Balanced: a randomised trial examining the efficacy of two self-monitoring methods for an app-based multi-behaviour intervention to improve physical activity, sitting and sleep in adults Use of the Fitbit to Measure Adherence to a Physical Activity Intervention Among Overweight or Obese, Postmenopausal Women: Self-Monitoring Trajectory During 16 Weeks Randomized controlled trial on cardiovascular risk management by practice nurses supported by self-monitoring in primary care Validation of the Fitbit One activity monitor device during treadmill walking. Shoulder Physiotherapy Exercise Recognition: Machine Learning the Inertial Signals from a Smartwatch Comparison of two different physical activity monitors The Influence of Wireless Self-Monitoring Program on the Relationship Between Patient Activation and Health Behaviors, Medication Adherence, and Blood Pressure Levels in Hypertensive Patients: A Substudy of a Randomized Controlled Trial Influence of Lightweight Ambulatory Oxygen on Oxygen Use and Activity Patterns of COPD Patients Receiving Long-Term Oxygen Therapy Use of Consumer Wearable Devices to Promote Physical Activity: A Review of Health Intervention Studies Activity monitoring in heart failure patients with cardiac resynchronization therapy. Activity-monitor accuracy in measuring step number and cadence in community-dwelling older adults. Promoting physical activity using an activity monitor and a tailored web-based advice: design of a randomized controlled trial [ISRCTN93896459] Pattern of active and inactive sequences of diabetes self-monitoring in mobile phone and paper diary users
Background Many adults are insufficiently physically active , have prolonged sedentary behaviour and report poor sleep . These behaviours can be improved by interventions that include education , goal setting , self-monitoring , and feedback strategies . Few interventions have explicitly targeted these behaviours simultaneously or examined the relative efficacy of different self-monitoring methods . Methods / Design This study aims to compare the efficacy of two self-monitoring methods in an app-based multi-behaviour intervention to improve objective ly measured physical activity , sedentary , and sleep behaviours , in a 9 week 2–arm r and omised trial . Participants will be adults ( n = 64 ) who report being physically inactive , sitting > 8 h/day and frequent insufficient sleep ( ≥14 days out of last 30 ) . The “ Balanced ” intervention is delivered via a smartphone ‘ app ’ , and includes education material s ( guidelines , strategies to promote change in behaviour ) , goal setting , self-monitoring and feedback support . Participants will be r and omly allocated to either a device-entered or user-entered self-monitoring method . The device-entered group will be provided with a activity tracker to self-monitor behaviours . The user-entered group will recall and manually record behaviours . Assessment s will be conducted at 0 , 3 , 6 , and 9 weeks . Physical activity , sedentary behaviour and sleep-wake behaviours will be measured using the wrist worn Geneactiv accelerometer . Linear mixed models will be used to examine differences between groups and over time using an alpha of 0.01 . Discussion This study will evaluate an app-based multi-behavioural intervention to improve physical activity , sedentary behaviour and sleep ; and the relative efficacy of two different approaches to self-monitoring these behaviours . Outcomes will provide information to inform future interventions and self-monitoring targeting these behaviours . Trial registration ACTRN12615000182594 ( Australian New Zeal and Clinical Trials Registry . Registry URL : www.anzctr.org.au ; registered prospect ively on 25 February 2015 ) Background Direct-to-consumer trackers and devices have potential to enhance theory-based physical activity interventions by offering a simple and pleasant way to help participants self-monitor their behavior . A secondary benefit of these devices is the opportunity for investigators to objective ly track adherence to physical activity goals across weeks or even months , rather than relying on self-report or a small number of accelerometry wear periods . The use of consumer trackers for continuous monitoring of adherence has considerable potential to enhance physical activity research , but few studies have been published in this rapidly developing area . Objective The objective of the study was to assess the trajectory of physical activity adherence across a 16-week self-monitoring intervention , as measured by the Fitbit tracker . Methods Participants were 25 overweight or obese , postmenopausal women enrolled in the intervention arm of a r and omized controlled physical activity intervention trial . Each participant received a 16-week technology-based intervention that used the Fitbit physical activity tracker and website . The overall study goal was 150 minutes/week of moderate to vigorous intensity physical