Ronny Bergquist

Extensive test batteries are often needed to obtain a comprehensive picture of a person’s functional status. Many test batteries are not suitable for active and healthy adults due to ceiling effects, or require a lot of space, time, and training. The Community Balance and Mobility Scale (CBMS) is considered a gold standard for this population, but the test is complex, as well as time- and resource intensive. There is a strong need for a faster, yet sensitive and robust test of physical function in seniors. We sought to investigate whether an instrumented Timed Up and Go (iTUG) could predict the CBMS score in 60 outpatients and healthy community-dwelling seniors, where features of the iTUG were predictive, and how the prediction of CBMS with the iTUG compared to standard clinical tests. A partial least squares regression analysis was used to identify latent components explaining variation in CBMS total score. The model with iTUG features was able to predict the CBMS total score with an accuracy of 85.2% (84.9–85.5%), while standard clinical tests predicted 82.5% (82.2–82.8%) of the score. These findings suggest that a fast and easily administered iTUG could be used to predict CBMS score, providing a valuable tool for research and clinical care.

Background: Objective measures of physical function in older adults are widely used to predict health outcomes such as disability, institutionalization, and mortality. App-based clinical tests allow users to assess their own physical function and have objective tracking of changes over time by use of their smartphones. Such tests can potentially guide interventions remotely and provide more detailed prognostic information about the participant’s physical performance for the users, therapists, and other health care personnel. We developed 3 smartphone apps with instrumented versions of the Timed Up and Go (Self-TUG), tandem stance (Self-Tandem), and Five Times Sit-to-Stand (Self-STS) tests. Objective: This study aimed to test the usability of 3 smartphone app–based self-tests of physical function using an iterative design. Methods: The apps were tested in 3 iterations: the first (n=189) and second (n=134) in a lab setting and the third (n=20) in a separate home-based study. Participants were healthy adults between 60 and 80 years of age. Assessors observed while participants self-administered the tests without any guidance. Errors were recorded, and usability problems were defined. Problems were addressed in each subsequent iteration. Perceived usability in the home-based setting was assessed by use of the System Usability Scale, the User Experience Questionnaire, and semi-structured interviews. Results: In the first iteration, 7 usability problems were identified; 42 (42/189, 22.0%) and 127 (127/189, 67.2%) participants were able to correctly perform the Self-TUG and Self-Tandem, respectively. In the second iteration, errors caused by the problems identified in the first iteration were drastically reduced, and 108 (108/134, 83.1%) and 106 (106/134, 79.1%) of the participants correctly performed the Self-TUG and Self-Tandem, respectively. The first version of the Self-STS was also tested in this iteration, and 40 (40/134, 30.1%) of the participants performed it correctly. For the third usability test, the 7 usability problems initially identified were further improved. Testing the apps in a home setting gave rise to some new usability problems, and for Self-TUG and Self-STS, the rates of correctly performed trials were slightly reduced from the second version, while for Self-Tandem, the rate increased. The mean System Usability Scale score was 77.63 points (SD 16.1 points), and 80-95% of the participants reported the highest or second highest positive rating on all items in the User Experience Questionnaire. Conclusions: The study results suggest that the apps have the potential to be used to self-test physical function in seniors in a nonsupervised home-based setting. The participants reported a high degree of ease of use. Evaluating the usability in a home setting allowed us to identify new usability problems that could affect the validity of the tests. These usability problems are not easily found in the lab setting, indicating that, if possible, app usability should be evaluated in both settings. Before being made available to end users, the apps require further improvements and validation.

