ORCID Profile
0000-0003-4222-5091
Current Organisations
National Research Centre for the Working Environment
,
Aalborg Universitet
,
University College Dublin
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Publisher: JMIR Publications Inc.
Date: 15-12-2021
Abstract: here is increasing recognition of the need for more comprehensive surveillance data, including information on physical activity of all intensities, sedentary behavior, and sleep. However, meeting this need poses significant challenges for current surveillance systems, which are mainly reliant on self-report. he primary objective of this project is to develop and evaluate the feasibility of a sensor-based system for use in the surveillance of physical activity, sedentary behavior, and sleep (SurPASS) at a national level in Denmark. he SurPASS project involves an international, multidisciplinary team of researchers collaborating with an industrial partner. The SurPASS system consists of (1) a thigh-worn accelerometer with Bluetooth connectivity, (2) a smartphone app, (3) an integrated back end, facilitating the automated upload, analysis, storage, and provision of in idualized feedback in a manner compliant with European Union regulations on data privacy, and (4) an administrator web interface (web application) to monitor progress. The system development and evaluation will be performed in 3 phases. These phases will include gathering user input and specifications (phase 1), the iterative development, evaluation, and refinement of the system (phase 2), and the feasibility evaluation (phase 3). he project started in September 2020 and completed phase 2 in February 2022. Phase 3 began in March 2022 and results will be made available in 2023. f feasible, the SurPASS system could be a catalyst toward large-scale, sensor-based surveillance of physical activity, sedentary behavior, and sleep. It could also be adapted for cohort and interventional research, thus contributing to the generation of evidence for both interventions and public health policies and recommendations. ERR1-10.2196/35697
Publisher: Springer Science and Business Media LLC
Date: 06-10-2020
DOI: 10.1186/S12966-020-01029-Z
Abstract: Researchers applying compositional data analysis to time-use data (e.g., time spent in physical behaviors) often face the problem of zeros, that is, recordings of zero time spent in any of the studied behaviors. Zeros hinder the application of compositional data analysis because the analysis is based on log-ratios. One way to overcome this challenge is to replace the zeros with sensible small values. The aim of this study was to compare the performance of three existing replacement methods used within physical behavior time-use epidemiology: simple replacement, multiplicative replacement, and log-ratio expectation-maximization (lrEM) algorithm. Moreover, we assessed the consequence of choosing replacement values higher than the lowest observed value for a given behavior. Using a complete dataset based on accelerometer data from 1310 Danish adults as reference, multiple datasets were simulated across six scenarios of zeros (5–30% zeros in 5% increments). Moreover, four ex les were produced based on real data, in which, 10 and 20% zeros were imposed and replaced using a replacement value of 0.5 min, 65% of the observation threshold, or an estimated value below the observation threshold. For the simulation study and the ex les, the zeros were replaced using the three replacement methods and the degree of distortion introduced was assessed by comparison with the complete dataset. The lrEM method outperformed the other replacement methods as it had the smallest influence on the structure of relative variation of the datasets. Both the simple and multiplicative replacements introduced higher distortion, particularly in scenarios with more than 10% zeros although the latter, like the lrEM, does preserve the ratios between behaviors with no zeros. The ex les revealed that replacing zeros with a value higher than the observation threshold severely affected the structure of relative variation. Given our findings, we encourage the use of replacement methods that preserve the relative structure of physical behavior data, as achieved by the multiplicative and lrEM replacements, and to avoid simple replacement. Moreover, we do not recommend replacing zeros with values higher than the lowest observed value for a behavior.
Publisher: Wiley
Date: 05-07-2020
DOI: 10.1111/SMS.13743
Abstract: The aim of this study was to compare the association between count‐ and activity type–based definitions of light‐intensity physical activity (LIPA) and adiposity markers. A total of 516 Danish workers participated in 1‐4 days of hip‐ and thigh‐based accelerometer measurements. Three definitions of average daily time spent in LIPA were derived: LIPA (1) time spent between 100 and 2029 CPM, LIPA (2) time spent moving and slow walking, and LIPA (3) time spent moving, walking slow, and standing. Adiposity markers were body mass index (BMI), body fat percentage, and waist circumference. The cross‐sectional association between the three LIPA definitions and adiposity markers was analyzed and interpreted using compositional regression models followed by reallocation of time between LIPA, moderate‐to‐vigorous physical activity (MVPA), and sedentary behavior (SB), respectively. The geometric means of daily time (min/day) spent in LIPA 1, LIPA 2, and LIPA 3 were 326, 102, and 274, respectively. We found the direction and strength of the association between the relative importance of daily time spent in LIPA and the adiposity markers to depend on the LIPA definition. For ex le, reallocating 30 minutes from MVPA to LIPA 1, LIPA 2 and LIPA 3 were associated with a 2.97 (95% CI: 0.68 5.27), −0.71 (95% CI: −1.43 0.02), and −0.45 (95% CI: −1.01 0.11) difference in BMI, respectively. Our findings highlight the need for caution when comparing results from studies using different definitions of LIPA.