activity ( MVPA ) and 10,000 steps/day ; however , goals were set individually for each participant and up date d at Week 4 based on progress . Adherence data were collected by the Fitbit and aggregated by Fitabase . Participants also wore an ActiGraph GT3X+ accelerometer for 7 days prior to the intervention and again during Week 16 . Results The median participant logged 10 hours or more/day of Fitbit  wear on 95 % of the 112 intervention days , with no significant decline in wear over the study period . Participants averaged 7540 ( SD 2373 ) steps/day and 82 minutes/week ( SD 43 ) of accumulated “ fairly active ” and “ very active ” minutes during the intervention . At Week 4 , 80 % ( 20/25 ) of women chose to maintain/increase their individual MVPA goal and 72 % ( 18/25 ) of participants chose to maintain/increase their step goal . Physical activity levels were relatively stable after peaking at 3 weeks , with only small declines of 8 % for steps ( P=.06 ) and 14 % for MVPA ( P=.05 ) by 16 weeks . Conclusions These data indicate that a sophisticated , direct-to-consumer activity tracker encouraged high levels of self-monitoring that were sustained over 16 weeks . Further study is needed to determine how to motivate additional gains in physical activity and evaluate the long-term utility of the Fitbit tracker as part of a strategy for chronic disease prevention . Trial Registration Clinical trials.gov NCT01837147 ; http:// clinical trials.gov/ct2/show/NCT01837147 ( Archived by WebCite at http://www.webcitation.org/6d0VeQpvB Background Treatment goals for cardiovascular risk management are generally not achieved . Specialized practice nurses are increasingly facilitating the work of general practitioners and self-monitoring devices have been developed as counseling aid . The aim of this study was to compare st and ard treatment supported by self-monitoring with st and ard treatment without self-monitoring , both conducted by practice nurses , on cardiovascular risk and separate risk factors . Methods Men aged 50–75 years and women aged 55–75 years without a history of cardiovascular disease or diabetes , but with a SCORE 10-year risk of cardiovascular mortality ≥5 % and at least one treatable risk factor ( smoking , hypertension , lack of physical activity or overweight ) , were r and omized into two groups . The control group received st and ard treatment according to guidelines , the intervention group additionally received pro-active counseling and self-monitoring ( pedometer , weighing scale and / or blood pressure device ) . After one year treatment effect on 179 participants was analyzed . Results SCORE risk assessment decreased 1.6 % ( 95 % CI 1.0–2.2 ) for the control group and 1.8 % ( 1.2–2.4 ) for the intervention group , difference between groups was .2 % ( −.6–1.1 ) . Most risk factors tended to improve in both groups . The number of visits was higher and visits took more time in the intervention group ( 4.9 ( SD2.2 ) vs. 2.6 ( SD1.5 ) visits p < .001 and 27 ( P25 –P75:20–33 ) vs. 23 ( P25 –P75:19–30 ) minutes/visit p = .048 ) . Conclusions In both groups cardiovascular risk decreased significantly after one year of treatment by practice nurses . No additional effect of basing the pro-active counseling on self-monitoring was found , despite the extra time investment . Trial registration trialregister.nl OBJECTIVES In order to quantify the effects of physical activity such as walking on chronic disease , accurate measurement of physical activity is needed . The objective of this study was to determine the validity and reliability of a new activity monitor , the Fitbit One , in a population of healthy adults . DESIGN Cross-sectional study . METHODS Thirty healthy adults ambulated at 5 different speeds ( 0.90 , 1.12 , 1.33 , 1.54 , 1.78 m/s ) on a treadmill  while  wearing three Fitbit One activity monitors  ( two on the hips and one in the pocket ) . The order of each speed condition was r and omized . Fitbit One step count output was compared to observer counts and distance output was compared to the calibrated treadmill output . Two-way repeated measures ANOVA , concordance correlation coefficients , and Bl and and Altman plots were used to assess validity and intra-class correlation coefficients ( ICC ) were used to assess reliability . RESULTS No significant differences were noted between Fitbit One step count outputs and observer counts , and concordance was substantial ( 0.97 - 1.00 ) . Inter-device reliability of the step count was high for all walking speeds ( ICC ≥ 0.95 ) . Percent relative error was less than 1.3 % . The distance output of the Fitbit One activity monitors  was significantly different from the criterion values for each monitor at all speeds ( P<0.001 ) and exhibited poor concordance ( 0.0 - 0.05 ) . Inter-device reliability was excellent for all treadmill speeds ( ICC ≥ 0.90 ) . Percent relative error was high ( up to 39.6 % ) . CONCLUSIONS The Fitbit One