BACKGROUND Objective measures of physical function in older adults are widely used to predict health outcomes such as disability, institutionalization, and mortality. App-based clinical tests allow users to assess their own physical function and have objective tracking of changes over time by use of their smartphones. Such tests can potentially guide interventions remotely and provide more detailed prognostic information about the participant’s physical performance for the users, therapists, and other health care personnel. We developed 3 smartphone apps with instrumented versions of the Timed Up and Go (Self-TUG), tandem stance (Self-Tandem), and Five Times Sit-to-Stand (Self-STS) tests. OBJECTIVE This study aimed to test the usability of 3 smartphone app–based self-tests of physical function using an iterative design. METHODS The apps were tested in 3 iterations: the first (n=189) and second (n=134) in a lab setting and the third (n=20) in a separate home-based study. Participants were healthy adults between 60 and 80 years of age. Assessors observed while participants self-administered the tests without any guidance. Errors were recorded, and usability problems were defined. Problems were addressed in each subsequent iteration. Perceived usability in the home-based setting was assessed by use of the System Usability Scale, the User Experience Questionnaire, and semi-structured interviews. RESULTS In the first iteration, 7 usability problems were identified; 42 (42/189, 22.0%) and 127 (127/189, 67.2%) participants were able to correctly perform the Self-TUG and Self-Tandem, respectively. In the second iteration, errors caused by the problems identified in the first iteration were drastically reduced, and 108 (108/134, 83.1%) and 106 (106/134, 79.1%) of the participants correctly performed the Self-TUG and Self-Tandem, respectively. The first version of the Self-STS was also tested in this iteration, and 40 (40/134, 30.1%) of the participants performed it correctly. For the third usability test, the 7 usability problems initially identified were further improved. Testing the apps in a home setting gave rise to some new usability problems, and for Self-TUG and Self-STS, the rates of correctly performed trials were slightly reduced from the second version, while for Self-Tandem, the rate increased. The mean System Usability Scale score was 77.63 points (SD 16.1 points), and 80-95% of the participants reported the highest or second highest positive rating on all items in the User Experience Questionnaire. CONCLUSIONS The study results suggest that the apps have the potential to be used to self-test physical function in seniors in a nonsupervised home-based setting. The participants reported a high degree of ease of use. Evaluating the usability in a home setting allowed us to identify new usability problems that could affect the validity of the tests. These usability problems are not easily found in the lab setting, indicating that, if possible, app usability should be evaluated in both settings. Before being made available to end users, the apps require further improvements and validation.

Assessment of physical performance by standard clinical tests such as the 30-s Chair Stand (30CST) and the Timed Up and Go (TUG) may allow early detection of functional decline, even in high-functioning populations, and facilitate preventive interventions. Inertial sensors are emerging to obtain instrumented measures that can provide subtle details regarding the quality of the movement while performing such tests. We compared standard clinical with instrumented measures of physical performance in their ability to distinguish between high and very high functional status, stratified by the Late-Life Function and Disability Instrument (LLFDI). We assessed 160 participants from the PreventIT study (66.3 ± 2.4 years, 87 females, median LLFDI 72.31, range: 44.33–100) performing the 30CST and TUG while a smartphone was attached to their lower back. The number of 30CST repetitions and the stopwatch-based TUG duration were recorded. Instrumented features were computed from the smartphone embedded inertial sensors. Four logistic regression models were fitted and the Areas Under the Receiver Operating Curve (AUC) were calculated and compared using the DeLong test. Standard clinical and instrumented measures of 30CST both showed equal moderate discriminative ability of 0.68 (95%CI 0.60–0.76), p = 0.97. Similarly, for TUG: AUC was 0.68 (95%CI 0.60–0.77) and 0.65 (95%CI 0.56–0.73), respectively, p = 0.26. In conclusion, both clinical and instrumented measures, recorded through a smartphone, can discriminate early functional decline in healthy adults aged 61–70 years.

Many balance and strength tests exist that have been designed for older seniors, often aged ≥70 years. To guide strategies for preventing functional decline, valid and reliable tests are needed to detect early signs of functional decline in young seniors. Currently, little is known about which tests are being used in young seniors and their methodological quality. This two-step review aims to 1) identify commonly used tests of balance and strength, and 2) evaluate their measurement properties in young seniors. First, a systematic literature search was conducted in MEDLINE to identify primary studies that employed performance-based tests of balance and muscle strength, and which aspects of balance and strength these tests assess in young seniors aged 60–70. Subsequently, for tests used in ≥3 studies, a second search was performed to identify method studies evaluating their measurement properties. The quality of included method studies was evaluated using the Consensus-based Standards for selection of health Measurement Instruments (COSMIN) checklist. Of 3454 articles identified, 295 met the inclusion criteria. For the first objective, 69 balance and 51 muscle strength tests were identified, with variations in administration mode and outcome reporting. Twenty-six balance tests and 15 muscle strength tests were used in ≥3 studies, with proactive balance tests and functional muscle power tests used most often. For the second objective, the search revealed 1880 method studies, of which nine studies (using 5 balance tests and 1 strength test) were included for quality assessment. The Timed Up and Go test was evaluated the most (4 studies), while the Community Balance and Mobility (CBM) scale was the second most assessed test (3 studies). For strength, one study assessed the reliability of the Five times sit-to-stand. Commonly used balance and muscle strength tests in young seniors vary greatly with regards to administration mode and outcome reporting. Few studies have evaluated measurement properties of these tests when used in young seniors. There is a need for standardisation of existing tests to improve their informative value and comparability. For measuring balance, the CBM is a new and promising tool to detect even small balance deficits in balance in young seniors.

