Purpose: The purpose of this study was to validate optimized algorithm parameter settings for step count and physical behavior for a pocket worn activity tracker in older adults during ADL. Secondly, for a more relevant interpretation of the results, the performance of the optimized algorithm was compared to three reference applications Methods: In a cross-sectional validation study, 20 older adults performed an activity protocol based on ADL with MOXMissActivity versus MOXAnnegarn, activPAL, and Fitbit. The protocol was video recorded and analyzed for step count and dynamic, standing, and sedentary time. Validity was assessed by percentage error (PE), absolute percentage error (APE), Bland-Altman plots and correlation coefficients. Results: For step count, the optimized algorithm had a mean APE of 9.3% and a correlation coefficient of 0.88. The mean APE values of dynamic, standing, and sedentary time were 15.9%, 19.9%, and 9.6%, respectively. The correlation coefficients were 0.55, 0.91, and 0.92, respectively. Three reference applications showed higher errors and lower correlations for all outcome variables. Conclusion: This study showed that the optimized algorithm parameter settings can more validly estimate step count and physical behavior in older adults wearing an activity tracker in the trouser pocket during ADL compared to reference applications.
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This thesis focuses on topics such as preterm birth, variation in gross motor development, factors that influence (premature) infant gross motor development, and parental beliefs and practices. By gaining insight into these topics, this thesis aims to contribute to clinical decision-making of paediatric physiotherapists together with parents, and with that shape early intervention.
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Living a sedentary lifestyle is one of the major causes of numerous health problems. To encourage employees to lead a less sedentary life, the Hanze University started a health promotion program. One of the interventions in the program was the use of an activity tracker to record participants' daily step count. The daily step count served as input for a fortnightly coaching session. In this paper, we investigate the possibility of automating part of the coaching procedure on physical activity by providing personalized feedback throughout the day on a participant's progress in achieving a personal step goal. The gathered step count data was used to train eight different machine learning algorithms to make hourly estimations of the probability of achieving a personalized, daily steps threshold. In 80% of the individual cases, the Random Forest algorithm was the best performing algorithm (mean accuracy = 0.93, range = 0.88–0.99, and mean F1-score = 0.90, range = 0.87–0.94). To demonstrate the practical usefulness of these models, we developed a proof-of-concept Web application that provides personalized feedback about whether a participant is expected to reach his or her daily threshold. We argue that the use of machine learning could become an invaluable asset in the process of automated personalized coaching. The individualized algorithms allow for predicting physical activity during the day and provides the possibility to intervene in time.
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Background: Rising healthcare costs, an increasing general practitioner shortage and an aging population have made healthcare organization transformation a priority. To meet these challenges, traditional roles of non-medical members have been reconsidered. Within the domain of physiotherapy, there has been significant interest in Extended Scope Physiotherapy (ESP). Although studies have focused on the perceptions of different stakeholders in relation to ESP, there is a large variety in the interpretation of ESP. Aim: To identify a paradigm of ESP incorporating goals, roles and tasks, to provide a consistent approach for the implementation of ESP in primary care. Methods: An exploratory, qualitative multi-step design was used containing a scoping review, focus groups and semi-structured interviews. The study population consisted of patients, physiotherapists, general practitioners and indirect stakeholders such as lecturers, health insurers and policymakers related to primary care physiotherapy. The main topics discussed in the focus groups and semi-structured interviews were the goals, skills and roles affiliated with ESP. The ‘framework’ method, developed by Ritchie & Spencer, was used as analytical approach to refine the framework. Results: Two focus groups and twelve semi-structured interviews were conducted to explore stakeholder perspectives on ESP in Dutch primary care. A total of 11 physiotherapists, six general practitioners, five patients and four indirect stakeholders participated in the study. There was a lot of support for ‘decreasing healthcare costs’, ‘tackling increased health demand’ and ‘improving healthcare effectiveness’ as main goals of ESP. The most agreement was reached on ‘triaging’, ‘referring to specialists’ and ‘ordering diagnostic imaging’ as tasks fitting for ESP. Most stakeholders also supported ‘working in a multidisciplinary team’, ‘working as a consultant’ and ‘an ESP role separated from a physiotherapist role’ as roles of ESP. Conclusions: Based on the scoping review, focus groups and interviews with direct and indirect stakeholders, it appears that there is sufficient support for ESP in the Netherlands. This study provides a clear presentation of how ESP can be conceptualized in primary care. A pilot focused on determining the feasibility of ESP in Dutch primary care will be the next step.
