Fall risk stratification of community-living older people. Commentary on the world guidelines for fall prevention and management.

The Task Force on Global Guidelines for Falls in Older Adults has put forward a fall risk stratification tool for community-dwelling older adults. This tool takes the form of a flowchart and is based on expert opinion and evidence. It divides the population into three risk categories and recommends specific preventive interventions or treatments for each category. In this commentary, we share our insights on the design, validation, usability and potential impact of this fall risk stratification tool with the aim of guiding future research.

Circumstances of Falls During Sit-to-Stand Transfers in Older People: A Cohort Study of Video-Captured Falls in Long-Term Care.

OBJECTIVE: To characterize the circumstances of falls during sit-to-stand transfers in long-term care (LTC), including the frequency, direction, stepping and grasping responses, and injury risk, based on video analysis of real-life falls. DESIGN: Cohort study. SETTING: LTC. PARTICIPANTS: We analyzed video footage of 306 real-life falls by 183 LTC residents that occurred during sit-to-stand transfers, collected from 2007 to 2020. The mean age was 83.7 years (SD=9.0 years), and 93 were female (50.8%). INTERVENTION: Not applicable. MAIN OUTCOME MEASURES: We used Generalized Estimating Equations to test for differences in the odds that a resident would fall at least once during the rising vs stabilization phases of sit-to-stand and to test the association between the phase of the transfer when the fall occurred (rising vs stabilization) and the following outcomes: (1) the initial fall direction; (2) the occurrence, number, and direction of stepping responses; (3) grasping of environmental supports; and (4) documented injury. RESULTS: Falls occurred twice as often in the rising phase than in the stabilization phase of the transfer (64.0% and 36.0%, respectively). Falls during rising were more often directed backward, while falls during stabilization were more likely to be sideways (odds ratio [OR]=1.95; 95% confidence interval [CI]=1.07-3.55). Falls during rising were more often accompanied by grasping responses, while falls during stabilization were more likely to elicit stepping responses (grasping: OR=0.30; 95% CI=0.14-0.64; stepping: OR=8.29; 95% CI=4.54-15.11). Injuries were more likely for falls during the stabilization phase than the rising phase of the transfer (OR=1.73; 95% CI=1.04-2.87). CONCLUSION: Most falls during sit-to-stand transfers occurred from imbalance during the rising phase of the transfer. However, falls during the subsequent stabilization phase were more likely to cause injury.

A Self-Guided Online Cognitive Behavioural Therapy to Reduce Fear of Falling in Older People: a Randomised Controlled Trial.

BACKGROUND: Traditional face-to-face cognitive behavioural therapy (CBT) has been successful at reducing fear of falling (FOF) in older people but can be labour-intensive and costly. Online CBT has been suggested as a cost-effective alternative but has not yet been tested in the context of FOF. This study evaluates the effectiveness of a readily available, self-guided and generalised online CBT program (myCompass) on reducing FOF in older people. METHODS: Fifty community-dwelling older people with FOF received a paper-based health education program, and half were randomly assigned to receive three selected modules from myCompass for 6 weeks. The primary outcome was feared consequences of falling at 6 weeks. Secondary outcomes were concern about falling, balance confidence, activity avoidance, physical activity, exercise self-efficacy, health literacy and mental health at 6/26/52 weeks and falls incidence at 12 months. RESULTS: All intervention participants completed at least 2-out-of-3 myCompass modules. There was a significant main effect of time on feared consequences of falling (Cohen's f = 0.55). The group by time interactions for concern about falling (f = 0.28), stress (f = 0.26) and social support for health (health literacy) (f = 0.26) was also significant, favouring the control group. The overall attrition rate at 12 months was 24% (n = 12). CONCLUSION: The high program compliance and low attrition rate suggest that online CBT is feasible among older people. However, the myCompass program had no effect at reducing FOF in older people. A more targeted CBT program with a well-integrated psychoeducation module on FOF might be the solution to boost the therapeutic effects of a generalised CBT program at reducing FOF for older people.

Theoretical framework of concerns about falling in older people: the role of health literacy.

