Cross-sectional assessment of sleep and fatigue in middle-aged Japanese women with primary Sjogren syndrome or rheumatoid arthritis using self-reports and wrist actigraphy.

ABSTRACT: To investigate fatigue, health-related quality of life (HR-QOL), and sleep quality in women with primary Sjogren syndrome (pSS) or rheumatoid arthritis (RA) as compared with healthy controls using self-reports and wrist actigraphy.In this cross-sectional observational study, we evaluated a total of 25 patients (aged 40-75 years) with pSS, 10 with RA, and 17 healthy control subjects living in Japan. The HR-QOL was assessed using the Short Form-36. Fatigue was evaluated using the Short Form-36 vitality score, visual analog scale (VAS) for fatigue, and 2 questionnaire items using scores based on a 4-point Likert scale. Sleep quality was measured using the Japanese version of the Pittsburgh Sleep Quality Index, VAS for sleep quality, and wrist actigraphy for 14 days.Patients with pSS reported severer fatigue and lower HR-QOL than healthy controls, especially in mental health. Based on the Pittsburgh Sleep Quality Index score, 56% of the patients with pSS were poor sleepers, which was higher than healthy controls (29.4%). Furthermore, the patients with pSS scored significantly lower on the VAS for sleep quality than healthy controls (40.5 vs 63.7, P = .001). Although subjective assessments revealed slight sleep disturbances in patients with pSS, wrist actigraphy revealed no differences when compared with healthy controls for total sleep time (421.8 minutes vs 426.5 minutes), sleep efficiency (95.2% vs 96.4%), number of awakenings (1.4 vs 0.9), and wake after sleep onset (22.4 minutes vs 16.1 minutes). Poor subjective sleep quality was associated with enhanced fatigue. However, sleep efficiency, as determined by actigraphy, was not associated with fatigue. Notably, the patients with RA and healthy controls did not differ significantly in terms of fatigue or sleep quality, although patients with RA experienced more nocturnal awakenings than healthy controls (1.7 vs 0.9, P = .04).Patients with pSS experience severe fatigue, poor HR-QOL, and sleep disturbances, which are associated with fatigue. However, wrist actigraphy did not reveal differences in sleep quality, suggesting that it may not be an appropriate measure of sleep in patients with pSS.

Objective Assessment of Daytime Napping and Incident Heart Failure in 1140 Community-Dwelling Older Adults: A Prospective, Observational Cohort Study.

Background Disrupted nighttime sleep has been associated with heart failure (HF). However, the relationship between daytime napping, an important aspect of sleep behavior commonly seen in older adults, and HF remains unclear. We sought to investigate the association of objectively assessed daytime napping and risk of incident HF during follow-up. Methods and Results We studied 1140 older adults (age, 80.7±7.4 [SD] years; female sex, 867 [76.1%]) in the Rush Memory and Aging Project who had no HF at baseline and were followed annually for up to 14 years. Motor activity (ie, actigraphy) was recorded for ≈10 days at baseline. We assessed daytime napping episodes between 9 am and 7 pm objectively from actigraphy using a previously published algorithm for sleep detection. Cox proportional hazards models examined associations of daily napping duration and frequency with incident HF. Eighty-six participants developed incident HF, and the mean onset time was 5.7 years (SD, 3.4; range, 1-14). Participants who napped longer than 44.4 minutes (ie, the median daily napping duration) showed a 1.73-fold higher risk of developing incident HF than participants who napped <44.4 minutes. Consistently, participants who napped >1.7 times/day (ie, the median daily napping frequency) showed a 2.20-fold increase compared with participants who napped <1.7 times/day. These associations persisted after adjustment for covariates, including nighttime sleep, comorbidities, and cardiovascular disease/risk factors. Conclusions Longer and more frequent objective napping predicted elevated future risk of developing incident HF. Future studies are needed to establish underlying mechanisms.

Evaluation of a very brief pedometer-based physical activity intervention delivered in NHS Health Checks in England: The VBI randomised controlled trial.