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This doctoral thesis describes three case studies of service engineers participating in organizational change, interacting with managers and consultants. The study investigates the role of differences in professional discourse and culture when these three professional groups interact in organizational change, and how this affects the change result. We bring together two scientific fields, first change management and second, linguistics. The intersection represents the overlapping field of professional discourse and culture. The research design was an explorative multiple case study using qualitative linguistic analyses. The study found that successful organizational change is the result of interaction between professional culture, the organizational culture and the organization/change context. The differences between the professional cultures and discourses can hamper the change process. The practical contribution of this study might be the increased awareness among professionals about their own professional, and often implicit, assumptions. Managers, consultants and service engineers have to be aware of the group dynamics and the specific role of their own typical professional discourse and culture in a change project setting.
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Background: Activity trackers can potentially stimulate users to increase their physical activity behavior. The aim of this study was to examine the reliability and validity of ten consumer activity trackers for measuring step count in both laboratory and free-living conditions.Method: Healthy adult volunteers (n = 33) walked twice on a treadmill (4.8 km/h) for 30 min while wearing ten different activity trackers (i.e. Lumoback, Fitbit Flex, Jawbone Up, Nike+ Fuelband SE, Misfit Shine, Withings Pulse, Fitbit Zip, Omron HJ-203, Yamax Digiwalker SW-200 and Moves mobile application). In free-living conditions, 56 volunteers wore the same activity trackers for one working day. Test-retest reliability was analyzed with the Intraclass Correlation Coefficient (ICC).Validity was evaluated by comparing each tracker with the gold standard (Optogait system for laboratory and ActivPAL for free-living conditions), using paired samples t-tests, mean absolute percentage errors, correlations and Bland-Altman plots.Results: Test-retest analysis revealed high reliability for most trackers except for the Omron (ICC .14), Moves app (ICC .37) and Nike+ Fuelband (ICC .53). The mean absolute percentage errors of the trackers in laboratory and free-living conditions respectively, were: Lumoback (−0.2, −0.4), Fibit Flex (−5.7, 3.7), Jawbone Up (−1.0, 1.4), Nike+ Fuelband (−18, −24), Misfit Shine (0.2, 1.1), Withings Pulse (−0.5, −7.9), Fitbit Zip (−0.3, 1.2), Omron (2.5, −0.4), Digiwalker (−1.2, −5.9), and Moves app (9.6, −37.6). Bland-Altman plots demonstrated that the limits of agreement varied from 46 steps (Fitbit Zip) to 2422 steps (Nike+ Fuelband) in the laboratory condition, and 866 steps (Fitbit Zip) to 5150 steps (Moves app) in the free-living condition.Conclusion: The reliability and validity of most trackers for measuring step count is good. The Fitbit Zip is the most valid whereas the reliability and validity of the Nike+ Fuelband is low.
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Lower cardiorespiratory fitness (CRF) and physical activity (PA) associate with higher cardiovascular disease (CVD) risk, but the relationship between CRF and PA in people who have rheumatoid arthritis (RA) at an increased CVD risk (CVD-RA) is not known. The objectives of this study were to determine the levels of CRF and PA in people who have CVD-RA and to investigate the association of CRF with PA in people who have CVD-RA. A total of 24 consecutive patients (19 women) with CVD-RA (> 4% for 10-year risk of fatal CVD development as calculated using the Systematic Coronary Risk Evaluation)-were included in the study. CRF was assessed with a graded maximal exercise test determining maximal oxygen uptake (VO2max). PA was assessed with an accelerometer to determine the amount of step count, sedentary, light and moderate-to-vigorous physical activity (MVPA) minutes per day. Mean age of patients was 65.3 ± 8.3 years. CRF mean values were 16.3 ± 1.2 ml·kg-1 min-1, mean step count per day was 6033 ± 2256, and the mean MVPA time was 16.7 min per day. Significant positive associations were found for CRF with step count (B = 0.001, P = 0.01) and MVPA time (B = 0.15, P = 0.02); a negative association was found for CRF with sedentary time (B = - 0.02, P = 0.03). CRF is low and is associated with step count, sedentary time and MVPA time in people who have RA at an increased CVD risk.
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The purpose of the study was to assess the accuracy of estimates of step frequency from trunk acceleration data analyzed with commonly used algorithms and time window lengths, at a wide range of gait speeds. Twenty healthy young subjects performed an incremental treadmill protocol from 1 km/h up to 6 km/h, with steps of 1 km/h. Each speed condition was maintained for two minutes. A waist worn accelerometer recorded trunk accelerations, while video analysis provided the correct number of steps taken during each gait speed condition. Accuracy of two commonly used signal analysis methods was examined with several different time windows.
