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[Purpose] This study aimed to examine the characteristics of preoperative physical activity and its impact on the postoperative period in patients who underwent surgery for esophageal cancer. [Participants and Methods] The participants were 30 patients who were diagnosed with esophageal cancer, underwent surgery, and fulfilled their conditions. Preoperative physical activity was measured using the step count, and metabolic equivalents as the amount of physical activity. We examined the relationships between preoperative step count and METs, patient demographics, treatment-related factors, preoperative physical function, and activities of daily living. Moreover, we examined the relationships of preoperative step count and METs with postoperative mobilization, physical activity, physical function, and activities of daily living. [Results] Preoperative step count was related to age, Glasgow prognostic score, and preoperative functional independence and associated with step count on postoperative days 7-13, METs on postoperative days 7-9, 6-min walking distance, and functional independence measures at discharge. [Conclusion] Improving the nutritional status and increasing preoperative physical activity by walking for esophageal cancer may help improve physical activity after postoperative day 7, exercise tolerance, and activities of daily after discharge., Competing Interests: There are no conflicts of interest to disclose., (2024©by the Society of Physical Therapy Science. Published by IPEC Inc.)

Introduction: Very few studies have examined patterns of physical activity (PA) during a pulmonary rehabilitation (PR) program in people with COPD., Aims: To compare the patterns of PA in: 1) the week before commencing PR (pre-PR) with a week during PR (PR week); 2) PR days and non-PR days during a PR week; 3) pre-PR and the week following PR completion (post-PR)., Methods: This was a multicenter, prospective cohort study. Participants attended twice weekly supervised PR for 8-12 weeks. Daily step count (primary outcome), time in light activities, time in moderate to vigorous PA (MVPA), total sedentary time and sit-to-stand (STS) transitions were measured using a thigh worn accelerometer for seven days, at each assessment time point: pre-PR, PR week and post-PR., Results: 29 participants, mean age (SD) 69years(7), FEV 1 53%pred(16). The PR week compared to pre-PR, showed higher daily: step count (mean difference (95%CI)), 941steps(388-1494); and MVPA, 11mins(6-15), with no difference in: time in light activities, -1min(-6-5); total sedentary time, 7mins(-21-36); or STS transitions, 0(-5-6). PR days compared to non-PR days showed higher: step count, 2810steps(1706-3913); time in light activities 11mins(1-20); time in MVPA, 27mins(17-35) and STS transitions, 8(4-12), with no difference in total sedentary time: -33mins(-80-15). There were no differences in any PA measures post-PR compared to pre-PR (p < 0.05)., Conclusion: Daily step count and time spent in MVPA increased significantly during the PR week, solely due to increased PA on days participants attended PR., Competing Interests: Declaration of competing interest There is no conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Older adults living in retirement communities are an understudied population, and the association between their motivation and daily physical activity is unknown. We recruited participants (n = 173) living in a retirement community who completed the Behavioral Regulation in Exercise Questionnaire-2 and wore an activPAL accelerometer to evaluate this relationship. Participants had a median age of 81 years and demonstrated low levels of daily activity with an average step count of 3,637 (±1,965) steps per day and 52 (±25) min of daily stepping time. External motivation was negatively associated with the square root of daily step count (β = -4.57; p < .001) and square root of daily stepping time (β = -0.49; p < .001). Older adults living in retirement communities demonstrated low levels of daily activity, with a negative association between external motivation and daily activity. Strategies are needed to make an active lifestyle supportive and enticing for older adults in these communities.

Background/objectives: Few studies have investigated associations between the motivational outcome based on physical activity (PA) affective experiences (i.e., attraction vs. antipathy toward PA) and behavior. This study investigated cross-sectional and longitudinal associations between attraction (vs. antipathy) toward PA and device-based PA in older adults., Methods: Older adults (n = 139; 71% female, Mage = 70.5) completed assessments of attraction (vs. antipathy) toward PA and 14 days of device-based accelerometry at Times 1 and 2., Results: Greater attraction toward PA at Time 1 was associated with greater steps (β = 5.31, p < .01) and moderate to vigorous intensity PA (β = 3.08, p < .05) at Time 1. Greater attraction toward PA at Time 1 was not significantly associated with steps or moderate to vigorous intensity PA at Time 2., Conclusion: Greater emphasis on resultant motivation from PA affective experiences may be useful in promoting PA in older adults. Significance/Implications: In spite of mixed findings in the present study, there is strong evidence that positive affective responses during a single bout of PA play an important role in predicting future engagement. Yet, affective experiences during PA can be individualistic and often influenced by contextual factors. Interventions designed to increase PA should focus on factors that may create positive affective experiences for participants.

Objective: This study aimed to describe the variability in estimates of the association of daily steps and all-cause mortality in systematic reviews with meta-analyses, to identify the factors potentially responsible for it, and to provide an updated estimate., Methods: Five databases were systematically searched up to May 2024 to identify systematic reviews with meta-analyses and prospective cohort studies. A qualitative synthesis of previous reviews and an updated meta-analysis of cohort studies were performed. Pooled hazard ratios (HRs) with their 95% confidence intervals (CIs) were calculated using a random-effects model., Results: Eleven systematic reviews with meta-analyses and 14 cohort studies were included, revealing considerable variability in result presentation. Our updated meta-analysis showed a nonlinear association, indicating a lower risk of all-cause mortality with increased daily steps, with a protective threshold at 3143 steps/day, and a pooled HR of 0.91 (95% CI: 0.87, 0.95) per 1000 steps/day increment. Physical activity categories consistently indicated progressively reduced mortality risk, with the highly active category (>12,500 steps/day) exhibiting the lowest risk (0.35 (95% CI: 0.29, 0.42))., Conclusion: Systematic reviews and meta-analyses showed considerable variability in effect estimates due to different methods of quantifying exposure. Despite it, our study underscores the importance of increased daily steps in reducing all-cause mortality, with a minimum protective dose of 3000 steps/day, although the optimal dose differed according to age and sex. It is recommended that future studies categorise daily steps by physical activity category, perform dose-response analyses, and use increments of 1000 steps/day., Competing Interests: Declaration of competing interest The authors have no relevant financial or non-financial interests to disclose., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Objective: Individuals with chronic pain due to knee osteoarthritis (OA) are insufficiently physically active, and alterations of facilitatory and inhibitory nociceptive signaling are common in this population. Our objective was to examine the association of these alterations in nociceptive signaling with objective accelerometer-based measures of physical activity in a large observational cohort., Design: We used data from the Multicenter Osteoarthritis Study. Measures of peripheral and central pain sensitivity included pressure pain threshold at the knee and mechanical temporal summation at the wrist, respectively. The presence of descending pain inhibition was assessed by conditioned pain modulation (CPM). Physical activity was quantitatively assessed over 7 days using a lower back-worn activity monitor. Summary metrics included steps/day, activity intensity, and sedentary time. Linear regression analyses were used to evaluate the association of pain sensitivity and the presence of descending pain inhibition with physical activity measures., Results: Data from 1873 participants was analyzed (55.9% female, age = 62.8 ± 10.0 years). People having greater peripheral and central sensitivity showed lower step counts. CPM was not significantly related to any of the physical activity measures, and none of the exposures were significantly related to sedentary time., Conclusions: In this cohort, greater peripheral and central sensitivity were associated with reduced levels of objectively-assessed daily step counts. Further research may investigate ways to modify or treat heightened pain sensitivity as a means to increase physical activity in older adults with knee OA., (Copyright © 2024 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.)

Purpose: Determine the level of agreement of three activity monitors compared with the gold standard (video review) on the activity level of patients with stroke., Methods: A prospective, observational, agreement study was performed on 47 individuals with sub-acute stroke in an inpatient rehabilitation facility. Data was collected during one physical therapy session. Individuals wore three device types; Actigraph (AG), Activpal (AP), and stepwatch activity monitor (SAM). Variables assessed were step counts for each limb (hemiparetic and non-hemiparetic) and percent time standing and other., Analysis: Results from the activity monitors were compared to the video review and assessed for agreement using the intraclass correlation coefficient (ICC) and accuracy of mean difference from video observation., Results: The step counts with the SAM on the non-hemiparetic limb had the highest ICC for step counts (ICC = 0.98, p  < 0.001) and were overestimated with 21% accuracy. The SAM on the hemiparetic limb had 9.7% accuracy (ICC = 0.92, p  < 0.001). For percent standing time all devices overestimated with poor reliability. For percent other activity time, the AP had the best accuracy and underestimated for both the hemiparetic limb (9.9% accuracy; ICC = 0.90, p  < 0.001) and non-hemiparetic limb (8.3% accuracy; ICC = 0.84, p  < 0.001)., Conclusions: The use of multiple devices may be warranted to capture an accurate understanding of activity levels in this population of individuals with sub-acute stroke. There are concerns with all monitors and clinicians and researchers should be aware of what measures they are wanting to understand about their population.

