Search

PurposeThe impact of a sedentary lifestyle on health and well-being is well recognized. However, there is limited understanding of how a lifetime of physical activity and sedentary behaviour influences an active lifestyle in older adults. The aim of this study was to describe how lived experience of physical activity and sedentary behaviour impacts daily activities among older adults, from a life course perspective.MethodsQualitative content analysis was used; individual telephone interviews were conducted with fourteen older adults aged 71 to 92 years. The participants received initial support from community care and lived in ordinary housing in southern Sweden.ResultsThe interviews yielded one theme, "Navigating with an embodied activity compass," and two sub-themes: "Being guided by the past" and "Unveiling pathways through body awareness."ConclusionsOur study highlights how older adults' lived experiences of physical activity, with their connections to body awareness and acceptance, impact daily physical activity. These findings offer new knowledge for clinical practitioners balancing recommendations of sedentary behaviour and physical activity, to promote healthy daily physical activity among older adults. Future research and policies should consider the lived experiences of older adults when addressing public health matters related to sedentary behaviour and physical activity.

Background: Many studies have identified key factors affecting the rates of engagement in physical activity in older adults with chronic disease. Environmental conditions, such as weather variations, can present challenges for individuals with chronic diseases, such as type 2 diabetes when engaging in physical activity. However, few studies have investigated the influence of weather on daily steps in people with chronic diseases, especially those with prediabetes and type 2 diabetes. Objective: This study investigated the association between weather variations and daily self-monitored step counts over two years among individuals with prediabetes and type 2 diabetes in Sweden. Methods: The study is a secondary analysis using data from the Sophia Step Study, aimed at promoting physical activity among people with prediabetes and type 2 diabetes, which recruited participants from two urban primary care centers in Stockholm and one rural primary care center in southern Sweden over eight rounds. This study measured physical activity using step counters (Yamax Digiwalker SW200) and collected self-reported daily steps. Environmental factors such as daily average temperature, precipitation, and hours of sunshine were obtained from the Swedish Meteorological and Hydrological Institute. A robust linear mixed-effects model was applied as the analysis method. Results: There was no association found between weather variations and the number of steps taken on a daily basis. The analysis indicated that only 10% of the variation in daily steps could be explained by the average temperature, precipitation, and sunshine hours after controlling for age, gender, and BMI. Conversely, individual factors explained approximately 38% of the variation in the observations. Conclusion: This study revealed that there was no association between weather conditions and the number of daily steps reported by individuals with prediabetes and type 2 diabetes taking part in a physical activity interventi

Purpose: In vivo confocal microscopy (IVCM) of the cornea is a valuable tool for clinical assessment of the cornea but does not provide stand-alone diagnostic support. The aim of this work was to develop an artificial intelligence (AI)-based decision-support system (DSS) for automated diagnosis of Acanthamoeba keratitis (AK) using IVCM images. Methods: The automated workflow for the AI-based DSS was defined and implemented using deep learning models, image processing techniques, rule-based decisions, and valuable input from domain experts. The models were evaluated with 5-fold-cross validation on a dataset of 85 patients (47,734 IVCM images from healthy, AK, and other disease cases) collected at a single eye clinic in Sweden. The developed DSS was validated on an additional 26 patients (21,236 images). Results: Overall, the DSS uses as input raw unprocessed IVCM image data, successfully separates artefacts from true images (93% accuracy), then classifies the remaining images by their corneal layer (90% accuracy). The DSS subsequently predicts if the cornea is healthy or diseased (95% model accuracy). In disease cases, the DSS detects images with AK signs with 84% accuracy, and further localizes the regions of diagnostic value with 76.5% accuracy. Conclusions: The proposed AI-based DSS can automatically and accurately preprocess IVCM images (separating artefacts and sorting images into corneal layers) which decreases screening time. The accuracy of AK detection using raw IVCM images must be further explored and improved. Translational Relevance: The proposed automated DSS for experienced specialists assists in diagnosing AK using IVCM images.

