Evaluation of Concurrent Validity between a Smartphone Self-Test Prototype and Clinical Instruments for Balance and Leg Strength

Smartphone-Based Sit-to-Stand Analysis for Mobility Assessment in Middle Age

Background and Objectives

Mobility can decline in middle age and growing evidence highlights the importance of assessing mobility at this stage of life. Smartphone-based accelerometry during sit-to-stand has been shown to identify mobility impairments, but its utility in detecting subtle mobility deterioration in middle age has not been tested. This study aimed to examine whether smartphone-based accelerometry data measured during sit-to-stand tests performed on a regular chair and a cushioned sofa could be useful for detecting subtle changes in mobility in middle age.

Research Design and Methods

Twenty-three young (25.0 ± 2.5 years), 25 middle-aged (52.0 ± 5.2 years), and 17 older adults (70.0 ± 4.1 years) performed the 5-times sit-to-stand test on both a standard chair and a sofa. A smartphone attached to the participants' lower back was used to measure lower-limb muscle power, maximal vertical velocity (MVV) during rising, the duration of the total task and the subphase of transition from sitting to standing (SiToSt), and repetition variability using the dynamic time warping method.

Results

Middle-aged adults had reduced lower-limb muscle power compared to young adults (5.25 ± 1.08 vs 6.19 ± 1.38 W/kg, p = .034), being more pronounced on the sofa (6.23 ± 1.61 vs 8.08 ± 2.17 W/kg, p = .004). Differences between middle-aged and young adults in terms of MVV (p = .011) and SiToSt duration (p = .038) were only detected on the sofa, and the middle-aged adults showed less variability compared to the older adults on the chair (p = .018). There was no difference in total task duration between the middle-aged group and the young or older adults in either condition.

Discussion and Implications

Most common tests are limited in their ability to detect early mobility deterioration in midlife due to a ceiling effect. Our results, which show the potential of smartphone-based sit-to-stand assessment in detecting subtle mobility decline in midlife, could serve as a screening tool for this purpose.

Accelerometry applications and methods to assess standing balance in older adults and mobility-limited patient populations: a narrative review

Accelerometers provide an opportunity to expand standing balance assessments outside of the laboratory. The purpose of this narrative review is to show that accelerometers are accurate, objective, and accessible tools for balance assessment. Accelerometry has been validated against current gold standard technology, such as optical motion capture systems and force plates. Many studies have been conducted to show how accelerometers can be useful for clinical examinations. Recent studies have begun to apply classification algorithms to accelerometry balance measures to discriminate populations at risk for falls. In addition to healthy older adults, accelerometry can monitor balance in patient populations such as Parkinson's disease, multiple sclerosis, and traumatic brain injury. The lack of software packages or easy-to-use applications have hindered the shift into the clinical space. Lack of consensus on outcome metrics has also slowed the clinical adoption of accelerometer-based balance assessments. Future studies should focus on metrics that are most helpful to evaluate balance in specific populations and protocols that are clinically efficacious.

Validity of muscular fitness self-assessments in the ecofit smartphone application: A correlation study

BACKGROUND

Mobile app-based interventions have the potential for wide-reach and therefore may be a useful tool in up-scaling physical activity interventions. In larger-scale interventions, face-to-face assessments are less cost-effective, and researchers often rely on surveys or activity trackers to assess outcomes. However, there is limited evidence of valid muscular fitness assessments that can be self-administered within mHealth interventions. As such, this study will evaluate the concurrent validity of upper and lower body muscular fitness that have been independently assessed by participants via the ecofit app, and face-to-face assessments conducted by a trained researcher.

METHODS

This study compared baseline data from two muscular fitness tests from the ecofit two-armed randomised controlled trial and self-assessed data collected via the ecofit smartphone app (i.e., validated 90-degree push-up and 60-second sit-to-stand test). To assess the concurrent validity, the self-assessed push-up and sit-to-stand tests (i.e., collected via the ecofit app) were correlated using Spearman's correlation coefficient against the researcher-assessed results (i.e., objective results collected during baseline assessment for the ecofit trial). Bland-Altman plots were also used to allow visualisation of the differences between the self- and research-assessed tests.

RESULTS

Participants (N = 54) completed the push-up (24.1%) and sit-to-stand (100%) tests within 14-days of receiving the app. The results revealed a strong significant correlation for the push-up test (0.83, p<0.001) and a moderate significant correlation for the sit-to-stand test (0.63, p<0.001).

CONCLUSION

This study provides support for the concurrent validity of self-reported upper and lower body muscular fitness assessments (i.e., the push-up and sit-to-stand tests) in mHealth. While these tests may be a feasible option for large scale physical activity interventions, more research is needed to determine the generalisability of these results.