Purpose: The aim of this study is to determine the validity of consumer grade step counter devices during the early recovery period after knee replacement surgery., Methods: Twenty-three participants wore a Fitbit Charge or Apple Watch Series 4 smart watch and performed a walking test along a 50-metre hallway. There were 9 males and 14 females included in the study with an average age of 68.5 years and BMI of 32. Each patient wore both the Fitbit Charge and Apple Watch while completing the walking test and an observer counted the ground truth value using a thumb-push tally counter. This test was repeated pre-operatively with no gait aid, immediately post operatively with a walker, at 6 weeks follow up with a cane and at 6 months with no gait aid. Bland-Altman plots were performed for all walking tests to compare the agreement between measurement techniques., Results: Mean overall agreement of step count for pre-operative and at 6 months for subjects walking without gait aids was excellent for both the Apple Watch vs. actual and Fitbit vs. actual with bias values ranging from - 0.87 to 1.36 with limits of agreement (LOA) ranging between - 10.82 and 15.91. While using a walker both devices showed extremely little agreement with the actual step count with bias values between 22.5 and 24.37 with LOA between 11.7 and 33.3. At 6 weeks post-op while using a cane, both the Apple Watch and Fitbit devices had a range of bias values between - 2.8 and 5.73 with LOA between - 13.51 and 24.97., Conclusions: These devices show poor validity in the early post operative setting, especially with the use of gait aids, and therefore results should be interpreted with caution., (© 2024. The Author(s).)

Background: eHealth applications can support early mobilization and physical activity (PA) after surgery. This systematic review provides an overview of eHealth services to enhance or record PA after visceral surgery interventions., Methods: Two electronic databases (MEDLINE PubMed and Web of Science) were systematically searched (November 2023). Articles were considered eligible if they were controlled trials and described digital devices used to promote PA after visceral surgery. The Cochrane risk of bias (RoB-2) tool was used to determine the methodological quality of studies., Results: A total of nine randomized controlled studies (RCT) were included in this systematic review. The studies differed with respect to the interventions, surgical indications and evaluation variables. The risk of bias of the individual studies was moderate. The six studies using activity trackers (AT) predominantly showed insignificant improvements in the postoperative step count. The more complex fitness applications could partially reveal significant advantages compared to the control groups and the home-based online training also showed a significant increase in functional capacity., Conclusion: Activity tracking alone has so far failed to show clinically relevant effects. In contrast, the more complex eHealth applications revealed advantages compared to usual postoperative care. More high-quality studies are needed for evidence-based recommendations for eHealth services in conjunction with visceral surgery., (© 2024. The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature.)

Objective: This study aimed to quantify the association between step count and multiple health outcomes in a healthy population., Methods: PubMed, Embase, Web of Science, and The Cochrane Library were systematically searched for systematic reviews and meta-analyses from inception to April 1, 2022. Literature screening, data extraction, and data analysis were performed in this umbrella review. The intervention factor was daily step counts measured based on devices. Multiple health outcomes included metabolic diseases, cardiovascular diseases, all-cause mortality, and other outcomes in the healthy population., Results: Twenty studies with 94 outcomes were identified in this umbrella review. The increase in daily step count contributed to a range of human health outcomes. Furthermore, the special population, different age groups, countries, and cohorts should be carefully considered. Negative correlation between step counts and the following outcomes: metabolic outcomes, cardiovascular diseases, all-cause mortality, postural balance, cognitive function, and mental health. However, there was no association between participation in the outdoor walking group and the improvement of systolic blood pressure and diastolic blood pressure. Analysis of the dose-response association between increasing daily step count and the risk of cardiovascular disease events and all-cause mortality showed a substantially linear relationship., Conclusion: A wide range of health outcomes can benefit from the right number of steps., (© 2024 Chinese Cochrane Center, West China Hospital of Sichuan University and John Wiley & Sons Australia, Ltd.)

With the increased push for personalized medicine, researchers and clinicians have begun exploring the use of wearable sensors to track patient activity. These sensors typically prioritize device life over robust onboard analysis, which results in lower accuracies in step count, particularly at lower cadences. To optimize the accuracy of activity-monitoring devices, particularly at slower walking speeds, proven methods must be established to identify suitable settings in a controlled and repeatable manner prior to human validation trials. Currently, there are no methods for optimizing these low-power wearable sensor settings prior to human validation, which requires manual counting for in-laboratory participants and is limited by time and the cadences that can be tested. This article proposes a novel method for determining sensor step counting accuracy prior to human validation trials by using a mechanical camshaft actuator that produces continuous steps. Sensor error was identified across a representative subspace of possible sensor setting combinations at cadences ranging from 30 steps/min to 110 steps/min. These true errors were then used to train a multivariate polynomial regression to model errors across all possible setting combinations and cadences. The resulting model predicted errors with an R 2 of 0.8 and root-mean-square error (RMSE) of 0.044 across all setting combinations. An optimization algorithm was then used to determine the combinations of settings that produced the lowest RMSE and median error for three ranges of cadence that represent disabled low-mobility ambulators, disabled high-mobility ambulators, and healthy ambulators (30-60, 20-90, and 30-110 steps/min, respectively). The model identified six setting combinations for each range of interest that achieved a ±10% error in cadence prior to human validation. The anticipated range of errors from the optimized settings at lower walking speeds are lower than the reported errors of wearable sensors (±30%), suggesting that pre-human-validation optimization of sensors may decrease errors at lower cadences. This method provides a novel and efficient approach to optimizing the accuracy of wearable activity monitors prior to human validation trials.

While physical activity (PA) is understood to promote vascular health, little is known about whether the daily and weekly patterns of PA accumulation associate with vascular health. Accelerometer-derived (activPAL3) 6- or 7-day stepping was analyzed for 6430 participants in The Maastricht Study (50.4% women; 22.4% Type 2 diabetes mellitus (T2DM)). Multivariable regression models examined associations between stepping metrics (average step count, and time spent slower and faster paced stepping) with arterial stiffness (measured as carotid-femoral pulse wave velocity (cfPWV)), and several indices of microvascular health (heat-induced skin hyperemia, retinal vessel reactivity and diameter), adjusting for confounders and moderators. PA pattern metrics were added to the regression models to identify associations with vascular health beyond that of stepping metrics. Analyses were stratified by T2DM status if an interaction effect was present. Average step count and time spent faster paced stepping was associated with better vascular health, and the association was stronger in those with compared to those without T2DM. In fully adjusted models a higher step count inter-daily stability was associated with a higher (worse) cfPWV in those without T2DM (std β = 0.04, p = 0.007) and retinal venular diameter in the whole cohort (std β = 0.07, p = 0.002). A higher within-day variability in faster paced stepping was associated with a lower (worse) heat-induced skin hyperemia in those with T2DM (std β = -0.31, p = 0.008). Above and beyond PA volume, the daily and weekly patterns in which PA was accumulated were additionally associated with improved macro- and microvascular health, which may have implications for the prevention of vascular disease., (© 2024 The Authors. Scandinavian Journal of Medicine & Science In Sports published by John Wiley & Sons Ltd.)

