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Background: Physical activity has been shown to have a positive impact on cystic fibrosis (CF) symptoms and slows decline in lung function. Additionally, moderate-intensity activities have been shown to improve sputum expectoration and oxygen saturation in children with CF, improving symptoms [1]. This study assessed whether using fitness trackers and providing a daily step goal would increase physical activity in hospitalized children with CF. Method(s): This pre-post pilot study included participants aged 6 to 21 who were admitted to the hospital for a pulmonary exacerbation of CF between October 2020 and November 2021. Garmin vivosmart 4 wrist-based activity trackers were issued, and baseline datawere tracked and analyzed for the first 2 study days. Pre-goal number of steps was defined as average number of steps taken on those 2 days. On study day 3, a step goal and menu of activities designed to increase physical activity were shared with the participants. Steps after goal settingwere defined as average number of steps taken on study day 3 and beyond while hospitalized, excluding day of discharge. Data collected from the medical record and the activity tracker web-based profile included daily oxygen requirement, daily step count, sleep duration, overnight pulse oximetry levels, resting heart rate, calories expended, and intensity minutes. The primary outcome of change in daily steps and attainment of step goals was analyzed using descriptive statistical testing, means, and standard deviations. Outpatient data were collected for 3 months to observe adherence to goals after discharge. Result(s): Eight participants aged 6 to 18 completed the study. Hospital length of stay ranged from 4 to 14 days. Participants took an average of 1508 +/- 1078 steps before goal setting, which increased to an average of 3704 +/- 1555 steps after the intervention. Step goals were met 56% of the time, although these data were highly variable. During the first week after hospital discharge, participants took an average of 6303 +/- 1786 steps per day (Figure 1).(Figure Presented) Figure 1. During the intervention, patients met their step goal 56% of the time, although this was highly variable. Two patients met their goal 100% of the time (9- year-old boy, 7-year-old girl), two met it 0% of the time (18-year-old boy, 17-year-old girl), one met it 44% of the time (6-year-old boy), and the remaining three met it 67% of the time (10-year-old girl, 17-year-old girl, 14-year-old boy). Conclusion(s): This intervention shows promise, with daily number of steps doubling from baseline during the intervention period. There was great variability among participants, suggesting that the approach helps some more than others. Enrollment was initially planned for 20 patients, but the SARS-CoV-2 pandemic and changes to CF therapy reduced hospitalizations during the study period. Outpatient data were analyzed for only the first week after discharge because of poor adherence to wearing the device. Although our results showa positive impact, further research is needed to determine the effect such an intervention would have on a larger scale. Future directions of research include determining potential clinical benefit from increased activity during hospitalization and prolonged follow-up to assess long-term benefits of intervention.Copyright © 2022, European Cystic Fibrosis Society. All rights reserved
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BACKGROUND: Pulmonary rehabilitation (PR) is the standard of care for chronic obstructive pulmonary disease (COPD) management. However, significant barriers limit access and adherence to PR and alternatives are needed. The purpose of this randomized controlled trial is to test the efficacy of a web-based, pedometer-mediated intervention to increase physical activity (PA) for persons with COPD who decline PR or meet U.S. guidelines for referral to PR but have not participated (CAPRI-1). In addition, we will test whether the intervention maintains PA following PR in an exploratory aim (CAPRI-2). METHODS: Participants with COPD (N = 120) will be recruited and randomized 1:1 to a 12-week web-based, pedometer-mediated intervention or usual care (UC) (CAPRI-1). The intervention provides: 1) objective monitoring of walking and iterative feedback, 2) individualized step-count goals, 3) motivational messages and educational content, and 4) an online community. The primary outcome is change in daily step count from baseline to 12 weeks. Secondary outcomes include: (a) exercise capacity; (b) self-reported PA; (c) PA intensity; (d) exercise self-regulatory efficacy, (e) health-related quality of life, (f) dyspnea, (g) depression symptoms, and (h) healthcare utilization. CAPRI-2 will test whether participants (N = 96) assigned to the intervention following PR completion show greater maintenance of daily step count compared to UC at 3, 6, 9, and 12 months. DISCUSSION: If the intervention is efficacious, it may be an alternative for those who cannot attend PR or a maintenance program following completion of conventional PR. We also present adaptations made to the protocol in response to the COVID-19 pandemic.
