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CONTEXT: Long-term adherence to physical activity (PA) interventions is challenging. The Lifestyle-integrated Functional Exercise programmes were adapted Lifestyle-integrated Functional Exercise (aLiFE) to include more challenging activities and a behavioural change framework, and then enhanced Lifestyle-integrated Functional Exercise (eLiFE) to be delivered using smartphones and smartwatches. OBJECTIVES: To (1) compare adherence measures, (2) identify determinants of adherence and (3) assess the impact on outcome measures of a lifestyle-integrated programme. DESIGN, SETTING AND PARTICIPANTS: A multicentre, feasibility randomised controlled trial including participants aged 61-70 years conducted in three European cities. INTERVENTIONS: Six-month trainer-supported aLiFE or eLiFE compared with a control group, which received written PA advice. OUTCOME MEASURES: Self-reporting adherence per month using a single question and after 6-month intervention using the Exercise Adherence Rating Scale (EARS, score range 6-24). Treatment outcomes included function and disability scores (measured using the Late-Life Function and Disability Index) and sensor-derived physical behaviour complexity measure. Determinants of adherence (EARS score) were identified using linear multivariate analysis. Linear regression estimated the association of adherence on treatment outcome. RESULTS: We included 120 participants randomised to the intervention groups (aLiFE/eLiFE) (66.3±2.3 years, 53% women). The 106 participants reassessed after 6 months had a mean EARS score of 16.0±5.1. Better adherence was associated with lower number of medications taken, lower depression and lower risk of functional decline. We estimated adherence to significantly increase basic lower extremity function by 1.3 points (p<0.0001), advanced lower extremity function by 1.0 point (p<0.0001) and behavioural complexity by 0.008 per 1.0 point higher EARS score (F(3,91)=3.55, p=0.017) regardless of group allocation. CONCLU

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.

Background: Behavioral change is the key to alter individuals' lifestyle from sedentary to active. The aim was to assess the feasibility of delivering a Lifestyle-integrated Functional Exercise programme and evaluate the delivery of the intervention by use of digital technology (eLiFE) to prevent functional decline in 61-70 year-old adults. Methods: This multicentre, feasibility randomized controlled trial was run in three countries (Norway, Germany, and the Netherlands). Out of 7,500 potential participants, 926 seniors (12%) were screened and 180 participants randomized to eLiFE (n = 61), aLiFE (n = 59), and control group (n = 60). eLiFE participants used an application on smartphones and smartwatches while aLiFE participants used traditional paper-based versions of the same lifestyle-integrated exercise intervention. Participants were followed for 12 months, with assessments at baseline, after a 6 month active trainer-supported intervention, and after a further 6 months of unsupervised continuation of the programme. Results: At 6 months, 87% of participants completed post-test, and 77% completed the final assessment at 12 months. Participants were willing to be part of the programme, with compliance and reported adherence relatively high. Despite small errors during start-up in the technological component, intervention delivery by use of technology appeared acceptable. No serious adverse events were related to the interventions. All groups improved regarding clinical outcomes over time, and complexity metrics show potential as outcome measure in young seniors. Conclusion: This feasibility RCT provides evidence that an ICT-based lifestyle-integrated exercise intervention, focusing on behavioral change, is feasible and safe for young seniors. Clinical Trial Registration: ClinicalTrials.gov, identifier: NCT03065088. Registered on 14 February 2017.

BACKGROUND: Understanding the association between motor capacity (MC) (what people can do in a standardized environment), mobility performance (MP) (what people actually do in real-life) and falls is important for early detection of and counteracting on functional decline, particularly in the rapidly growing population of young seniors. Therefore, this study aims to 1) explore the association between MC and MP, and between MC and falls, and 2) investigate whether challenging MC measures are better associated with MP and falls than basic MC measures. METHODS: Basic (habitual gait speed, Timed Up-and-Go) and challenging (fast gait speed, Community Balance & Mobility Scale) MC measures were performed in 169 young seniors (61-70 years). MP was assessed using one-week sensor-monitoring including time being sedentary, light active, and at least moderately active. Falls in the previous six months were reported. Associations and discriminative ability were calculated using correlation, regression and receiver operating curve analysis. RESULTS: Mean age was 66.4 (SD 2.4) years (50.6 % women). Small to moderate associations (r = 0.06-0.31; p < .001-.461) were found between MC, MP and falls. Challenging MC measures showed closer associations with MP and falls (r = 0.10-0.31; p < .001-.461) compared to basic (r = 0.06-0.22; p = .012-.181), remained significant in three out of four regression models explaining 2.5-8.6 % of the variance, and showed highest discriminative ability (area under the curve = 0.59-0.70) in all analyses. CONCLUSIONS: Challenging MC measures are closer associated with mobility performance and falls as compared to basic MC measures in young seniors. This indicates the importance of applying challenging motor capacity assessments in young seniors. On the same note, small to moderate associations imply a need for an assessment of both MC and MP in order to capture the best possible MC and the actual daily-life MP in young seniors.

INTRODUCTION: The European population is rapidly ageing. In order to handle substantial future challenges in the healthcare system, we need to shift focus from treatment towards health promotion. The PreventIT project has adapted the Lifestyle-integrated Exercise (LiFE) programme and developed an intervention for healthy young older adults at risk of accelerated functional decline. The intervention targets balance, muscle strength and physical activity, and is delivered either via a smartphone application (enhanced LiFE, eLiFE) or by use of paper manuals (adapted LiFE, aLiFE). METHODS AND ANALYSIS: The PreventIT study is a multicentre, three-armed feasibility randomised controlled trial, comparing eLiFE and aLiFE against a control group that receives international guidelines of physical activity. It is performed in three European cities in Norway, Germany, and The Netherlands. The primary objective is to assess the feasibility and usability of the interventions, and to assess changes in daily life function as measured by the Late-Life Function and Disability Instrument scale and a physical behaviour complexity metric. Participants are assessed at baseline, after the 6 months intervention period and at 1 year after randomisation. Men and women between 61 and 70 years of age are randomly drawn from regional registries and respondents screened for risk of functional decline to recruit and randomise 180 participants (60 participants per study arm). ETHICS AND DISSEMINATION: Ethical approval was received at all three trial sites. Baseline results are intended to be published by late 2018, with final study findings expected in early 2019. Subgroup and further in-depth analyses will subsequently be published. TRIAL REGISTRATION NUMBER: NCT03065088; Pre-results.

Assessment of physical performance by standard clinical tests such as the 30-sec 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.

The emerging mHealth applications, incorporating wearable sensors, enables continuous monitoring of physical activity (PA). This study aimed at analyzing the relevance of a multivariate complexity metric in assessment of functional change in younger older adults. Thirty individuals (60⁻70 years old) participated in a 4-week home-based exercise intervention. The Community Balance and Mobility Scale (CBMS) was used for clinical assessment of the participants’ functional balance and mobility performance pre- and post- intervention. Accelerometers worn on the low back were used to register PA of one week before and in the third week of the intervention. Changes in conventional univariate PA metrics (percentage of walking and sedentary time, step counts, mean cadence) and complexity were compared to the change as measured by the CBMS. Statistical analyses (21 participants) showed significant rank correlation between the change as measured by complexity and CBMS (ρ = 0.47, p = 0.03). Smoothing the activity output improved the correlation (ρ = 0.58, p = 0.01). In contrast, change in univariate PA metrics did not show correlations. These findings demonstrate the high potential of the complexity metric being useful and more sensitive than conventional PA metrics for assessing functional changes in younger older adults.