Objectives: Commercially available wearable activity monitors can promote physical activity behaviour. Clinical trials typically quantify physical activity with research grade activity monitors prior to testing interventions utilising commercially available wearable activity monitors aimed at increasing step count. Therefore, it is important to test the agreement of these two types of activity monitors., Objectives: Observational., Methods: Thirty adults (20-65 years, n = 19 females) were provided a Fitbit Charge 4©. To determine reliability using an intraclass correlation coefficient, two, one-minute bouts of treadmill walking were performed at a self-selected pace. Subsequently, participants wore both an ActiGraph wGT3X-BT and the Fitbit for seven days. To determine agreement, statistical equivalence and the mean absolute percentage error were calculated and represented graphically with a Bland-Altman plot. Ordinary least products regression was performed to identify fixed or proportional bias., Results: The Fitbit showed 'good' step count reliability on the treadmill (intraclass correlation coefficient = 0.75, 95 % CI = 0.53-0.87, p < 0.001). In free-living however, it overestimated step count when compared to the ActiGraph wGT3X-BT (mean absolute percentage error = 26.02 % ± 14.63). Measurements did not fall within the ± 10 % equivalence region and proportional bias was apparent (slope 95 % CI = 1.09-1.35)., Conclusions: The Fitbit Charge 4© is reliable when measuring step count on a treadmill. However, there is an overestimation of daily steps in free-living environments which may falsely indicate compliance with physical activity recommendations., Competing Interests: Declaration of interest statement The authors declare no conflicts of interest., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Chronic pain is associated with substantial impairment in physical function, which has been identified as a top concern among persons with pain. GetActive-Fitbit, a mind-body activity program, is feasible, acceptable, and associated with improvement in physical function among primarily White, sedentary individuals with pain. In preparation for a multisite efficacy trial, we must examine feasibility across multiple sites with diverse patient populations. Here we describe the protocol of a multisite, feasibility RCT comparing GetActive-Fitbit with a time- and attention-matched educational comparison (Healthy Living for Pain). We aim to 1) test multisite fidelity of clinician training; 2) evaluate multisite feasibility benchmarks, including recruitment of chronic pain patients taking <5000 steps/day and racial and ethnic minorities; and 3) optimize fidelity and study protocol in preparation for a future multisite efficacy trial., Methods: Clinician training fidelity was assessed via roleplays and mock group sessions. Feasibility (i.e., recruitment, acceptability, credibility, adherence, satisfaction), multimodal physical function (e.g., self-report, 6-Minute Walk Test, step-count), and other psychosocial outcomes are assessed at baseline, posttest, and 6 months. Protocol optimization will be assessed using exit interviews and cross-site meetings., Results: The trial is ongoing. Clinician training is complete. 87 participants have been recruited. 54 completed baseline assessments and randomization, 44 are mid-intervention, and 9 have completed the intervention and posttest., Conclusions: This study addresses the critical need for feasible, acceptable mind-body-activity interventions for chronic pain that follow evidence-based guidelines and improve all aspects of physical function across diverse populations. Results will inform a future fully-powered multisite efficacy trial., Clinical Trial Registration: NCT05700383., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Purpose: Little is known about the changes and the factors in physical activity as following total hip arthroplasty (THA). There are potential discrepancies between subjective and objective measurements of physical activity. Thus, our porpose is to compare objective and subjective measurements of activity levels in patients undergoing THA preoperatively, three months and one year following surgery, and investigated the factors that predicts the objective activity level after THA., Methods: This prospective observational study included 42 patients with unilateral symptomatic hip osteoarthritis who underwent THA. The objective activity level (step counts, sit-to-stands, and upright time) by using a tri-axial accelerometer, PRO (Oxford hip score; OHS and University of California, Los Angeles activity score; UCLA score), and muscle volume around the hip joint by using preoperative computed tomography were measured., Results: The number of steps, OHS, and UCLA score before, at three months, and one year after THA averaged 5092, 6532, and 6545 steps, 30.3, 43.0, and 44.2 points, and 3.4, 4.8, and 4.6 points, respectively, with significant postoperative increases (P < 0.05). No significant difference was found between three months and one year postoperatively. In multivariate analysis, younger age and higher preoperative contralateral gluteal medius volume were the predictors of higher postoperative step counts (P < 0.05)., Conclusions: Physical activity, including step counts, OHS, and UCLA score increased significantly until three months after unilateral THA. Early surgical intervention before contralateral muscle declines and preoperative rehabilitation including contralateral side may additionally improve postoperative activity levels., (© 2023. The Author(s) under exclusive licence to SICOT aisbl.)

Background and Objectives : Mild cognitive impairment (MCI) is an early stage of dementia in which everyday tasks can be maintained; however, notable challenges may occur in memory, focus, and problem-solving skills. Therefore, motor-cognitive dual-task training is warranted to prevent cognitive decline and improve cognition in aging populations. This study aimed to determine the influence of such dual-task activities during straight and curved walking on the activities of the prefrontal cortex and associated gait variables in older adults with MCI. Materials and Methods : Twenty-seven older adults aged ≥65 years and identified as having MCI based on their scores (18-23) on the Korean Mini-Mental State Examination were enrolled. The participants performed four task scenarios in random order: walking straight, walking straight with a cognitive task, walking curved, and walking curved with a cognitive task. The activation of the prefrontal cortex, which is manifested by a change in the level of oxyhemoglobin, was measured using functional near-infrared spectroscopy. The gait speed and step count were recorded during the task performance. Results : Significant differences were observed in prefrontal cortex activation and gait variables ( p < 0.05). Specifically, a substantial increase was observed in prefrontal cortex activation during a dual task compared with that during a resting-state ( p < 0.013). Additionally, significant variations were noted in the gait speed and step count ( p < 0.05). Conclusions : This study directly demonstrates the impact of motor-cognitive dual-task training on prefrontal cortex activation in older adults with MCI, suggesting the importance of including such interventions in enhancing cognitive function.

Although walking has proven efficacy for glycemic control, patients struggle to meet daily step goals. This secondary analysis investigated the effect of step count measurement rate on glycemic control. Patients with type 2 diabetes from eight hospitals in Japan participated in a 12-month randomized controlled trial. The intervention group received DialBetesPlus, a self-management support system that allowed patients to monitor step count using a pedometer. We divided the intervention group into two groups based on whether daily step count measurement rate (the percentage of days with pedometer use) increased or decreased during the last three months of the intervention (month 10-12), relative to the first three months of the intervention (month 1-3). Patients with a reduced measurement rate experienced a worsening in glycemic control, with between-group difference of 0.516% in the amount of change in HbA1c (p=0.012). We conclude that step count measurement may lead to a better glycemic profile.

Background: Established health-related quality of life scores do not consider both subjective and objective indices of health. We propose the subjective and objective quality of life score (SOQOL) for the comprehensive assessment of health-related quality of life and aim to provide normative population data. The SOQOL is compatible with smartphone applications, allowing widespread use on a global scale., Methods: Normative SOQOL population data was sourced from pre-existing datasets on the EQ-5D-5L, daily step count, and walking speed. Normative values were calculated using weighted grand means. We trialled the SOQOL in a group of five patients presenting to a spinal neurosurgery clinic., Results: SOQOL scores decreased with age, and women had lower scores in every age group. In our case series, the spine patients with the biggest SOQOL deficit compared to age- and sex-matched population averages were found to be surgical while the rest were non-surgical., Conclusions: The SOQOL shows promise as a simple and effective scoring tool that is compatible with smartphones, potentially useful for screening in primary and specialized care settings, and for assessment following healthcare interventions. This study, however, is preliminary, and the findings are primarily suggestive. They underline the necessity for future, more comprehensive studies to validate and expand upon these initial observations. The conclusion of both this abstract and the full paper will clearly state these limitations and the preliminary nature of the study., (© 2024. The Author(s).)

Children should engage in at least 60 min of physical activity daily to develop or maintain healthy habits (Centers for Disease Control and Prevention, 2021a). Previous research suggests that contingent attention is a powerful tool for increasing moderate to vigorous physical activity. In this study, the researchers examined the effects of a group game on steps per minute at recess in an inclusive classroom with preschoolers. The researcher taught the game called the T-Rex game in which the game rules (chasing students who were moving) involved contingencies for natural attention to follow moderate to vigorous physical activity. The results showed a functional relation between step count and the group game in which students engaged in higher step counts when the group game was in place than during baseline. These findings extend other work by demonstrating that contingent attention embedded in group games can increase step count., (© 2023 The Authors. Journal of Applied Behavior Analysis published by Wiley Periodicals LLC on behalf of Society for the Experimental Analysis of Behavior (SEAB).)

Physical activity (PA) is suggested to reduce osteoarthritis pain; however, it may be avoided by patients requiring arthroplasty. Our goal was to investigate objective and patient-reported outcomes as a function of pre-operative PA levels in patients undergoing total knee arthroplasty (TKA). A total of 1941 patients enrolled in a multicenter prospective cohort study investigating a smartphone-based care management platform for self-directed rehabilitation underwent TKA and were included in the analysis. Activity was categorized based on the cohort's step count quartiles into low, moderate, and high pre-operative PA. Pre-operative and post-operative pain, EQ5D5L, KOOS JR, and step counts were compared by ANOVA according to activity group. Pre-operative pain scores increased with the decreasing activity level (all, p < 0.05) and were most improved post-operatively in the low PA group. High PA patients demonstrated the smallest improvements in EQ-5D-5L and KOOS JR. Low and moderate PA patients increased physical activity by three months, reaching 176% and 104% of pre-operative steps; high PA patients did not return to full step counts by one year post-operatively. Patients undergoing TKA who present with higher levels of physical activity report lower levels of pain and higher function pre-operatively but appreciate less improvement up to one year post-operatively. These results may be helpful in appropriate counseling of patient expectations before TKA.