Adherence and participation can be improved in health programs for older people with concerns about falling. While health literacy empowers older people to have greater control over their health, little is known about the extent to which health literacy influences health behaviours associated with concerns about falling in older people. This study aimed to synthesise current findings on health literacy, concerns about falling and falls to propose a multicomponent theoretical model on health literacy and concerns about falling. The model was developed based on a review of the literature, existing frameworks and models on health literacy and concerns about falling. Existing evidence on the relationship between health literacy and concerns about falling in older people is limited. Evidence from other research areas, however, shows that health literacy is closely related to many of the determinants of concerns about falling. More research is needed to clarify the impact of health literacy on intervention adherence and decision-making processes of older people with concerns about falling. Our model offers a novel perspective on the role of health literacy in health behaviours associated with concerns about falling, suggesting new research directions and providing insights for clinicians to consider health literacy when managing older patients with concerns about falling.

Economic evaluation of the e-Health StandingTall balance exercise programme for fall prevention in people aged 70 years and over.

BACKGROUND: globally, falls and fall-related injuries are the leading cause of injury-related morbidity and mortality in older people. In our ageing society healthcare costs are increasing, therefore programmes that reduce falls and are considered value for money are needed. OBJECTIVE: to complete an economic evaluation of an e-Health balance exercise programme that reduced falls and injurious falls in community-dwelling older people compared to usual care from a health and community-care funder perspective. DESIGN: a within-trial economic evaluation of an assessor-blinded randomised controlled trial with 2 years of follow-up. SETTING: StandingTall was delivered via tablet-computer at home to older community-dwelling people in Sydney, Australia. PARTICIPANTS: five hundred and three individuals aged 70+ years who were independent in activities of daily living, without cognitive impairment, progressive neurological disease or any other unstable or acute medical condition precluding exercise. MAIN OUTCOME MEASURES: cost-effectiveness was measured as the incremental cost per fall and per injurious fall prevented. Cost-utility was measured as the incremental cost per quality-adjusted life year (QALY) gained. MAIN RESULTS: the total average cost per patient for programme delivery and care resource cost was $8,321 (standard deviation [SD] 18,958) for intervention participants and $6,829 (SD 15,019) for control participants. The incremental cost per fall prevented was $4,785 and per injurious fall prevented was $6,585. The incremental cost per QALY gained was $58,039 (EQ5D-5L) and $110,698 (AQoL-6D). CONCLUSION: this evaluation found that StandingTall has the potential to be cost-effective in specific subpopulations of older people, but not necessarily the whole older population. TRIAL REGISTRATION: ACTRN12615000138583.

Responsiveness of Daily Life Gait Quality Characteristics over One Year in Older Adults Who Experienced a Fall or Engaged in Balance Exercise.

Gait quality characteristics obtained from daily-life accelerometry are clinically relevant for fall risk in older adults but it is unknown whether these characteristics are responsive to changes in gait quality. We aimed to test whether accelerometry-based daily-life gait quality characteristics are reliable and responsive to changes over one year in older adults who experienced a fall or an exercise intervention. One-week trunk acceleration data were collected from 522 participants (65-97 years), at baseline and after one year. We calculated median values of walking speed, regularity (sample entropy), stability (logarithmic rate of divergence per stride), and a gait quality composite score, across all 10-s gait epochs derived from one-week gait episodes. Intraclass correlation coefficients (ICC) and limits of agreement (LOA) were determined for 198 participants who did not fall nor participated in an exercise intervention during follow-up. For responsiveness to change, we determined the number of participants who fell (n = 209) or participated in an exercise intervention (n = 115) that showed a change beyond the LOA. ICCs for agreement between baseline and follow-up exceeded 0.70 for all gait quality characteristics except for vertical gait stability (ICC = 0.69, 95% CI [0.62, 0.75]) and walking speed (ICC = 0.68, 95% CI [0.62, 0.74]). Only walking speed, vertical and mediolateral gait stability changed significantly in the exercisers over one year but effect sizes were below 0.2. The characteristic associated with most fallers beyond the LOA was mediolateral sample entropy (4.8% of fallers). For the exercisers, this was gait stability in three directions and the gait quality composite score (2.6% of exercisers). The gait quality characteristics obtained by median values over one week of trunk accelerometry were not responsive to presumed changes in gait quality after a fall or an exercise intervention in older people. This is likely due to large (within subjects) differences in gait behaviour that participants show in daily life.

The Relationship Between Concerns About Falling and Daily Life Activity in Older Men and Women.

