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BackgroundImplementation and process evaluation is vital for understanding how interventions function in different settings, including if and why interventions have different effects or do not work at all. ObjectiveThis paper presents the protocol for an implementation and process evaluation embedded in a multicenter randomized controlled trial conducted in Denmark and Norway (the selfBACK project). selfBACK is a data-driven decision support system that provides participants with weekly self-management plans for low back pain. These plans are delivered through a smartphone app and tailored to individual participants by using case-based reasoning methodology. In the trial, we compare selfBACK in addition to usual care with usual care alone. MethodsThe aim of this study is to conduct a convergent mixed-methods implementation and process evaluation of the selfBACK app by following the reach, effectiveness, adoption, implementation, and maintenance framework. We will evaluate the process of implementing selfBACK and investigate how participants use the intervention in daily life. The evaluation will also cover the reach of the intervention, health care provider willingness to adopt it, and participant satisfaction with the intervention. We will gather quantitative measures by questionnaires and measures of data analytics on app use and perform a qualitative exploration of the implementation using semistructured interviews theoretically informed by normalization process theory. Data collection will be conducted between March 2019 and October 2020. ResultsThe trial opened for recruitment in February 2019. This mixed-methods implementation and evaluation study is embedded in the randomized controlled trial and will be collecting data from March 2019 to October 2020; dissemination of trial results is planned thereafter. The results from the process evaluation are expected 2021-2022. ConclusionsThis study will provide a detailed understanding of how self-management of low back pain can be improved and how a digital health intervention can be used as an add-on to usual care to support patients to self-manage their low back pain. We will provide knowledge that can be used to explore the possibilities of extending the generic components of the selfBACK system and key drivers that could be of use in other conditions and diseases where self-management is an essential prevention or treatment strategy. Trial RegistrationClinicalTrials.gov NCT03798288; https://www.clinicaltrials.gov/ct2/show/NCT03798288 International Registered Report Identifier (IRRID)DERR1-10.2196/20308

BackgroundTo measure sustainable improvements in the work environment, a flexible and highly responsive tool is needed that will give important focus to the implementation process. A digital checklist was developed in collaboration with key stakeholders to document the implementation of changes in eldercare sector workplaces. ObjectiveThis paper describes the study protocol of a dissemination study that aims to examine when, why, and how the digital checklist is spread to the Danish eldercare sector following a national campaign particularly targeting nursing homes and home care. MethodsThis prospective observational study will use quantitative data from Google Analytics describing use of the checklist as documented website engagement, a survey among members in the largest union in the sector, information from a central business register, and monitoring of campaign activities. The evaluation will be guided by the five elements of the RE-AIM framework: reach, effectiveness, adoption, implementation, and maintenance. ResultsThe study was approved in June 2016 and began in October 2018. The campaign that is the foundation for the evaluation began in 2017 and ended in 2018. However, the webpage where we collect data is still running. Results are expected in 2020. ConclusionsThis protocol provides a working example of how to evaluate dissemination of a checklist to improve implementation of work environment initiatives in the eldercare sector in Denmark. To our knowledge, implementation in a nationwide Danish work environment has not been previously undertaken. Given that the checklist is sector-specific for work environment initiatives and developed through systematic collaboration between research and practice, it is likely to have high utility and impact; however, the proposed evaluation will determine this. This study will advance dissemination research and, in particular, the evaluation of the impact of these types of studies. Finally, this study advances the field through digital tools that can be used for evaluation of dissemination efforts (eg, Google Analytics associated with website) in the context of a rigorous research design activity. International Registered Report Identifier (IRRID)DERR1-10.2196/16039

Background: Poor health in passenger rail drivers, resulting from perceived highly sedentary work and leisure time, has implications for public safety. To date, no studies have described the physical behaviors of passenger rail drivers. This study aimed to characterize the physical behaviors of passenger rail drivers by investigating the volume, pattern, variation, and composition of behaviors at and outside of work. Methods: A convenience sample of 31 rail drivers (77% male, median age 51.0 [12.5] y) in South Australia wore an activity monitor on their right thigh for 8 days and completed a work logbook. Physical behaviors (sitting, standing, light-intensity physical activity, moderate- to vigorous-intensity physical activity [MVPA], and steps) were recorded for workdays and nonworkdays, and work and nonwork time on workdays. The volume, bouts, between-participants variation, and 3-way composition were compared across the 4 time periods. Results: Drivers sat for 10.6 (1.5) hours, did 76.3 (38.8) minutes of MVPA, and took 9727.3 (4088.4) steps daily. At work, drivers were sitting 369.3 (41.8) minutes (187.1 [54.2] min in prolonged bouts) and doing MVPA 31.7 (10.0) minutes. Between-participants variation in sitting time during work (11%) was lower than both nonwork on a workday (19%) and on a nonworkday (24%; P <.001). Compositions at work differed from nonwork on workdays (F = 27.7, P <.001), as did compositions on workdays compared with nonworkdays (F = 6.8, P =.002). Conclusions: Passenger rail drivers were highly sedentary, but also surprisingly active. At work, drivers were more sedentary and had lower variation in behaviors, suggesting work constraints play an important role. Therefore, work may be the most appropriate domain to intervene for promoting healthy physical behavior profiles among these passenger rail drivers. [ABSTRACT FROM AUTHOR]