activity monitors are valid and reliable devices for measuring step counts in healthy young adults . The distance output of the monitors is inaccurate and should be noted with caution OBJECTIVE Participation in a physical therapy program is considered one of the greatest predictors of successful conservative management of common shoulder disorders . However , adherence to these protocol s is often poor and typically worse for unsupervised home exercise programs . Currently , there are limited tools available for objective measurement of adherence in the home setting . The goal of this study was to develop and evaluate the potential for performing home shoulder physiotherapy monitoring using a commercial smartwatch . APPROACH Twenty healthy adult subjects with no prior shoulder disorders performed seven exercises from an evidence -based rotator cuff physiotherapy protocol , while 6-axis inertial sensor data was collected from the active extremity . Within an activity recognition chain ( ARC ) framework , four supervised learning algorithms were trained and optimized to classify the exercises : k-nearest neighbor ( k-NN ) , r and om forest ( RF ) , support vector machine classifier ( SVC ) , and a convolutional recurrent neural network ( CRNN ) . Algorithm performance was evaluated using 5-fold cross-validation stratified first temporally and then by subject . MAIN RESULTS Categorical classification accuracy was above 94 % for all algorithms on the temporally stratified cross validation , with the best performance achieved by the CRNN algorithm ( 99.4 % ) . The subject stratified cross validation , which evaluated classifier performance on unseen subjects , yielded lower accuracies scores again with CRNN performing best ( 88.9 % ) . SIGNIFICANCE This proof of concept study demonstrates the technical feasibility of a smartwatch device and supervised machine learning approach to more easily monitor and assess the at-home adherence of shoulder physiotherapy exercise protocol Background Underst and ing the relationships between  physical activity ( PA ) and disease has become a major area of research interest . Activity monitors , devices that quantify free-living PA for prolonged periods of time ( days or weeks ) , are increasingly being used to estimate PA . A range of different activity monitors br and s are available for investigators to use , but little is known about how they respond to different levels of PA in the field , nor if data conversion between br and s is possible . Methods 56 women and men were fitted with two different activity monitors , the Actigraph ™ ( Actigraph LLC ; AGR ) and the Actical ™ ( Mini-Mitter Co. ; MM ) for 15 days . Both activity monitors were fixed to an elasticized belt worn over the hip , with the anterior and posterior position of the activity monitors r and omized . Differences between activity monitors and the validity of br and inter-conversion were measured by t-tests , Pearson correlations , Bl and -Altman plots , and coefficients of variation ( CV ) . Results The AGR detected a significantly greater amount of daily PA ( 216.2 ± 106.2 vs. 188.0 ± 101.1 counts/min , P < 0.0001 ) . The average difference between activity monitors expressed as a CV were 3.1 and 15.5 % for log-transformed and raw data , respectively . When a conversion equation was applied to convert data sets from one br and to another , the differences were no longer significant , with CV 's of 2.2 and 11.7 % , log-transformed and raw data , respectively . Conclusion Although activity monitors predict PA on the same scale ( counts/min ) , the results between these two br and s are not directly comparable . However , the data are comparable if a conversion equation is applied , with better results for log-transformed data Background Active engagement in the management of hypertension is important in improving self-management behaviors and clinical outcomes . Mobile phone technology using wireless monitoring tools are now widely available to help individuals monitor their blood pressure , but little is known about the conditions under which such technology can effect positive behavior changes or clinical outcomes . Objective To study the influence of wireless self-monitoring program and patient activation measures on health behaviors , medication adherence , and blood pressure levels as well as control of blood pressure in hypertensive patients . Methods We examined a subset of 95 hypertensive participants from a 6-month r and omized controlled trial design ed to determine the utility of a  wireless self-monitoring program ( n=52 monitoring program , n=43 control ) , which consisted of a blood pressure monitoring device connected with a mobile phone , reminders for self-monitoring , a Web-based disease management program , and a mobile app for monitoring and education , compared with the control group receiving a st and ard disease management program . Study participants provided measures of patient