Tailored implementation of national recommendations on fall prevention among older adults in municipalities in Norway (FALLPREVENT trial): a study protocol for a cluster-randomised trial.

BACKGROUND: Despite substantial research evidence indicating the effectiveness of a range of interventions to prevent falls, uptake into routine clinical practice has been limited by several implementation challenges. The complexity of fall prevention in municipality health care underlines the importance of flexible implementation strategies tailored both to general determinants of fall prevention and to local contexts. This cluster-randomised trial (RCT) investigates the effectiveness of a tailored intervention to implement national recommendations on fall prevention among older home-dwelling adults compared to usual practice on adherence to the recommendations in health professionals. METHODS: Twenty-five municipalities from four regions in Norway will be randomised to intervention or control arms. Each municipality cluster will recruit up to 30 health professionals to participate in the study as responders. The tailored implementation intervention comprises four components: (1) identifying local structures for implementation, (2) establishing a resource team from different professions and levels, (3) promoting knowledge on implementation and fall prevention and (4) supporting the implementation process. Each of these components includes several implementation activities. The Consolidated Framework for Implementation Research (CFIR) will be used to categorise determinants of the implementation process and the Expert Recommendations for Implementing Change (ERIC) will guide the matching of barriers to implementation strategies. The primary outcome measure for the study will be health professionals' adherence to the national recommendations on fall prevention measured by a questionnaire. Secondary outcomes include injurious falls, the feasibility of the intervention, the experiences of the implementation process and intervention costs. Measurements will be carried out at baseline in August 2023, post-intervention in May 2024 and at a follow-up in November 2024. DISCUSSION: This study will provide evidence on the effectiveness, intervention costs and underlying processes of change of tailored implementation of evidence-based fall prevention recommendations. TRIAL REGISTRATION: The trial is registered in the Open Science Registry: https://doi.org/10.17605/OSF.IO/JQ9T5 . Registered: March 03, 2023.

Real-World Balance Assessment While Standing for Fall Prediction in Older Adults.

OBJECTIVE: Postural control naturally declines with age, leading to an increased risk of falling. Within clinical settings, the deployment of balance assessments has become commonplace, facilitating the identification of postural instability and targeted interventions to forestall falls among older adults. Some studies have ventured beyond the controlled laboratory, leaving, however, a gap in our understanding of balance in real-world scenarios. METHODS: Previously reported algorithms were used to build a finite-state machine (FSM) with four states: walking, turning, sitting, and standing. The FSM was validated against video annotations (gold standard) in an independent dataset with data collected on 20 older adults. Later, the FSM was applied to data from 168 community-dwelling older people in the InCHIANTI cohort who were evaluated both in the laboratory and then remotely in real-world conditions for a week. A 70/30 data split with recursive feature selection and resampling techniques was used to train and test four machine-learning models. RESULTS: In identifying fallers, duration, distance, and mean frequency computed during standing in real-world settings revealed significant relationships with fall risk. Also, the best-performing model (Lasso Regression) built on real-world balance features had a higher area under the curve (AUC, 0.76) than one built on lab-based assessments (0.57). CONCLUSION: Real-world balance features differ considerably from laboratory balance assessments (Romberg test) and have a higher predictive capacity for identifying patients at high risk of falling. SIGNIFICANCE: These findings highlight the need to move beyond traditional laboratory-based balance measures and develop more sensitive and accurate methods for predicting falls.

Longitudinal trajectories of functional recovery after hip fracture.

BACKGROUND: There is limited evidence regarding predictors of functional trajectories after hip fracture. We aimed to identify groups with different trajectories of functional recovery the first year after hip fracture, and to determine predictors for belonging to such groups. METHODS: This longitudinal study combined data from two large randomized controlled trials including patients with hip fracture. Participants were assessed at baseline, four and 12 months. We used the Nottingham Extended Activities of Daily Living (NEADL) as a measure of instrumental ADL (iADL) and Barthel Index for personal ADL (pADL). A growth mixture model was estimated to identify groups of patients following distinct trajectories of functioning. Baseline characteristics potentially predicting group-belonging were assessed by multiple nominal regression. RESULTS: Among 726 participants (mean age 83.0; 74.7% women), we identified four groups of patients following distinct ADL trajectories. None of the groups regained their pre-fracture ADL. For one of the groups identified in both ADL outcomes, a steep decline in function was shown the first four months after surgery, and none of the groups showed functional recovery between four and 12 months after surgery. CONCLUSIONS: No groups regained their pre-fracture ADL. Some of the patients with relatively high pre-fracture function, had a steep ADL decline. For this group there is a potential for recovery, but more knowledge and research is needed in this group. These findings could be useful in uncovering groups of patients with different functioning after a hip fracture, and aid in discharge planning.