Background: The ActiPASS software was developed from the open-source Acti4 activity classification algorithm for thigh-worn accelerometry. However, the original algorithm has not been validated in children or compared with a child-specific set of algorithm thresholds. This study aims to evaluate the accuracy of ActiPASS in classifying activity types in children using 2 published sets of Acti4 thresholds. Methods: Laboratory and free-living data from 2 previous studies were used. The laboratory condition included 41 school-aged children (11.0 [4.8] y; 46.5% male), and the free-living condition included 15 children (10.0 [2.6] y; 66.6% male). Participants wore a single accelerometer on the dominant thigh, and annotated video recordings were used as a reference. Postures and activity types were classified with ActiPASS using the original adult thresholds and a child-specific set of thresholds. Results: Using the original adult thresholds, the mean balanced accuracy (95% CI) for the laboratory condition ranged from 0.62 (0.56–0.67) for lying to 0.97 (0.94–0.99) for running. For the free-living condition, accuracy ranged from 0.61 (0.48–0.75) for lying to 0.96 (0.92–0.99) for cycling. Mean balanced accuracy for overall sedentary behavior (sitting and lying) was ≥0.97 (0.95–0.99) across all thresholds and conditions. No meaningful differences were found between the 2 sets of thresholds, except for superior balanced accuracy of the adult thresholds for walking under laboratory conditions. Conclusions: The results indicate that ActiPASS can accurately classify different basic types of physical activity and sedentary behavior in children using thigh-worn accelerometer data. [ABSTRACT FROM AUTHOR]

Background: ActiMotus, a thigh-accelerometer-based software used for the classification of postures and movements (PaMs), has shown high accuracy among adults and school-aged children; however, its accuracy among younger children and potential differences between sexes are unknown. This study aimed to evaluate the accuracy of ActiMotus to measure PaMs among children between 3 and 14 years and to assess if this was influenced by the sex or age of children. Method: Forty-eight children attended a structured ~1-hour data collection session at a laboratory. Thigh acceleration was measured using a SENS accelerometer, which was classified into nine PaMs using the ActiMotus software. Human-coded video recordings of the session provided the ground truth. Results: Based on both F1 scores and balanced accuracy, the highest levels of accuracy were found for lying, sitting, and standing (63.2–88.2%). For walking and running, accuracy measures ranged from 48.0 to 85.8%. The lowest accuracy was observed for classifying stair climbing. We found a higher accuracy for stair climbing among girls compared to boys and for older compared to younger age groups for walking, running, and stair climbing. Conclusions: ActiMotus could accurately detect lying, sitting, and standing among children. The software could be improved for classifying walking, running, and stair climbing, particularly among younger children. [ABSTRACT FROM AUTHOR]

The clear public messaging from international health authorities is that individuals should "sit less and move more." While it is acknowledged that this guidance needs to be tailored to the age of people and also to their health, and abilities, the guidance is not tailored to their current level of physical behaviors. This opinion piece aims to highlight that although people with excessive sitting and insufficient moderate-to-vigorous physical activity should sit more and move less, for other people their health would be promoted by sitting more and moving less. Thus, physical behaviors are not always "poison" or "medicine," but rather the health impact of changes in physical behaviors depends on people's initial levels. Policy, research, and practice implications of this realization are presented. Only tailoring messaging to age and health status could be far from optimal for people with very different current levels of physical behaviors. Policy, research, and practice will be enhanced when the potential for physical behaviors to be either health hindering or health promoting is adequately considered. [ABSTRACT FROM AUTHOR]

Background: Transferrin receptor 1 (TfR1), glucose transporter 1 (GLUT1), and CD98hc are candidates for targeted therapy at the blood–brain barrier (BBB). Our objective was to challenge the expression of TfR1, GLUT1, and CD98hc in brain capillaries using the histone deacetylase inhibitor (HDACi) valproic acid (VPA). Methods: Primary mouse brain capillary endothelial cells (BCECs) and brain capillaries isolated from mice injected intraperitoneally with VPA were examined using RT-qPCR and ELISA. Targeting to the BBB was performed by injecting monoclonal anti-TfR1 (Ri7217)-conjugated gold nanoparticles measured using ICP-MS. Results: In BCECs co-cultured with glial cells, Tfrc mRNA expression was significantly higher after 6 h VPA, returning to baseline after 24 h. In vivo Glut1 mRNA expression was significantly higher in males, but not females, receiving VPA, whereas Cd98hc mRNA expression was unaffected by VPA. TfR1 increased significantly in vivo after VPA, whereas GLUT1 and CD98hc were unchanged. The uptake of anti-TfR1-conjugated nanoparticles was unaltered by VPA despite upregulated TfR expression. Conclusions: VPA upregulates TfR1 in brain endothelium in vivo and in vitro. VPA does not increase GLUT1 and CD98hc proteins. The increase in TfR1 does not result in higher anti-TfR1 antibody targetability, suggesting targeting sufficiently occurs with available transferrin receptors without further contribution from accessory VPA-induced TfR1. [ABSTRACT FROM AUTHOR]

The role and potential impact of digital screen technology in the lives of children is heavily debated. Current evidence is limited by the weakness of measures typically used to characterise screen use, predominantly proxy- or self-reports with known inaccuracy and bias. However, robust and detailed evidence is needed to provide practical trustworthy guidance to families and professionals working with families. The purpose of this paper is to support researchers to select measurement method(s) that will provide robust and detailed evidence. The paper outlines the challenges in measuring contemporary screen use by children, using a child–technology interaction model to organise considerations. A range of different methods used to measure digital screen technology use in children and adolescents (i.e., questionnaires, diaries, electronically prompted sampling, direct observation, fixed room cameras, wearable/portable cameras, audio recorders, screen-device onboard logging, remote digital trace logging and proximity logging) are described along with examples of their use and constructs typically measured as well as a summary of the advantages and disadvantages of each method. A checklist and worked examples are provided to support researchers determining the best methods or combination of methods for a research project. [ABSTRACT FROM AUTHOR]