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COVID-19 , Pulmonary Disease, Chronic Obstructive , Humans , Quality of Life , Pandemics , Exercise , Randomized Controlled Trials as TopicABSTRACT
The number of people with diabetes globally, is rising at an alarming rate. South Asia is one of the hot spots of the diabetes epidemic. In India alone, there are over 74 million people with diabetes today. Unfortunately, 70% of the doctors in India practice in urban areas while 70% of India's population lives in rural areas. This mismatch between the availability of health care professionals and the rapid spread of diabetes in rural areas, provides an opportunity to use technology to deliver the diabetes care to remote rural areas. The first part of this presentation will talk about a model of successful delivery of diabetes health care in rural India. The Chunampet Rural Diabetes Program was carried out in a group of 42 villages in Kancheepuram District in Tamilnadu. Using a Mobile van, a population of 27,014 individuals (86.5% of the adult population) were screened for diabetes. All those detected with diabetes were offered a follow up care at a rural diabetes centre which was set up during the project. The results were very impressive and led to good improvement in A1c levels using low cost generic drugs. The second use of technology was during the COVID - 19 pandemic and the lock down which was enforced in India and many other countries. Thankfully, Telemedicine was also legalized in India at that time. Using technology, a system was created whereby the doctor and the patient stayed at home but blood tests were arranged at home for the patient.With the results, teleconsultation was done by doctors using the Electronic Medical Records which were made available on their mobile phones. Thus, despite the lockdown, patients managed to get their tests and diabetes consultations done remotely. The third use of technology is through our network of diabetes clinics across India. Even at centres where there was no ophthalmologist, retinal photographs were obtained using a lowcost retinal camera and were uploaded for centralized diabetic retinopathy grading unit where the images were read by trained retina specialists. The eye reports were sent back to the peripheral clinics in real time. Over one year period, 25,316 individuals with diabetes could have their eyes screened for diabetic retinopathy. Only 11.4 % needed referral to an ophthalmologist for further management. Finally, the use of mobile Apps has revolutionized diabetes treatment. Recently, we have developed three diabetes related tools. 'DIA' - an AI powered chatbot to assist people through automated digital conversations, 'DIALA' - a patientfriendly mobile app and 'DIANA' - a healthcare application for precision diabetes care. The details of these three tools are briefly described below : DIA : The Conversational AI Virtual Assistant 'DIA' can interact in English with its unique conversational AI technology and intuitive interface, it has proved to be a useful solution for patients, providing complex dialogues, with quick response time and offers comprehensive solutions for patients with diabetes. DIA's uses range from scheduling appointments and reminders for visits, lab tests and teleconsultation, to addressing enquiries on available medicines, treatments, and facilities.During an emergency, health crisis or in pandemic situations, it connects with caregivers and patients to take proper action as per the seriousness of their conditions. Further, it shares notifications, updates patient engagement and special offers. In addition to this, DIA can assist patients through reminders on their medicine refill via WhatsApp or SMS notifications and even facilitate purchase and tracking of medicine orders. DIALA : 'DIALA' is a DIAbetes Lifestyle Assistant Mobile Application. This app helps deliver superior and positive patient outcomes with weight tracking, step counts, diet plan adjustment, prescription refilling, availing reports of tests done, glucose monitoring data, scheduling appointments and sends reminders. It can help to monitor one's health and manage diabetes effectively. It is currently available in Android. DIANA : An advanced machine learning tool DIANA (DIAbetes Novel subgroup Assessment) is used to classify individuals with newly detected type 2 diabetes into specific subgroups such as insulin deficient or insulin resistance forms. This tool also gives the estimates of the risk for developing diabetes complications like eye or kidney disease. This machine learning approach has been developed based on published real world clinical data and will help the clinician offer individualized care for people with diabetes. In conclusion, judicious use of technology can help to bridge the socioeconomic and geographical challenges in delivering diabetes health care in developing countries.