Using Smartphone TechnolOGy to Support an EffecTive Home ExeRcise Intervention to Prevent Falls amongst Community-Dwelling Older Adults: The TOGETHER Feasibility RCT.

INTRODUCTION: Falls have major implications for quality of life, independence, and cost of health services. Strength and balance training has been found to be effective in reducing the rate/risk of falls, as long as there is adequate fidelity to the evidence-based programme. The aims of this study were to (1) assess the feasibility of using the "Motivate Me" and "My Activity Programme" interventions to support falls rehabilitation when delivered in practice and (2) assess study design and trial procedures for the evaluation of the intervention. METHODS: A two-arm pragmatic feasibility randomized controlled trial was conducted with five health service providers in the UK. Patients aged 50+ years eligible for a falls rehabilitation exercise programme from community services were recruited and received either (1) standard service with a smartphone for outcome measurement only or (2) standard service plus the "Motivate Me" and "My Activity Programme" apps. The primary outcome was feasibility of the intervention, study design, and procedures (including recruitment rate, adherence, and dropout). Outcome measures include balance, function, falls, strength, fear of falling, health-related quality of life, resource use, and adherence, measured at baseline, three-month, and six-month post-randomization. Blinded assessors collected the outcome measures. RESULTS: Twenty four patients were randomized to control group and 26 to intervention group, with a mean age of 77.6 (range 62-92) years. We recruited 37.5% of eligible participants across the five clinical sites. 77% in the intervention group completed their full exercise programme (including the use of the app). Response rates for outcome measures at 6 months were 77-80% across outcome measures, but this was affected by the COVID-19 pandemic. There was a mean 2.6 ± 1.9 point difference between groups in change in Berg balance score from baseline to 3 months and mean 4.4 ± 2.7 point difference from baseline to 6 months in favour of the intervention group. Less falls (1.8 ± 2.8 vs. 9.1 ± 32.6) and less injurious falls (0.1 ± 0.5 vs. 0.4 ± 0.6) in the intervention group and higher adherence scores at three (17.7 ± 6.8 vs. 13.1 ± 6.5) and 6 months (15.2 ± 7.8 vs. 14.9 ± 6.1). There were no related adverse events. Health professionals and patients had few technical issues with the apps. CONCLUSIONS: The motivational apps and trial procedures were feasible for health professionals and patients. There are positive indications from outcome measures in the feasibility trial, and key criteria for progression to full trial were met.

Impacts of COVID-19 restrictions on level of physical activity and health in home-dwelling older adults in Norway.

BACKGROUND: The spread of the coronavirus in spring 2020 led to a lockdown of physical activity (PA) offers. The aim of this study was to investigate how PA, as well as general and mental health, in community-dwelling older adults were affected by the COVID-19 restrictions in Norway. METHODS: Invitation to participate in the study was sent via Facebook and the Norwegian Pensioners' Association. Inclusion criteria were being ≥ 65 years old and living at home. Participants completed a questionnaire either digitally or on paper in June-August 2020. The questionnaire included questions on PA, general health, and mental health both before (13th of March) and during lockdown. RESULTS: We included 565 participants (mean age 74 ± 5.3 years, 60.4% female); almost 60% had a university degree, 84% reported performing PA more than once per week, and 20% reported a fall in the previous 12 months. The Wilcoxon signed-rank test indicated that the corona lockdown significantly reduced activity level (Z = -4.918, p < 0.001), general health (Z = -6,910, p < 0.001) and mental health (Z = -12.114, p < 0.001). Those who were less active during lockdown had higher odds of experiencing worse health than those who maintained their activity level, odds ratio: 9.36 (95% CI = 4.71-18.58, p < 0.001) for general health and 2.41 (95% CI = 1.52-3.83, p < 0.001) for mental health. Those who attended organized exercise offers before lockdown had higher odds of being less active during lockdown compared to those who did not exercise in an organized setting, odds ratio: 3.21 (95% CI = 2.17-5.76, p < 0.001). CONCLUSIONS: In a relatively highly educated and active group of older participants, COVID-19 restrictions still negatively affected level of activity as well as general and mental health. These short-term decreases in activity level and health suggest that preventive actions and increased focus on measures to support older adults in maintaining an active lifestyle are needed.

