Real-time Physical Activity Research Articles

Examining real-time physical activity in adolescents using the Multi-Process Action Control Model: An ecological momentary assessment study

The purpose of this study was to examine real-time associations between reflective (i.e., state motivation), regulatory (i.e., self-control), and reflexive (i.e., habit) constructs from the Multi-Process Action Control (M-PAC) model and real-time moderate-to-vigorous physical activity (MVPA) behaviour among adolescents using ecological momentary assessments. One hundred and ninety adolescents (Mage = 15.76 ± .47 years; n = 101 males) wore an accelerometer for seven consecutive days and responded to digital survey prompts up to four times daily during the after-school periods. MVPA in the 60-minute time window following each survey prompt was recorded. Multilevel mixed-effects linear and logistic models were computed with disaggregated between- and within-person effects to analyze the data. Results from both linear and logistic multilevel models revealed adolescents with higher state motivation in general and experiencing higher state motivation than one’s typical levels were associated with engaging in more MVPA and higher likelihood of engaging in ≥10 minutes of MVPA. Engaging in activities less consistent with habitual behaviours were associated with more MVPA and higher likelihood of engaging in ≥10 minutes of MVPA. By contrast, self-control was not associated with MVPA. Results from this study extend previous work demonstrating the importance of conscious and non-conscious processes on MVPA behaviour by examining associations in real-time using intensive longitudinal methods. Collectively, this study provides partial support for use of the M-PAC framework to explain acute MVPA among adolescents in real-time and natural contexts.

PENGEMBANGAN SISTEM IOT UNTUK PEMANTAUAN KESEHATAN DOMBA DENGAN ALGORITMA C4.5 BERBASIS THINGSPEAK

Effective livestock health monitoring is one of the primary challenges in modern farming, especially in detecting early health disorders in sheep. This research aims to develop a sheep health monitoring system based on the Internet of Things (IoT) using the C4.5 algorithm and the ThingSpeak platform. The system collects vital sheep data such as body temperature, heart rate, sound, and physical activity in real time through sensors and microphones connected to IoT devices. The data is then transmitted to the ThingSpeak platform for analysis and storage. The C4.5 algorithm is used to build a decision model capable of classifying the health conditions of sheep based on collected parameters such as temperature, heart rate, and respiration. The processed data results are displayed in the form of graphs and warning notifications on the ThingSpeak platform, allowing farmers to monitor livestock health easily and responsively. The accuracy test yielded a 90% accuracy rate using a confusion matrix with a data sampling split of 80% for training data and 20% for testing data. This indicates that the system has a high level of accuracy in detecting sheep health conditions. Consequently, the system has the potential to assist farmers in improving the efficiency of livestock health monitoring automatically and in real time. Moreover, the application of IoT technology and the C4.5 algorithm in the livestock sector is expected to provide innovative solutions to support productivity and animal welfare.

Feeling good means doing good: body appreciation as a predictor of physical activity, fitness, and motivation

The study aimed to investigate the influence of body appreciation on physical activity motivation, physical activity level, and physical fitness among 423 randomly selected state university students. The Body Appreciation Scale-2 was used to quantify body appreciation. For measuring physical activity level, the International Physical Activity Questionnaire was utilized. The Physical Activity and Leisure Motivation was also used to quantify physical activity motivation. Various field tests, such as a 3-minute Step test, a 1-minute Push-up test, a Plank test, a Wall sit test, and a Sit and Reach test, were used to assess physical fitness. The questionnaire, scale, and field tests were completed and performed by the participants. The data gathered were analyzed using multiple linear regression with SPSS Version 29. Body appreciation was found to be a predictor of physical activity and leisure motivation for males, females, and all participants. It also predicted the physical activity levels of males, females, and all participants. However, its influence on physical fitness was only found in male participants. Future studies should measure variables using alternative instruments, such as a varied scale for body appreciation, real-time physical activity tracking through wearables and fitness apps, and additional physical fitness components to better assess the influence of body appreciation on physical fitness.

Efficacy of Activity Trackers in Patients With Heart Failure With Preserved Ejection Fraction.