BACKGROUND: The majority of people do not achieve recommended levels of physical activity. There is a need for effective, scalable interventions to promote activity. Self-monitoring by pedometer is a potentially suitable strategy. We assessed the effectiveness and cost-effectiveness of a very brief (5-minute) pedometer-based intervention ('Step It Up') delivered as part of National Health Service (NHS) Health Checks in primary care. METHODS AND FINDINGS: The Very Brief Intervention (VBI) Trial was a two parallel-group, randomised controlled trial (RCT) with 3-month follow-up, conducted in 23 primary care practices in the East of England. Participants were 1,007 healthy adults aged 40 to 74 years eligible for an NHS Health Check. They were randomly allocated (1:1) using a web-based tool between October 1, 2014, and December 31, 2015, to either intervention (505) or control group (502), stratified by primary care practice. Participants were aware of study group allocation. Control participants received the NHS Health Check only. Intervention participants additionally received Step It Up: a 5-minute face-to-face discussion, written materials, pedometer, and step chart. The primary outcome was accelerometer-based physical activity volume at 3-month follow-up adjusted for sex, 5-year age group, and general practice. Secondary outcomes included time spent in different intensities of physical activity, self-reported physical activity, and economic measures. We conducted an in-depth fidelity assessment on a subsample of Health Check consultations. Participants' mean age was 56 years, two-thirds were female, they were predominantly white, and two-thirds were in paid employment. The primary outcome was available in 859 (85.3%) participants. There was no significant between-group difference in activity volume at 3 months (adjusted intervention effect 8.8 counts per minute [cpm]; 95% CI -18.7 to 36.3; p = 0.53). We found no significant between-group differences in the secondary outcomes of step counts per day, time spent in moderate or vigorous activity, time spent in vigorous activity, and time spent in moderate-intensity activity (accelerometer-derived variables); as well as in total physical activity, home-based activity, work-based activity, leisure-based activity, commuting physical activity, and screen or TV time (self-reported physical activity variables). Of the 505 intervention participants, 491 (97%) received the Step it Up intervention. Analysis of 37 intervention consultations showed that 60% of Step it Up components were delivered faithfully. The intervention cost £18.04 per participant. Incremental cost to the NHS per 1,000-step increase per day was £96 and to society was £239. Adverse events were reported by 5 intervention participants (of which 2 were serious) and 5 control participants (of which 2 were serious). The study's limitations include a participation rate of 16% and low return of audiotapes by practices for fidelity assessment. CONCLUSIONS: In this large well-conducted trial, we found no evidence of effect of a plausible very brief pedometer intervention embedded in NHS Health Checks on objectively measured activity at 3-month follow-up. TRIAL REGISTRATION: Current Controlled Trials (ISRCTN72691150).

Comparative validity of energy expenditure prediction algorithms using wearable devices for people with spinal cord injury.

STUDY DESIGN: Cross-sectional validation study. OBJECTIVES: To conduct a literature search for existing energy expenditure (EE) predictive algorithms using ActiGraph activity monitors for manual wheelchairs users (MWUs) with spinal cord injury (SCI), and evaluate their validity using an out-of-sample dataset. SETTING: Research institution in Pittsburgh, USA. METHODS: A literature search resulted in five articles containing five sets of predictive equations using an ActiGraph activity monitor for MWUs with SCI. Out-of-sample data were collected from 29 MWUs with chronic SCI who were asked to follow an activity protocol while wearing an ActiGraph GT9X Link on the dominant wrist. They also wore a portable metabolic cart which provided the criterion measure for EE. The out-of-sample dataset was used to evaluate the validity of the five sets of EE predictive equations. RESULTS: None of the five sets of predictive equations demonstrated equivalence within 20% of the criterion measure based on an equivalence test. The mean absolute error for the five sets of predictive equations ranged from 0.87 to 6.41 kilocalories per minute (kcal min-1) when compared with the criterion measure, and the intraclass correlation estimates ranged from 0.06 to 0.59. The range between the Bland-Altman upper and lower limits of agreement was from 4.70 kcal min-1 to 25.09 kcal min-1. CONCLUSIONS: The existing EE predictive equations based on ActiGraph monitors for MWUs with SCI showed varied performance when compared with the criterion measure. Their accuracies may not be sufficient to support future clinical and research use. More work is needed to develop more accurate EE predictive equations for this population.

Development and Pilot Study of an iOS Smartphone Application for Perioperative Functional Capacity Assessment.