Background: Step counts are increasingly used in public health and clinical research to assess well-being, lifestyle, and health status. However, estimating step counts using commercial activity trackers has several limitations, including a lack of reproducibility, generalizability, and scalability. Smartphones are a potentially promising alternative, but their step-counting algorithms require robust validation that accounts for temporal sensor body location, individual gait characteristics, and heterogeneous health states., Objective: Our goal was to evaluate an open-source, step-counting method for smartphones under various measurement conditions against step counts estimated from data collected simultaneously from different body locations ("cross-body" validation), manually ascertained ground truth ("visually assessed" validation), and step counts from a commercial activity tracker (Fitbit Charge 2) in patients with advanced cancer ("commercial wearable" validation)., Methods: We used 8 independent data sets collected in controlled, semicontrolled, and free-living environments with different devices (primarily Android smartphones and wearable accelerometers) carried at typical body locations. A total of 5 data sets (n=103) were used for cross-body validation, 2 data sets (n=107) for visually assessed validation, and 1 data set (n=45) was used for commercial wearable validation. In each scenario, step counts were estimated using a previously published step-counting method for smartphones that uses raw subsecond-level accelerometer data. We calculated the mean bias and limits of agreement (LoA) between step count estimates and validation criteria using Bland-Altman analysis., Results: In the cross-body validation data sets, participants performed 751.7 (SD 581.2) steps, and the mean bias was -7.2 (LoA -47.6, 33.3) steps, or -0.5%. In the visually assessed validation data sets, the ground truth step count was 367.4 (SD 359.4) steps, while the mean bias was -0.4 (LoA -75.2, 74.3) steps, or 0.1%. In the commercial wearable validation data set, Fitbit devices indicated mean step counts of 1931.2 (SD 2338.4), while the calculated bias was equal to -67.1 (LoA -603.8, 469.7) steps, or a difference of 3.4%., Conclusions: This study demonstrates that our open-source, step-counting method for smartphone data provides reliable step counts across sensor locations, measurement scenarios, and populations, including healthy adults and patients with cancer., (©Marcin Straczkiewicz, Nancy L Keating, Embree Thompson, Ursula A Matulonis, Susana M Campos, Alexi A Wright, Jukka-Pekka Onnela. Originally published in JMIR Cancer (https://cancer.jmir.org), 15.11.2023.)

Daily steps could be a valuable indicator of real-world ambulation in Parkinson's disease (PD). Nonetheless, no study to date has investigated the minimum number of days required to reliably estimate the average daily steps through commercial smartwatches in people with PD. Fifty-six patients were monitored through a commercial smartwatch for 5 consecutive days. The total daily steps for each day was recorded and the average daily steps was calculated as well as the working and weekend days average steps. The intraclass correlation coefficient (ICC) (3,k), standard error of measurement (SEM), Bland-Altman statistics, and minimum detectable change (MDC) were used to evaluate the reliability of the step count for every combination of 2-5 days. The threshold for acceptability was set at an ICC ≥ 0.8 with a lower bound of CI 95% ≥ 0.75 and a SAM < 10%. ANOVA and Mann-Whitney tests were used to compare steps across the days and between the working and weekend days, respectively. Four days were needed to achieve an acceptable reliability (ICC range: 0.84-0.90; SAM range: 7.8-9.4%). In addition, daily steps did not significantly differ across the days and between the working and weekend days. These findings could support the use of step count as a walking activity index and could be relevant to developing monitoring, preventive, and rehabilitation strategies for people with PD.

This study aimed to investigate the relationship between objectively measured step counts, step intensity and FOF in community-dwelling older Chinese women. Cross-sectional analyses were conducted on pooled data (n = 1101) from the baseline survey of the Physical Activity and Health Study (PAHIOWS). Step counts and step intensity were measured using wGT3X-BT accelerometers, and FOF was categorized into two levels (low and high) for logistic regression analysis. Higher step counts were significantly and negatively associated with FOF; however, after adjusting for step intensity, the association was no longer statistically significant. On the contrary, higher step intensity was negatively associated with FOF independent of step counts. This finding may provide new insights into the physical activity management of FOF in older women., Competing Interests: Declaration of Competing Interest None., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Background: Frailty is a syndrome related to declining functioning attributed to aging. As a reversible, often improved condition, preventive measures for frailty can be effective., Objective: This study aimed to evaluate a frailty prevention program for older men comprising face-to-face meetings and an original social mobile application. We also examined the effect of COVID-19-associated social isolation on the implementation of this program., Methods: We conducted a mixed-methods pilot study featuring a single group before and after comparison of 11 man participants, ≥65 years, living in Japanese cities with a spouse or relatives. Program outcome measures included frailty, loneliness, grip strength, step count and mental health status. Process evaluation considered the experience of participants through a semi-structured interview., Results: The intervention period included an interval of self-isolation owing to the spread of COVID-19. Among the outcomes, grip strength decreased after intervention. No significant negative changes were observed in other items. Themes emerging from participant experiences with the program included 'Cooperation with researchers and contributing to research', 'Greater awareness of health', 'Interest in and experience of "newness"', 'Hesitation over active engagement', 'Casual ties with members' and 'Relationships that do not breach personal boundaries'., Conclusions: Although the COVID-19 pandemic overlapped with the intervention, participants maintained their mental health. The program was a novel, stimulating experience for older men and demonstrated the usefulness of information and communication technology in supporting their social activities., Implications for Practice: As a community health nursing initiative for older people, we propose activities that combine group and online support. Frailty prevention programs for older men must contain content that stimulates their interests, such as 'health' and 'newness'., (© 2023 John Wiley & Sons Ltd.)

Introduction: Major depressive disorder (MDD) is a common debilitating psychiatric condition and a major cause of productivity loss in workers. Using intermittent, subjective indicators, previous studies have shown that physical activity can predict lower levels of depressive symptoms. However, there is an unmet need for continuous and objective measures to identify MDD development before it results in productivity loss. The aim of this study was to elucidate the association between continuously measured walking activity and the development of MDD., Methods: This retrospective, observational, longitudinal cohort study used health insurance claims data. Individuals aged 20-74 years were included if they had a record of MDD diagnosis and daily step count data for the 60 days before and after the first recorded MDD-related visit, which was defined as the index date. Multivariate analysis was conducted to compare 7-day moving averages of step counts on each day of the analysis period with the mean step count on the index date. Joinpoint regression analysis was used to determine when the trajectory of the moving step count average changed (inflection point)., Results: In total, 2,143 patients with a mean age of 41.2 (standard deviation [SD]: 10.6) years were included. The majority of patients were men (69.5%) and employed full-time (94.1%). Antidepressants were prescribed for 59.2% of patients. The 7-day moving average step count decreased from 6,310 (SD: 3758) at day -60 to 5,879 (SD: 3183) at the index date (first recorded MDD-related visit), and then increased to 6,062 (SD: 4029) at day +60. Compared with the index date, the 7-day moving average of step counts was significantly higher at days -60 to -1, +23 to +33, and + 42 to +60, and significantly lower at days +2 and + 3. Joinpoint regression analysis of 7-day moving average step counts from day -60 to day 0 identified an inflection point at day -14., Conclusion: In working-age Japanese people, a formal diagnosis of MDD was preceded by a notable decline in daily step counts by approximately 2 weeks. MDD diagnosis and (presumed) treatment were followed by a gradual increase in daily step counts., Competing Interests: FT and SF are employees of Takeda Pharmaceutical Company Limited. YF has a consulting service agreement with Takeda Pharmaceutical Company Limited and receives consulting fees. The authors declare that this study received funding from Takeda Pharmaceutical Company Limited. The funder had the following involvement: contribution to the study design and interpretation of the study results, involvement in the decision to submit, critical review of the manuscript, and approval of the final version for submission. All authors declare no other competing interests., (Copyright © 2023 Fujino, Tokuda and Fujimoto.)