Heart failure with preserved ejection fraction (HFpEF) is a common, complex syndrome associated with elevated morbidity and mortality. Patients with HFpEF have a high prevalence of comorbidities, including hypertension, diabetes mellitus, and obesity, which are closely related to the underlying mechanisms of the disease. Lifestyle modification with weight loss and physical activity can improve risk factors and functional outcomes in HFpEF. We sought to observe daily physical activity and determine whether utilizing an activity tracker can enhance functional status in HFpEF patients. We performed a prospective analysis of 57 patients with HFpEF from 2021 to 2023 at a single academic medical center who utilized a Fitbit to record one year of daily step activity. The patients were evaluated in the ambulatory setting for an initial visit and subsequently at intervals of 3, 6, and 12 months to gather vitals, labs, physical exam, and functional measurements, including the Six-Minute Walk Test (6MWT) and Kansas City Cardiomyopathy Questionnaire-12 (KCCQ-12). Associations between variables were assessed using Pearson's r correlation using Stata 18.0. Of the 49 patients who completed the study, the mean age was 68.1 ± 10.2 years, with 67% of patients identifying as female. The average BMI was 36.4 ± 8.6 kg/m2. Across each time interval, the median numbers of steps per day were 4,113 (2,517-6,520) (1-3 months), 4,583 (2,532-6,326) (4-6 months), and 3,957 (2,942-5,982) (7-12 months). There was no statistically significant variation in daily step count (p=0.06). We observed a statistically significant increase of 66 (6-200) feet in the 6MWT (p= 0.002) from baseline (1,175 (910-1,400)) to 12 months (1,321 (1,000-1,550)). The daily step count was highly correlated with the 6MWT across all time points (1-3 months: r= .70, p< .001; 4-6 months: r= .61, p< .001; 7-12 months: r= .69, p< .001).The total KCCQ-12scores increased by 6.8 (-4.2-19.8) points (p=0.005) from baseline (60.1 (41.7-73.4)) to 12 months (69.8 (50-84.4)). Among the sub-categories of the questionnaire, we observed a positive correlation between physical limitation scores and daily step count (1-3 months: r= .47, p=.001; 4-6 months: r= .63, p< .001; 7-12 months: r= .56, p= .001). Of interest, one patient who was taking over 15,000 daily steps scored their physical limitation 10-20 points lower than those taking less than half the steps and had one of the lowest quality of life scores in the cohort, reflecting the subjective nature of heart failure (HF) symptoms. Fitbit technology offers a convenient means to monitor real-time physical activity in patients with HFpEF. Utilizing a Fitbit to record daily step activity enhances health-related quality of life in this population. In contrast to the improved average total KCCQ-12 score, we did not observe a clinically significant increase in the 6MWT over the course of the year. Our findings establish the utility of daily step count as a valuable surrogate for six-minute walk distance.

Evaluating Weight Loss Efficacy in Obesity Treatment with Allurion's Ingestible Gastric Balloon: A Retrospective Study Utilizing the Scale App Health Tracker.

Obesity represents a growing public health concern, affecting more than 15% of the global adult population and involving a multi-billion market that comprises nutritional, surgical, psychological, and multidisciplinary interventions. The objective of this retrospective study was to evaluate the short-term efficacy and body weight measurements associated with differing levels of physical activity following the use of Allurion's ingestible gastric balloon that was designed to increase feelings of fullness and decrease food consumption, being naturally eliminated after approximately 16 weeks. This study involved 571 individuals who qualified for the intervention for being older than 20 years with a body mass index (BMI) of 27 kg/m2 or more. Utilizing the Scale App Health Tracker and Allurion's smartwatch, this study was able to track vital signs and physical activity in real time. The participants had an average initial BMI of 34.1 kg/m2 and a median age of 41 years. Notable outcomes were observed in both study groups, "Less Active" and "More Active", which were classified by achieving less or more than a median number of 8000 daily steps. Specifically, body fat percentage saw a reduction from 33.1 ± 9.4 to 28.3 ± 10.2 in the less active group and from 32.2 to 27.5 in the more active group, with both groups achieving statistical significance (p < 0.001). Additionally, there was a significant reduction in average weight, dropping from 98.2 ± 22.8 kg to 84.6 ± 19.3 kg in the less active group and from 97.7 ± 21.0 kg to 82.1 ± 22.9 kg in the more active group (both p < 0.001). Interestingly, those in the more active group also experienced a significant increase in lean mass compared to their less active counterparts (p = 0.045), although no substantial differences in weight loss, BMI reduction, and total body fat decrease were observed between the two groups. This investigation confirms the hypothesis that Allurion's ingestible gastric balloon significantly reduces weight in the short term and enhances several physical health metrics, demonstrating effectiveness as an autonomous method for challenging weight management, regardless of the level of daily physical activity.