BACKGROUND: Functional capacity assessment plays a core role in the preoperative evaluation. The Duke Activity Status Index (DASI) and the 6-minute walk test (6MWT) are 2 methods that have demonstrated the ability to evaluate functional capacity and predict perioperative outcomes. Smartphones offer a novel method to facilitate functional capacity assessment as they can easily administer a survey and accelerometers can track patient activity during a 6MWT. We developed a smartphone application to administer a 6MWT and DASI survey and performed a pilot study to evaluate the accuracy of a smartphone-based functional capacity tool in our Anesthesia and Perioperative Medicine Clinic. METHODS: Using the Apple ResearchKit software platform, we developed an application that administers a DASI survey and 6MWT on an iOS smartphone. The DASI was presented to the patient 1 question on the screen at a time and the application calculated the DASI score and estimated peak oxygen uptake (VO2). The 6MWT used the CMPedometer class from Apple's core motion facility to retrieve accelerometer data collected from the device's motion coprocessor to estimate steps walked. Smartphone estimated steps were compared to a research-grade pedometer using the intraclass correlation coefficient (ICC). Distance walked was directly measured during the 6MWT and we performed a multivariable linear regression with biometric variables to create a distance estimation algorithm to estimate distance walked from the number of steps recorded by the application. RESULTS: Seventy-eight patients were enrolled in the study and completed the protocol. Steps measured by the smartphone application as compared to the pedometer demonstrated moderate agreement with an ICC (95% CI) of 0.87 (0.79-0.92; P = .0001). The variables in the distance estimation algorithm included (ß coefficient [slope], 95% CI) steps walked (0.43, 0.29-0.57; P < .001), stride length (0.38, 0.22-0.53; P < .001), age in years (-1.90, -3.06 to -0.75; P = .002), and body mass index (-2.59, -5.13 to -0.06; P = .045). The overall model fit was R = 0.72, which indicates a moderate level of goodness of fit and explains 72% of the variation of distance walked during a 6MWT. CONCLUSIONS: Our pilot study demonstrated that a smartphone-based functional capacity assessment is feasible using the DASI and 6MWT. The DASI was easily completed by patients and the application clearly presented the results of the DASI to providers. Our application measured steps walked during a 6MWT moderately well in a preoperative patient population; however, future studies are needed to improve the smartphone application's step-counting accuracy and distance estimation algorithm.

The use of actograph in the assessment of fetal well-being.

Purpose: Third trimester maternal perception of fetal movements is often used to assess fetal well-being. However, its true clinical value is unknown, primarily because of the variability in subjective quantification. The actograph, a technology available on most cardiotocograph machines, quantifies movements, but has never previously been investigated in relation to fetal health and existing monitoring devices. The objective of this study was to quantify actograph output in healthy third trimester pregnancies and investigate this in relation to other methods of assessing fetal well-being.Methods: Forty-two women between 24 and 34 weeks of gestation underwent ultrasound scan followed by a computerized cardiotocograph (CTG). Post capture analysis of the actograph recording was performed and expressed as a percentage of activity over time. The actograph output results were analyzed in relation to Doppler, ultrasound and CTG findings expressed as z-score normalized for gestation.Results: There was a significant association between actograph output recording and estimated fetal weight Z-score (R = 0.546, p ≤ .005). This activity was not related to estimated fetal weight. Increased actograph activity was negatively correlated with umbilical artery pulsatility index Z-score (R = -0.306, p = .049) and middle cerebral artery pulsatility index Z-score (R = -0.390, p = .011).Conclusion: Fetal movements assessed by the actograph are associated both with fetal size in relation to gestation and fetoplacental Doppler parameters. It is not the case that larger babies move more, however, as the relationship with actograph output related only to estimated fetal weight z-score. These findings suggest a plausible link between the frequency of fetal movements and established markers of fetal health.RATIONALEThe objective of this study was to quantify actograph output in healthy third trimester pregnancies and investigate this in relation to other methods of assessing fetal well-being. This is a widely available method of assessing fetal movements objectively, which has been shown to be an important marker of fetal health. This research is novel in the fact that actograph has never been truly investigated in relation to fetal well-being, despite being available on most cardiotocograph (CTG) machines.Our results show that fetal movements assessed by the actograph are associated both with fetal size in relation to gestation and fetoplacental Doppler parameters. If this proves to be true, smaller babies that move less maybe at particular perinatal risk.

Sleep assessment devices: types, market analysis, and a critical view on accuracy and validation.