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Background Cardiac rehabilitation is accessed by only ~50% of eligible patients. Virtual options have become more important since Covid. The Our Hearts Our Minds (OHOM) programme used wearable technology (Fitbit) for virtual physical activity monitoring. Aim To examine whether a Fitbit smartwatch/dashboard component was an acceptable option to improve physical activity levels in the absence of supervised exercise classes. Methods Initial multidisciplinary assessments were conducted via telephone/video as per patient preference. Patients were offered a Fitbit, if they did not have their own smartwatch and to synchronise to a cloud based dashboard visible to the clinical team. Using behaviour change techniques, tailored physical activity advice was provided including personalised notifications pushed to the patient's Fitbit app. Patients also received coaching calls and virtual group education sessions. Average daily step count and active minutes (over a 7 day period) were calculated at the start and end of programme. Results 1066 referrals were received from 01/04/20 to 30/ 03/22, of which 1043 patients (98%) had an initial assessment. Of these, 407 wore a Fitbit device (33% provided by programme, 6% own Fitbit) and synchronised to OHOM Fitbit dashboard (39% uptake). 6% had their own non-Fitbit smartwatch. 55% declined Fitbit (5% didn't own a smartphone for app download or access the internet, 3% weren't interested in technology, 2% medical reasons, 2% didn't collect, 43% weren't interested in virtual monitoring). Physical activity outcomes pre and post programme are shown in table 1. Conclusion Fitbit (and other) smartwatches coupled with centralised monitoring provided a viable alternative to supervised exercise classes in approximately half of those attending cardiac rehabilitation with evidence of increased physical activity.
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Background Physical activity and dietary habit optimization in women with gestational diabetes mellitus (GDM) or such a history can improve both short-term [1,2] and long-term outcomes [3]. This requires strategies that are accessible, usable, and perceived as beneficial. Aim To examine uptake and engagement for the following interventions: (1) step and weight tracking through an online platform using a pedometer and weight scale, with delivery of weekly goals;(2) weekly telephone-based health coaching;and (3) a combination of these. We are assessing recruitment, completion of health coaching sessions and/or step count and weight data upload, and participant perspectives. Method Five-city pilot randomized controlled trial (Montreal, Halifax, Calgary, Winnipeg, Toronto;Canada). Women with GDM are recruited at 20-32 weeks' gestation. Data collection is through web-based questionnaire, electronic tracking of data upload, coaching session logs, chart review (gestational weight gain;blood pressure;A1C;glucose levels;offspring sex, weight, and gestational age), in-depth telephone interview (perspectives, breastfeeding status), and mailed in pedometers with concealed windows worn for 7 days (baseline and 37 weeks). Participants are randomized to one of the 3 interventions described or a control arm (resource website only). Results The trial started in August 2019 with COVID-related interruptions. By June 30, 2022, 192/225 mothers were recruited (recruitment ongoing): 27/192 (14%) withdrew, 13 are currently undergoing interventions, and 152 completed final questionnaires. An interim process analysis of the first 52 indicates that those randomized to step and weight tracking employ the pedometer and scale a mean 81.6% (SD 29.6%) and 69.0% (SD 32.0%) of the time, respectively. High proportions report step tracking (92.3%, n = 24/26) and health coach conversations (87.5% n = 21/24) as useful, with weight tracking endorsed by over half (61.5%, n = 16/26). Conclusion The findings will inform a larger scale clinical trial in terms of impacts on gestational weight gain and appropriate for size offspring status.Copyright © 2023 Elsevier B.V.
