, 18(8), 1225–1229 doi:10.1111/ggi.13452 [CrossRef] PMID:29897159
  • Granacher, U., Gollhofer, A., Hortobágyi, T., Kressig, R. W. & Muehlbauer, T. (2013). The importance of trunk muscle strength for balance, functional performance, and fall prevention in seniors: A systematic review. Sports Medicine (Auckland, N.Z.), 43(7), 627–641. doi:10.1007/s40279-013-0041-1 [CrossRef] PMID:23568373
  • Guirguis-Blake, J. M., Michael, Y. L., Perdue, L. A., Coppola, E. L. & Beil, T. L. (2018). Interventions to prevent falls in older adults: Updated evidence report and systematic review for the US Preventive Services Task Force. Journal of the American Medical Association, 319(16), 1705–1716 doi:10.1001/jama.2017.21962 [CrossRef] PMID:29710140
  • Hopewell, S., Adedire, O., Copsey, B. J., Boniface, G. J., Sherrington, C., Clemson, L., Close, J. C. & Lamb, S. E. (2018). Multifactorial and multiple component interventions for preventing falls in older people living in the community. Cochrane Database of Systematic Reviews, 7, CD012221. doi:10.1002/14651858.CD012221.pub2 [CrossRef] PMID:30035305
  • Jones, C. J., Rikli, R. E. & Beam, W. C. (1999). A 30-s chair-stand test as a measure of lower body strength in community-residing older adults. Research Quarterly for Exercise and Sport, 70(2), 113–119 doi:10.1080/02701367.1999.10608028 [CrossRef] PMID:10380242
  • Kelly, I. R. (2017). The shock of falling among older Americans. The Journal of the Economics of Ageing, 11. Advance online publication. doi:10.1016/j.jeoa.2017.06.001 [CrossRef]
  • Kempen, G. I. J., Yardley, L., van Haastregt, J. C. M., Zijlstra, G. A. R., Beyer, N., Hauer, K. & Todd, C. (2008). The Short FES-I: A shortened version of the falls efficacy scale-international to assess fear of falling. Age and Ageing, 37(1), 45–50 doi:10.1093/ageing/afm157 [CrossRef] PMID:18032400
  • Koo, T. K. & Li, M. Y. (2016). A guideline of selecting and reporting intraclass correlation coefficients for reliability research. Journal of Chiropractic Medicine, 15(2), 155–163 doi:10.1016/j.jcm.2016.02.012 [CrossRef] PMID:27330520
  • Kuhlenschmidt, M. L., Reeber, C., Wallace, C., Chen, Y., Barnholtz-Sloan, J. & Mazanec, S. R. (2016). Tailoring education to perceived fall risk in hospitalized patients with cancer: A randomized, controlled trial. Clinical Journal of Oncology Nursing, 20(1), 84–89 doi:10.1188/16.CJON.84-89 [CrossRef] PMID:26800411
  • Kumar, A., Carpenter, H., Morris, R., Iliffe, S. & Kendrick, D. (2014). Which factors are associated with fear of falling in community-dwelling older people?Age and Ageing, 43(1), 76–84 doi:10.1093/ageing/aft154 [CrossRef] PMID:24100619
  • Lachman, M. E., Weaver, S. L., Bandura, M., Elliott, E. & Lewkowicz, C. J. (1992). Improving memory and control beliefs through cognitive restructuring and self-generated strategies. Journal of Gerontology, 47(5), 293–299 doi:10.1093/geronj/47.5.P293 [CrossRef] PMID:1512434
  • Lamarche, L., Gionfriddo, A. M., Cline, L. E., Gammage, K. L. & Adkin, A. L. (2014). What would you do? The effect of verbal persuasion on task choice. Gait & Posture, 39, 583–587 doi:10.1016/j.gaitpost.2013.09.013 [CrossRef] PMID:24139683
  • Lesinski, M., Hortobágyi, T., Muehlbauer, T., Gollhofer, A. & Granacher, U. (2015). Effects of balance training on balance performance in healthy older adults: A systematic review and meta-analysis. Sports Medicine (Auckland, N.Z.), 45(12), 1721–1738. doi:10.1007/s40279-015-0375-y [CrossRef] PMID:26325622
  • Levy, S. S., Thralls, K. J. & Kviatkovsky, S. A. (2018). Validity and reliability of a portable balance tracking system, BTrackS, in older adults. Journal of Geriatric Physical Therapy, 41(2), 102–107 doi:10.1519/JPT.0000000000000111 [CrossRef] PMID:27893566
  • Litwin, H., Erlich, B. & Dunsky, A. (2018). The complex association between fear of falling and mobility limitation in relation to late-life falls: A SHARE-based analysis. Journal of Aging and Health, 30(6), 987–1008. doi:10.1177/0898264317704096 [CrossRef] PMID:28553817
  • Matz-Costa, C., Howard, E. P., Castaneda-Sceppa, C., Diaz-Valdes Iriarte, A. & Lachman, M. E. (2019). Peer-based strategies to support physical activity interventions for older adults: A typology, conceptual framework, and practice guidelines. The Gerontologist, 59(6), 1007–1016 doi:10.1093/geront/gny092 [CrossRef] PMID:30085074