Introduction: Sleep assessment devices are essential for the detection, diagnosis, and monitoring of sleep disorders. This paper provides a state-of-the-art review and comparison of sleep assessment devices and a market analysis.Areas covered: Hardware devices are classified into contact and contactless devices. For each group, the underlying technologies are presented, paying special attention to their limitations. A systematic literature review has been carried out by comparing the most important validation studies of sleep tracking devices in terms of sensitivity and specificity. A market analysis has also been carried out in order to list the most used, best-selling, and most highly-valued devices. Software apps have also been compared with regards to the market.Expert opinion: Thanks to technological advances, the reliability and accuracy of sensors has been significantly increased in recent years. According to validation studies, some actigraphs present a sensibility higher than 90%. However, the market analysis reveals that many hardware devices have not been validated, and especially software devices should be studied before their clinical use.

Physical Activity and Sedentary Behavior Assessment: A Laboratory-Based Evaluation of Agreement between Commonly Used ActiGraph and Omron Accelerometers.

Different models of accelerometer have the potential to provide a different estimate of the same physical activity or sedentary behavior. Our study compared the outputs of the Active Style Pro (ASP) and ActiGraph (AG) devices in assessing predicted metabolic equivalents (METs) for specific activities under laboratory conditions. Thirty healthy young adults wore two hip accelerometers (ASP and AG), simultaneously while performing twenty-two activities (eight sedentary, eight household, and six ambulatory activities) in a controlled laboratory setting. For the AG, predicted METs for each activity was calculated using four equations based on vertical-axis and vector magnitude data. Separate paired t-tests and Bland-Altman analysis examined the difference and agreement in METs between AG using four commonly used equations and ASP measurements for each activity. AG devices using different equations calculated significantly different outcomes for most activities compared with ASP devices. The smallest differences in predicted METs estimates between ASP and AG were observed for ambulatory activities. Ambulatory activities demonstrated the best agreement between ASP and AG regardless of which AG equation was used. Our findings can be used to assist researchers in their selection of accelerometer and output estimation equations for measuring physical activity and sedentary behavior in adults.

Accuracy of 12 Wearable Devices for Estimating Physical Activity Energy Expenditure Using a Metabolic Chamber and the Doubly Labeled Water Method: Validation Study.

BACKGROUND: Self-monitoring using certain types of pedometers and accelerometers has been reported to be effective for promoting and maintaining physical activity (PA). However, the validity of estimating the level of PA or PA energy expenditure (PAEE) for general consumers using wearable devices has not been sufficiently established. OBJECTIVE: We examined the validity of 12 wearable devices for determining PAEE during 1 standardized day in a metabolic chamber and 15 free-living days using the doubly labeled water (DLW) method. METHODS: A total of 19 healthy adults aged 21 to 50 years (9 men and 10 women) participated in this study. They followed a standardized PA protocol in a metabolic chamber for an entire day while simultaneously wearing 12 wearable devices: 5 devices on the waist, 5 on the wrist, and 2 placed in the pocket. In addition, they spent their daily lives wearing 12 wearable devices under free-living conditions while being subjected to the DLW method for 15 days. The PAEE criterion was calculated by subtracting the basal metabolic rate measured by the metabolic chamber and 0.1×total energy expenditure (TEE) from TEE. The TEE was obtained by the metabolic chamber and DLW methods. The PAEE values of wearable devices were also extracted or calculated from each mobile phone app or website. The Dunnett test and Pearson and Spearman correlation coefficients were used to examine the variables estimated by wearable devices. RESULTS: On the standardized day, the PAEE estimated using the metabolic chamber (PAEEcha) was 528.8±149.4 kcal/day. The PAEEs of all devices except the TANITA AM-160 (513.8±135.0 kcal/day; P>.05), SUZUKEN Lifecorder EX (519.3±89.3 kcal/day; P>.05), and Panasonic Actimarker (545.9±141.7 kcal/day; P>.05) were significantly different from the PAEEcha. None of the devices was correlated with PAEEcha according to both Pearson (r=-.13 to .37) and Spearman (ρ=-.25 to .46) correlation tests. During the 15 free-living days, the PAEE estimated by DLW (PAEEdlw) was 728.0±162.7 kcal/day. PAEE values of all devices except the Omron Active style Pro (716.2±159.0 kcal/day; P>.05) and Omron CaloriScan (707.5±172.7 kcal/day; P>.05) were significantly underestimated. Only 2 devices, the Omron Active style Pro (r=.46; P=.045) and Panasonic Actimarker (r=.48; P=.04), had significant positive correlations with PAEEdlw according to Pearson tests. In addition, 3 devices, the TANITA AM-160 (ρ=.50; P=.03), Omron CaloriScan (ρ=.48; P=.04), and Omron Active style Pro (ρ=.48; P=.04), could be ranked in PAEEdlw. CONCLUSIONS: Most wearable devices do not provide comparable PAEE estimates when using gold standard methods during 1 standardized day or 15 free-living days. Continuous development and evaluations of these wearable devices are needed for better estimations of PAEE.