Impact of adherence to a lifestyle-integrated programme on physical function and behavioural complexity in young older adults at risk of functional decline: a multicentre RCT secondary analysis.

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. CONCLUSION: PA adherence was associated with better lower extremity function and physical behavioural complexity. Barriers to adherence should be addressed preintervention to enhance intervention efficacy. Further research is needed to unravel the impact of behaviour change techniques embedded into technology-delivered activity interventions on adherence. TRIAL REGISTRATION NUMBER: NCT03065088.

Connecting real-world digital mobility assessment to clinical outcomes for regulatory and clinical endorsement-the Mobilise-D study protocol.

BACKGROUND: The development of optimal strategies to treat impaired mobility related to ageing and chronic disease requires better ways to detect and measure it. Digital health technology, including body worn sensors, has the potential to directly and accurately capture real-world mobility. Mobilise-D consists of 34 partners from 13 countries who are working together to jointly develop and implement a digital mobility assessment solution to demonstrate that real-world digital mobility outcomes have the potential to provide a better, safer, and quicker way to assess, monitor, and predict the efficacy of new interventions on impaired mobility. The overarching objective of the study is to establish the clinical validity of digital outcomes in patient populations impacted by mobility challenges, and to support engagement with regulatory and health technology agencies towards acceptance of digital mobility assessment in regulatory and health technology assessment decisions. METHODS/DESIGN: The Mobilise-D clinical validation study is a longitudinal observational cohort study that will recruit 2400 participants from four clinical cohorts. The populations of the Innovative Medicine Initiative-Joint Undertaking represent neurodegenerative conditions (Parkinson's Disease), respiratory disease (Chronic Obstructive Pulmonary Disease), neuro-inflammatory disorder (Multiple Sclerosis), fall-related injuries, osteoporosis, sarcopenia, and frailty (Proximal Femoral Fracture). In total, 17 clinical sites in ten countries will recruit participants who will be evaluated every six months over a period of two years. A wide range of core and cohort specific outcome measures will be collected, spanning patient-reported, observer-reported, and clinician-reported outcomes as well as performance-based outcomes (physical measures and cognitive/mental measures). Daily-living mobility and physical capacity will be assessed directly using a wearable device. These four clinical cohorts were chosen to obtain generalizable clinical findings, including diverse clinical, cultural, geographical, and age representation. The disease cohorts include a broad and heterogeneous range of subject characteristics with varying chronic care needs, and represent different trajectories of mobility disability. DISCUSSION: The results of Mobilise-D will provide longitudinal data on the use of digital mobility outcomes to identify, stratify, and monitor disability. This will support the development of widespread, cost-effective access to optimal clinical mobility management through personalised healthcare. Further, Mobilise-D will provide evidence-based, direct measures which can be endorsed by regulatory agencies and health technology assessment bodies to quantify the impact of disease-modifying interventions on mobility. TRIAL REGISTRATION: ISRCTN12051706.

Alpha-2-adrenergic receptor agonists for the prevention of delirium and cognitive decline after open heart surgery (ALPHA2PREVENT): protocol for a multicentre randomised controlled trial.