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Introduction: The long-term impact of severe COVID-19 on the physical activity (PA) of patients is unknown. Method(s): Forty-nine patients (63% male, 47% ICU stay, mean+/-SD 61+/-10 y, BMI 29.6+/-4.5 kg/m2) were assessed 1 year after hospital discharge for severe COVID-19. PA was objectively measured with the Dynaport Movemonitor for 1 week. Pulmonary function (FEV1, diffusion capacity (DL,co)), physical functioning (6 minute walking distance (6MWD), quadriceps force (QF)) and symptoms of dyspnea were assessed. Pearson correlations were used, to explore the association between PA (mean step count) and these outcomes. Low PA levels was defined as a mean step count of <7500 steps/day. Result(s): Patients had a mean daily total walking time of mean+/-SD 80+/-41 min/day and a mean movement intensity of 1.99+/-0.35 m/s2. They performed 6817+/-3567 steps/day. One year after discharge 65% of patients retained low PA levels. PA was not different between patients who had an ICU stay and those who did not (6667+/-4650 steps/day vs. 6943+/-2408 steps/day, p=0.80;71% vs 64% with low PA levels, p=0.29). 20% of patients reported mMRC dyspnea scale scores >1;90% of them had low PA levels. PA was associated with 6MWD, but not with QF, FEV1 and DL,co (figure 1). Conclusion(s): A significant proportion of patients was inactive 1 year after severe COVID-19 with no difference between patients with or without ICU stay. PA was positively associated with exercise capacity.
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Background: Physical inactivity and sedentary behaviour is associated with worse clinical and inflammatory outcomes and impaired quality of life in people with severe asthma (pwSA) (Cordova-Rivera et al. JACI:IP 2018;6(3):814-22). Since March 2020, national lockdowns have been periodically implemented in the UK to reduce the transmission of COVID-19, however, the impact of these restrictions on physical activity in pwSA has yet to be evaluated. Aim(s): To compare physical activity levels prior to and during COVID-19 lockdown in pwSA. Method(s): A preliminary retrospective analysis of physical activity (step count objectively assessed via an in-built smartphone pedometer (Reilly et al. J Asthma 2021:1-9)) between March-June 2019 (usual daily living) versus March-June 2020 (first UK lockdown) in adults attending a specialist asthma service Results: Twelve adults with severe asthma receiving biological therapies (male: n = 4) (age: 52 +/- 16;FEV % predicted: 64 +/- 16) were recruited. A significant and clinically meaningful reduction in daily step count was observed between 2019 and 2020 for all months: March (-25%) (P=0.02);April (-40%) (P=0.02);May (-33%) (P = 0.04);June (-38%) (P = 0.001). Total absolute reduction in daily step-count: 4627 +/- 1833 versus 3054 +/- 1967 (-34%) (P<0.001). Conclusion(s): COVID-19 restrictions reduced step-based physical activity by approximately one-third in pwSA. These findings underline the importance of monitoring and promoting physical activity during routine asthma review given the potential adverse impact on health and disease-related outcomes.
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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.
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Accelerometry , Energy Metabolism , Humans , Accelerometry/methods , Actigraphy , Fitness Trackers , WristABSTRACT
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.