activation , health behaviors including smoking , drinking , and exercise , medication adherence , and blood pressure levels . We assessed the influence of wireless self-monitoring as a moderator of the relationship between patient activation and health behaviors , medication adherence , and control of blood pressure . Results Improvements in patient activation were associated with improvements in cigarette smoking ( beta=−0.46 , P<.001 ) and blood pressure control ( beta=0.04 , P=.02 ) . This relationship was further strengthened in reducing cigarettes ( beta=−0.60 , P<.001 ) , alcohol drinking ( beta=−0.26 , P=.01 ) , and systolic ( beta=−0.27 , P=.02 ) and diastolic blood pressure ( beta=−0.34 , P=.007 ) at 6 months among individuals participating in the wireless self-monitoring program . No differences were observed with respect to medication adherence . Conclusions Participation in a wireless self-monitoring program provides individuals motivated to improve their health management with an added benefit above and beyond that of motivation alone . Hypertensive individuals eager to change health behaviors are excellent c and i date s for mobile health self-monitoring .. Trial Registration Clinical Trials.gov NCT01975428 , https:// clinical trials.gov/ct2/show/NCT01975428 ( Archived by WebCite at http://www.webcitation.org/6iSO5OgOG Abstract Lightweight ambulatory oxygen devices are provided on the assumptions that they enhance compliance and increase activity , but data to support these assumptions are lacking . We studied 22 patients with severe chronic obstructive pulmonary disease receiving long-term oxygen therapy ( 14 men , average age = 66.9 y , FEV1 = 33.6%pred , PaO2 at rest = 51.7 torr ) who were using E-cylinders as their portable oxygen . Subjects were recruited at 5 sites and studied over a 2-week baseline period and for 6 months after r and omizing them to either continuing to use 22-lb E-cylinders towed on a cart or to carrying 3.6-lb aluminum cylinders . Utilizing novel electronic devices , ambulatory and stationary oxygen use was monitored continuously over the 2 weeks prior to and the 6 months following r and omization . Subjects wore tri-axial accelerometers to monitor physical activity during waking hours for 2–3 weeks prior to , and at 3 and 6 months after , r and omization . Seventeen subjects completed the study . At baseline , subjects used 17.2 hours of stationary and 2.5 hours of ambulatory oxygen daily . At 6 months , ambulatory oxygen use was 1.4 ± 1.0 hrs in those r and omized to E-cylinders and 1.9 ± 2.4 hrs in those using lightweight oxygen ( P = NS ) . Activity monitoring revealed low activity levels prior to r and omization and no significant increase over time in either group . In this group of severe chronic obstructive pulmonary disease patients , providing lightweight ambulatory oxygen did not increase either oxygen use or activity . Future efforts might focus on strategies to encourage oxygen use and enhance activity in this patient group . This trial is registered at Clinical Trials.gov ( NCT003257540 ) Background Although many wearable devices for monitoring and tracking physical activity are available to consumers , relatively few research studies have been conducted to determine their efficacy in promoting health . Methods In this article , data on the use of consumer wearable devices in promoting healthy behaviors  are summarized based upon bibliographic search es in PubMed and Psychology and Behavioral Sciences Collection with relevant search terms through September 2016 . Results A total of 274 articles were identified in the bibliographic search es . By screening abstract s or full-text articles , six pre/post test trials and seven r and omized controlled trials were identified . In initial trials , consumer wearable devices have been shown to increase physical activity and help users lose weight . However , the number of studies completed to date is small and limited by small sample sizes , short study duration s , and uncertain generalizability of the findings . Conclusions Future studies should utilize r and omized controlled trial research design s , larger sample sizes , and longer study periods to better establish the efficacy of wearable devices in promoting physical activity . Additional research is needed to determine the feasibility and effectiveness of wearable devices in promoting physical activity and weight loss in community setting s including communities affected by health disparities . Studies focusing on children and adolescents are also needed BACKGROUND Cardiac resynchronization therapy ( CRT ) improves functional capacity in heart failure patients . This study aim ed to prospect ively analyze long-term device-based monitoring of physical activity in patients undergoing CRT .  