Mobile Technology for Falls Prevention in Older Adults

Falls are the leading cause of accidental death in older adults that result from a complex interplay of risk factors. Recently, the need for person-centered approach utilizing personalization, prediction, prevention and participation, known as the P4 model, in fall prevention has been highlighted. Features of mobile technology make it a suitable technological infrastructure to employ such an approach. This narrative review aims to review the evidence for using mobile technology for personalized fall risk assessment and prevention since 2017 in older adults. We aim to identify lessons learned and future directions for using mobile technology as a fall risk assessment and prevention tool. Articles were searched in PubMed and Web of Science with search terms related to older adults, mobile technology, and falls prevention. A total of 23 articles were included. Articles were identified as those examining aspects of the P4 model including prediction (measurement of fall risk), personalization (usability), prevention, and participation. Mobile technology appears to be comparable to gold-standard technology in measuring well-known fall risk factors including static and dynamic balance. Seven applications were developed to measure different fall risk factors and tested for personalization, and/or participation aspects, and four were integrated into a falls prevention program. Mobile health technology offers an innovative solution to provide tailored fall risk screening, prediction, and participation. Future studies should incorporate multiple, objective fall risk measures and implement them in community settings to determine if mobile technology can offer tailored and scalable interventions.

The Developments and Iterations of a Mobile Technology-Based Fall Risk Health Application

Falls are a prevalent and serious health concern across clinical populations. A critical step in falls prevention is identifying modifiable risk factors, but due to time constraints and equipment costs, fall risk screening is rarely performed. Mobile technology offers an innovative approach to provide personalized fall risk screening for clinical populations. To inform future development, this manuscript discusses the development and testing of mobile health fall risk applications for three unique clinical populations [older adults, individuals with Multiple Sclerosis (MS), and wheeled-device users]. We focus on key lessons learned and future directions to improve the field of fall risk mHealth. During the development phase, we first identified fall risk factors specific to each population that are measurable with mobile technology. Second, we determined whether inertial measurement units within smartphones can measure postural control within the target population. Last, we developed the interface of each app with a user-centered design approach with usability testing through iterative semi-structured interviews. We then tested our apps in real-world settings. Our cumulative work demonstrates that mobile technology can be leveraged to provide personalized fall risk screening for different clinical populations. Fall risk apps should be designed and tailored for the targeted group to enhance usefulness and feasibility. In addition, fall risk factors measured with mobile technology should include those that are specific to the population, are measurable with mobile technology, and can accurately measure fall risk. Future work should improve fall risk algorithms and implement mobile technology into fall prevention programs.

Feasibility of performance-based and self-reported outcomes in self-managed falls prevention exercise interventions for independent older adults living in the community

Background

Little is known about associations between performance-based measurements and self-reported scales, nor about ceiling effects or sensitivity to change to evaluate effects in the target population for self-managed exercise interventions. This study aimed to explore the feasibility of using performance-based outcomes for gait speed, functional leg strength and balance, and self-reported outcomes of falls-efficacy and functional ability in two self-managed falls prevention exercise interventions for community dwelling older adults.

Methods

Independent living, community-dwelling older adults (n = 67) exercised with one of two self-managed falls prevention exercise programmes, a digital programme (DP) or a paper booklet (PB) in a 4-month participant preference trial. Pre- and post-assessments, by blinded assessors, included Short Physical Performance Battery (SPPB) and 30s Chair stand test (30s CST). Participants completed self-reported questionnaires: Activities-specific and Balance Confidence scale (ABC), Iconographical Falls Efficacy Scale (Icon-FES), Late-Life Function and Disability Instrument Function Component (LLFDI-FC). In addition, improvement in balance and leg strength was also self-rated at post-assessment. Participants’ mean age was 76 ± 4 years and 72% were women.

Results

Ceiling effects were evident for the balance sub-component of the SPPB, and also indicated for ABC and Icon-FES in this high functioning population. In SPPB, gait speed, 30s CST, and LLFDI-FC, 21–56% of participants did not change their scores beyond the Minimal Clinically Important Difference (MCID). At pre-assessment all performance-based tests correlated significantly with the self-reported scales, however, no such significant correlations were seen with change-scores. Improvement of performance-based functional leg strength with substantial effect sizes and significant correlations with self-reported exercise time was shown. There were no differences in outcomes between the exercise programmes except that DP users reported improved change of leg strength to a higher degree than PB users.

Conclusion

The LLFDI-FC and sit-to-stand tests were feasible and sensitive to change in this specific population. The balance sub-component of SPPB and self-reported measures ABC and Icon-FES indicated ceiling effects and might not be suitable as outcome measures for use in a high functioning older population. Development and evaluation of new outcome measures are needed for self-managed fall-preventive interventions with high functioning community-dwelling older adults.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-02851-9.

App-based strength and balance self-test in older adults: an exploratory study from a user perspective

Objectives

Falls are a common problem, especially in the older population. The number of older adults aged over 65 years is increasing globally, leading to a major challenge in providing effective fall prevention interventions to older adults requiring such interventions. This study aimed to explore the usability of an app-based strength and balance self-tests in a small sample of four older adults. This study is a side product of another project.

Results

The results from this study indicated that self-test of strength and balance by using a smartphone application is a challenge for older adults. Basic test measures, such as start and stop and counts of sit-to-stand, were difficult to self-administer. However, from a user perspective, the possibility of independently performing these measures was considered important and needed to be further developed and evaluated in future studies.