INTRODUCTION: Postoperative delirium is common in older cardiac surgery patients and associated with negative short-term and long-term outcomes. The alpha-2-adrenergic receptor agonist dexmedetomidine shows promise as prophylaxis and treatment for delirium in intensive care units (ICU) and postoperative settings. Clonidine has similar pharmacological properties and can be administered both parenterally and orally. We aim to study whether repurposing of clonidine can represent a novel treatment option for delirium, and the possible effects of dexmedetomidine and clonidine on long-term cognitive trajectories, motor activity patterns and biomarkers of neuronal injury, and whether these effects are associated with frailty status. METHODS AND ANALYSIS: This five-centre, double-blind randomised controlled trial will include 900 cardiac surgery patients aged 70+ years. Participants will be randomised 1:1:1 to dexmedetomidine or clonidine or placebo. The study drug will be given as a continuous intravenous infusion from the start of cardiopulmonary bypass, at a rate of 0.4 µg/kg/hour. The infusion rate will be decreased to 0.2 µg/kg/hour postoperatively and be continued until discharge from the ICU or 24 hours postoperatively, whichever happens first.Primary end point is the 7-day cumulative incidence of postoperative delirium (Diagnostic and Statistical Manual of Mental Disorders, fifth edition). Secondary end points include the composite end point of coma, delirium or death, in addition to delirium severity and motor activity patterns, levels of circulating biomarkers of neuronal injury, cognitive function and frailty status 1 and 6 months after surgery. ETHICS AND DISSEMINATION: This trial is approved by the Regional Committee for Ethics in Medical Research in Norway (South-East Norway) and by the Norwegian Medicines Agency. Dissemination plans include publication in peer-reviewed medical journals and presentation at scientific meetings. TRIAL REGISTRATION NUMBER: NCT05029050.

Effect of 5 years of exercise training on the cardiovascular risk profile of older adults: the Generation 100 randomized trial.

AIMS: The aim of this study was to compare the effects of 5 years of supervised exercise training (ExComb), and the differential effects of subgroups of high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT), with control on the cardiovascular risk profile in older adults. METHODS AND RESULTS: Older adults aged 70-77 years from Trondheim, Norway (n = 1567, 50% women), able to safely perform exercise training were randomized to 5 years of two weekly sessions of HIIT [∼90% of peak heart rate (HR), n = 400] or MICT (∼70% of peak HR, n = 387), together forming ExComb (n = 787), or control (instructed to follow physical activity recommendations, n = 780). The main outcome was a continuous cardiovascular risk score (CCR), individual cardiovascular risk factors, and peak oxygen uptake (VO2peak). CCR was not significantly lower [-0.19, 99% confidence interval (CI) -0.46 to 0.07] and VO2peak was not significantly higher (0.39 mL/kg/min, 99% CI -0.22 to 1.00) for ExComb vs. control. HIIT showed higher VO2peak (0.76 mL/kg/min, 99% CI 0.02-1.51), but not lower CCR (-0.32, 99% CI -0.64 to 0.01) vs. control. MICT did not show significant differences compared to control or HIIT. Individual risk factors mostly did not show significant between-group differences, with some exceptions for HIIT being better than control. There was no significant effect modification by sex. The number of cardiovascular events was similar across groups. The healthy and fit study sample, and contamination and cross-over between intervention groups, challenged the possibility of detecting between-group differences. CONCLUSIONS: Five years of supervised exercise training in older adults had little effect on cardiovascular risk profile and did not reduce cardiovascular events. REGISTRATION: ClinicalTrials.gov: NCT01666340.

Technical validation of real-world monitoring of gait: a multicentric observational study.

INTRODUCTION: Existing mobility endpoints based on functional performance, physical assessments and patient self-reporting are often affected by lack of sensitivity, limiting their utility in clinical practice. Wearable devices including inertial measurement units (IMUs) can overcome these limitations by quantifying digital mobility outcomes (DMOs) both during supervised structured assessments and in real-world conditions. The validity of IMU-based methods in the real-world, however, is still limited in patient populations. Rigorous validation procedures should cover the device metrological verification, the validation of the algorithms for the DMOs computation specifically for the population of interest and in daily life situations, and the users' perspective on the device. METHODS AND ANALYSIS: This protocol was designed to establish the technical validity and patient acceptability of the approach used to quantify digital mobility in the real world by Mobilise-D, a consortium funded by the European Union (EU) as part of the Innovative Medicine Initiative, aiming at fostering regulatory approval and clinical adoption of DMOs.After defining the procedures for the metrological verification of an IMU-based device, the experimental procedures for the validation of algorithms used to calculate the DMOs are presented. These include laboratory and real-world assessment in 120 participants from five groups: healthy older adults; chronic obstructive pulmonary disease, Parkinson's disease, multiple sclerosis, proximal femoral fracture and congestive heart failure. DMOs extracted from the monitoring device will be compared with those from different reference systems, chosen according to the contexts of observation. Questionnaires and interviews will evaluate the users' perspective on the deployed technology and relevance of the mobility assessment. ETHICS AND DISSEMINATION: The study has been granted ethics approval by the centre's committees (London-Bloomsbury Research Ethics committee; Helsinki Committee, Tel Aviv Sourasky Medical Centre; Medical Faculties of The University of Tübingen and of the University of Kiel). Data and algorithms will be made publicly available. TRIAL REGISTRATION NUMBER: ISRCTN (12246987).