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The COVID-19 outbreak resulted in the shutdown of athletic training facilities. Although the effects of these restrictions on daily activity and sleep patterns have been widely analyzed, the employed tools often lacked accuracy, and were based on subjective measures. This study assessed the effects of home confinement on objective physical activity (PA), physiological and sleep parameters in active individuals. Sixteen male elite fitness coaches (age: 29±3 years; height: 183±6 cm; body mass: 82±5 kg, body mass index: 24.7±1.8 kg/m2) participated in this retrospective study. One-way analysis of variance was conducted to analyze selected PA, physiological and sleep parameters collected by smartwatch (Garmin Fenix 6 pro, USA) data during four consecutive months [i.e., pre-confinement, 1st and 2nd months of confinement, and post-confinement, year 2020]. Ramadan intermittent fasting (RIF) month occurred during the 2nd month of confinement. Compared to pre-confinement, significant changes were registered for almost all parameters during the 1st and/or the 2nd month of confinements (p<0.001), with (i) higher values for resting heart rate, sleep latency, and total, light and rapid eye movements sleep times (% change=7-523 %), and (ii) lower values for PA parameters, calories/day spent, average and highest respiratory rates, and deep sleep time during the home confinement period (% change=5-36 %). During the post-confinement month, all parameters regained pre-confinement values. In conclusion, home confinement-induced detraining negatively influenced the objective measurements of cardiorespiratory and sleep parameters among fitness coaches with a deeper effect during the 2nd month of home confinement, possibly due to the effect of RIF.
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Background: When the WHO declared COVID-19 a global pandemic on March 11, 2020, stay-at-home orders and business closures were imposed to contain viral spread. Accumulating evidence suggests that these societal disruptions caused abrupt changes in important health behaviors such as physical activity, but most work to date has used self-report measures. Longitudinal studies collecting objective measures of activity and sleep behavior and heart rate before and after the pandemic could shed light on potential health implications of the ongoing pandemic and associated social distancing measures. Objective: To determine whether significant within-person changes in objective heart rate, sleep, and physical activity occurred from pre- to post-COVID pandemic. Methods: Adult smartphone users were recruited from an online registry. 22 participants (M 47 years old, range 20-72;76% female;91% White;55% with at least one chronic medical condition) provided access to their Fitbit data and had at least one week of pre-COVID (March 11, 2019 to March 10, 2020;M = 256 days of data, range 25-366 days) and post-COVID (March 11, 2020 to December 31, 2020;M = 231 days of data, range 107-294 days) Fitbit data. Results: Paired t-tests revealed significant decreases in mean heart rate (77 to 75 bpm;t(18) = 2.91, p < .01), step counts (7946 to 6969 steps/day;t(21) = 2.72, p = .01), and total active time (185 to 165 minutes/day;t(21) = 3.02, p < .001) and significant increases in total sedentary time (766 to 781 minutes/day;t(21) =-2.88, p < .01) from pre- to post-COVID but no significant changes in Fitbit-assessed sleep time, latency, or efficiency. Conclusions: These prospective sensor data captured before and after the pandemic contribute to our understanding of how COVID-19 has affected physical activity and heart rate. Findings suggest that adults became less physically active and more sedentary after the pandemic relative to the year prior to COVID-19 but that sleep behaviors remained relatively stable. Although this is a small nonrepresentative sample, these longitudinal objective behavioral data corroborate larger self-report studies. Future analyses will examine trajectories of activity change over the course of the pandemic and characteristics of participants who maintained or increased activity levels despite social distancing mandates.