  • McInnes, E., Seers, K. & Tutton, L. (2011). Older people's views in relation to risk of falling and need for intervention: A meta-ethnography. Journal of Advanced Nursing, 67(12), 2525–2536 doi:10.1111/j.1365-2648.2011.05707.x [CrossRef] PMID:21627679
  • Ory, M. G., Smith, M. L., Jiang, L., Lee, R., Chen, S., Wilson, A. D., Stevens, J. A. & Parker, E. M. (2015). Fall prevention in community settings: Results from implementing stepping on in three states. Frontiers in Public Health, 2, 232–232 doi:10.3389/fpubh.2014.00232 [CrossRef] PMID:25964924
  • Podsiadlo, D. & Richardson, S. (1991). The timed “Up & Go”: A test of basic functional mobility for frail elderly persons. Journal of the American Geriatrics Society, 39(2), 142–148.
  • Robinson, J. B. & Wetherell, J. L. (2018). An interdisciplinary intervention for fear of falling: Lessons learned from two case studies. Clinical Gerontologist, 41(4), 366–373. doi:10.1080/07317115.2017.1325423 [CrossRef] PMID:28548888
  • Schaubert, K. L. & Bohannon, R. W. (2005). Reliability and validity of three strength measures obtained from community-dwelling elderly persons. Journal of Strength and Conditioning Research, 19(3), 717–720.
  • Serbetar, I. (2015). Establishing some measures of absolute and relative reliability of a motor test. Croatian Journal of Education, 17(1), 37–48 doi:10.15516/cje.v17i0.1484 [CrossRef]
  • Sherrington, C., Fairhall, N. J., Wallbank, G. K., Tiedemann, A., Michaleff, Z. A., Howard, K., Clemson, L., Hopewell, S. & Lamb, S. E. (2019). Exercise for preventing falls in older people living in the community. Cochrane Database of Systematic Reviews, 1(1), CD012424. Advance online publication. doi:10.1002/14651858.CD012424.pub2 [CrossRef] PMID:30703272
  • Sherrington, C., Michaleff, Z. A., Fairhall, N., Paul, S. S., Tiedemann, A., Whitney, J., Cumming, R. G., Herbert, R. D., Close, J. C. T. & Lord, S. R. (2017). Exercise to prevent falls in older adults: An updated systematic review and meta-analysis. British Journal of Sports Medicine, 51(24), 1750–1758 doi:10.1136/bjsports-2016-096547 [CrossRef] PMID:27707740
  • Shumway-Cook, A., Brauer, S. & Woollacott, M. (2000). Predicting the probability for falls in community-dwelling older adults using the Timed Up & Go Test. Physical Therapy, 80(9), 896–903 doi:10.1093/ptj/80.9.896 [CrossRef] PMID:10960937
  • Shumway-Cook, A., Silver, I. F., LeMier, M., York, S., Cummings, P. & Koepsell, T. D. (2007). Effectiveness of a community-based multifactorial intervention on falls and fall risk factors in community-living older adults: A randomized, controlled trial. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 62(12), 1420–1427 doi:10.1093/gerona/62.12.1420 [CrossRef] PMID:18166695
  • Stein, K., Goodwin, V. A., Ukoumunne, O. C., Thompson-Coon, J., Whear, R., Bethel, A. & Abbott, R. A. (2014). Multiple component interventions for preventing falls and fall-related injuries among older people: Systematic review and meta-analysis. http://www.biomedcentral.com/1471-2318/14/15
  • Thiamwong, L., Huang, H. J., Ng, B. P., Yan, X., Sole, M. L., Stout, J. R. & Talbert, S. (2019). Shifting maladaptive fall risk appraisal in older adults through an in-home physio-feedback and exercise program (PEER): A pilot study. Clinical Gerontologist. Advanced online publication. doi:10.1080/07317115.2019.1692120 [CrossRef]
  • Thiamwong, L., Sole, M. L., Ng, B. P., Welch, G., Huang, H. & Stout, J. (2020). Assessing fall risk through combined physiological and perceived fall risk measures using innovative technology. Journal of Gerontological Nursing, 46(4), 41–47 doi:10.3928/00989134-20200302-01 [CrossRef]
  • van de Vijver, P. L., Wielens, H., Slaets, J. P. J. & van Bodegom, D. (2018). Vitality club: A proof-of-principle of peer coaching for daily physical activity by older adults. Translational Behavioral Medicine, 8(2), 204–211 doi:10.1093/tbm/ibx035 [CrossRef] PMID:29325113
  • Whipple, M. O., Hamel, A. V. & Talley, K. M. C. (2018). Fear of falling among community-dwelling older adults: A scoping review to identify effective evidence-based interventions. Geriatric Nursing, 39, 170–177 doi:10.1016/j.gerinurse.2017.08.005 [CrossRef] PMID:28941942