METHODS AND RESULTS The Activity Log Index ( ALI ) , calculated by CRT devices , represents the percentage of time when acceleration exceeds a threshold and monitors the physical activity . Data from 178 CRT patients ( New York Heart Association III 91 % , left ventricular ejection fraction 21+/-6 % , left ventricular end-diastolic diameter 69+/-9 mm , QRS 159+/-27 ms , sinus rhythm 81 % ) were retrieved . The ALI increased from a baseline value of 3.6+/-2.0 to 11.2+/-4.6 ( p<0.005 ) 104 weeks after initiation of CRT . A plateau was reached at approximately 12 weeks and thereafter ALI remained stable for up to 2 years . The magnitude of the changes in ALI was similar in patients with different etiologies and underlying rhythms . Despite similar values at baseline , elderly patients ( > or=65 years ) exhibited significantly lower ALI values than younger patients during the follow-up and at the plateau ( 9.5+/-4.2 vs 13.3+/-4.8 , p<0.001 ) . CONCLUSIONS Device-based monitoring of physical activity in CRT patients is feasible . CRT result ed in a large and long-term increase in physical activity The primary purpose of this study was to investigate the accuracy of the activPAL physical activity monitor in measuring step number and cadence in older adults .  Two pedometers ( New-Lifestyles Digi-Walker SW-200 and New-Lifestyles NL2000 ) used in clinical practice to count steps were simultaneously evaluated . Observation was the criterion measure . Twenty-one participants ( 65 - 87 yr old ) recruited from community-based exercise classes walked on a treadmill at 5 speeds ( 0.67 , 0.90 , 1.12 , 1.33 , and 1.56 m/s ) and outdoors at 3 self-selected speeds ( slow , normal , and fast ) . The absolute percentage error of the activPAL was < 1 % for all treadmill and outdoor conditions for measuring steps and cadence . With the exception of the slowest treadmill speed , the NL-2000 error was < 2 % . The SW-200 was the least accurate device , particularly at slower walking speeds . The activPAL monitor accurately recorded step number and cadence . Combined with its ability to identify primary postures , the activPAL might be a useful and versatile device for measuring activity in older adults Background Ageing is associated with a decrease in physical activity . This decrease particularly occurs during specific transitional life stages . Especially during adolescence and young adulthood a steep decrease in physical activity is observed . Inactive people are often not aware of their inactivity . Providing feedback on the actual physical activity level by an activity monitor can increase awareness and may in combination with an individually tailored physical activity advice stimulate a physically active lifestyle . Methods In a r and omized controlled trial the effectiveness of providing an activity monitor in combination with a personal physical activity advice through the Internet will be examined . Outcome measures are level of physical activity , determinants of physical activity , quality of life , empowerment , aerobic fitness and body composition .  Participants are relatively inactive adolescents and young adults who are measured at baseline , after 3 months intervention and 5 months after the end of the intervention . In addition , facilitating and hindering factors for implementation of the intervention will be investigated . Discussion The use of a personal activity monitor in combination with web-based assisted individually tailored health promotion offers a good opportunity to work interactively with large groups of adolescents and young adults and provide them with advice based on their actual activity level . It has great potential to motivate people to change their behaviour and to our knowledge has not been evaluated before In a pilot r and omized controlled trial involving overweight or obese participants with type 2 diabetes , we find that  smartphone users have sharply higher adherence to self-monitoring of diet , physical activity , blood glucose , and body weight  , as compared to paper diary users . By characterizing the pattern of adherence with the probability of continuation of active and inactive sequences of self-monitoring , we find that smartphone users have longer active sequences of self-monitoring of all four behaviors that were being monitored . Smartphone users are also quicker to resume  self-monitoring of diet and physical activity after a lapse in self-monitoring , whereas paper diary users have shorter inactive sequences for monitoring blood glucose and body weight . The findings are informative for data collection methodology in this burgeoning area of research
Conclusion This review indicates that current research on activity monitoring devices may be overstated due to the variability in adherence .
Results showed that physical activity tracking in women and in young adults have been understudied
Background Activity monitoring devices are currently being used to facilitate and monitor physical activity .
No prior review has examined adherence to the use of activity monitoring devices amongst adults with cardiovascular disease .