Gait, physical function, and physical activity in three groups of home-dwelling older adults with different severity of cognitive impairment - a cross-sectional study.

BACKGROUND: The research on associations between gait, physical function, physical activity (PA), and cognitive function is growing. Still, clinical assessments of cognitive function and motor function is often kept separate. In this study, we aimed to look at a broad range of measures of gait, physical function, and PA in three groups of home-dwelling older adults with no or questionable dementia, mild dementia, and moderate/severe dementia. METHODS: This cross-sectional study included 100 home-dwelling older adults, recruited from an outpatient geriatric memory clinic. Severity of dementia was categorised using the clinical dementia rating scale (CDR), with no or questionable dementia (CDR score 0 and 0.5), mild dementia (CDR score 1) and moderate/severe dementia (CDR score 2 and 3). We used thigh worn accelerometers to measure daily PA, the Short Physical Performance Battery (SPPB) to measure physical function, and an electronic gait mat to evaluate gait characteristics. Associations between severity of dementia and measures of PA, physical function, and gait characteristics were assessed by linear regression. RESULTS: Participants' (mean age 78.9 (SD 6.7) years, 57% women) average gait speed was 0.93 m/sec, and average upright time was 301 min/day. Statistically significant associations were found for the severity of dementia and gait speed (p=0.002), step time (p=0.001), physical function (SPPB, p=0.007), and PA (upright time, p=0.031), after adjusting for age. Overall, having no or questionable dementia was associated with faster gait speed (mean difference 0.163 (95% CI: 0.053 to 0.273)), shorter step time (-0.043 (-0.082 to -0.005)), better SPPB score (1.7 (0.5 to 2.8)), and longer upright time (78.9 (18.9 to 139.0)), compared to those with mild dementia. Furthermore, having no or questionable dementia was also associated with faster gait speed and better SPPB scores, as compared to those with moderate to severe dementia. No evidence of any differences was found between the participants with the mild dementia versus the moderate to severe dementia. CONCLUSIONS: After adjusting for age, we found that the no or questionable dementia group to be associated with better gait and physical function, and more PA, as compared with the two groups with mild or moderate/severe dementia. Evaluation of gait, physical function, and PA can add clinically important information of everyday functioning in memory clinics meeting geriatric patients, but investigations on how to use these results to guide interventions are still needed.

Consensus based framework for digital mobility monitoring.

Digital mobility assessment using wearable sensor systems has the potential to capture walking performance in a patient's natural environment. It enables monitoring of health status and disease progression and evaluation of interventions in real-world situations. In contrast to laboratory settings, real-world walking occurs in non-conventional environments and under unconstrained and uncontrolled conditions. Despite the general understanding, there is a lack of agreed definitions about what constitutes real-world walking, impeding the comparison and interpretation of the acquired data across systems and studies. The goal of this study was to obtain expert-based consensus on specific aspects of real-world walking and to provide respective definitions in a common terminological framework. An adapted Delphi method was used to obtain agreed definitions related to real-world walking. In an online survey, 162 participants from a panel of academic, clinical and industrial experts with experience in the field of gait analysis were asked for agreement on previously specified definitions. Descriptive statistics was used to evaluate whether consent (> 75% agreement as defined a priori) was reached. Of 162 experts invited to participate, 51 completed all rounds (31.5% response rate). We obtained consensus on all definitions ("Walking" > 90%, "Purposeful" > 75%, "Real-world" > 90%, "Walking bout" > 80%, "Walking speed" > 75%, "Turning" > 90% agreement) after two rounds. The identification of a consented set of real-world walking definitions has important implications for the development of assessment and analysis protocols, as well as for the reporting and comparison of digital mobility outcomes across studies and systems. The definitions will serve as a common framework for implementing digital and mobile technologies for gait assessment and are an important link for the transition from supervised to unsupervised gait assessment.