Background: Exercise has various health benefits for people with Parkinson's disease (PD). However, implementing exercise into daily life and long-term adherence remain challenging. To increase a sustainable engagement with physical activity of people with PD, interventions that are motivating, accessible, and scalable are needed. We primarily aim to investigate whether a smartphone app (STEPWISE app) can increase physical activity (i.e., step count) in people with PD over one year. Our second aim is to investigate the potential effects of the intervention on physical fitness, and motor- and non-motor function. Our third aim is to explore whether there is a dose-response relationship between volume of physical activity and our secondary endpoints., Methods: STEPWISE is a double-blind, randomized controlled trial. We aim to include 452 Dutch people with PD who can walk independently (Hoehn & Yahr stages 1-3) and who do not take more than 7,000 steps per day prior to inclusion. Physical activity levels are measured as step counts on the participant's own smartphone and scaled as percentage of each participant's baseline. Participants are randomly assigned to an active control group with an increase of 5-20% (active controls) or any of the three intervention arms with increases of 25-100% (intermediate dose), 50-200% (large dose), or 100-400% (very large dose). The primary endpoint is change in step count as measured by the STEPWISE smartphone app from baseline to 52 weeks. For our primary aim, we will evaluate the between-group difference in average daily step count change from baseline to 52 weeks. For our second aim, measures of physical fitness, and motor- and non-motor function are included. For our third aim, we will associate 52-week changes in step count with 52-week changes in secondary outcomes., Discussion: This trial evaluates the potential of a smartphone-based intervention to increase activity levels in people with PD. We envision that motivational apps will increase adherence to physical activity recommendations and could permit conduct of remote clinical trials of exercise for people with PD or those at risk of PD., Trial Registration: ClinicalTrials.gov; NCT04848077; 19/04/2021., Clinicaltrials: gov/ct2/show/NCT04848077., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Background: High blood pressure (BP) and physical inactivity are the major risk factors for cardiovascular diseases. Mobile health is expected to support patients' self-management for improving cardiovascular health; the development of fully automated systems is necessary to minimize the workloads of health care providers., Objective: The objective of our study was to evaluate the preliminary efficacy, feasibility, and perceived usefulness of an intervention using a novel smartphone-based self-management system (DialBetes Step) in increasing steps per day among workers with high BP., Methods: On the basis of the Social Cognitive Theory, we developed personalized goal-setting and feedback functions and information delivery functions for increasing step count. Personalized goal setting and feedback consist of 4 components to support users' self-regulation and enhance their self-efficacy: goal setting for daily steps, positive feedback, action planning, and barrier identification and problem-solving. In the goal-setting component, users set their own step goals weekly in gradual increments based on the system's suggestion. We added these fully automated functions to an extant system with the function of self-monitoring daily step count, BP, body weight, blood glucose, exercise, and diet. We conducted a single-arm before-and-after study of workers with high BP who were willing to increase their physical activity. After an educational group session, participants used only the self-monitoring function for 2 weeks (baseline) and all functions of DialBetes Step for 24 weeks. We evaluated changes in steps per day, self-reported frequencies of self-regulation and self-management behavior, self-efficacy, and biomedical characteristics (home BP, BMI, visceral fat area, and glucose and lipid parameters) around week 6 (P1) of using the new functions and at the end of the intervention (P2). Participants rated the usefulness of the system using a paper-based questionnaire., Results: We analyzed 30 participants (n=19, 63% male; mean age 52.9, SD 5.3 years); 1 (3%) participant dropped out of the intervention. The median percentage of step measurement was 97%. Compared with baseline (median 10,084 steps per day), steps per day significantly increased at P1 (median +1493 steps per day; P<.001), but the increase attenuated at P2 (median +1056 steps per day; P=.04). Frequencies of self-regulation and self-management behavior increased at P1 and P2. Goal-related self-efficacy tended to increase at P2 (median +5%; P=.05). Home BP substantially decreased only at P2. Of the other biomedical characteristics, BMI decreased significantly at P1 (P<.001) and P2 (P=.001), and high-density lipoprotein cholesterol increased significantly only at P1 (P<.001). DialBetes Step was rated as useful or moderately useful by 97% (28/29) of the participants., Conclusions: DialBetes Step intervention might be a feasible and useful way of increasing workers' step count for a short period and, consequently, improving their BP and BMI; self-efficacy-enhancing techniques of the system should be improved., (©Tomomi Shibuta, Kayo Waki, Kana Miyake, Ayumi Igarashi, Noriko Yamamoto-Mitani, Akiko Sankoda, Yoshinori Takeuchi, Masahiko Sumitani, Toshimasa Yamauchi, Masaomi Nangaku, Kazuhiko Ohe. Originally published in JMIR Cardio (https://cardio.jmir.org), 21.07.2023.)

Background: Smartphones are often equipped with inertial sensors that measure individuals' physical activity (PA). However, their role in remote monitoring of the patients' PAs in telemedicine needs to be adequately explored., Objective: This study aimed to explore the correlation between a participant's actual daily step counts and the daily step counts reported by their smartphone. In addition, we inquired about the usability of smartphones for collecting PA data., Methods: This prospective observational study was conducted among patients undergoing lower limb orthopedic surgery and a group of nonpatients as control. The data from the patients were collected from 2 weeks before surgery until 4 weeks after the surgery, whereas the data collection period for the nonpatients was 2 weeks. The participant's daily step count was recorded by PA trackers worn 24/7. In addition, a smartphone app collected the number of daily steps registered by the participants' smartphones. We compared the cross-correlation between the daily steps time series obtained from the smartphones and PA trackers in different groups of participants. We also used mixed modeling to estimate the total number of steps, using smartphone step counts and the characteristics of the patients as independent variables. The System Usability Scale was used to evaluate the participants' experience with the smartphone app and the PA tracker., Results: Overall, 1067 days of data were collected from 21 patients (n=11, 52% female patients) and 10 nonpatients (n=6, 60% female patients). The median cross-correlation coefficient on the same day was 0.70 (IQR 0.53-0.83). The correlation in the nonpatient group was slightly higher than that in the patient group (median 0.74, IQR 0.60-0.90 and median 0.69, IQR 0.52-0.81, respectively). The likelihood ratio tests on the models fitted by mixed effects methods demonstrated that the smartphone step count was positively correlated with the PA tracker's total number of steps (χ 2 1 =34.7, P<.001). In addition, the median usability score for the smartphone app was 78 (IQR 73-88) compared with median 73 (IQR 68-80) for the PA tracker., Conclusions: Considering the ubiquity, convenience, and practicality of smartphones, the high correlation between the smartphones and the total daily step count time series highlights the potential usefulness of smartphones in detecting changes in the number of steps in remote monitoring of a patient's PA., (©Arash Ghaffari, Rikke Emilie Kildahl Lauritsen, Michael Christensen, Trine Rolighed Thomsen, Harshit Mahapatra, Robert Heck, Søren Kold, Ole Rahbek. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 04.07.2023.)

While a higher level of physical activity (PA) is inversely associated with a higher breast cancer (BC) risk, the health benefits of daily steps on obesity-related BC biomarkers remain unclear. We aimed to understand the associations of changes in step counts with levels of five obesity-related BC biomarkers during a two-year follow-up. In total, 144 non-cancer women (47.96 ± 5.72) were observed on both 2019 and 2021. A structured questionnaire, daily steps and fasting blood samples were collected before (t0, 2019) and after (t1, 2021). Levels of biomarkers (IGF-binding proteins 3, adiponectin, soluble leptin receptor, C-reactive protein, and resistin) were assayed by ELISA. Participants were divided into persistent low steps, decreasing steps, increasing steps, and persistent high steps. Associations of categories on proposed biomarkers were estimated using linear regression models, with persistent low steps as reference. Associations between time-varying step counts with biomarkers were quantified using mixed linear models. Compared with persistent low steps, increasing steps is associated with a reduction in C-reactive protein level ( β =-0.74, 95%CI=-1.23--0.26, P -value = 2.98 × 10 -3 ). An inverse association between time-varying step counts with C-reactive protein level was identified, consistent across different obesity types and baseline step level categories. No association with daily step counts was observed for other proteins.

Measures of stepping volume and rate are common outputs from wearable devices, such as accelerometers. It has been proposed that biomedical technologies, including accelerometers and their algorithms, should undergo rigorous verification as well as analytical and clinical validation to demonstrate that they are fit for purpose. The aim of this study was to use the V3 framework to assess the analytical and clinical validity of a wrist-worn measurement system of stepping volume and rate, formed by the GENEActiv accelerometer and GENEAcount step counting algorithm. The analytical validity was assessed by measuring the level of agreement between the wrist-worn system and a thigh-worn system (activPAL), the reference measure. The clinical validity was assessed by establishing the prospective association between the changes in stepping volume and rate with changes in physical function (SPPB score). The agreement of the thigh-worn reference system and the wrist-worn system was excellent for total daily steps (CCC = 0.88, 95% CI 0.83-0.91) and moderate for walking steps and faster-paced walking steps (CCC = 0.61, 95% CI 0.53-0.68 and 0.55, 95% CI 0.46-0.64, respectively). A higher number of total steps and faster paced-walking steps was consistently associated with better physical function. After 24 months, an increase of 1000 daily faster-paced walking steps was associated with a clinically meaningful increase in physical function (0.53 SPPB score, 95% CI 0.32-0.74). We have validated a digital susceptibility/risk biomarker-pfSTEP-that identifies an associated risk of low physical function in community-dwelling older adults using a wrist-worn accelerometer and its accompanying open-source step counting algorithm.

Background: Regular participation in physical activity (PA) is encouraged for people with Cystic Fibrosis (CF). This study aimed to assess the effectiveness of an intervention using wearable technology, goal setting and text message feedback on PA and health outcomes in people with CF., Methods: This was a pilot randomised trial conducted at University Hospital Limerick. Participants were randomly assigned to the intervention (INT) or active comparator (AC). The 12-week intervention consisted of wearable technology (Fitbit Charge 2) which was remotely monitored, and participants set step count goals. Participants were sent a one-way text message once a week over 12 weeks to positively reinforce and encourage PA participation. The AC group received the wearable technology alone. Follow up was assessed at 24 weeks. Outcomes assessed were PA, aerobic capacity, lung function, sleep, quality of life and wellbeing., Results: Step count increased significantly for the INT group over 12 weeks when compared to the AC group (p=0.019). The INT group had a 28% week-to-week percentage change (Weeks 1-12), while the AC group reduced by 1%, p=0.023. Within group changes demonstrated that VO2 peak (ml/kg/min) significantly increased for the INT group at 12 weeks (24.4 ±7.65 to 26.13 ±7.79, p=0.003) but not at 24 weeks (24.45 ±7.05, p=0.776). There were no significant differences observed for VO2 peak (ml/kg/min) for the AC group. There was no significant effect on lung function, sleep, well-being, or quality of life for either group., Conclusions: A personalised PA intervention using wearable technology, goal setting and text message feedback increased PA and aerobic capacity in people with CF. Integration of this intervention into usual care may encourage regular PA participation for people with CF., Competing Interests: Declaration of Competing Interest The authors declares that there is no conflict of interest., (Copyright © 2022. Published by Elsevier B.V.)

