App-based Self-administrable Clinical Tests of Physical Function: Development and Usability Study

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

Spoon handling in two- to four year old children

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Robustness of In-Laboratory and Daily-Life Gait Speed Measures over One Year in High Functioning 61- To 70-Year-Old Adults

Introduction: Gait speed is a simple and safe measure with strong predictive value for negative health outcomes in clinical practice, yet in-laboratory gait speed seems not representative for daily-life gait speed. This study aimed to investigate the interrelation between and robustness of in-laboratory and daily-life gait speed measures over 12 months in 61- to 70-year-old adults. Methods: Gait speed was assessed in laboratory through standardized stopwatch tests and in daily life by 7 days of trunk accelerometry in the PreventIT cohort, at baseline, and after 6 and 12 months. The interrelation was investigated using Pearson's correlations between gait speed measures at each time point. For robustness, changes over time and variance components were assessed by ANOVA and measurement agreement over time by Bland-Altman analyses. Results: Included were 189 participants (median age 67 years [interquartile range: 64-68], 52.2% females). In-laboratory and daily-life gait speed measures showed low correlations (Pearson's r = 0.045-0.455) at each time point. Moreover, both in-laboratory and daily-life gait speed measures appeared robust over time, with comparable and smaller within-subject than between-subject variance (range 0.001-0.095 m/s and 0.032-0.397 m/s, respectively) and minimal differences between measurements over time (Bland-Altman) with wide limits of agreement (standard deviation of mean difference range: 0.12-0.34 m/s). Discussion/Conclusion: In-laboratory and daily-life gait speed measures show robust assessments of gait speed over 12 months and are distinct constructs in this population of high-functioning adults. This suggests that (a combination of) both measures may have added value in predicting health outcomes

Concurrent validity and reliability of the Community Balance and Mobility scale in young-older adults

Background: 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. Methods: 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. Results: 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. Conclusions: 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 registration Trial number: ISRCTN37750605 . (Registered on 21/04/2016)

Effects of the number of markers per haplotype and clustering of haplotypes on the accuracy of QTL mapping and prediction of genomic breeding values

The aim of this paper was to compare the effect of haplotype definition on the precision of QTL-mapping and on the accuracy of predicted genomic breeding values. In a multiple QTL model using identity-by-descent (IBD) probabilities between haplotypes, various haplotype definitions were tested i.e. including 2, 6, 12 or 20 marker alleles and clustering base haplotypes related with an IBD probability of > 0.55, 0.75 or 0.95. Simulated data contained 1100 animals with known genotypes and phenotypes and 1000 animals with known genotypes and unknown phenotypes. Genomes comprising 3 Morgan were simulated and contained 74 polymorphic QTL and 383 polymorphic SNP markers with an average r2 value of 0.14 between adjacent markers. The total number of haplotypes decreased up to 50% when the window size was increased from two to 20 markers and decreased by at least 50% when haplotypes related with an IBD probability of > 0.55 instead of > 0.95 were clustered. An intermediate window size led to more precise QTL mapping. Window size and clustering had a limited effect on the accuracy of predicted total breeding values, ranging from 0.79 to 0.81. Our conclusion is that different optimal window sizes should be used in QTL-mapping versus genome-wide breeding value prediction

A roadmap to inform development, validation and approval of digital mobility outcomes: the Mobilise-D approach

Health care has had to adapt rapidly to COVID-19, and this in turn has highlighted a pressing need for tools to facilitate remote visits and monitoring. Digital health technology, including body-worn devices, offers a solution using digital outcomes to measure and monitor disease status and provide outcomes meaningful to both patients and health care professionals. Remote monitoring of physical mobility is a prime example, because mobility is among the most advanced modalities that can be assessed digitally and remotely. Loss of mobility is also an important feature of many health conditions, providing a read-out of health as well as a target for intervention. Real-world, continuous digital measures of mobility (digital mobility outcomes or DMOs) provide an opportunity for novel insights into health care conditions complementing existing mobility measures. Accepted and approved DMOs are not yet widely available. The need for large collaborative efforts to tackle the critical steps to adoption is widely recognised. Mobilise-D is an example. It is a multidisciplinary consortium of 34 institutions from academia and industry funded through the European Innovative Medicines Initiative 2 Joint Undertaking. Members of Mobilise-D are collaborating to address the critical steps for DMOs to be adopted in clinical trials and ultimately health care. To achieve this, the consortium has developed a roadmap to inform the development, validation and approval of DMOs in Parkinson’s disease, multiple sclerosis, chronic obstructive pulmonary disease and recovery from proximal femoral fracture. Here we aim to describe the proposed approach and provide a high-level view of the ongoing and planned work of the Mobilise-D consortium. Ultimately, Mobilise-D aims to stimulate widespread adoption of DMOs through the provision of device agnostic software, standards and robust validation in order to bring digital outcomes from concept to use in clinical trials and health care

Walking on common ground: a cross-disciplinary scoping review on the clinical utility of digital mobility outcomes

Physical mobility is essential to health, and patients often rate it as a high-priority clinical outcome. Digital mobility outcomes (DMOs), such as real-world gait speed or step count, show promise as clinical measures in many medical conditions. However, current research is nascent and fragmented by discipline. This scoping review maps existing evidence on the clinical utility of DMOs, identifying commonalities across traditional disciplinary divides. In November 2019, 11 databases were searched for records investigating the validity and responsiveness of 34 DMOs in four diverse medical conditions (Parkinson’s disease, multiple sclerosis, chronic obstructive pulmonary disease, hip fracture). Searches yielded 19,672 unique records. After screening, 855 records representing 775 studies were included and charted in systematic maps. Studies frequently investigated gait speed (70.4% of studies), step length (30.7%), cadence (21.4%), and daily step count (20.7%). They studied differences between healthy and pathological gait (36.4%), associations between DMOs and clinical measures (48.8%) or outcomes (4.3%), and responsiveness to interventions (26.8%). Gait speed, step length, cadence, step time and step count exhibited consistent evidence of validity and responsiveness in multiple conditions, although the evidence was inconsistent or lacking for other DMOs. If DMOs are to be adopted as mainstream tools, further work is needed to establish their predictive validity, responsiveness, and ecological validity. Cross-disciplinary efforts to align methodology and validate DMOs may facilitate their adoption into clinical practice