Classical Machine Learning Versus Deep Learning for the Older Adults Free-Living Activity Classification.

Physical activity has a strong influence on mental and physical health and is essential in healthy ageing and wellbeing for the ever-growing elderly population. Wearable sensors can provide a reliable and economical measure of activities of daily living (ADLs) by capturing movements through, e.g., accelerometers and gyroscopes. This study explores the potential of using classical machine learning and deep learning approaches to classify the most common ADLs: walking, sitting, standing, and lying. We validate the results on the ADAPT dataset, the most detailed dataset to date of inertial sensor data, synchronised with high frame-rate video labelled data recorded in a free-living environment from older adults living independently. The findings suggest that both approaches can accurately classify ADLs, showing high potential in profiling ADL patterns of the elderly population in free-living conditions. In particular, both long short-term memory (LSTM) networks and Support Vector Machines combined with ReliefF feature selection performed equally well, achieving around 97% F-score in profiling ADLs.

Interventions for reducing sedentary behaviour in community-dwelling older adults.

BACKGROUND: Older adults are the most sedentary segment of society, often spending in excess of 8.5 hours a day sitting. Large amounts of time spent sedentary, defined as time spend sitting or in a reclining posture without spending energy, has been linked to an increased risk of chronic diseases, frailty, loss of function, disablement, social isolation, and premature death. OBJECTIVES: To evaluate the effectiveness of interventions aimed at reducing sedentary behaviour amongst older adults living independently in the community compared to control conditions involving either no intervention or interventions that do not target sedentary behaviour. SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, CINAHL, PsycINFO, PEDro, EPPI-Centre databases (Trials Register of Promoting Health Interventions (TRoPHI) and the Obesity and Sedentary behaviour Database), WHO ICTRP, and ClinicalTrials.gov up to 18 January 2021. We also screened the reference lists of included articles and contacted authors to identify additional studies. SELECTION CRITERIA: We included randomised controlled trials (RCTs) and cluster-RCTs. We included interventions purposefully designed to reduce sedentary time in older adults (aged 60 or over) living independently in the community. We included studies if some of the participants had multiple comorbidities, but excluded interventions that recruited clinical populations specifically (e.g. stroke survivors). DATA COLLECTION AND ANALYSIS: Two review authors independently screened titles and abstracts and full-text articles to determine study eligibility. Two review authors independently extracted data and assessed risk of bias. We contacted authors for additional data where required. Any disagreements in study screening or data extraction were settled by a third review author. MAIN RESULTS: We included seven studies in the review, six RCTs and one cluster-RCT, with a total of 397 participants. The majority of participants were female (n = 284), white, and highly educated. All trials were conducted in high-income countries. All studies evaluated individually based behaviour change interventions using a combination of behaviour change techniques such as goal setting, education, and behaviour monitoring or feedback. Four of the seven studies also measured secondary outcomes. The main sources of bias were related to selection bias (N = 2), performance bias (N = 6), blinding of outcome assessment (N = 2), and incomplete outcome data (N = 2) and selective reporting (N=1). The overall risk of bias was judged as unclear. Primary outcomes The evidence suggests that interventions to change sedentary behaviour in community-dwelling older adults may reduce sedentary time (mean difference (MD) -44.91 min/day, 95% confidence interval (CI) -93.13 to 3.32; 397 participants; 7 studies; I2 = 73%; low-certainty evidence). We could not pool evidence on the effect of interventions on breaks in sedentary behaviour or time spent in specific domains such as TV time, as data from only one study were available for these outcomes. Secondary outcomes We are uncertain whether interventions to reduce sedentary behaviour have any impact on the physical or mental health outcomes of community-dwelling older adults. We were able to pool change data for the following outcomes. • Physical function (MD 0.14 Short Physical Performance Battery (SPPB) score, 95% CI -0.38 to 0.66; higher score is favourable; 98 participants; 2 studies; I2 = 26%; low-certainty evidence). • Waist circumference (MD 1.14 cm, 95% CI -1.64 to 3.93; 100 participants; 2 studies; I2 = 0%; low-certainty evidence). • Fitness (MD -5.16 m in the 6-minute walk test, 95% CI -36.49 to 26.17; higher score is favourable; 80 participants; 2 studies; I2 = 29%; low-certainty evidence). • Blood pressure: systolic (MD -3.91 mmHg, 95% CI -10.95 to 3.13; 138 participants; 3 studies; I2 = 73%; very low-certainty evidence) and diastolic (MD -0.06 mmHg, 95% CI -5.72 to 5.60; 138 participants; 3 studies; I2 = 97%; very low-certainty evidence). • Glucose blood levels (MD 2.20 mg/dL, 95% CI -6.46 to 10.86; 100 participants; 2 studies; I2 = 0%; low-certainty evidence). No data were available on cognitive function, cost-effectiveness or adverse effects. AUTHORS' CONCLUSIONS: It is not clear whether interventions to reduce sedentary behaviour are effective at reducing sedentary time in community-dwelling older adults. We are uncertain if these interventions have any impact on the physical or mental health of community-dwelling older adults. There were few studies, and the certainty of the evidence is very low to low, mainly due to inconsistency in findings and imprecision. Future studies should consider interventions aimed at modifying the environment, policy, and social and cultural norms. Future studies should also use device-based measures of sedentary time, recruit larger samples, and gather information about quality of life, cost-effectiveness, and adverse event data.