Concerns about falling (CAF) affect daily life activities in older people; however, it is unclear whether gender moderates this relationship. The authors investigated the cross-sectional relationship between CAF and objectively measured physical activity (PA) and gait quality in 503 community-dwelling older men and women. About 448 people (age = 76.2 [SD 7.9] years, 296 females) contributed sufficient data on movement intensity, activity duration (bouts of walking, sitting, and standing), number of transitions between activities (sit-to-stand and sit-to-walk), number of steps and gait quality, quantified as walking speed, and sample entropy. Associations with the Iconographical Falls Efficacy Scale were tested. The authors found no significant moderation by gender. However, women participated in less PA than men and showed a more irregular walking pattern. Higher levels of CAF led to lower PA and poorer gait quality. Our findings suggest that prevention of CAF-related PA avoidance may be particularly important for women, who are less active and at higher risk of falls.

The Iconographical Falls Efficacy Scale (IconFES) in community-dwelling older people-a longitudinal validation study.

BACKGROUND: This study aimed to develop cut-points for the 30-item and 10-item Iconographical Falls Efficacy Scale (IconFES) in community-dwelling older people and evaluate the psychometric properties, including construct and predictive validity with respect to falls and reduced physical activity over 1 year. METHODS: Eight hundred and one participants completed the IconFES and underwent physical, psychological and cognitive measures at baseline. Physical activity was recorded at baseline and 12 months using an activity monitor, and 1-year fall incidence was collected using monthly falls calendars. RESULTS: Using receiver-operating characteristic curves and the Youden's index for history of falls, physiological fall risk and depressive symptoms, cut-points were defined to differentiate between low and high concern about falling (30-item: <53; 10-item: <19). For the 30-item IconFES, we additionally defined cut-points for low (≤40), moderate (41-58) and high (≥59) concern about falling. Groups based on these cut-points differed significantly: low coordinated stability, executive function and amount of daily walking, and high level of disability (30-item version) and female gender (low/high 30-item version). Although there were some inconsistencies across IconFES classifications, high concern about falling predicted having had multiple falls or multiple/injurious falls, low amount of daily walking and low movement intensity at 12 months. CONCLUSIONS: The developed IconFES cut-points were sensitive to variables associated with concern about falling and predicted fall incidence and physical activity restriction after 12 months. Applying these cut-points appears useful to identify older people with high concern about falling, who are at higher risk of falls and activity curtailment.

Sensorimotor, Cognitive, and Affective Functions Contribute to the Prediction of Falls in Old Age and Neurologic Disorders: An Observational Study.

OBJECTIVE: To determine whether impairments across cognitive and affective domains provide additional information to sensorimotor deficits for fall prediction among various populations. DESIGN: We pooled data from 5 studies for this observational analysis of prospective falls. SETTING: Community or low-level care facility. PARTICIPANTS: Older people (N=1090; 74.0±9.4y; 579 female); 500 neurologically intact (NI) older people and 3 groups with neurologic disorders (cognitive impairment, n=174; multiple sclerosis (MS), n=111; Parkinson disease, n=305). INTERVENTIONS: None. MAIN OUTCOME MEASURES: Sensorimotor function was assessed with the Physiological Profile Assessment, cognitive function with tests of executive function, affect with questionnaires of depression, and concern about falling with falls efficacy questionnaires. These variables were associated with fall incidence rates, obtained prospectively over 6-12 months. RESULTS: Poorer sensorimotor function was associated with falls (incidence rate ratio [95% CI], 1.46 [1.28-1.66]). Impaired executive function was the strongest predictor of falls overall (2.91 [2.27-3.73]), followed by depressive symptoms (2.07 [1.56-2.75]) and concern about falling (2.02 [1.61-2.55]). Associations were similar among groups, except for a weaker relationship with executive impairment in NI persons and a stronger relationship with concern about falling in persons with MS. Multivariable analyses showed that executive impairment, poorer sensorimotor performance, depressive symptoms, and concern about falling were independently associated with falls. CONCLUSIONS: Deficits in cognition (executive function) and affect (depressive symptoms) and concern about falling are as important as sensorimotor function for fall prediction. These domains should be included in fall risk assessments for older people and clinical groups.

Association between health literacy and physical activity in older people: a systematic review and meta-analysis.

