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 Adherence to a physical activity intervention among older adults in a post-transitional middle income country: A quantitative and qualitative analysis Feasibility and Acceptability of a Wearable Technology Physical Activity Intervention With Telephone Counseling for Mid-Aged and Older Adults: A Randomized Controlled Pilot Trial Wearable fitness device does not help maintain weight loss, study finds The effect of ongoing feedback on physical activity levels following an exercise intervention in older adults: a randomised controlled trial protocol Use of Electronic Monitoring Devices to Measure Antiretroviral Adherence: Practical Considerations A comparison of energy expenditure estimates from the Actiheart and Actical physical activity monitors during low intensity activities, walking, and jogging Monitoring of physical activity and heart rate variability in patients with chronic heart failure using cardiac resynchronization devices. Use of text messaging services to promote health behaviors in children. Daily Text Messaging for Weight Control Among Racial and Ethnic Minority Women: Randomized Controlled Pilot Study Multidimensional individualised Physical ACTivity (Mi-PACT) – a technology-enabled intervention to promote physical activity in primary care: study protocol for a randomised controlled trial
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 Objectives The effectiveness of community level interventions depends to a great extent on adherence . Currently , information on factors related to adherence in older adults from developing countries is scarce . Our aim was to identify factors associated to adherence to a physical activity intervention in older adults from a post-transitional middle income country . Design , setting and participants Using a combination of quantitative and qualitative methods we studied 996 older Chilean subjects ( 65–67.9 years at baseline ) with low to medium socioeconomic status from 10 health centers r and omized to receive a physical activity intervention as part of the CENEX cluster trial ( IS RCT N48153354 ) . Measurements Using a multilevel regression model , the relationship between adherence ( defined a priori as attendance at a minimum of 24 physical activity classes spread over at least 12 months ) and individual , intervention-related and context ual factors was evaluated . We also conducted 40 semi-structured interviews with older adults ( n=36 ) and instructors ( n=4 ) . Transcripts of the interviews were analyzed using content analysis to identify barriers and facilitators to adherence . Results Adherence to physical activity intervention was 42.6 % ( CI 95 % 39.5 to 45.6 ) . Depression , diabetes mellitus , percentage of impoverished households and rate of arrests for violent crimes in the neighborhood predicted less adherence ( p<0.05 ) while being retired , participation in physical activity prior to the intervention , and green areas per habitant were positively associated with adherence ( p<0.05 ) . The qualitative interviews identified three primary barriers to adherence : current health problems , lack of time due to commitments for caring for family members , and being employed , and two primary facilitators to adherence : the health benefits attributed to the intervention and the opportunity the classes provided for social interaction with others . Conclusion In order to enhance effectiveness of community exercise interventions , strategies to improve participation should be targeted to older adults from deprived areas and those with psychological and medical conditions Background As adults age , their physical activity decreases and sedentary behavior increases , leading to increased risk of negative health outcomes .  Wearable electronic activity monitors have shown promise for delivering effective behavior change techniques . However , little is known about the feasibility and acceptability of non-Fitbit wearables ( Fitbit , Inc , San Francisco , California ) combined with telephone counseling among adults aged more than 55 years . Objective The purpose of our study was to determine the feasibility , acceptability , and effect on physical activity of an intervention combining a wearable physical activity monitor , tablet device , and telephone counseling  among adults aged 55 - 79 years . Methods Adults ( N=40 , aged 55 - 79 years , body mass index=25 - 35 , < 60 min of activity per week ) were r and omized to receive a 12-week intervention or to a wait list control . Intervention participants received a Jawbone Up24 monitor , a tablet with the Jawbone Up app installed , and brief weekly telephone counseling . Participants set daily and weekly step goals and used the monitor ’s idle alert to notify them when they were sedentary for more than 1 h. Interventionists provided brief counseling once per week by telephone .  Feasibility was measured using observation and study records , and acceptability was measured by self-report using vali date d items . Physical activity and sedentary time were measured using ActivPAL monitors following st and ard protocol s. Body composition was measured using dual-energy x-ray absorptiometry scans , and fitness was measured using a 6-min walk test . Results Participants were 61.48 years old ( SD 5.60 ) , 85 % ( 34/40 ) female , 65 % ( 26/40 ) white .  