Sensitivity to Change and Responsiveness of the Original and the Shortened Version of the Community Balance and Mobility Scale for Young Seniors.

OBJECTIVE: To examine sensitivity to change and responsiveness of the Community Balance and Mobility Scale (CBM) and shortened CBM (s-CBM). DESIGN: Secondary analysis using data of a randomized controlled trial. SETTING: General community. PARTICIPANTS: Young community-dwelling seniors aged 61-70 years (N=134; mean age, 66.2±2.5y). INTERVENTIONS: Participants underwent 12 months of exercise intervention. MAIN OUTCOME MEASURES: CBM and s-CBM. Sensitivity to change was assessed using standardized response mean (SRM) and paired t tests as appropriate. Responsiveness was assessed using 2 minimal important difference (MID) estimates. Analyses were conducted for the full sample and for the subgroups "high-balance" and "low-balance," divided by median split. RESULTS: Inferential statistics revealed a significant CBM (P<.001) and s-CBM (P<.001) improvement within the full sample and the subgroups (high-balance: P=.001, P=.019; low-balance: P<.001, P<.001). CBM and s-CBM were moderately sensitive to change (SRM, 0.48 vs 0.38) within the full sample. In the high-balance subgroup, moderate SRM values (0.70) were found for the CBM and small values for the s-CBM (0.29). In the low-balance subgroup, moderate SRM values were found for the CBM (0.67) and high values for the s-CBM (0.80). For the full sample, CBM and s-CBM exceeded the lower but not the higher MID value. In the high-balance subgroup, the CBM exceeded both MID values, but the s-CBM exceeded only the lower. In the low-balance subgroup, CBM and s-CBM exceeded both MID values. CONCLUSIONS: The CBM is a suitable tool to detect intervention-related changes of balance and mobility in young, high-performing seniors. Both versions of the CBM scale show good sensitivity to change and responsiveness, particularly in young seniors with low balance.

Template-Based Recognition of Human Locomotion in IMU Sensor Data Using Dynamic Time Warping.