A RE-AIM Evaluation of a Workplace Physical Activity Microgrant Initiative: The 10,000 Steps Workplace Challenge.

OBJECTIVE: This study examines the reach, effectiveness, adoption, implementation, and maintenance of the 10,000 Steps Pedometer Microgrant Scheme using the RE-AIM framework. METHODS: The study used a mixed methods pre-post design. RE-AIM indicators were examined using employee surveys and workplace reports of microgrant implementation, adoption, and maintenance. RESULTS: A total of 259 microgrants and 21,211 pedometers were awarded (reach). Significant increases in physical activity were observed (P < 0.05) (effectiveness). Many (78%) workplaces reported using at least one challenge resource (adoption). Barriers were higher (26.5%) or lower (20.5%) than anticipated participation rates (implementation). Fifty percent of workplaces would continue to promote physical activity (maintenance). CONCLUSIONS: The microgrant reached a large number of employees and workplaces, increased physical activity, and achieved good levels of adoption and implementation. Employee and workplace levels of maintenance were mixed and need to be improved.

The ActiGraph counts processing and the assessment of vigorous activity.

The purpose of this study was to investigate the effect of different band-pass filters on the measurement bias with ActiGraph counts during high speed running and for estimating free-living vigorous physical activity (VPA). Two alternative band-pass filters were designed, extending the original frequency range from 0·29 to 1·66 Hz (AG) to 0·29-4 Hz (AC4) and 0·29-10 Hz (AC10). Sixty-two subjects in three age groups participated in a structured locomotion protocol consisting of multiple walking and running speeds. The time spent in free-living VPA using the three different band-pass filters were evaluated in 1121 children. Band-pass filter specific intensity cut-points from both linear regression and ROC analysis was identified from a calibration experiment using indirect calorimetry. The ActiGraph GT3X+ device recording raw acceleration at 30 Hz was used in all experiments. The linear association between counts and running speed was negative for AG but positive for AC4 and AC10 across all age groups. The time spent in free-living VPA was similar for all band-pass filters. Considering higher frequency information in the generation of ActiGraph counts with a hip/waist worn device reduces the measurement bias with running above 10 km·h-1 . However, additional developments are required to accurately capture all VPA, including intermittent activities.

Upper limb motor pre-clinical assessment in Parkinson's disease using machine learning.

INTRODUCTION: Parkinson's disease (PD) is a common neurodegenerative disorder characterized by disabling motor and non-motor symptoms. For example, idiopathic hyposmia (IH), which is a reduced olfactory sensitivity, is typical in >95% of PD patients and is a preclinical marker for the pathology. METHODS: In this work, a wearable inertial device, named SensHand V1, was used to acquire motion data from the upper limbs during the performance of six tasks selected by MDS-UPDRS III. Three groups of people were enrolled, including 30 healthy subjects, 30 IH people, and 30 PD patients. Forty-eight parameters per side were computed by spatiotemporal and frequency data analysis. A feature array was selected as the most significant to discriminate among the different classes both in two-group and three-group classification. Multiple analyses were performed comparing three supervised learning algorithms, Support Vector Machine (SVM), Random Forest (RF), and Naïve Bayes, on three different datasets. RESULTS: Excellent results were obtained for healthy vs. patients classification (F-Measure 0.95 for RF and 0.97 for SVM), and good results were achieved by including subjects with hyposmia as a separate group (0.79 accuracy, 0.80 precision with RF) within a three-group classification. Overall, RF classifiers were the best approach for this application. CONCLUSION: The system is suitable to support an objective PD diagnosis. Further, combining motion analysis with a validated olfactory screening test, a two-step non-invasive, low-cost procedure can be defined to appropriately analyze people at risk for PD development, helping clinicians to identify also subtle changes in motor performance that characterize PD onset.