Use of a wearable patch sensor for continuous activity and posture tracking to assess risk of early infection after transcatheter aortic valve replacement

Abstract Background Early infections after transcatheter aortic valve replacement (TAVR) represent one of the most common risk factors for non-cardiac 30-day mortality. Several wearable devices have been developed to measure vital signs and physical activity in real time while allowing full mobilization of the patient. However, their use has not been evaluated in a clinical setting with patients undergoing TAVR yet. Purpose We aimed to evaluate the feasibility of wearable patch sensors in assessing vital signs and daily activity before and after TAVR to predict an increased risk of early infections following TAVR. Methods Patients at high risk for infection undergoing transfemoral TAVR under local anesthesia were enrolled between September 2022 and January 2023. Postprocedural early infections were assessed, defined as C-reactive protein rise within 5 days after the procedure inducing antibiotic treatment. Vital signs (heart rate, respiratory rate, single-lead ECG) and activity (steps, posture) were monitored by a wearable patch sensor two days before (pre-TAVR) and two days after TAVR (post-TAVR). Results 54 patients completed 5 days of in-hospital monitoring with wearable patch sensors. The mean age was 80.3+5.2 years, 31 patients (57.4%) were male. Early infections occurred in 8 of 54 (14.8%) high-risk patients, of whom one was a urinary tract, one a pulmonary, and two access site-related etiology. Four infections remained with unknown focus. Respiratory rate was generally higher in patients developing an early infection after TAVR in both time periods, before (early infection 22±3 vs. no infection 18±2 bpm; p=0.001) and after TAVR (early infection 24±3 vs. no infection 19±3 bpm; p&amp;lt;0.001). Early infections were more prevalent in patients who showed less activity in the two days before TAVR regarding lower step count (early infection 242±360 vs. no infection 515±566; p=0.048) and high percentage of lying position during the whole day (early infection 89±12% vs. no infection 64±23%; p=0.071). Two days after TAVR, there were no significant differences in activity levels between both cohorts. Physical activity was reduced in both groups compared to the two days before TAVR, resulting in a reduced number of steps (pre-TAVR 473±546 vs. post-TAVR 267±434; p=0.039) and more daytime spent in lying position (pre-TAVR 57±19% vs. post-TAVR 73±24%; p&amp;lt;0.0001). Conclusion Wearable patch sensors are feasible to track vital signs and physical activity during hospital stay with promising opportunity for improving clinical management in TAVR patients. Early infections after TAVR are associated with decreased preprocedural mobility in high-risk patients. Therefore, these patients may be prematurely detected using wireless respiratory rate monitoring and infections prevented by intensified physiotherapy.

Investigating real-time physical activity behavior using ecological momentary assessment: Effects of mental fatigue and benefit-cost valuations

BackgroundCurrent research investigating the relationship between mental fatigue and physical activity behaviors relies on laboratory-based, experimental studies which lack ecological validity. ObjectiveThis study used ecological momentary assessment (EMA) to assess feelings of mental fatigue and subjective evaluations (benefits and costs) as predictors of moderate-to-vigorous intensity physical activity in the everyday lives of young adults. MethodsOne hundred participants (n = 22 males, n = 78 females, Mage = 20.60 years, 70% meeting or exceeding physical activity guidelines) responded to digital survey prompts up to four times a day and wore an accelerometer for seven consecutive days. Moderate-to-vigorous intensity physical activity in the 180-min time window following each survey prompt was recorded. Data from the 28 survey-moderate-to-vigorous intensity physical activity epochs were analyzed using multilevel mixed-effects linear modelling. ResultsHigher levels of mental fatigue than one’s average level were associated with engaging in fewer moderate-to-vigorous intensity physical activity minutes (p = .004) and lower benefit vs. cost scores (p = .001). Higher benefit vs. cost scores than one’s average level were associated with engaging in more minutes of moderate-to-vigorous intensity physical activity (p < .001). ConclusionsResults are the first to demonstrate outside the lab, that mental fatigue experienced in everyday life may amplify the perceived costs of moderate-to-vigorous intensity physical activity, with both factors playing a potential role in moderate-to-vigorous intensity physical activity decision-making. Future research may apply insights gained from this study in design and testing of real-time interventions promoting moderate-to-vigorous intensity physical activity.