Objective: This study explored healthcare quality issues affecting the reporting and investigation levels of digital incidentreporting systems. Methods: A total of 38 health information technology-related incident reports (free-text narratives) were collected from oneof Sweden’s national incident reporting repositories. The incidents were analysed using an existing framework, i.e., theHealth Information Technology Classification System, to identify the types of issues and consequences. The frameworkwas applied in two fields, ‘event description’ by the reporters and ‘manufacturer’s measures’, to assess the quality of report-ing incidents by the reporters. Additionally, the contributing factors, i.e., either human or technical factors for both fields,were identified to evaluate the quality of the reported incidents. Results: Five types of issues were identified and changes made between before-and-after investigations: Machine to soft-ware-related issues (n = 8), machine to use-related issues (n = 5), software to software-related issues (n = 5), use to soft-ware-related issues (n = 4) and use to use-related issues (n = 1). Over two-thirds (n = 15) of the incidents demonstrated achange in the contributing factors after the investigation. Only four incidents were identified as altering the consequencesafter the investigation. Conclusion: This study shed some light on the issues of incident reporting and the gap between the reporting and investi-gation levels. Facilitating sufficient staff training sessions, agreeing on common terms for health information technology sys-tems, refining the existing classifications systems, enforcing mini-root cause analysis, and ensuring unit-based localreporting and standard national reporting may help bridge the gap between reporting and investigation levels in digitalincident reporting.

Background: The trend of an exponential increase in prediabetes and type 2 diabetes (T2D) is projected to continue rising worldwide. Physical activity could help prevent T2D and the progression and complications of the disease. Therefore, we need to create opportunities for individuals to acquire the necessary knowledge and skills to self-manage their chronic condition through physical activity. eHealth is a potential resource that could facilitate self-management and thus improve population health. However, there is limited research on users’ perception of eHealth in promoting physical activity in primary care settings. Objective: This study aims to explore the perspectives of health care professionals and individuals with prediabetes and T2D on eHealth to promote physical activity in primary care. Methods: A qualitative approach was applied using focus group discussions among individuals with prediabetes or T2D (14 participants in four groups) and health care professionals (10 participants in two groups). The discussions were audio-recorded and transcribed verbatim. Qualitative content analysis was used inductively to code the data. Results: Three main categories emerged: utility, adoption process, and accountability. The utility of eHealth was described as a motivational, entertaining, and stimulating tool. Registration of daily medical measurements and lifestyle parameters in a cohesive digital platform was recognized as a potential resource for strengthening self-management skills. The adoption process includes eHealth to increase the accessibility of care and personalize the support of physical activity. However, participants stated that digital technology might only suit some and could increase health care providers’ administrative burden. Accountability refers to the knowledge and skills to optimize eHealth and ensure data integrity and security. Conclusions: People with prediabetes and T2D and health care professionals positively viewed an integration of eH

Objective: This study explored the Swedish digital health testbeds through the lens of complexity science. Methods: The purposive sampling was used to identify 38 digital health testbed organizations to conduct interviews in written or audio-conferencing. The interview responses were aggregated and analyzed using thematic analysis. The themes were mainly generated through complexity theory and the principles of complex adaptive systems. Results: Fifteen testbed organizations responded, comprising 13 written responses and two audio-conferencing. Five maintheoretical themes were generated: agents and diversity, connections and communication, adaptation and learning, perturbations,and path dependence. Agents and diversity depicted different types of testbeds, stakeholders and innovation, and the primary function and purpose of the testbeds. Various factors enhancing connections and communications among multiple stakeholders were identified, such as the quality of e-health solutions and the 2030 Agenda for Sustainable Development. Some adaptation and learning factors, such as internal reorganization, sharing and creating learning opportunities, and additional funding, guaranteed the sustainability of testbeds. Perturbations were characterized by two factors: non-linear interactions – lack of commitment and transparency in stakeholders’ engagement, and uncertainty about testbed definitions and concepts. Path dependence highlighted the importance of history, such as previous positive and negative experiences. Conclusion: This study provided insights into testbeds’ organization, their functions, how various aspects were challenged,and how they adapted to overcome and improve the system issues. Identifying the stakeholders and relevant factors, commissioning an evaluation, backing up with a contingency plan, securing adequate funding, and disseminating the findings can improve the testbeds’ design and implementation., eHealth Arena