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Objective: The COVID-19 pandemic has necessitated public health measures including school closures and stay-at-home orders. These measures have resulted in decreased physical activity and walking activity (WA). Children with cerebral palsy (CP) have decreased WA compared to typically developing youth. Our objective was to determine how isolation orders have affected WA in children with CP. We hypothesized that children with CP would exhibit decreased WA during the pandemic compared to pre-pandemic. Design: This was an IRB-approved retrospective cohort study. Method: Inclusion criteria were a diagnosis of CP, Gross Motor Function Classification System (GMFCS) levels I-III, and WA monitoring using a StepWatch™ device during the pandemic (3/13/2020 to 10/5/2020) and within two years before the pandemic. Forty-three youth (age 12.0 [4], GMFCS I [7], II [17], III [19]) met the inclusion criteria. WA was compared using paired t-tests before versus during the pandemic across all participants and each GMFCS level. Two case studies were included to demonstrate the effects of remote and hybrid school on WA. The first case is a 15-year-old girl (GMFCS III) who had orthopaedic surgery in December 2018 and underwent WA monitoring in June 2019 and June 2020. The second case is a 14-year-old girl who had no surgical history and underwent WA monitoring in January 2021. Results: Average time between pre-pandemic and pandemic WA monitoring was 9.2 (5.3) months. The overall study group (p < 0.01) and the GMFCS III group (p < 0.05) had a significant reduction in walking activity during the pandemic. The GMFCS I and II groups demonstrated a trend to decreasing WA (p < 0.2), with a majority of children in each group having decreased WA. For the first case, during remote school, a child classified GMFCS III walked less than the non-pandemic GMFCS III average and her most active days changed from weekdays to weekends. For the second case, during hybrid school, the child's WA was drastically higher on days with in-person instruction compared to remote. Conclusion: Children with CP were less active, as evaluated by step count, during the pandemic. Additionally, our case studies demonstrate that in-person school days drive WA. It is important to understand the effects of school closures on activity behaviours and prioritize future work to mitigate negative health effects as we emerge from this crisis.
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Purpose: Current walking interventions for people with knee osteoarthritis (OA) focus on either reducing knee joint loading or on increasing physical activity. There is a need for interventions that could address both quality and quantity of walking for people with knee OA. The goal of this randomized controlled trial (clinicaltrials.gov # NCT03064139) was to determine the feasibility of a mindful walking intervention to improve quality and quantity of walking in people with knee OA. Methods: Individuals with symptomatic knee OA were recruited from the community using advertisements. Study criteria are shown in Table 1. [Formula presented] During enrollment, the more symptomatic knee, or a knee selected at random in case of equal symptoms, was designated as the study knee. After the baseline visit, participants were randomized to either a mindful walking group (MWG) or an attention-matched self-management group (SMG). Participants in both groups received 11 intervention sessions delivered over a 6-month period (4 in 1 st month, 2 each in 2nd and 3rd months, 1 each in 4th, 5th, and 6th months). Interventions were delivered via in-person groups (4-10 in each group) and each session was 1.5-3 hours in duration. For MWG, a certified instructor provided training in mindful walking that includes whole-body movement retraining and mindful body-awareness skill building. Biomechanical elements include: shorter stride length, higher cadence, greater toe-in, and more aligned posture. Participants were coached to progressively increase their mindful walking activity each week. Mindfulness elements include mindful body-awareness skills to increase sensitivity and awareness of deviations from the taught techniques. The approach is based on “ChiWalking®” so called because the movement approaches are drawn in part from T’ai Chi. For SMG, a researcher delivered a curriculum consisting of education and self-management techniques (e.g., importance of physical activity and exercise, nutrition, weight-management, etc.). This information was also provided to MWG in a condensed form. Gait analyses and physical performance tests were completed at baseline and 6-months. Physical activity was assessed using a commercial wrist-worn activity monitor (Charge 3, Fitbit Inc, San Francisco, CA). Participant-reported outcomes (PROs) were completed at baseline and every 3-months. Participants were remotely followed for an additional 6-months after the end of the intervention. Given the feasibility nature of the study, primary outcomes included recruitment, adherence, retention and number of adverse events. Secondary outcomes included peak external knee adduction moment [KAM], daily step count, Knee injury and osteoarthritis outcome score (KOOS) Pain, Five Facet Mindfulness Questionnaire (FFMQ), Arthritis Self-Efficacy Scale (ASES), 30-second chair stand test (30STS), 40-meter fast