Design of a Real-Time Physical Activity Detection and Classification Framework for Individuals With Type 1 Diabetes.

Managing glycemia during and after exercise events in type 1 diabetes (T1D) is challenging since these events can have wide-ranging effects on glycemia depending on the event timing, type, intensity. To this end, advanced physical activity-informed technologies can be beneficial for improving glucose control. We propose a real-time physical activity detection and classification framework, which builds upon random forest models. This module automatically detects exercise sessions and predicts the activity type and intensity from tri-axial accelerometer, heart rate, and continuous glucose monitoring records. Data from 19 adults with T1D who performed structured sessions of either aerobic, resistance, or high-intensity interval exercise at varying times of day were used to train and test this framework. The exercise onset and completion were both predicted within 1 minute with an average accuracy of 81% and 78%, respectively. Activity type and intensity were identified within 2.38 minutes and from the exercise onset. On participants assigned to the test set, the average accuracy for activity type and intensity classification was 74% and 73%, respectively, if exercise was announced. For unannounced exercise events, the classification accuracy was 65% for the activity type and 70% for its intensity. The proposed module showed high performance in detection and classification of exercise in real-time within a minute of exercise onset. Integration of this module into insulin therapy decisions can help facilitate glucose management around physical activity.

A Novel Approach to Assess Weekly Self-efficacy for Meeting Personalized Physical Activity Goals Via a Cellphone: 12-Week Longitudinal Study.

Despite the health benefits of engaging in regular physical activity (PA), the majority of American adults do not meet the PA guidelines for aerobic and muscle-strengthening activities. Self-efficacy, the belief that one can execute specific actions, has been suggested to be a strong determinant of PA behaviors. With the increasing availability of digital technologies, collecting longitudinal real-time self-efficacy and PA data has become feasible. However, evidence in longitudinal real-time assessment of self-efficacy in relation to objectively measured PA is scarce. This study aimed to examine a novel approach to measure individuals' real-time weekly self-efficacy in response to their personalized PA goals and performance over the 12-week intervention period in community-dwelling women who were not meeting PA guidelines. In this secondary data analysis, 140 women who received a 12-week PA intervention were asked to report their real-time weekly self-efficacy via a study mobile app. PA (daily step counts) was measured by an accelerometer every day for 12 weeks. Participants rated their self-efficacy on meeting PA goals (ranging from "not confident" to "very confident") at the end of each week via a mobile app. We used a logistic mixed model to examine the association between weekly self-efficacy and weekly step goal success, controlling for age, BMI, self-reported White race, having a college education or higher, being married, and being employed. The mean age was 52.7 (SD 11.5, range 25-68) years. Descriptive analyses showed the dynamics of real-time weekly self-efficacy on meeting PA goals and weekly step goal success. The majority (74.4%) of participants reported being confident in the first week, whereas less than half of them (46.4%) reported confidence in the final week of the intervention. Participants who met weekly step goals were 4.41 times more likely to be confident about achieving the following week's step goals than those who did not meet weekly step goals (adjusted odds ratio 4.41; 95% CI 2.59-7.50; P<.001). Additional analysis revealed that participants who were confident about meeting the following week's step goals were 2.07 times more likely to meet their weekly step goals in the following week (adjusted odds ratio 2.07; 95% CI 1.16-3.70; P=.01). The significant bidirectional association between real-time self-efficacy and weekly step goal success was confirmed in a series of sensitivity analyses. This study demonstrates the potential utility of a novel approach to examine self-efficacy in real time for analysis of self-efficacy in conjunction with objectively measured PA. Discovering the dynamic patterns and changes in weekly self-efficacy on meeting PA goals may aid in designing a personalized PA intervention. Evaluation of this novel approach in an RCT is warranted.