Increased levels of light, moderate and vigorous physical activity (PA) are positively associated with health benefits. Therefore, sensor-based human activity recognition can identify different types and levels of PA. In this paper, we propose a two-layer locomotion recognition method using dynamic time warping applied to inertial sensor data. Based on a video-validated dataset (ADAPT), which included inertial sensor data recorded at the lower back (L5 position) during an unsupervised task-based free-living protocol, the recognition algorithm was developed, validated and tested. As a first step, we focused on the identification of locomotion activities walking, ascending and descending stairs. These activities are difficult to differentiate due to a high similarity. The results showed that walking could be recognized with a sensitivity of 88% and a specificity of 89%. Specificity for stair climbing was higher compared to walking, but sensitivity was noticeably decreased. In most cases of misclassification, stair climbing was falsely detected as walking, with only 0.2-5% not assigned to any of the chosen types of locomotion. Our results demonstrate a promising approach to recognize and differentiate human locomotion within a variety of daily activities.

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.

Effect of exercise training for five years on all cause mortality in older adults-the Generation 100 study: randomised controlled trial.

OBJECTIVE: To evaluate the effect of five years of supervised exercise training compared with recommendations for physical activity on mortality in older adults (70-77 years). DESIGN: Randomised controlled trial. SETTING: General population of older adults in Trondheim, Norway. PARTICIPANTS: 1567 of 6966 individuals born between 1936 and 1942. INTERVENTION: Participants were randomised to two sessions weekly of high intensity interval training at about 90% of peak heart rate (HIIT, n=400), moderate intensity continuous training at about 70% of peak heart rate (MICT, n=387), or to follow the national guidelines for physical activity (n=780; control group); all for five years. MAIN OUTCOME MEASURE: All cause mortality. An exploratory hypothesis was that HIIT lowers mortality more than MICT. RESULTS: Mean age of the 1567 participants (790 women) was 72.8 (SD 2.1) years. Overall, 87.5% of participants reported to have overall good health, with 80% reporting medium or high physical activity levels at baseline. All cause mortality did not differ between the control group and combined MICT and HIIT group. When MICT and HIIT were analysed separately, with the control group as reference (observed mortality of 4.7%), an absolute risk reduction of 1.7 percentage points was observed after HIIT (hazard ratio 0.63, 95% confidence interval 0.33 to 1.20) and an absolute increased risk of 1.2 percentage points after MICT (1.24, 0.73 to 2.10). When HIIT was compared with MICT as reference group an absolute risk reduction of 2.9 percentage points was observed (0.51, 0.25 to 1.02) for all cause mortality. Control participants chose to perform more of their physical activity as HIIT than the physical activity undertaken by participants in the MICT group. This meant that the controls achieved an exercise dose at an intensity between the MICT and HIIT groups. CONCLUSION: This study suggests that combined MICT and HIIT has no effect on all cause mortality compared with recommended physical activity levels. However, we observed a lower all cause mortality trend after HIIT compared with controls and MICT. TRIAL REGISTRATION: ClinicalTrials.gov NCT01666340.

Spatiotemporal gait parameters for older adults - An interactive model adjusting reference data for gender, age, and body height.

INTRODUCTION: Since it is well documented that spatiotemporal gait parameters are affected by body size, it is of limited clinical value to compare individual scores against reference values without taking body size into consideration. For older adults, reference values have been presented in recent reports, but unfortunately the effect of body size on gait characteristics was not taken into account and neither prediction intervals nor percentile ranks were included. It is the aim of this study to present and assess a model where individual spatiotemporal gait parameter values for older adults can be compared to reference values adjusted for gender, age, and body height. METHODS: Reference gait data were collected from l464 older adults aged 69-80 years with no impairments believed to affect gait, stratified by gender, intermediately adjusted to a common body height using a pendulum model and entered into a simple regression model for each parameter with age as predictor. From the regression coefficients predicted gait parameter values could be back transformed to the individual body height of a new subject. Calculations were done using spreadsheet formulae and equations. RESULTS: A spreadsheet based graphical user interface (GUI) has been developed in Microsoft Excel® where individual spatiotemporal gait data is entered for comparison with reference data taking gender, age and body height into account, and returning predicted point estimates with confidence intervals, prediction intervals, and percentile ranks. SIGNIFICANCE: A GUI solution where individual spatiotemporal gait data is compared to reference data is feasible to researchers and for clinical use. To the best of our knowledge, this is the first model presented for comparison of basic gait parameters between individuals and reference data from older adults where gender, age, and body height are taken into account.

Predicting Advanced Balance Ability and Mobility with an Instrumented Timed Up and Go Test.

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.