paced walk test (40FPW), and Stair Climbing Test (SCT). Analyses were conducted on intention-to-treat basis with all randomized participants included and missing values were not imputed. Results: Participants were recruited between March 2019 and January 2020. During this period, ∼450 individuals completed pre-screening questionnaires (∼41 per month), 66 completed in-person screening visits, 47 were enrolled, and 44 were randomized (Table 2). Interventions for 19 participants were interrupted, delayed for 3-months, and then transitioned to virtual format due to the COVID-19 pandemic. While the original recruitment goal was 62, the trial was halted earlier due to COVID-19. [Formula presented] Attendance is shown in Table 3. On average, MWG group attended 63% of the sessions vs. 70% in the SMG group. Among those who attended at least 1 session, MWG group attended 69% vs. 77% for SMG. Among those who attended at least 3 sessions, MWG group attended 75% vs. 84% for SMG. Post-intervention, 65% (n=15) and 87% (n=20) of MWG completed the in-person visits and PROs, respectively. In SMG, 81% (n=17) completed in-person visits and PROs. At 12-months, 91% (n=21) and 71% (n 15) completed the PROs for MWG and SMG, respectively. [Formula presented] Participant feedback at 6- and 12-months showed that the intervention was acceptable (Table 4). There were no serious adverse events related to the intervention in either group. Within group and between group differences for secondary outcomes are shown in Table 5. [Formula presented] [Formula presented] Conclusions: Our benchmarks were recruitment over 1.5 years, attendance of 75% in MWG group, and retention of 80% of participants at 6-months. While all of these benchmarks were negatively impacted by COVID-19, the recruitment rates over the period studied, adherence in those who attended at least 3 sessions, and retention for some secondary outcomes were acceptable. Participants in both groups found the interventions helpful, enjoyable, and rated it highly. At 12-month follow-up, MWG participants continued to practice mindful walking 1-2 days a week. Between group differences for secondary outcomes were small. Given the feasibility nature of the study, conclusions regarding efficacy cannot be made and larger trial would be needed. Our results show that our methods are appropriate for conducting such a larger trial.
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Purpose of Study Cystic Fibrosis (CF) is a progressive, genetic disease that affects over 30,000 individuals across the nation and results in decreased functionality of the lungs. Physical activity has a positive impact on the symptoms of CF and works to slow the decline in lung function. Additionally, activities with moderate intensity have been shown to improve sputum expectoration and oxygen saturation in children with CF. This study assessed whether using fitness trackers and providing a daily step goal would increase physical activity in hospitalized children and young adults with CF. Methods Used This prospective study included participants 6- 21 years of age who were admitted to the hospital for a pulmonary exacerbation of CF between October 2020-May 2021. Study enrollment occurred no more than 48 hours after hospital admission. Garmin vivosmart® 4 wrist-based activity trackers were issued and baseline data were tracked and analyzed for the first 2 study days. Pre-goal steps were defined as the average of steps taken on those 2 days. On study day 3, a step goal and menu of activities designed to increase physical activity were shared with the participant. Steps after goal setting were defined as the average of steps taken on study day 3 and beyond, excluding day of discharge. Data were collected from the electronic medical record and the activity tracker web-based profile and included the following: daily oxygen requirement, daily step count, sleep duration, overnight pulse oximetry levels, resting heart rate, calories expended, and intensity minutes. The primary outcome of change in daily steps and attainment of step goals was analyzed using descriptive statistical testing, means and standard deviations. Summary of Results Six patients, aged 6-18 years, completed the study. Mean baseline FEV1for study participants was 66% predicted (range 38 to 92%). Hospital length of stay ranged from 4-14 days. Participants took an average of 1772 ± 1011 steps before goal setting. This increased to an average of 3741 ± 1780 steps after goal setting. Overall, step goals were met 52% (Range 0-100%) of the time. Conclusions This intervention shows promise, as daily steps doubled from baseline during the intervention period. There was great variability among the participants, suggesting the device may help some people much more than others. Enrollment was initially planned for 20 patients;however, the SARS-CoV-2 pandemic and consequent changes to CF therapy drastically reduced hospitalizations during the study period. Though our results show a positive impact of increased physical activity following goal implementation, further research is needed to determine the effect such an intervention would have on a larger scale. Future directions of research include having a larger sample size, conducting a multi-center study to increase population diversity, and implementing a longer follow- up period to better assess long term benefits of intervention.