Participants' Baseline Descriptive Characteristics (N = 19)

Variablen (%)
Age (mean, SD, range) (years)75.5 (5.4) (66 to 84)
Gender
  Female14 (74)
  Male5 (26)
Ethnicity
  Non-Hispanic White15 (79)
  Hispanic4 (21)
Education level
  College or higher12 (63)
  High school6 (32)
  Primary or middle school1 (5)
General health
  Excellent1 (5)
  Very good8 (42)
  Good5 (26)
  Fair4 (21)
  Poor1 (5)
Financial problems
  Rarely6 (32)
  Often1 (5)
  Occasionally10 (53)
  Never2 (11)
  Always0 (0)
Living status
  With partner or spouse13 (68)
  Alone4 (21)
  With family or friend2 (11)
Falls in the past 1 year
  None10 (53)
  One6 (32)
  Two2 (11)
  More than two1 (5)
Injurious falls in the past 1 year
  None15 (79)
  One1 (5)
  Two2 (11)
  More than two1 (5)
Fear of falling
  A lot3 (16)
  A little8 (42)
  Somewhat6 (32)
  Not at all2 (11)
Influence of fear of falling on daily activities
  A little7 (37)
  Somewhat4 (21)
  Not at all8 (42)

Changes in Balance, Muscle Strength, and Fall Risk Measures From Baseline to 8 Weeks (N = 19)

MeasurePretestPosttestPercentage ChangeEffect Size (Cohen's d)p Value
BTrackS Balance Testa29.79 (15.74)26.84 (12.21)9.90.470.056
Timed-Up & Go testb11.81 (3.37)10.26 (3.12)13.10.001
Sit-to-Stand testa10.68 (3.11)13.68 (5.34)280.95<0.001
Fall riska,c4.58 (4.10)3.74 (3.72)18.30.610.016
Handgrip strengthb27.25 (10.19)32.08 (12.61)17.70.004
Authors

Dr. Thiamwong is Assistant Professor, Dr. Sole is Dean and Professor, Orlando Health Endowed Chair, Dr. Ng is Assistant Professor, and Dr. Talbert is Assistant Professor, College of Nursing, and Dr. Stout is Professor, School of Kinesiology and Physical Therapy, College of Health Professions and Sciences, and Dr. Yan is Professor, Department of Statistics and Data Science, College of Science, University of Central Florida, Orlando, Florida. Dr. Sole is also Clinical Scientist, Orlando Health, Orlando, Florida.

The authors have disclosed no potential conflicts of interest, financial or otherwise. This study received financial support from the Office of Research, University of Central Florida.

Address correspondence to Ladda Thiamwong, PhD, RN, Assistant Professor, College of Nursing, University of Central Florida, 12201 Research Parkway, Orlando, FL 32826-2210; email: ladda.thiamwong@ucf.edu.

Received: August 27, 2019
Accepted: November 21, 2019
Posted Online: April 14, 2020

10.3928/19404921-20200324-01

Sign up to receive

Journal E-contents