Physical inactivity is common in older people and contributes to morbidity and mortality. Health literacy might play a role in motivating people to become or stay physically active. However, little is known about the influence of health literacy on physical activity in older people. This review aims to determine the association between health literacy and physical activity in older people. A systematic search was conducted in CINAHL, MEDLINE, PsychINFO and CENTRAL. Inclusion criteria: (i) community-dwelling people with an average age of ≥55 and (ii) reported on the association between health literacy and physical activity. Exclusion criteria: (i) population with a health condition and (ii) case study or qualitative study. Data were extracted independently by two reviewers. Risk of bias was assessed using the Downs and Black checklist. A meta-analysis was conducted using random-effects models with inverse variance. Thirteen articles were included in the review and five articles were selected for the meta-analysis. Older people with inadequate health literacy were 38% less likely than older people with adequate health literacy to report engaging in physical activity on ≥5 days per week [odds ratio = 0.62, 95% confidence interval (CI) 0.55-0.77]. Only two articles used activity monitors; the mean number of steps taken per day was not significantly different between older people with adequate and inadequate health literacy (standardized mean difference = -0.15, 95% CI -0.30 to 0.01). Physical activity could potentially be fostered by increasing health literacy and empowering older people to make beneficial health decisions.

Recreational Therapy to Promote Mobility in Long-Term Care: A Scoping Review.

The objective of this study was to explore and synthesize evidence on the effectiveness and implementation of recreational therapy programs to enhance mobility outcomes (e.g., balance, functional performance, fall incidence) for older adults in long-term care. The authors conducted a scoping review of 66 studies following the PRISMA guidelines. Two independent reviewers evaluated each article, and a third reviewer resolved discrepancies. Randomized controlled studies provided strong to moderate evidence that tai chi programs, walking, dancing, and ball games improve flexibility, functional mobility, and balance. Studies assessing program implementation highlighted that program delivery was facilitated by clear instruction, encouragement, attendance documentation, and minimal equipment. This review elucidated the benefit of recreational therapy programs on mobility. It also identified the need for customized programs based on individuals' interests and their physical and mental abilities. These findings and recommendations will assist practitioners in designing effective and feasible recreational therapy programs for long-term care.

Deep Learning for Activity Recognition in Older People Using a Pocket-Worn Smartphone.

Activity recognition can provide useful information about an older individual's activity level and encourage older people to become more active to live longer in good health. This study aimed to develop an activity recognition algorithm for smartphone accelerometry data of older people. Deep learning algorithms, including convolutional neural network (CNN) and long short-term memory (LSTM), were evaluated in this study. Smartphone accelerometry data of free-living activities, performed by 53 older people (83.8 ± 3.8 years; 38 male) under standardized circumstances, were classified into lying, sitting, standing, transition, walking, walking upstairs, and walking downstairs. A 1D CNN, a multichannel CNN, a CNN-LSTM, and a multichannel CNN-LSTM model were tested. The models were compared on accuracy and computational efficiency. Results show that the multichannel CNN-LSTM model achieved the best classification results, with an 81.1% accuracy and an acceptable model and time complexity. Specifically, the accuracy was 67.0% for lying, 70.7% for sitting, 88.4% for standing, 78.2% for transitions, 88.7% for walking, 65.7% for walking downstairs, and 68.7% for walking upstairs. The findings indicated that the multichannel CNN-LSTM model was feasible for smartphone-based activity recognition in older people.

Association between Daily-Life Gait Quality Characteristics and Physiological Fall Risk in Older People.

Gait quality characteristics obtained from accelerometry during daily life are predictive of falls in older people but it is unclear how they relate to fall risk. Our aim was to test whether these gait quality characteristics are associated with the severity of fall risk. We collected one week of trunk accelerometry data from 279 older people (aged 65-95 years; 69.5% female). We used linear regression to investigate the association between six daily-life gait quality characteristics and categorized physiological fall risk (QuickScreen). Logarithmic rate of divergence in the vertical (VT) and anteroposterior (AP) direction were significantly associated with the level of fall risk after correction for walking speed (both p < 0.01). Sample entropy in VT and the mediolateral direction and the gait quality composite were not significantly associated with the level of fall risk. We found significant differences between the high fall risk group and the very low- and low-risk groups, the moderate- and very low-risk and the moderate and low-risk groups for logarithmic rate of divergence in VT and AP (all p ≤ 0.01). We conclude that logarithmic rate of divergence in VT and AP are associated with fall risk, making them feasible to assess the physiological fall risk in older people.