Actigraphy as an assessment of performance status in patients with advanced lung cancer.

OBJECTIVE: Wearable devices such as a wrist actigraph may have a potential to objectively estimate patients' functioning and may supplement performance status (PS). This proof-of-concept study aimed to evaluate whether actigraphy data are significantly associated with patients' functioning and are predictive of their survival in patients with metastatic non-small cell lung cancer. METHOD: We collected actigraphy data for a three-day period in ambulatory patients with stage IV non-small cell lung cancer. We computed correlations between actigraphy data (specifically, proportion of time spent immobile while awake) and clinician-rated PS, subjective report of physical activities, quality of life (the Functional Assessment of Cancer Therapy - Trial Outcome Index), and survival. RESULT: Actigraphy data (the proportion of time awake spent immobile) were significantly correlated with Functional Assessment of Cancer Therapy - Trial Outcome Index (r = -0.53, p < 0.001) and with the Eastern Cooperative Oncology Group PS (ECOG PS) (r = 0.37, p < 0.001). The proportion of time awake spent immobile was significantly associated with worse survival. For each 10% increase in this measure, the hazard ratio (HR) was 1.48 (95% confidence interval [CI95%] = 1.06, 2.06) for overall mortality, and odds ratio was 2.99 (CI95% = 1.27, 7.05) for six-month mortality. ECOG PS was also associated with worse survival (HR = 2.80, CI95% = 1.34, 5.86). Among patients with ECOG PS 0-1, the percentage of time awake spent immobile was significantly associated with worse survival, HR = 1.93 (CI95% = 1.10, 3.42), whereas ECOG PS did not predict survival. SIGNIFICANCE OF RESULTS: Actigraphy may have potential to predict important clinical outcomes, such as quality of life and survival, and may serve to supplement PS. Further validation study is warranted.

Objective assessment of WHO/ECOG performance status.

PURPOSE: Performance status is an important factor in determining quality of life, the choice of treatment, and prognostic tool in patients. All scoring systems currently in use measure the patient's performance subjectively. A new method of objective assessment of performance ECOG/WHO grades 2 and 3 was constructed and tested. METHODS: A performance meter-an adapted USB data logger with a mercury tilt switch-was constructed. The device was tested in a feasibility study on 33 residents of a retirement home. Parallel to the objective assessment, each resident gave their own estimate of their performance, and each resident was in turn assessed by the nursing staff. RESULTS: With the performance meter, 4 residents (12%) were assessed as PS ≥ 3 in comparison with 8 (24%) and 7 (21%) residents with an ECOG score ≥ 3 estimated by patients themselves and nursing staff respectively. CONCLUSION: Subjective scoring-estimated by patients themselves and by nursing staff-showed underestimation of patients' performance. In 12% of patients, a better performance score was observed with objective measurement in comparison with subjective assessment. Performance meter could be a useful tool for health care professionals for type of care decisions.

The validity of two commercially-available sleep trackers and actigraphy for assessment of sleep parameters in obstructive sleep apnea patients.

OBJECTIVE: The use of activity and sleep trackers that operate through dedicated smartphone applications has become popular in the general population. However, the validity of the data they provide has been disappointing and only Total Sleep Time (TST) is reliably recorded in healthy individuals for any of the devices tested. The purpose of this study was to evaluate the ability of two sleep trackers (Withings pulse 02 (W) and Jawbone Up (U)) to measure sleep parameters in patients suffering from obstructive sleep apnea (OSA). METHODS: All patients evaluated for OSA in our sleep laboratory underwent overnight polysomnography (PSG). PSG was conducted simultaneously with three other devices: two consumer-level sleep monitors (U and W) and one actigraph (Bodymedia SenseWear Pro Armband (SWA)). RESULTS: Of 36 patients evaluated, 22 (17 men) were diagnosed with OSA (mean apnea-hypopnea index of 37+ 23/h). Single comparisons of sleep trackers (U and W) and actigraph (SWA) were performed. Compared to PSG, SWA correctly assessed TST and Wake After Sleep Onset (WASO), and U and W correctly assessed Time In Bed (TIB) and light sleep. Intraclass correlations (ICC) revealed poor validity for all parameters and devices, except for WASO assessed by SWA. CONCLUSIONS: This is the first study assessing the validity of sleep trackers in OSA patients. In this series, we have confirmed the limited performance of wearable sleep monitors that has been previously observed in healthy subjects. In OSA patients, wearable app-based health technologies provide a good estimation of TIB and light sleep but with very poor ICC.