Objectives: Daily step counts are an easy-to-understand indicator of physical activity; however, there is limited evidence regarding the optimal daily step count to prevent sarcopenia. This study examined the dose-response relationship between daily step count and the prevalence of sarcopenia and explored the optimal dose., Design: Cross-sectional study., Setting and Participants: The study included 7949 community-dwelling middle-aged and older adults (aged 45-74 years) from Japan., Measurements: Skeletal muscle mass (SMM) was assessed using bioelectrical impedance spectroscopy, and muscle strength was quantified through handgrip strength (HGS) measurement. Participants who exhibited both low HGS (men: <28 kg, women: <18 kg) and low SMM (lowest quartile in each sex-specific category) were defined as having sarcopenia. Daily step counts were measured for 10 days using a waist-mounted accelerometer. To examine the association between daily step count and sarcopenia, a multivariate logistic regression analysis was performed, adjusting for potential confounding factors such as age, sex, body mass index, smoking status, alcohol consumption, protein intake, and medical history. The odds ratios (ORs) and confidence intervals (CIs) were calculated based on the daily step counts categorized into quartiles (Q1-Q4). Finally, a restricted cubic spline curve was fitted to further investigate the dose-response relationship between daily step count and sarcopenia., Results: The prevalence of sarcopenia in the overall participants was 3.3 % (259/7949 participants), with a mean daily step count of 7292 ± 2966 steps. Expressed in quartiles, the mean daily step counts were 3873 ± 935 steps in Q1, 6025 ± 503 steps in Q2, 7942 ± 624 steps in Q3, and 11,328 ± 1912 steps in Q4. The prevalence of sarcopenia in each quartile of daily step count was 4.7 % (93/1987 participants) in Q1, 3.4 % (68/1987 participants) in Q2, 2.7 % (53/1988 participants) in Q3, and 2.3 % (45/1987 participants) in Q4. The ORs and 95 % CIs adjusted for covariates demonstrated a statistically significant inverse association between daily step count and sarcopenia prevalence (P for trend <0.01), as follows: Q1, reference; Q2, 0.79 (95 % CI: 0.55-1.11); Q3, 0.71 (95 % CI: 0.49-1.03); Q4, 0.61 (95 % CI: 0.41-0.90). The restricted cubic spline curve indicated that the ORs leveled off at approximately 8000 steps per day, and no statistically significant decrease in ORs was observed for daily step counts above this threshold., Conclusions: The study found a significant inverse association between daily step count and the prevalence of sarcopenia, with the association plateauing when the daily step count exceeded approximately 8000 steps. These findings suggest that 8000 steps per day may be the optimal dose to prevent sarcopenia. Further intervention and longitudinal studies are needed to validate the results., Competing Interests: Declaration of competing interest None declared., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Maintaining physical activity is an important clinical goal for people with Parkinson's disease (PwPD). We investigated the validity of two commercial activity trackers (ATs) to measure daily step counts. We compared a wrist- and a hip-worn commercial AT against the research-grade Dynaport Movemonitor (DAM) during 14 days of daily use. Criterion validity was assessed in 28 PwPD and 30 healthy controls (HCs) by a 2 × 3 ANOVA and intraclass correlation coefficients (ICC 2,1 ). The ability to measure daily step fluctuations compared to the DAM was studied by a 2 × 3 ANOVA and Kendall correlations. We also explored compliance and user-friendliness. Both the ATs and the DAM measured significantly fewer steps/day in PwPD compared to HCs ( p < 0.01). Step counts derived from the ATs showed good to excellent agreement with the DAM in both groups (ICC 2,1 > 0.83). Daily fluctuations were detected adequately by the ATs, showing moderate associations with DAM-rankings. While compliance was high overall, 22% of PwPD were disinclined to use the ATs after the study. Overall, we conclude that the ATs had sufficient agreement with the DAM for the purpose of promoting physical activity in mildly affected PwPD. However, further validation is needed before clinical use can be widely recommended.

Maladaptive exercise (i.e., exercise that compensates for binge eating or is used to avoid negative consequences of not exercising-like weight gain) is a common eating disorder (ED) behavior, yet, some individuals with EDs only engage in adaptive exercise. CBT for EDs targets reducing maladaptive exercise but does not address adaptive exercise. Thus, research is limited on how adaptive and maladaptive exercise are impacted during CBT for EDs. The current study examined how assessor-rated adaptive and maladaptive exercise and objectively measured physical activity changed over a 12-week CBT treatment among adults with transdiagnostic binge eating and restrictive eating that did and did not engage in maladaptive exercise at the start of treatment (n = 13 non-maladaptive exercise group, n = 17 maladaptive exercise group). The overall amount of adaptive and maladaptive exercise was measured via the Eating Disorder Examination Interview and objectively measured physical activity (e.g., step count, minutes of moderate-to-vigorous physical activity [MVPA]) was measured via a wrist-worn fitness tracker. Throughout treatment, the overall amount of adaptive exercise did not significantly change for both groups, but the overall amount of maladaptive exercise significantly decreased in the maladaptive exercise group. Step count did not significantly change for both groups, but minutes of MVPA significantly increased over treatment for the non-maladaptive exercise group. Increases in step count and minutes of MVPA were not associated with ED symptom changes in either group. These results enhance an understanding of exercise changes during transdiagnostic CBT-based ED treatment for individuals with varying baseline exercise profiles.Level of evidence: Level 1, randomized controlled trial., (© 2023. The Author(s).)

Background: The number of steps by an individual, has traditionally been assessed with a pedometer, but increasingly with an accelerometer. The ActiLife software (AL) is the most common way to process accelerometer data to steps, but it is not open source which could aid understanding of measurement errors. The aim of this study was to compare assessment of steps from the open-source algorithm part of the GGIR package and two closed algorithms, AL normal (n) and low frequency extension (lfe) algorithms to Yamax pedometer, as reference. Free-living in healthy adults with a wide range of activity level was studied., Results: A total 46 participants divided by activity level into a low-medium active group and a high active group, wore both an accelerometer and a pedometer for 14 days. In total 614 complete days were analyzed. A significant correlation between Yamax and all three algorithms was shown but all comparisons were significantly different with paired t-tests except for ALn vs Yamax. The mean bias shows that ALn slightly overestimated steps in the low-medium active group and slightly underestimated steps in high active group. The mean percentage error (MAPE) was 17% and 9% respectively. The ALlfe overestimated steps by approximately 6700/day in both groups and the MAPE was 88% in the low-medium active group and 43% in the high active group. The open-source algorithm underestimated steps with a systematic error related to activity level. The MAPE was 28% in the low-medium active group and 48% in the high active group., Conclusion: The open-source algorithm captures steps fairly well in low-medium active individuals when comparing with Yamax pedometer, but did not show satisfactory results in more active individuals, indicating that it must be modified before implemented in population research. The AL algorithm without the low frequency extension measures similar number of steps as Yamax in free-living and is a useful alternative before a valid open-source algorithm is available., (© 2023. The Author(s).)

Background: The number of elderly patients undergoing adult spinal deformity (ASD) surgery has increased with the advent of new techniques and more nuanced understanding of global malalignment as patients age. The relationship between inpatient physical activity after ASD surgery and postoperative complications in elderly patients has not been reported; thus, we sought to investigate this relationship., Methods: We performed a medical record review of 185 ASD patients older than 65 years (age: 71.5 ± 4.7; body mass index: 30.0 ± 6.1, American Society of Anesthesiologists: 2.7 ± 0.5, and levels fused: 10.5 ± 3.4). We derived the number of feet walked over the first 3 days after surgery from physical therapy documentation and evaluated for association with 90-day perioperative complications. Patients who sustained an incidental durotomy were excluded from the study., Results: The 185 patients were divided into groups based on whether they were among the 50th percentile for number of feet walked (62 ft). Walking less than 62 ft after ASD surgery was associated with higher incidence of postoperative complications (54.3%, P = 0.05), cardiac complications (34.8%, P = 0.03), pulmonary complications (21.7%, P = 0.01), and ileus (15.2%, P = 0.03). Patients who developed any postoperative complication (106 ± 172 vs 211 ± 279 ft, P = 0.001), ileus (26 ± 49 vs 174 ± 248 ft, P = 0.001), deep venous thrombosis (23 ± 30 vs 171 ± 247 ft, P = 0.001), and cardiac complications (58 ± 94 vs 192 ± 261 ft) walked less than patients who did not., Conclusion: Elderly patients who walked less than 62 ft in the first 3 days after ASD surgery have a higher rate of postoperative complications, specifically pulmonary and ileus compared with those patients who walked more. Steps walked after ASD surgery may be a helpful and practical addition to the surgeon's armamentarium for monitoring the recovery of their patients., Clinical Relevence: Monitoring the steps walked by patients after ASD surgery can be a practical and useful tool for surgeons to track and improve their patients' recovery., Competing Interests: Declaration of Conflicting Interests : The authors report no conflicts of interest in this work., (This manuscript is generously published free of charge by ISASS, the International Society for the Advancement of Spine Surgery. Copyright © 2023 ISASS. To see more or order reprints or permissions, see http://ijssurgery.com.)