Catch the ruler: concurrent validity and test-retest reliability of the ReacStick measures of reaction time and inhibitory executive function in older people.

BACKGROUND: Reduced cognitive function, particularly executive function (EF), is associated with an increased risk of falling in older people. We evaluated the utility of the ReacStick test, a clinical test of reaction time, and inhibitory EF developed, for young athletes, for fall-risk assessment in older people. AIMS: To evaluate the psychometric properties of ReacStick measures of reaction time and executive functioning in healthy community-dwelling older people. METHODS: 140 participants (aged 77 ± 5 years) underwent testing. Two test conditions-simple and inhibitory go/no-go-provided measures of reaction time, recognition load (difference in reaction time between conditions), and go/no-go accuracy. Concurrent validity was evaluated against the conventional tests of reaction time and EF (simple hand reaction time, trail-making test, and Stroop colour test). Discriminant ability was determined for fall-risk factors (age, gender, physiological profile assessment, and fall history). Test-retest reliability after 1 week was evaluated in 30 participants. RESULTS: ReacStick reaction time correlated with tests of reaction time and EF, recognition load correlated with inhibitory EF, and go accuracy correlated with reaction time and inhibitory EF. No-go accuracy was not significantly correlated with any of the reaction time and EF tests. Test-retest reliability was good-to-excellent (ICC > 0.6) for all the outcomes. ReacStick reaction time discriminated between groups based on age, recognition load between genders, and no-go accuracy between retrospective fallers and non-fallers. DISCUSSION: An unavoidable time pressure may result in complementary information to the traditional measures. CONCLUSIONS: The ReacStick is a reliable test of reaction time and inhibitory EF in older people and could have value for fall-risk assessment.

Quality of Daily-Life Gait: Novel Outcome for Trials that Focus on Balance, Mobility, and Falls.

Technological advances in inertial sensors allow for monitoring of daily-life gait characteristics as a proxy for fall risk. The quality of daily-life gait could serve as a valuable outcome for intervention trials, but the uptake of these measures relies on their power to detect relevant changes in fall risk. We collected daily-life gait characteristics in 163 older people (aged 77.5 ± 7.5, 107♀) over two measurement weeks that were two weeks apart. We present variance estimates of daily-life gait characteristics that are sensitive to fall risk and estimate the number of participants required to obtain sufficient statistical power for repeated comparisons. The provided data allows for power analyses for studies using daily-life gait quality as outcome. Our results show that the number of participants required (i.e., 8 to 343 depending on the anticipated effect size and between-measurements correlation) is similar to that generally used in fall prevention trials. We propose that the quality of daily-life gait is a promising outcome for intervention studies that focus on improving balance and mobility and reducing falls.

The association between age and accelerometry-derived types of habitual daily activity: an observational study over the adult life span in the Netherlands.

BACKGROUND: Advances in sensor technology allow for objective and high-resolution monitoring of physical activity and sedentary behaviour. Novel epidemiological data is required to provide feedback on an individual's habitual daily activity in comparison to peers and might eventually lead to refined physical activity guidelines. METHODS: We merged data of 762 people between 18 and 99 years of age, who all wore a DynaPort MoveMonitor accelerometer on their lower back during 1 week in daily-life, to provide insight into habitual types and durations of daily activities, and examine the association between age and physical activity and sedentary behaviour. RESULTS: We found associations between age and almost all activity outcomes. These associations suggested that physical activity declines and sedentary behaviour increases from the age of 50. We further describe an association with gender, with men walking more often in fewer but longer bouts and having fewer, longer bouts of sitting and standing. CONCLUSIONS: These data provide a valuable reference and may call for more age- and gender-specific activity interventions.

Deep Learning to Predict Falls in Older Adults Based on Daily-Life Trunk Accelerometry.

Early detection of high fall risk is an essential component of fall prevention in older adults. Wearable sensors can provide valuable insight into daily-life activities; biomechanical features extracted from such inertial data have been shown to be of added value for the assessment of fall risk. Body-worn sensors such as accelerometers can provide valuable insight into fall risk. Currently, biomechanical features derived from accelerometer data are used for the assessment of fall risk. Here, we studied whether deep learning methods from machine learning are suited to automatically derive features from raw accelerometer data that assess fall risk. We used an existing dataset of 296 older adults. We compared the performance of three deep learning model architectures (convolutional neural network (CNN), long short-term memory (LSTM) and a combination of these two (ConvLSTM)) to each other and to a baseline model with biomechanical features on the same dataset. The results show that the deep learning models in a single-task learning mode are strong in recognition of identity of the subject, but that these models only slightly outperform the baseline method on fall risk assessment. When using multi-task learning, with gender and age as auxiliary tasks, deep learning models perform better. We also found that preprocessing of the data resulted in the best performance (AUC = 0.75). We conclude that deep learning models, and in particular multi-task learning, effectively assess fall risk on the basis of wearable sensor data.