Mental states and personality based on real-time physical activity and facial expression recognition.

To explore a quick and non-invasive way to measure individual psychological states, this study developed interview-based scales, and multi-modal information was collected from 172 participants. We developed the Interview Psychological Symptom Inventory (IPSI) which eventually retained 53 items with nine main factors. All of them performed well in terms of reliability and validity. We used optimized convolutional neural networks and original detection algorithms for the recognition of individual facial expressions and physical activity based on Russell's circumplex model and the five factor model. We found that there was a significant correlation between the developed scale and the participants' scores on each factor in the Symptom Checklist-90 (SCL-90) and Big Five Inventory (BFI-2) [r = (-0.257, 0.632), p < 0.01]. Among the multi-modal data, the arousal of facial expressions was significantly correlated with the interval of validity (p < 0.01), valence was significantly correlated with IPSI and SCL-90, and physical activity was significantly correlated with gender, age, and factors of the scales. Our research demonstrates that mental health can be monitored and assessed remotely by collecting and analyzing multimodal data from individuals captured by digital tools.

IoT-Inspired Monitoring Framework for Real-Time Stereotypic Movement Analysis

Physical activity recognition has become one of the prominent domain of research in the field of smart healthcare. The identification of physical activities through wearable sensors provide significant information about the functional ability and lifestyle of an individual. In this article, a smart physical activity-assisted behavior prediction framework is presented to recognize different stereotypical motor movements of the individual suffering from autism spectrum disorder in real time. This article employs the data acquisition efficiency of Internet of Things (IoT) assisted smart wearable sensors to capture the physical activities of an individual. To predict the physical activities, a deep learning-inspired multilayered convolutional neural network (CNN) + long short-term memory network is proposed. Furthermore, the utility of the framework is increased by presenting an effective fog-assisted alert-based decision-making module. The decision-making module notifies the concerned caretaker or medical specialist about the performed irregular physical activity in real time. Moreover, the process of cloud-based record generation also enhances the significance of the proposed solution. The proposed approach is validated by comparing the prediction performance with traditional handcraft-based and modern deep learning-based state-of-the-art approaches such as <formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex>$k$</tex></formula> -nearest neighbors, hidden Markov model, and CNN, where it outperformed by achieving the overall accuracy of 91.88%.

Ecological Momentary Assessment of Physical Activity and Wellness Behaviors in College Students Throughout a School Year: Longitudinal Naturalistic Study.

BackgroundThe Wellness Environment app study is a longitudinal study focused on promoting health in college students.ObjectiveThe two aims of this study were (1) to assess physical activity (PA) variation across the days of the week and throughout the academic year and (2) to explore the correlates that were associated with PA, concurrently and longitudinally.MethodsThe participants were asked to report their wellness and risk behaviors on a 14-item daily survey through a smartphone app. Each student was provided an Apple Watch to track their real time PA. Data were collected from 805 college students from Sept 2017 to early May 2018. PA patterns across the days of the week and throughout the academic year were summarized. Concurrent associations of daily steps with wellness or risk behavior were tested in the general linear mixed-effects model. The longitudinal, reciprocal association between daily steps and health or risk behaviors were tested with cross-lagged analysis.ResultsFemale college students were significantly more active than male ones. The students were significantly more active during the weekday than weekend. Temporal patterns also revealed that the students were less active during Thanksgiving, winter, and spring breaks. Strong concurrent positive correlations were found between higher PA and self-reported happy mood, 8+ hours of sleep, ≥1 fruit and vegetable consumption, ≥4 bottles of water intake, and ≤2 hours of screen time (P<.001). Similar longitudinal associations found that the previous day’s wellness behaviors independently predicted the following day’s higher PA except for mood. Conversely, the higher previous-day PA levels were associated with better mood, more fruit and vegetable consumption, and playing less music, but with higher liquor consumption the next day.ConclusionsThis study provides a comprehensive surveillance of longitudinal PA patterns and their independent association with a variety of wellness and risk behaviors in college students.