Effectiveness of individual counseling and activity monitors to promote physical activity among university students.

BACKGROUND: Physical activity (PA) promotion among university students is important to contribute to a lifelong healthy lifestyle. Nevertheless, research in the field is still limited in quantity, quality and generalizability. This study aimed at evaluating the effectiveness of two individual-based strategies for promoting PA among university students in such university contexts where course-based interventions are difficult to implement. METHODS: Thirty-three university students were recruited by means of face-to-face interviews and randomly assigned to three groups. The first group attended individual counselling sessions (based on the social cognitive theory and the transtheoretical model of behavior change) via videoconferencing calls, the second used wearable PA monitors designed to motivate to PA, and the third served as control. Interventions lasted 12 weeks. Measures of weekly PA (self-reported by questionnaires and recorded by ActiGraph-GT3X+ monitors) and the stage of change of participants were collected at baseline (t0), immediately after the 12-week intervention (t1), and after a 3-month follow-up (t2). RESULTS: Students in the individual counselling group increased self-reported energy expenditure between t0 and t1 and maintained this improvement at t2; on the contrary, there was no increase in ActiGraph measures of PA. Progression through stages of changes was observed in the same group at t1, followed by some relapses at t2. No significant differences were found neither in the group of students who used the PA monitors nor in the control group. CONCLUSIONS: Although measures of self-reported PA and stage of change suggest the effectiveness of the counselling intervention, the results obtained with accelerometers are contrasting, probably due to the fact that some types of PA participants engaged in could not be recorder by accelerometers. Further studies are needed to determine the efficacy of individual counselling to promote PA in university students. The autonomous use of PA monitors had no effects on PA behavior. The low participation rate in the study suggests considering carefully the difficulties in motivating this population and in finding low time-consuming strategies to incentive participation.

Validity of wearable activity monitors for tracking steps and estimating energy expenditure during a graded maximal treadmill test.

The purpose of this study was to assess the accuracy of energy expenditure (EE) estimation and step tracking abilities of six activity monitors (AMs) in relation to indirect calorimetry and hand counted steps and assess the accuracy of the AMs between high and low fit individuals in order to assess the impact of exercise intensity. Fifty participants wore the Basis watch, Fitbit Flex, Polar FT7, Jawbone, Omron pedometer, and Actigraph during a maximal graded treadmill test. Correlations, intra-class correlations, and t-tests determined accuracy and agreement between AMs and criterions. The results indicate that the Omron, Fitbit, and Actigraph were accurate for measuring steps while the Basis and Jawbone significantly underestimated steps. All AMs were significantly correlated with indirect calorimetry, however, no devices showed agreement (p < .05). When comparing low and high fit groups, correlations between AMs and indirect calorimetry improved for the low fit group, suggesting AMs may be better at measuring EE at lower intensity exercise.

Calibration of wrist-worn ActiWatch 2 and ActiGraph wGT3X for assessment of physical activity in young adults.

BACKGROUND: The validity of Actiwatch 2 in assessing sleep was evident, but its validity in assessing physical activity (PA) level was unknown. RESEARCH QUESTION: The objective of this study was to validate the wrist-worn Actiwatch 2 and ActiGraph wGT3X as a measurement of PA level against energy expenditure measured by indirect calorimetry. METHODS: Twenty-seven university students aged 18-26 were recruited from July 2016 to May 2017. They were instructed to run at different speeds (4, 6, 8, 10, and 12 km/h) on a treadmill, each speed for 10 min. Oxygen consumption and carbon dioxide production of the subjects was measured by indirect calorimetry using the Cosmed K4b2 gas analyzer. Each subjects wore a single pair of accelerometers (Actiwatch 2 and ActiGraph wGT3X) on both wrists. RESULTS: All the accelerometers were strongly correlated (ρ=0.83-0.94, all p-values <0.001), and all four accelerometers were strongly correlated with the METs obtained from the Cosmed K4b2 (ρ=0.72-0.74, all p-values <0.001). Regression analysis showed that the non-dominant wrist-worn Actiwatch 2 cutoff cpm for moderate and vigorous PA were 399 and 1,404, respectively; for the ActiGraph wGT3X-BT the corresponding cutoffs were 4,514 and 15,044, respectively. The goodness-of-fit of the MET prediction equations were all >75%. When classifying the activities as either sedentary, light activity, moderate-intensity activity, or vigorous-intensity activity using the MET prediction equations, the agreements between the four accelerometers and that by the Cosmed K4b2 were high, all AUCs were above 80% except those of the Actiwatch worn on the left (non-dominant) wrist. The Bland-Altman plots show that, for all four accelerometers, the biases were close to zero and error variances were largest when the mean measurements were around 6 METs. SIGNIFICANCE: We showed that wrist-worn Actiwatch 2 and ActiGraph wGT3X-BT were strongly correlated in PA assessment.