Characteristics of daily life gait in fall and non fall-prone stroke survivors and controls.

BACKGROUND: Falls in stroke survivors can lead to serious injuries and medical costs. Fall risk in older adults can be predicted based on gait characteristics measured in daily life. Given the different gait patterns that stroke survivors exhibit it is unclear whether a similar fall-prediction model could be used in this group. Therefore the main purpose of this study was to examine whether fall-prediction models that have been used in older adults can also be used in a population of stroke survivors, or if modifications are needed, either in the cut-off values of such models, or in the gait characteristics of interest. METHODS: This study investigated gait characteristics by assessing accelerations of the lower back measured during seven consecutive days in 31 non fall-prone stroke survivors, 25 fall-prone stroke survivors, 20 neurologically intact fall-prone older adults and 30 non fall-prone older adults. We created a binary logistic regression model to assess the ability of predicting falls for each gait characteristic. We included health status and the interaction between health status (stroke survivors versus older adults) and gait characteristic in the model. RESULTS: We found four significant interactions between gait characteristics and health status. Furthermore we found another four gait characteristics that had similar predictive capacity in both stroke survivors and older adults. CONCLUSION: The interactions between gait characteristics and health status indicate that gait characteristics are differently associated with fall history between stroke survivors and older adults. Thus specific models are needed to predict fall risk in stroke survivors.

Fall-related gait characteristics on the treadmill and in daily life.

BACKGROUND: Body-worn sensors allow assessment of gait characteristics that are predictive of fall risk, both when measured during treadmill walking and in daily life. The present study aimed to assess differences as well as associations between fall-related gait characteristics measured on a treadmill and in daily life. METHODS: In a cross-sectional study, trunk accelerations of 18 older adults (72.3 ± 4.5 years) were recorded during walking on a treadmill (Dynaport Hybrid sensor) and during daily life (Dynaport MoveMonitor). A comprehensive set of 32 fall-risk-related gait characteristics was estimated and compared between both settings. RESULTS: For 25 gait characteristics, a systematic difference between treadmill and daily-life measurements was found. Gait was more variable, less symmetric, and less stable during daily life. Fourteen characteristics showed a significant correlation between treadmill and daily-life measurements, including stride time and regularity (0.48 < r < 0.73; p < 0.022). No correlation between treadmill and daily-life measurements was found for stride-time variability, acceleration range and sample entropy in vertical and mediolateral direction, gait symmetry in vertical direction, and stability estimated as the local divergence exponent by Rosenstein's method in mediolateral direction (r < 0.16; p > 0.25). CONCLUSIONS: Gait characteristics revealed less stable, less symmetric, and more variable gait during daily life than on a treadmill, yet about half of the characteristics were significantly correlated between conditions. These results suggest that daily-life gait analysis is sensitive to static personal factors (i.e., physical and cognitive capacity) as well as dynamic situational factors (i.e., behavior and environment), which may both represent determinants of fall risk.

Assessing physical activity in older adults: required days of trunk accelerometer measurements for reliable estimation.

We investigated the reliability of physical activity monitoring based on trunk accelerometry in older adults and assessed the number of measured days required to reliably assess physical activity. Seventy-nine older adults (mean age 79.1 ± 7.9) wore an accelerometer at the lower back during two nonconsecutive weeks. The duration of locomotion, lying, sitting, standing and shuffling, movement intensity, the number of locomotion bouts and transitions to standing, and the median and maximum duration of locomotion were determined per day. Using data of week 2 as reference, intraclass correlations and smallest detectable differences were calculated over an increasing number of consecutive days from week 1. Reliability was good to excellent when whole weeks were assessed. Our results indicate that a minimum of two days of observation are required to obtain an ICC ≥ 0.7 for most activities, except for lying and median duration of locomotion bouts, which required up to five days.