Lessons Learned for Training a Research Team and Teaching Kidney Transplant Recipients How to Use a Mobile Health Technology for Dietary Intake and Physical Activity via a Virtual Platform

Kidney transplant centers and other health care organizations historically have struggled to merge lifestyle management for diet and physical activity into clinical practice. The use of mobile health (mHealth) applications has the potential for kidney transplant recipients to track calorie intake and physical activity in real time. Few studies have reported how they trained their research team and participants how to use mHealth technology in real time. The purpose of this study was to describe lessons learned for training a research team and teaching kidney transplant recipients how to use mHealth technology utilizing a virtual format. Findings suggest that time and educational materials, and using verbal, written, and visual information are critical when conducting a research study using a virtual format.

Application of trekrevit in a complex with fitness — training for men’s health correction, diabetes patients

The possibility of complex correction using the method of adaptive physical culture and the use of a biologically active additive trerevit the health status of men with type 2 diabetes mellitus was studied. It was found that the use of automatic control of the assigned physical load using the body composition analyzer “TANITA”, in the conditions of fitness and trekrevit, helps to reduce the level of glucose in the blood. The use of automatic, objective control of physical activity in real time in the process of fitness improves the methods of health-improving and adaptive physical culture.

Correction in the conditions of fitness of women’s health people with diabetes and arterial hypertension 1 A

The possibility of correction by the method of adaptive physical culture of the state of health of women with type 2 diabetes mellitus complicated by hypertension was studied. It is established that the use of automatic control of the given physical load by the program « TANITA», in conditions of fitness, helps to reduce the level of arterial pressure and glucose in the blood. Use in the process of fitness automatic, objective control of physical activity in real time improves the methods of health and adaptive physical culture.

Racial Discrimination, Sedentary Time, and Physical Activity in African Americans: Quantitative Study Combining Ecological Momentary Assessment and Accelerometers.

BackgroundA growing number of studies indicate that exposure to social stress, such as perceived racial discrimination, may contribute to poor health, health behaviors, and health disparities. Increased physical activity (PA) may buffer the impact of social stress resulting from racial discrimination. However, to date, data on the relationship between racial discrimination and PA have been mixed. Part of the reason is that the effect of perceived racial discrimination on PA has primarily been examined in cross-sectional studies that captured retrospective measures of perceived racial discrimination associated with individuals’ current PA outcomes. The association between real-time perceived racial discrimination and PA among African Americans remains unclear.ObjectiveThe purpose of this study is to examine the relationship among demographic, anthropometric and clinical, and psychological factors with lifetime racial discrimination and examine the within- and between-person associations between daily real-time racial discrimination and PA outcomes (total energy expenditure, sedentary time, and moderate-to-vigorous PA patterns) measured by ecological momentary assessment (EMA) and accelerometers in healthy African Americans.MethodsThis pilot study used an intensive, observational, case-crossover design of African Americans (n=12) recruited from the community. After participants completed baseline surveys, they were asked to wear an accelerometer for 7 days to measure their PA levels. EMA was sent to participants 5 times per day for 7 days to assess daily real-time racial discrimination. Multilevel models were used to examine the within- and between-person associations of daily racial discrimination on PA.ResultsMore EMA-reported daily racial discrimination was associated with younger age (r=0.75; P=.02). Daily EMA-reported microaggression was associated with depressive symptoms (r=0.66; P=.05), past race-related events (r=0.82; P=.004), and lifetime discrimination (r=0.78; P=.01). In the within-person analyses, the day-level association of racial discrimination and sedentary time was significant (β=.30, SE 0.14; P=.03), indicating that on occasions when participants reported more racial discrimination than usual, more sedentary time was observed. Between-person associations of racial discrimination (β=−.30, SE 0.28; P=.29) or microaggression (β=−.34, SE 0.36; P=.34) with total energy expenditure were suggestive but inconclusive.ConclusionsConcurrent use of EMA and accelerometers is a feasible method to examine the relationship between racial discrimination and PA in real time. Examining daily processes at the within-person level has the potential to elucidate the mechanisms of which racial discrimination may have on health and health behaviors and to guide the development of personalized interventions for increasing PA in racial ethnic minorities. Future studies with a precision health approach, incorporating within- and between-person associations, are warranted to further elucidate the effects of racial discrimination and PA.International Registered Report Identifier (IRRID)RR2-10.1002/nur.22068

Comprehensive ambulatory monitoring during immunotherapy in patients with advanced melanoma: A prospective trial (CAMP-IT).