Background: Knowledge on physical activity recovery after COVID-19 survival is limited. The AFTER (App-Facilitated Tele-Rehabilitation) program for COVID-19 survivors randomized participants, following hospital discharge, to either education and unstructured physical activity or a telerehabilitation program. Step count data were collected as a secondary outcome, and we found no significant differences in total step count trajectories between groups at 6 weeks. Further step count data were not analyzed., Objective: The purpose of this analysis was to examine step count trajectories and correlates among all participants (combined into a single group) across the 12-week study period., Methods: Linear mixed models with random effects were used to model daily steps over the number of study days. Models with 0, 1, and 2 inflection points were considered, and the final model was selected based on the highest log-likelihood value., Results: Participants included 44 adults (41 with available Fitbit [Fitbit LLC] data). Initially, step counts increased by an average of 930 (95% CI 547-1312; P<.001) steps per week, culminating in an average daily step count of 7658 (95% CI 6257-9059; P<.001) at the end of week 3. During the remaining 9 weeks of the study, weekly step counts increased by an average of 67 (95% CI -30 to 163; P<.001) steps per week, resulting in a final estimate of 8258 (95% CI 6933-9584; P<.001) steps., Conclusions: Participants showed a marked improvement in daily step counts during the first 3 weeks of the study, followed by more gradual improvement in the remaining 9 weeks. Physical activity data and step count recovery trajectories may be considered surrogates for physiological recovery, although further research is needed to examine this relationship., Trial Registration: ClinicalTrials.gov NCT04663945; https://tinyurl.com/2p969ced., (©Laura Churchill, Mary Morrow, Jacob J Capin, Sarah E Jolley, Kristine Hare, Samantha MaWhinney, Jennifer E Stevens-Lapsley, Kristine M Erlandson. Originally published in JMIR Rehabilitation and Assistive Technology (https://rehab.jmir.org), 20.03.2023.)

Background: Physical inactivity is a known risk factor for atrial fibrillation (AF). Wearable devices, such as smartwatches, present an opportunity to investigate the relation between daily step count and AF risk., Objective: The objective of this study was to investigate the association between daily step count and the predicted 5-year risk of AF., Methods: Participants from the electronic Framingham Heart Study used an Apple smartwatch. Individuals with diagnosed AF were excluded. Daily step count, watch wear time (hours and days), and self-reported physical activity data were collected. Individuals' 5-year risk of AF was estimated, using the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)-AF score. The relation between daily step count and predicted 5-year AF risk was examined via linear regression, adjusting for age, sex, and wear time. Secondary analyses examined effect modification by sex and obesity (BMI≥30 kg/m 2 ), as well as the relation between self-reported physical activity and predicted 5-year AF risk., Results: We examined 923 electronic Framingham Heart Study participants (age: mean 53, SD 9 years; female: n=563, 61%) who had a median daily step count of 7227 (IQR 5699-8970). Most participants (n=823, 89.2%) had a <2.5% CHARGE-AF risk. Every 1000 steps were associated with a 0.08% lower CHARGE-AF risk (P<.001). A stronger association was observed in men and individuals with obesity. In contrast, self-reported physical activity was not associated with CHARGE-AF risk., Conclusions: Higher daily step counts were associated with a lower predicted 5-year risk of AF, and this relation was stronger in men and participants with obesity. The utility of a wearable daily step counter for AF risk reduction merits further investigation., (©Ayelet Shapira-Daniels, Jelena Kornej, Nicole L Spartano, Xuzhi Wang, Yuankai Zhang, Chathurangi H Pathiravasan, Chunyu Liu, Ludovic Trinquart, Belinda Borrelli, David D McManus, Joanne M Murabito, Emelia J Benjamin, Honghuang Lin. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 06.03.2023.)

(1) Background: This study examined the cross-sectional association between metabolic syndrome (MetS) status classified into three groups and daily physical activity (PA; step count and active minutes) using a wearable device in Japanese office workers. (2) Methods: This secondary analysis used data from 179 participants in the intervention group of a randomized controlled trial for 3 months. Individuals who had received an annual health check-up and had MetS or were at a high risk of MetS based on Japanese guidelines were asked to use a wearable device and answer questionnaires regarding their daily life for the entire study period. Multilevel mixed-effects logistic regression models adjusted for covariates associated with MetS and PA were used to estimate associations. A sensitivity analysis investigated the associations between MetS status and PA level according to the day of the week. (3) Results: Compared to those with no MetS, those with MetS were not significantly associated with PA, while those with pre-MetS were inversely associated with PA [step count Model 3: OR = 0.60; 95% CI: 0.36, 0.99; active minutes Model 3: OR = 0.62; 95% CI: 0.40, 0.96]. In the sensitivity analysis, day of the week was an effect modifier for both PA ( p < 0.001). (4) Conclusions: Compared to those with no MetS, those with pre-MetS, but not MetS, showed significantly lower odds of reaching their daily recommended PA level. Our findings suggest that the day of the week could be a modifier for the association between MetS and PA. Further research with longer study periods and larger sample sizes are needed to confirm our results.

Background: Commercial activity trackers are increasingly used in research and compared with research-based accelerometers are often less intrusive, cheaper, with improved storage and battery capacity, although typically less validated. The present study aimed to determine the validity of Oura Ring step-count and energy expenditure (EE) in both laboratory and free-living., Methods: Oura Ring EE was compared against indirect calorimetry in the laboratory, followed by a 14-day free-living study with 32 participants wearing an Oura Ring and reference monitors (three accelerometers positioned at hip, thigh, and wrist, and pedometer) to evaluate Oura EE variables and step count., Results: Strong correlations were shown for Oura versus indirect calorimetry in the laboratory (r = 0.93), and versus reference monitors for all variables in free-living (r ≥ 0.76). Significant (p < 0.05) mean differences for Oura versus reference methods were found for laboratory measured sitting (- 0.12 ± 0.28 MET), standing (- 0.27 ± 0.33 MET), fast walk (- 0.82 ± 1.92 MET) and very fast run (- 3.49 ± 3.94 MET), and for free-living step-count (2124 ± 4256 steps) and EE variables (MET: - 0.34-0.26; TEE: 362-494 kcal; AEE: - 487-259 kcal). In the laboratory, Oura tended to underestimate EE with increasing discrepancy as intensity increased. The combined activities and slow running in the laboratory, and all MET placements, TEE hip and wrist, and step count in free-living had acceptable measurement errors (< 10% MAPE), whereas the remaining free-living variables showed close to (≤13.2%) acceptable limits., Conclusion: This is the first study investigating the validity of Oura Ring EE against gold standard methods. Oura successfully identified major changes between activities and/or intensities but was less responsive to detailed deviations within activities. In free-living, Oura step-count and EE variables tightly correlated with reference monitors, though with systemic over- or underestimations indicating somewhat low intra-individual validity of the ring versus the reference monitors. However, the correlations between the devices were high, suggesting that the Oura can detect differences at group-level for active and total energy expenditure, as well as step count., (© 2023. The Author(s).)

Commercial smartwatches could be useful for step counting and monitoring ambulatory activity. However, in Parkinson's disease (PD) patients, an altered gait, pharmacological condition, and symptoms lateralization may affect their accuracy and potential usefulness in research and clinical routine. Steps were counted during a 6 min walk in 47 patients with PD and 47 healthy subjects (HS) wearing a Garmin Vivosmart 4 (GV4) on each wrist. Manual step counting was used as a reference. An inertial sensor (BTS G-Walk), placed on the lower back, was used to compute spatial-temporal gait parameters. Intraclass correlation coefficient (ICC) and mean absolute percentage error (MAPE) were used for accuracy evaluation and the Spearman test was used to assess the correlations between variables. The GV4 overestimated steps in PD patients with only a poor-to-moderate agreement. The OFF pharmacological state and wearing the device on the most-affected body side led to an unacceptable accuracy. The GV4 showed an excellent agreement and MAPE in HS at a self-selected speed, but an unacceptable performance at a slow speed. In PD patients, MAPE was not associated with gait parameters and clinical variables. The accuracy of commercial smartwatches for monitoring step counting might be reduced in PD patients and further influenced by the pharmacological condition and placement of the device.

Background: This paper examined whether the criterion validity of step count (SC), energy expenditure (EE), and heart rate (HR) varied across studies depending on the average age, body mass index (BMI), and predominant gender of participants., Methods: Data from 1536 studies examining the validity of various wearable devices were used. Separate multilevel regression models examined the associations among age, gender, and BMI with device criterion validity assessed using mean absolute percent error (MAPE) at the study level., Results: MAPE values were reported in 970 studies for SC, 328 for EE, and 238 for HR, respectively. There were several significant differences in MAPE between age, gender, and BMI categories for SC, EE, and HR. SC MAPE was significantly different for older adults compared with adults. Compared with studies among normal-weight populations, MAPE was greater among studies with overweight samples for SC, HR, and EE. Comparing studies with more women than men, MAPE was significantly greater for EE and HR., Conclusions: There are important differences in the criterion validity of commercial wearable devices across studies of varying ages, BMIs, and genders. Few studies have examined differences in error between different age groups, particularly for EE and HR.