Average activity monitor wear time was 81.85 ( SD 3.73 ) of 90 days . Of the 20 Up24 monitors , 5 were reported broken and 1 lost . No related adverse events were reported . Acceptability items were rated at least 4 on a scale of 1 - 5 . Effect sizes for most outcomes were small , including stepping time per day ( d=0.35 ) , steps per day ( d=0.26 ) , sitting time per day ( d=0.21 ) , body fat ( d=0.17 ) , and weight ( d=0.33 ) . Conclusions The intervention was feasible and acceptable in this population . Effect sizes were similar to the sizes found using other wearable electronic activity monitors , indicating that when combined with telephone counseling , wearable activity monitors are a potentially effective tool for increasing physical activity and decreasing sedentary behavior . Trial registration Clinical trials.gov NCT01869348 ; https:// clinical trials.gov/ct2/show/NCT01869348 ( Archived by WebCite at http://www.webcitation.org/6odlIolqy Participants in a r and omised weight loss study who used a wearable fitness device to monitor their physical activity lost less weight over two years than those who self monitored their diet and activity using a website , a US study published in JAMA has found.1 The study , led by University of Pittsburgh research ers , r and omly assigned 470 overweight participants aged 18 - 35 with a body mass index of 25 - 40 either to wear a BodyMedia FIT Core armb and device or to self report exercise and calorie intake . Both arms of the study first underwent a Background Physical inactivity ranks as a major contributing factor in the development and progression of chronic disease . Lifestyle interventions reduce the progression of chronic disease , however , compliance decreases over time and health effects only persist as long as the new lifestyle is maintained . Telephone counselling ( TC ) is an effective way to provide individuals with ongoing support to maintain lifestyle changes . Remote physical activity monitoring and feedback ( RAMF ) via interactive technologies such as activity trackers and smartphones may be a cost-effective alternative to TC , however , this comparison has not been made . This study , therefore , aims to determine the effect of ongoing feedback ( TC vs. RAMF ) on the maintenance of physical activity following a 12-week individualised lifestyle program , and the effect of this on health risk factors and health services usage . Methods and design A r and omised controlled trial with a parallel groups design . A total of 150 adults ( ≥60 years ) who participate in a 12-week face-to-face individualised lifestyle program will be r and omised to twelve months of RAMF ( n = 50 ) , TC ( n = 50 ) , or usual care ( n = 50 ) . Participants r and omised to RAMF will use a smartphone activity tracker app , synced to a wrist worn activity tracker , to provide them with automated feedback regarding compliance to prescribed activity targets . Telephone counselling involves a follow-up phone call every fortnight for the first three months and a monthly call for the remaining nine months of the follow-up period . The primary outcome measures are physical activity compliance ( accelerometry and Active Australia survey ) . Secondary outcome measures include cardiorespiratory fitness , muscle strength , dynamic balance , quality of life , blood pressure , body composition , and health services usage . Measures will be made before and after the individualised lifestyle program , and at three , six and twelve months during the intervention . Discussion The results of this study will help to determine the efficacy of RAMF devices on compliance to prescribed physical activity compared to the current gold st and ard of TC . If the remote monitoring proves effective , it may provide a cost efficient alternative method of assisting maintenance of behaviour change from lifestyle interventions .Trial registration ACTRN12615001104549 . Retrospectively Registered 20/10/2015 The purpose of this paper is to describe electronic monitoring device ( EMD ) ( e.g. , MEMS caps ) use among HIV-infected adults enrolled in a r and omized clinical trial and to make explicit some of the benefits and caveats of using electronic monitoring device technology . This is a descriptive , exploratory study of EMD use among 128 HIV-infected adults treated with at least three antiretroviral agents . Thirty-six percent of the sample admitted that they did not use the  EMD  consistently . Forty-one percent of the subjects reported taking out more than one dose at a time and 26 % reported opening the EMD  but not taking the medication . Special subject-related issues accounted for only a small percentage of all reported problems with EMD use ( e.g. , transient housing , incarceration , substance abuse relapse and drug treatment ) . Results of this study suggest that EMDs may underestimate antiretroviral adherence among HIV-infected adults . Recommendations for improving EMD data quality are presented Combining accelerometry with heart rate monitoring has been suggested to improve energy estimates , however , it remains unclear whether the single , currently existing commercially available device combining these data streams ( Actiheart ) provides improved energy estimates compared to simpler and less expensive accelerometry-only devices . The purpose of this study was to compare the validity of the heart rate ( HR ) , accelerometry ( ACC ) , and combined ACC/HR estimates of the Actiheart to the ACC estimates of the Actical during low and moderate intensity activities . Twenty-seven participants ( mean age 26.3 ± 7.3 ) wore an Actical , Actiheart and indirect calorimeter ( K4b2 ) while performing card playing , sweeping , lifting weights , walking and jogging activities . All estimates tended to underestimate energy , sometimes by substantial amounts . Viewed across all activities studied , there was no significant difference in the ability of the waist-mounted Actical and torso-mounted Actiheart ( ACC , HR , ACC/HR ) estimates to predict energy expenditure . However , the Actiheart provided significantly better estimates than the Actical for the activities in which acceleration of the pelvis is not closely related to energy expenditure ( card playing , sweeping , lifting weights ) and the Actical provided significantly better estimates for level walking and level jogging . Similar to a previous study , the ACC component of the Actiheart was found to be the weakest predictor of energy suggesting it may be responsible for the failure of the combined ACC/HR estimate to equal or better the estimates derived solely from a waist mounted ACC device