With the growing number of young-older adults (baby-boomers), there is an increasing demand for assessment tools specific for this population, which are able to detect subtle balance and mobility deficits. Various balance and mobility tests already exist, but suffer from ceiling effects in higher functioning older adults. A reliable and valid challenging balance and mobility test is critical to determine a young-older adult’s balance and mobility performance and to timely initiate preventive interventions. The aim was to evaluate the concurrent validity, inter- and intrarater reliability, internal consistency, and ceiling effects of a challenging balance and mobility scale, the Community Balance and Mobility Scale (CBM), in young-older adults aged 60 to 70 years. Fifty-one participants aged 66.4 ± 2.7 years (range, 60–70 years) were assessed with the CBM. The Fullerton Advanced Balance scale (FAB), 3-Meter Tandem Walk (3MTW), 8-level balance scale, Timed-Up-and-Go (TUG), and 7-m habitual gait speed were used to estimate concurrent validity, examined by Spearman correlation coefficient (ρ). Inter- and intrarater reliability were calculated as Intra-class-correlations (ICC), and internal consistency by Cronbach alpha and item-total correlations (ρ). Ceiling effects were determined by obtaining the percentage of participants reaching the highest possible score. The CBM significantly correlated with the FAB (ρ = 0.75; p < .001), 3MTW errors (ρ = − 0.61; p < .001), 3MTW time (ρ = − 0.35; p = .05), the 8-level balance scale (ρ = 0.35; p < .05), the TUG (ρ = − 0.42; p < .01), and 7-m habitual gait speed (ρ = 0.46, p < .001). Inter- (ICC2,k = 0.97), intrarater reliability (ICC3,k = 1.00) were excellent, and internal consistency (α = 0.88; ρ = 0.28–0.81) was good to satisfactory. The CBM did not show ceiling effects in contrast to other scales. Concurrent validity of the CBM was good when compared to the FAB and moderate to good when compared to other measures of balance and mobility. Based on this study, the CBM can be recommended to measure balance and mobility performance in the specific population of young-older adults. Trial number: ISRCTN37750605 . (Registered on 21/04/2016).

Elastic resistance bands require little space, are light and portable, but their efficacy has not yet been established for several resistance exercises. The main objective of this study was to compare the muscle activation levels induced by elastic resistance bands versus conventional resistance training equipment (dumbbells) in the upper-body resistance exercises flyes and reverse flyes. The level of muscle activation was measured with surface electromyography in 29 men and women in a cross-over design where resistance loadings with elastic resistance bands and dumbbells were matched using 10-repetition maximum loadings. Elastic resistance bands induced slightly lower muscle activity in the muscles most people aim to activate during flyes and reverse flies, namely pectoralis major and deltoideus posterior, respectively. However, elastic resistance bands increased the muscle activation level substantially in perceived ancillary muscles, that is deltoideus anterior in flyes, and deltoideus medius and trapezius descendens in reverse flyes, possibly due to elastic bands being a more unstable resistance modality. Overall, the results show that elastic resistance bands can be considered a feasible alternative to dumbbells in flyes and reverse flyes.

Physical activity monitoring algorithms are often developed using conditions that do not represent real-life activities, not developed using the target population, or not labelled to a high enough resolution to capture the true detail of human movement. We have designed a semi-structured supervised laboratory-based activity protocol and an unsupervised free-living activity protocol and recorded 20 older adults performing both protocols while wearing up to 12 body-worn sensors. Subjects’ movements were recorded using synchronised cameras (≥25 fps), both deployed in a laboratory environment to capture the in-lab portion of the protocol and a body-worn camera for out-of-lab activities. Video labelling of the subjects’ movements was performed by five raters using 11 different category labels. The overall level of agreement was high (percentage of agreement >90.05%, and Cohen’s Kappa, corrected kappa, Krippendorff’s alpha and Fleiss’ kappa >0.86). A total of 43.92 h of activities were recorded, including 9.52 h of in-lab and 34.41 h of out-of-lab activities. A total of 88.37% and 152.01% of planned transitions were recorded during the in-lab and out-of-lab scenarios, respectively. This study has produced the most detailed dataset to date of inertial sensor data, synchronised with high frame-rate (≥25 fps) video labelled data recorded in a free-living environment from older adults living independently. This dataset is suitable for validation of existing activity classification systems and development of new activity classification algorithms.