Introduction: This review synthesized evidence from prospective cohort studies on the association of device-measured physical activity and sedentary behavior with cardiovascular disease and all-cause mortality among adults., Methods: Five databases were searched from 2000 through April 29, 2020. Study quality was appraised using the NIH Quality Assessment Tool. Pooled hazard ratio and 95% CI were obtained from random-effects meta-analyses. Subgroup analyses by age and sex were conducted for studies on all-cause mortality., Results: Of 29 articles included in the systematic review, 5 studies on cardiovascular disease mortality and 15 studies on all-cause mortality were included in meta-analyses. Comparing the highest with the lowest exposure categories, the pooled hazard ratios (95% CIs) for cardiovascular disease mortality were 0.29 (CI=0.18, 0.47) for total physical activity, 0.37 (CI=0.25, 0.55) for moderate-to-vigorous physical activity, 0.62 (0.41-0.93) for light physical activity, and 1.89 (CI=1.09, 3.29) for sedentary behavior. The pooled hazard ratios (95% CIs) for all-cause mortality were 0.42 (CI=0.34, 0.53) for total physical activity, 0.43 (CI=0.35, 0.53) for moderate-to-vigorous physical activity, 0.58 (CI=0.43, 0.80) for light physical activity, and 1.58 (CI=1.19, 2.09) for sedentary behavior. The pooled hazard ratio (95% CI) for all-cause mortality was 0.35 (CI=0.29, 0.42) for steps per day, but the studies available for analysis were conducted in older adults. The results of subgroup analyses were consistent with the main results., Discussion: Rapidly accumulating evidence suggests that more physical activity and less sedentary behavior are associated with a lower risk of cardiovascular disease and all-cause mortality. Similar beneficial relationships were found for step counts and all-cause mortality among older adults. Future studies employing standardized research methodologies and up-to-date data processing approaches are warranted to recommend specific amounts of physical activity and limits to sedentary behavior., (© 2022 The Author(s).)

Introduction/purpose: The amount of stepping activity during rehabilitation post-stroke can predict walking outcomes, although the most accurate methods to evaluate stepping activity are uncertain with conflicting findings on available stepping monitors during walking assessments. Rehabilitation sessions also include non-stepping activities and the ability of activity monitors to differentiate these activities from stepping is unclear. The objective of this study was to examine the accuracy of different activity monitors worn by individuals post-stroke with variable walking speeds during clinical physical therapy (PT) and research interventions focused on walking., Methods: In Part I, 28 participants post-stroke wore a StepWatch, ActiGraph with and without a Low Frequency Extension (LFE) filter, and Fitbit on paretic and non-paretic distal shanks at or above the ankle during clinical PT or research interventions with steps simultaneously hand counted. Mean absolute percent errors were compared between limbs and tasks performed. In Part II, 12 healthy adults completed 8 walking and 9 non-walking tasks observed during clinical PT or research. Data were descriptively analyzed and used to assist interpretation of Part I results., Results: Part I results indicate most devices did not demonstrate an optimal limb configuration during research sessions focused on walking, with larger errors during clinical PT on the non-paretic limb. Using the limb that minimized errors for each device, the StepWatch had smaller errors than the ActiGraph and Fitbit (p<0.01), particularly in those who walked < 0.8 m/s. Conversely, errors from the ActiGraph-LFE demonstrated inconsistent differences in step counts between Fitbit and ActiGraph. Part II results indicate that errors observed during different stepping and non-stepping activities were often device-specific, with non-stepping tasks frequently detected as stepping., Conclusions: The StepWatch and ActiGraph-LFE had smaller errors than the Fitbit or ActiGraph, with greater errors in those walking at slower speeds. Inclusion of non-stepping activities affected step counts and should be considered when measuring stepping activity in individuals post-stroke to predict locomotor outcomes following rehabilitation., Competing Interests: Conflict of Interest: No conflicts of interest are declared by any of the authors. The results of this study do no constitute endorsement by ACSM. The results of this study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation.

Background: Physical activity (PA) is reduced in persons with multiple sclerosis (MS), though it is known to aid in symptom and fatigue management. Methods for measuring PA are diverse and the impact of this heterogeneity on study outcomes is unclear. We aimed to clarify this impact by comparing common methods for deriving PA metrics in MS populations., Methods: First, a rapid review of existing literature identified methods for calculating PA in studies which used the Actigraph GT3X in populations with MS. We then compared methods in a prospective study on 42 persons with MS [EDSS 4.5 (3.5-6)] during a voluntary course of inpatient neurorehabilitation. Mixed-effects linear regression identified methodological factors which influenced PA measurements. Non-parametric hypothesis tests, correlations, and agreement statistics assessed overall and pairwise differences between methods., Results: In the rapid review, searches identified 421 unique records. Sixty-nine records representing 51 eligible studies exhibited substantial heterogeneity in methodology and reporting practices. In a subsequent comparative study, multiple methods for deriving six PA metrics (step count, activity counts, total time in PA, sedentary time, time in light PA, time in moderate to vigorous PA), were identified and directly compared. All metrics were sensitive to methodological factors such as the selected preprocessing filter, data source (vertical vs. vector magnitude counts), and cutpoint. Additionally, sedentary time was sensitive to wear time definitions. Pairwise correlation and agreement between methods varied from weak (minimum correlation: 0.15, minimum agreement: 0.03) to perfect (maximum correlation: 1.00, maximum agreement: 1.00). Methodological factors biased both point estimates of PA and correlations between PA and clinical assessments., Conclusions: Methodological heterogeneity of existing literature is high, and this heterogeneity may confound studies which use the Actigraph GT3X. Step counts were highly sensitive to the filter used to process raw accelerometer data. Sedentary time was particularly sensitive to methodology, and we recommend using total time in PA instead. Several, though not all, methods for deriving light PA and moderate to vigorous PA yielded nearly identical results. PA metrics based on vertical axis counts tended to outperform those based on vector magnitude counts. Additional research is needed to establish the relative validity of existing methods., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2022 Polhemus, Haag, Sieber, Sylvester, Kool, Gonzenbach and von Wyl.)

Background: Preoperative telemonitoring of vital signs, physical activity, and well-being might be able to optimize prehabilitation of the patient's physical and mental condition prior to surgery, support setting alarms during in-hospital monitoring, and allow personalization of the postoperative recovery process., Objective: The primary aim of this study was to evaluate when and how long patients awaiting major abdominal surgery should be monitored to get reliable preoperative individual baseline values of heart rate (HR), daily step count, and patient-reported outcome measures (PROMs). The secondary aim was to describe the perioperative course of these measurements at home., Methods: In this observational single-center cohort study, patients used a wearable sensor during waking hours and reported PROMs (pain, anxiety, fatigue, nausea) on a tablet twice a day. Intraclass correlation coefficients (ICCs) were used to evaluate the reliability of mean values on 2 specific preoperative days (the first day of telemonitoring and the day before hospital admission) and randomly selected preoperative periods compared to individual reference values. Mean values of HR, step count, and PROMs per day were visualized in a boxplot from 14 days before hospital admission until 30 days after surgery., Results: A total of 16 patients were included in the data analyses. The ICCs of mean values on the first day of telemonitoring were 0.91 for HR, 0.71 for steps, and at least 0.86 for PROMs. The day before hospital admission showed reliability coefficients of 0.76 for HR, 0.71 for steps, and 0.92-0.99 for PROMs. ICC values of randomly selected measurement periods increased over the continuous period of time from 0.68 to 0.99 for HR and daily step counts. A lower bound of the 95% CI of at least 0.75 was determined after 3 days of measurements. The ICCs of randomly selected PROM measurements were 0.89-0.94. Visualization of mean values per day mainly showed variable preoperative daily step counts (median 2409, IQR 1735-4661 steps/day) and lower postoperative daily step counts (median 884, IQR 474-1605 steps/day). In addition, pain was visually reduced until 30 days after surgery at home., Conclusions: In this prospective pilot study, for patients awaiting major abdominal surgery, baseline values for HR and daily step count could be measured reliably by a wearable sensor worn for at least 3 consecutive days and PROMs during any preoperative day. No clear conclusions were drawn from the description of the perioperative course by showing mean values of HR, daily step count, and PROM values over time in the home situation., (©Marjolein E Haveman, Rianne van Melzen, Mostafa El Moumni, Richte C L Schuurmann, Hermie J Hermens, Monique Tabak, Jean-Paul P M de Vries. Originally published in JMIR Perioperative Medicine (http://periop.jmir.org), 28.11.2022.)