ABSTRACT
Background/Introduction: Cardiaovascular prevention/rehabilitation programmes continue to reduce cardiovascular mortality even with contemporary treatment. During covid the majority of face-to-face programmes were suspended but these services have never been more crucial as control of cardiovascular risk factors can mitigate the morbidity/mortality risk from covid. Programmes must now however be delivered in a way that reduces patient exposure. Here we describe how we rapidly transitioned our previously fully face to face cardiovascular prevention/programme to a completely virtual platform adopting Fitbit as wearable technology. Methods: The previously face-to-face initial assessment (IA) conducted by the multidisciplinary team (MDT) - nurse, dietician and physiotherapist is now delivered via video/phone as per patient preference. Patients are provided with equipment kits (tape measures, blood pressure monitors (BP), Fitbit smartwatches and Fibricheck app as required. The virtual IA includes assessment of: Smoking habit, blood pressure (BP), heart rate, lipid profile and HbA1c (taken in community phlebotomy hub), cardioprotective medications, weight, BMI, waist circumference, Mediterranean Diet Score, functional capacity via the Duke Activity Status Index, habitual activity levels, risk stratification for exercise, hospital anxiety and depression scores (HADS) and quality of life (QOL). Patients receive education and tailored advice with SMART goals as well as a written care plan. The subsequent 12 programme is comprised of • Weekly virtual meeting with cardiologist to optimise BP/lipids and medications • Alternate weekly virtual coaching consultation by MDT for monitoring/ goal resetting • Alternate weekly video group education sessions on key cardiovascular health topics • Online educational videos filmed by the MDT Monitoring of physical activity (step count, active minutes) in real time via Fibit dashboard with personalised messages sent to patients via the Fitbit app • Provision of Fibricheck app via Fibit for rhythm assessment • End of programme (EOP) assessments are then also conducted virtually Results: Between April and November 2020 n=262 had a virtual IA (94% of those offered and n=114 (95% of those offered) attended an end of programme assessment. 64% were male and the mean age was 64.1 years. Acceptance of the Fitbit device was 72% of those offered. Table 1 below shows the main clinical and patient-reported outcomes in those attending both an IA and EOP with the data for the same 6 months the year prior (face to face programme) also for comparison. Programme satisfaction ratings were high with 85% rating the programme as excellent or very good. Conclusions: Transitioning a previously fully face to face cardiac rehabilitation programme to a wholly virtual platform was feasible and acceptable to patients. Early data analysis would suggest that the virtual programme achieves similar clinical and patient reported outcomes. (Figure Presented).
ABSTRACT
We investigated which population groups were impacted most in terms of physical activity levels during the restrictions applied during the COVID-19 pandemic. We surveyed UK residents, sampled through users of a rewards-for-exercise app (Sweatcoin; n = 749) and an online panel (Prolific; n = 907). Of the app users, n = 487 further provided daily step-count data collected by the app, prior to, and during the periods of restrictions in the UK between March-June 2020. Regression models were used to investigate factors associated with self-reported change in physical activity and change in daily step-count during the periods of restrictions. Significant factors associated with self-reported change in physical activity included rural residents (positive, b = 0.87, p < 0.001), relative to urban dwellers, people classed as obese (negative, b = -0.51, p = 0.008, relative to healthy weight) and gym users (negative, b = -1.10, p < 0.001, relative to walkers). All groups had reduced step counts during restrictions, with Black, Asian and minority ethnic groups showing greater reductions compared to White British ethnicity (negative, b = -0.18, p = 0.008). Targeted interventions are required to ensure that physical and mental health impacts of sedentary behaviour are not exacerbated over the long-term by significant reductions in physical activity identified in these groups particularly those who are also more vulnerable to COVID-19.