Publisher: Oxford University Press (OUP)
Date: 27-12-2019
Abstract: Previous research has shown strong associations between occupational physical activity (OPA) and need for recovery (NFR). However this research has only utilized self-reported measures of OPA which may be biased. Thus, there is a need for investigating if the previously documented association between self-reported OPA and NFR can be found when using technical measures of OPA. There is also the need to investigate whether older workers are particularly susceptible to increased NFR, since age-related declines in physical capacity mean that it is likely these workers will have a higher NFR for a given physical activity. The aim of this study was to investigate the association between technically measured OPA and NFR, and whether this relationship is modified by age. This study utilized data from the Danish Physical Activity Cohort with Objective Measurements cohort—comprising Danish workers (n = 840) from the cleaning, manufacturing, and transportation sectors. OPA was measured by accelerometers attached to the thigh and upper back for at least one work day and classified into four physical behaviour categories (sedentary, standing, light, or moderate/vigorous). NFR was measured using a shortened version of the Danish NFR scale. Analysis was conducted using linear regression and isotemporal substitution analyses for compositional data. The overall association between OPA and NFR was statistically significant in the unadjusted model (P & 0.001), but not when adjusted for age, sex, occupation, and shift work (P = 0.166). Isotemporal substitution showed small but significant reductions in NFR when increasing sedentary time relative to other behaviours (adjusted: ΔNFR = −0.010 [−0.019 −0.001]). There were no significant interactions between age and OPA (P = 0.409). This study found significant associations between OPA and NFR, but the effect sizes were small. Reallocating 30 min to sedentary behaviours from other behaviours was associated with a reduced NFR, but the effect size may not be practically relevant. Moreover, no clear modifying effects of age were identified.
Publisher: JMIR Publications Inc.
Date: 06-06-2022
DOI: 10.2196/35697
Abstract: There is increasing recognition of the need for more comprehensive surveillance data, including information on physical activity of all intensities, sedentary behavior, and sleep. However, meeting this need poses significant challenges for current surveillance systems, which are mainly reliant on self-report. The primary objective of this project is to develop and evaluate the feasibility of a sensor-based system for use in the surveillance of physical activity, sedentary behavior, and sleep (SurPASS) at a national level in Denmark. The SurPASS project involves an international, multidisciplinary team of researchers collaborating with an industrial partner. The SurPASS system consists of (1) a thigh-worn accelerometer with Bluetooth connectivity, (2) a smartphone app, (3) an integrated back end, facilitating the automated upload, analysis, storage, and provision of in idualized feedback in a manner compliant with European Union regulations on data privacy, and (4) an administrator web interface (web application) to monitor progress. The system development and evaluation will be performed in 3 phases. These phases will include gathering user input and specifications (phase 1), the iterative development, evaluation, and refinement of the system (phase 2), and the feasibility evaluation (phase 3). The project started in September 2020 and completed phase 2 in February 2022. Phase 3 began in March 2022 and results will be made available in 2023. If feasible, the SurPASS system could be a catalyst toward large-scale, sensor-based surveillance of physical activity, sedentary behavior, and sleep. It could also be adapted for cohort and interventional research, thus contributing to the generation of evidence for both interventions and public health policies and recommendations. DERR1-10.2196/35697
Publisher: JMIR Publications Inc.
Date: 15-04-2023
Abstract: evice-based measurements of physical behavior, using the current methods, place a large burden on participants. The MOTUS system could reduce this burden by removing the necessity for in-person meetings, replacing diaries written on paper with digital diaries, and increasing the automation of feedback generation. o describe the development of the MOTUS system and evaluate the potential of MOTUS to reduce participant burden in a two-phase usability evaluation. OTUS was developed around 1) a thigh-worn accelerometer with Bluetooth data transfer, 2) a smartphone app containing an attachment guide, a digital diary, and facilitating automated data transfer, 3) a cloud infrastructure for data storage, 4) an analysis software to generate feedback for participants, and 5) a web-based app for administrators. We recruited 19 adults (mean age [SD, range] 45 [11, 27-63] years, 11 female) to assist in the two-phase evaluation of MOTUS. In phase one, seven participants evaluated the usability of mockups for a smartphone app. Participants interacted with the app while thinking aloud and any issues raised were classified as critical, serious, or minor, by observers. This information was used to create an improved and functional smartphone app for evaluation in phase two. In phase two, 12 participants completed a 7-day free-living measurement with MOTUS. On day 1, participants attempted 20 system-related tasks under observation, including registration on the study webpage, reading the information letter, downloading and navigating the smartphone app, attaching an accelerometer on the thigh, and completing a diary entry for both work and sleep hours. The success of task completion and any issues encountered were noted by the observer. On completion of the 7-day measurement, participants provided a rating from 0 to 100 on the System Usability Scale and participated in a semi-structured interview aimed at understanding their experience in more detail. ask completion rate was 100% for 13/20 tasks, % for 4/20 tasks, and % for 3/20 tasks. The average rating of system usability was 86 on a 0-100 scale. Thematic analysis indicated that participants perceived the system as easy to use, easy to remember, and subjectively pleasing overall. Participants with shift work reported difficulty with the entry of sleep hours, and 66% of the participants experienced slow data transfer between the app and the cloud infrastructure. Finally, a few participants desired a greater degree of detail in the generated feedback. ur two-phase usability evaluation indicated that MOTUS can reduce the burden of device-based measurements on participants. Issues around the system’s slow data transfer, participants with atypical work shifts, and the degree of automation and detail of generated feedback, should be addressed in future iterations of the MOTUS system. R2-10.2196/35697
Publisher: JMIR Publications Inc.
Date: 15-04-2023
DOI: 10.2196/48209
Location: Denmark
No related grants have been discovered for Patrick Crowley.