TPS1589 Background: The emergence of immune checkpoint inhibitors has improved survival outcomes for patients with advanced melanoma. However, these treatment modalities are also associated with specific immune-related toxicities. These are often reversible after prompt recognition and initiation of appropriate management, but can result in severe morbidity and hamper health-related quality of life (HRQoL) if left undetected. Hence, accurate and regular monitoring of these patients is critical. Recent advances in mHealth technologies and the rapidly expanding armamentarium of wearable devices allow for real-time objective (vital signs and physical activity) data and patient-reported outcome measurement (PROMs) collection and, hence, serve this purpose. We hypothesize that collection of real-time objective data adds to the early detection of disease- and treatment-related adverse events. The primary objective of this study is to determine the feasibility of collecting real-time PROMs, vital signs, and physical activity data in advanced melanoma patients receiving immunotherapy using a comprehensive ambulatory monitoring platform (CAMP) that consists of a smartphone app, activity monitor, digital thermometer, and online dashboard for physicians. Methods: In this prospective multi-center trial, patients (n = 50) with advanced melanoma, scheduled to receive immunotherapy with immune checkpoint inhibitors, and with access to a smartphone are eligible for inclusion. Consenting patients will be asked to wear a FitBit Versa 2.0 during waking hours, collect daily temperature measurements using a Withings Smart Temporal thermometer, and answer weekly toxicity questionnaires (NCI PRO-CTCAE) using the smartphone app for the duration of the study (12 weeks). Primary outcome is feasibility in terms of (i) participation rates, (ii) wear-time, (iii) compliance rates with in-app questionnaires and temperature measurements, and (iv) satisfaction with the platform. Secondary exploratory outcomes include associations between CAMP-derived parameters and clinical outcomes: performance status (PS), HR-QoL scores (EORTC QLQ-C30 questionnaire), unplanned hospitalizations, physician-assessed adverse events, and 1-year survival outcomes. PS and HR-QoL will be rated at baseline, mid-study, and end-of-study. The occurrence of adverse events will be documented up to 12 months from baseline. Survival outcomes will be compared to a propensity score matched group from the Netherlands Cancer Registry. Accrual has started in February 2021. Clinical trial information: NL8827.

The physical activity at work (PAW) study protocol: a cluster randomised trial of a multicomponent short-break intervention to reduce sitting time and increase physical activity among office workers in Thailand

BackgroundHigh levels of sedentary behaviour (SB) are associated with non-communicable diseases. In 2016, the estimated total healthcare expenditure from physical activity (PA) in Thailand added up to $190 million in international dollars. The challenge to reduce SB and increase PA among office workers is more urgent now than ever as Thailand is transforming itself from a predominantly rural country to an increasingly urban one. This study will investigate the effectiveness of a multicomponent short break intervention on the reduction of SB during office hours.Methods/designThis two-armed Physical Activity at Work (PAW) cluster randomised controlled trial will recruit 360 office workers from 18 offices in the Thailand’s Ministry of Public Health (MOPH). Offices will be randomised to either the intervention group or the control group. The multicomponent intervention is informed by the Social Ecological Model and Behaviour Change Techniques (BCTs) and contains four components: (i) organisational, including heads of the participating divisions leading exercises, sending encouragement text messages and acknowledging efforts; (ii) social, including team movement breaks and team-based incentives; (iii) environmental, including posters to encourage exercise; and (iv) individual components including real-time PA feedback via an individual device. The main intervention component will be a short break intervention. The primary outcome of this study is the sedentary time of office workers. Secondary outcomes include time spent on PA, cardiometabolic outcomes, work productivity, musculoskeletal pain, and quality of life. The study also includes process and economic evaluations from the individual and societal perspective.DiscussionThe study will be the first experimental study in Thailand to investigate the effect of a short-break intervention at the workplace on SBs of office workers and health outcomes. The study will also include a cost-effectiveness analysis to inform investments on short break interventions under the Universal Healthcare Coverage in Thailand, which includes health promotion and disease prevention component.Trial registrationThe PAW study has been registered at the Thai Clinical Trials Registry (TCTR) under the study ID TCTR20200604007. Registered 02 June 2020,