Cardiac resynchronization therapy ( CRT ) devices not only deliver effective treatment but may also serve as valuable diagnostic tools in heart failure management . In the present study , the minutes of daily physical activity and heart rate variability , measured by sensors incorporated into such a device , reflected the effects of CRT and were related to New York Heart Association functional class OBJECTIVE To examine adherence to , satisfaction with , and preliminary efficacy of mobile phone short message service ( SMS ) to promote health behaviors in school-aged children . METHODS A total of 49 children ( aged 8 - 10 years ) were r and omized by school classes into a monitoring vs no-monitoring group . All children participated in 2 educational group sessions that focused on health behaviors : the advantages of increasing fruit and vegetable consumption and physical activity , and decreasing screen time . The monitoring group also reported daily behavior using SMS and received supportive feedback for 8 weeks . RESULTS Children su bmi tted 61 % of the required SMS , which indicated good adherence to the intervention . A number of children ( 95 % ) reported being satisfied with the program . Analyses of covariance indicated increase in fruit and vegetable consumption ( χ² [ 2 ] = 7.27 ; P < .05 ) and a decrease in screen time ( χ² [ 2 ] = 6.79 ; P < .05 ) . CONCLUSIONS AND IMPLICATION S The current SMS intervention was a useful tool to monitor and promote health behaviors in children Background Daily self-monitoring of diet and physical activity behaviors is a strong predictor of weight loss success . Text messaging holds promise as a viable self-monitoring modality , particularly among racial/ethnic minority population s. Objective This pilot study evaluated the feasibility of a text messaging intervention for weight loss  among predominantly black women . Methods Fifty obese women were r and omized to either a 6-month intervention using a fully automated system that included daily text messages for self-monitoring tailored behavioral goals ( eg , 10,000 steps per day , no sugary drinks ) along with brief feedback and tips ( n=26 ) or to an education control arm ( n=24 ) . Weight was objective ly measured at baseline and at 6 months . Adherence was defined as the proportion of text messages received in response to self-monitoring prompts . Results The average daily text messaging adherence rate was 49 % ( SD 27.9 ) with 85 % ( 22/26 ) texting self-monitored behavioral goals 2 or more days per week . Approximately 70 % ( 16/23 ) strongly agreed that daily texting was easy and helpful and 76 % ( 16/21 ) felt the frequency of texting was appropriate . At 6 months , the intervention arm lost a mean of 1.27 kg ( SD 6.51 ) , and the control arm gained a mean of 1.14 kg ( SD 2.53 ; mean difference –2.41 kg , 95 % CI –5.22 to 0.39 ; P=.09 ) . There was a trend toward greater text messaging adherence being associated with greater percent weight loss ( r=–.36 ; P=.08 ) , but this did not reach statistical significance . There was no significant association between goal attainment and text messaging adherence and no significant predictors of adherence . Conclusions Given the increasing penetration of mobile devices , text messaging may be a useful self-monitoring tool for weight control , particularly among population s most in need of intervention . Trial Registration Clinical trials.gov : NCT00939081 ; http:// clinical trials.gov/show/NCT00939081 ( Archived by WebCite at http://www.webcitation.org/6KiIIcnk1 ) Background Low physical activity is a major public health problem . New cost-effective approaches that stimulate meaningful long-term changes in physical activity are required , especially within primary care setting s. It is becoming clear that there are various dimensions to physical activity with independent health benefits . Advances in technology mean that it is now possible to generate multidimensional physical activity ‘ profiles ’ that provide a more complete representation of physical activity and offer a variety of options that can be tailored to the individual . Mi-PACT is a r and omised controlled trial design ed to examine whether personalised multidimensional physical activity feedback and self-monitoring alongside trainer-supportive sessions increases physical activity and improves health outcomes in at-risk men and women . Methods / Design We aim to recruit 216 patients from within primary care aged 40 to 70 years and at medium or high risk of cardiovascular disease and /or type II diabetes mellitus . Adopting an unequal allocation ratio ( intervention : control ) of 2:1 , participants will be r and omised to one of two groups , usual care or the intervention . The control group will receive usual care from their general practitioner ( GP ) and st and ardised messages about physical activity for health . The intervention group will receive physical activity monitors and access to a web-based platform for a 3-month period to enable self-monitoring and the provision of personalised feedback regarding the multidimensional nature of physical activity . In addition , this technology-enabled feedback will be discussed with participants on 5 occasions during supportive one-to-one coaching sessions across the 3-month intervention . The primary outcome measure is physical activity , which will be directly assessed using activity monitors for a 7-day period at baseline , post intervention and at 12 months . Secondary measures ( at these time-points ) include weight loss , fat mass , and markers of metabolic control , motivation and well-being . Discussion Results from this study will provide insight into the effects of integrated physical activity profiling and self-monitoring combined with in-person support on physical activity and health outcomes in patients at risk of future chronic disease . Trial registration IS RCT N18008011 Trial registration date : 31 July
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 .