Associations between Health Assessment Questionnaire Disability Index and physical performance in rheumatoid arthritis and osteoarthritis.

OBJECTIVES: To investigate whether the Health Assessment Questionnaire Disability Index (HAQ-DI) reflects objective measures of physical function in people with osteoarthritis (OA) and rheumatoid arthritis (RA). METHODS: In total, 139 people, 71 with RA fulfilling the American College of Rheumatology (ACR) criteria (1987) and 68 with OA fulfilling ACR criteria for OA of the hip or knee, completed the HAQ-DI. Physical function was assessed using Timed Up and Go (TUG), 30 seconds Sit to Stand (STS), grip strength dynamometry and pedometer steps over 7 days. RESULTS: The strongest association with HAQ-DI was with the TUG (R2 of 0.671 and 0.512 in RA and OA groups, respectively). HAQ-DI and STS showed a non-linear association in both groups with R2 of 0.380 in RA and 0.359 in OA. A strong association was found between HAQ-DI and grip strength in the OA group (R2  = 0.681), whereas the RA group showed a moderate association (R2  = 0.285). There was a strong association between the HAQ-DI and pedometer measures in RA (R2  = 0.562), although this association was weak in OA (R2  = 0.156). CONCLUSION: The HAQ-DI has a strong association with the TUG in both RA and OA. There was variable association between the HAQ-DI and other physical performance measures, as well as differences between the RA and OA cohorts. In order to form a full and accurate clinical picture, health professionals should perform both subjective patient-reported outcome measures and objective physical performance measures of disability.

Loss-Framed Financial Incentives and Personalized Goal-Setting to Increase Physical Activity Among Ischemic Heart Disease Patients Using Wearable Devices: The ACTIVE REWARD Randomized Trial.

BACKGROUND: Regular physical activity reduces the risk of cardiovascular events, but most ischemic heart disease (IHD) patients do not obtain enough. METHODS AND RESULTS: ACTIVE REWARD (A Clinical Trial Investigating Effects of a Randomized Evaluation of Wearable Activity Trackers with Financial Rewards) was a 24-week home-based, remotely monitored, randomized trial with a 16-week intervention (8-week ramp-up incentive phase and 8-week maintenance incentive phase) and an 8-week follow-up. Patients used wearable devices to track step counts and establish a baseline. Patients in control received no other interventions. Patients in the incentive arm received personalized step goals and daily feedback for all 24 weeks. In the ramp-up incentive phase, daily step goals increased weekly by 15% from baseline with a maximum of 10 000 steps and then remained fixed. Each week, $14 was allocated to a virtual account; $2 could be lost per day for not achieving step goals. The primary outcome was change in mean daily steps from baseline to the maintenance incentive phase. Ischemic heart disease patients had a mean (SD) age of 60 (11) years and 70% were male. Compared with control, patients in the incentive arm had a significantly greater increase in mean daily steps from baseline during ramp-up (1388 versus 385; adjusted difference, 1061 [95% confidence interval, 386-1736]; P<0.01), maintenance (1501 versus 264; adjusted difference, 1368 [95% confidence interval, 571-2164]; P<0.001), and follow-up (1066 versus 92; adjusted difference, 1154 [95% confidence interval, 282-2027]; P<0.01). CONCLUSIONS: Loss-framed financial incentives with personalized goal setting significantly increased physical activity among ischemic heart disease patients using wearable devices during the 16-week intervention, and effects were sustained during the 8-week follow-up. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT02531022.