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OBJECTIVES: To determine the number of steps taken by older patients in hospital and 1 week after discharge; to identify factors associated with step numbers after discharge; and to examine the association between functional decline and step numbers after discharge.DESIGN: Prospective observational cohort study conducted in 2015-2017.SETTING AND PARTICIPANTS: Older adults (≥70 years of age) acutely hospitalized for at least 48 hours at internal, cardiology, or geriatric wards in 6 Dutch hospitals.METHODS: Steps were counted using the Fitbit Flex accelerometer during hospitalization and 1 week after discharge. Demographic, somatic, physical, and psychosocial factors were assessed during hospitalization. Functional decline was determined 1 month after discharge using the Katz activities of daily living index.RESULTS: The analytic sample included 188 participants [mean age (standard deviation) 79.1 (6.7)]. One month postdischarge, 33 out of 174 participants (19%) experienced functional decline. The median number of steps was 656 [interquartile range (IQR), 250-1146] at the last day of hospitalization. This increased to 1750 (IQR 675-4114) steps 1 day postdischarge, and to 1997 (IQR 938-4098) steps 7 days postdischarge. Age [β = -57.93; 95% confidence interval (CI) -111.15 to -4.71], physical performance (β = 224.95; 95% CI 117.79-332.11), and steps in hospital (β = 0.76; 95% CI 0.46-1.06) were associated with steps postdischarge. There was a significant association between step numbers after discharge and functional decline 1 month after discharge (β = -1400; 95% CI -2380 to -420; P = .005).CONCLUSIONS AND IMPLICATIONS: Among acutely hospitalized older adults, step numbers double 1 day postdischarge, indicating that their capacity is underutilized during hospitalization. Physical performance and physical activity during hospitalization are key to increasing the number of steps postdischarge. The number of steps 1 week after discharge is a promising indicator of functional decline 1 month after discharge.
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Background: Rheumatoid arthritis (RA) is associated with increased risk of cardiovascular disease (CVD) disease and CV mortality1. High values of cardiorespiratory fitness (CRF) are protective against CVD and CV mortality2. Physical activity levels in patients with RA are low. Knowledge on whether physical activity is associated with CRF in patients with RA and high CV risk is scarce. This knowledge is important because improving the level of physical activity could improve CRF and lower CV risk in this group of patients with RA and high CV risk. However, it is unclear whether physical activity is associated with CRF in this group of patients. This study presents the preliminary results at baseline of the association of physical activity with CRF from an ongoing pilot study aimed at improving CRF through exercise therapy in patients with RA and high CV risk.Objectives: To determine (i) the level of physical activity in patients with RA and high CV risk and (ii) whether physical activity is associated with CRF in patients with RA and high CV risk.Methods: Patients with RA and high CV risk participated in this pilot study. Increased 10-year risk of CV mortality was determined by using the Dutch SCORE-table. Anthropometrics and disease characteristics were collected. Physical activity was assessed with an Actigraph accelerometer to determine the number of steps and intensity of physical activity expressed in terms of sedentary, light, and moderate-to-vigorous time per day. Participants wore the accelerometer for seven days. A minimum of four measurement days with a wear time of at least 10 hours was required. The VO2 max measured with a graded maximal exercise test was used to determine the CRF. Pearson correlation coefficients were calculated for the associations between the different measures of physical activity and VO2max. For the variables that were associated, linear regression analysis was carried out, with pain and disease activity as possible confounders.Results: Thirteen females and five males were included in the study. The mean age was 66.5 (± 15.0) years. Only 22% of the patients met public health physical activity guidelines for the minimal amount of 150 minutes a week. The mean step count was 6237 (± 2297) steps per day and mean moderate-to-vigorous physical activity time was 16.50 (± 23.56) minutes per day. The median VO2max was 16.23 [4.63] ml·kg-1·min-1, which is under the standard. Pearson correlations showed a significant positive association for step count with VO2max. No associations were found for sedentary, light, and moderate-to-vigorous physical activity with VO2max. The significant association between step count and VO2max(p = 0.01) was not confounded by disease severity and pain.Discussion: Since better CRF protects against CVD, increasing daily step count may be a simple way to reduce the risk of CVD in patients with RA and high CV risk. However, these results need to be confirmed in a larger study group. Future research should investigate if improving daily step count will lead to better CRF levels and ultimately will lead to a reduction in CV risk in patients with RA and high CV risk.Conclusion: Physical activity levels of patients with RA and high CV risk do not meet public health requirements for physical activity criteria and the VO2max was under the standard. Step count is positively associated with CRF.
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