Physical Activity And Its Association With Other Wellness And Risk Behaviors From A College Sample

PURPOSE: The University of Vermont Wellness Environment App Study is an app-based longitudinal research study focused on promoting health and reducing risky behaviors in a college student population. The mobile ecological momentary assessment over an academic year provides a unique opportunity to accomplish two aims in this study: 1) to assess physical activity (PA) variation across days of the week and throughout the academic year and 2) to explore the correlates that were associated with PA. METHODS: Students who enrolled in the study were asked to report their wellness and risk behaviors on a 14-item survey through a smartphone app every day. Each student was also provided an Apple Watch to track their real-time PA. Data were collected from 805 college students, with an average of 97 days of daily surveys and steps data from Sept 2017 to early May 2018. Daily survey and step data were merged by day for each participant. General estimating equations were implemented in SAS PROC MIXED, with an autoregressive covariance structure to estimate the daily steps by demographic variables and other wellness behaviors. RESULTS: Based on average daily step counts, females were significantly more active than male college students (Female=8904 and Male=8488, p=.0082). Age-related PA decline was found from freshmen to seniors, but only freshmen was significantly more active than seniors (freshmen=8714 and senior=8023, p=.0051). Students were significantly more active (p<.0001) during the weekday (Monday to Friday ranged from 8800 to 9384 steps) than weekend (Sat=8356 and Sun=7145). Temporal patterns were also revealed that students were less active during Thankgiving, Winter, and Spring breaks. Strong correlations were found between daily steps and self-reported mood (p<.0001), sleep (p<.0001), fruit and vegetable consumption (p<.0001), water intake (p<.0001), and screen time (p<.0001). No significant associations were found for marijuana use (p=.997), cigarette use (p=.2518), drug use (p=.1546) but significant associated were observed for illicit pill use (p=.0083), alcoholic drink consumption (p<.0001), and liquor shot consumption (p<.0001). CONCLUSION: The study provides a comphrensive surveillance on longitudinal PA pattern and its association with a variety of wellness and risky behaviors in college students.

Types Of Social Support And Change In Daily Steps Among Adults

Evidence has shown a favorable link between social support and leading a physically active lifestyle. Yet, little is known about the types of social support that may be the most influential. PURPOSE: This study examined the association between physical activity (PA) change and the types of social support adults participating in a PA intervention identified as the most helpful for their PA efforts. METHODS: Insufficiently active adults were randomized as self-selected teams of 3-8 participants (n=24 teams) to a 12-week technology-mediated, theory-based PA treatment (n=59 participants) or the same intervention plus a real-time PA gamified challenge (n=57 participants). There were no significant differences between conditions in changes in mean daily steps, so analyses collapsed groups and examined participants at 12 weeks (N=116) and 1 year (n=98). Participants completed an online survey at both time points, which asked them to select the most helpful type of social support they received (informational; tangible; emotional; esteem). Configural Frequency Analysis was used to analyze participants grouped according to their characteristic configurations in terms of meaningful changes in mean daily steps from baseline (> 1,000 steps/d) as measured by an accelerometer and reported type of perceived social support. RESULTS: Participants averaged 4853+1333 steps/d at baseline and 39% and 36% achieved a > 1000 steps/d increase from baseline at 12 weeks and 1 year, respectively. Esteem support emerged as the most frequently reported most helpful type of support at 12 weeks and 1 year, followed by emotional and tangible support. At 12 weeks, those who achieved a > 1,000 steps/d increase and reported emotional support as the most helpful type represented the most notable statistically significant configuration (n=14; p<.001). At 1 year, those who achieved a > 1,000 steps/d increase and reported tangible support as the most helpful type represented the most notable statistically significant configuration (n=9; p=.004). CONCLUSION: These findings suggest that different types of support may be especially influential at varying phases of the behavior change process. Future studies should employ designs that allow for the direct comparison of the effectiveness of different types of support on physical activity in adults.