Objective It has been suggested that the mechanism behind cardiac troponin elevation after strenuous exercise is passage through a cell membrane with changed permeability rather than myocardial cell death. We hypothesised that an increase of cardiac specific myosin heavy chain-alpha (MHC-α; 224 kDa compared with cardiac troponin T’s (cTnT) 37 kDa) could hardly be explained by passage through a cell membrane. Methods Blood samples were collected from 56 athletes (15 female, age 42.5±9.7, range 24–70 years) before, directly after and on days 1–8 after an Ironman. Biomarkers (C reactive protein (CRP), cTnT, creatinekinase (CK), MHC-α, myoglobin (MG), creatinine (C) and N-terminal prohormone of brain natriuretic peptide (NTproBNP) were measured. Results The course of MHC-α concentration (μg/L) was 1.33±0.53 (before), 2.57±0.78 (directly after), 1.51±0.53 (day 1), 2.74±0.55 (day 4) and 1.83±0.76 (day 6). Other biomarkers showed a one-peaked increase with maximal values either directly after the race or at day 1: cTnT 76 ±80 ng/L (12–440; reference<15), NT-proBNP 776±684 ng/L (92–4700; ref.<300), CK 68±55 μkat/L (5–280; ref.<1.9), MG 2088±2350 μg/L (130–17 000; ref.<72) and creatinine 100±20 μmol/L (74–161; ref.<100), CRP 49±23 mg/L(15–119; ref.<5). Conclusion MHC-α exhibited a two-peaked increase which could represent a first release from the cytosolic pool and later from cell necrosis. This is the first investigation of MHC-α plasma concentration afterexercise.

Accelerometrar används i stor utsträckning inom forskning och i viss grad i klinisk verksamhet för att fastställa fysisk aktivitet, men de ställer krav på användarna. God kännedom krävs om utformning av mätprotokoll och bearbetning av rådata till användbara mått, som kan användas i lämpliga statistiska analyser för att undvika mätfel. Mätfel medför felskattning av den fysiska aktiviteten, uteblivna gruppskillnader, försvagade samband med hälsa och felaktiga slutsatser om interventionseffekter. Mätning av fysisk aktivitet i klinisk verksamhet främjas genom samarbete mellan kliniskt verksamma, kliniska forskare och forskare med metodologisk kompetens inom fysisk aktivitetsmätning.

The development of accelerometers has revolutionized measurement of physical activity, and they are used to a large extent in research and have started to be implemented into clinical settings. However, achievement of reliable outcomes requires good methodological knowledge and skills by the user. Otherwise, significant measurement errors may occur, interfering with assessment of the physical activity level in the population, group differences, associations with health parameters or effect of treatments. This paper by the Swedish Network for Objective Measurement of Movement (NORM) provides an overview of physical activity measurement including sections of data collection, processing of raw data into useful metrics and statistical analysis. It targets users of accelerometer in research, health care and national surveys., Mätning av det dagliga aktivitetsmönstret

Purpose: The purpose of this study was to test the hypothesis that the ”outdoors” has an added health effect on top of that of physical activity. This hypothesis is based on the fairly extensive volume of evidens suggesting that the outdoor environment is beneficial for overall health. We, however, consider most previous studies insufficiently designed in order to draw causal relationship between spending time outdoors and examined health parameters. In this study we state that our experimental design allows us to do just that. Methods: In this randomized cross-over experimental design, 49 healthy subjects (+65 years, 27 female) performed a standardized submaximal bike ergometer test in three different environments (indoors, simulated outdoors and outdoors). The test consisted of 20 minutes cycling and subjects were instructed to stay between 11-13 at the Borg RPE scale (i.e. moderate intensity). Each test was followed by two hours of passive recovery. We measured power output, heart rate, lactate and counts of five fractions (lymphocytes, monocytes, neutrophiles, basophiles and eosinophiles) of white blood cells (leukocytes) in circulation. Results: Our results revealed that the outdoor treatment resulted in higher levels of lactate, higher heart rate and higher power output despite that there were no differences in Borg RPE-rating between the treatments. The white blood cell analysis showed an increase of circulating leukocytes in almost all fractions immediately post exercise in all treatments. Numbers decreased rapidly post exercise and the lymphocyte numbers stayed well under baseline for more than one hour during recovery. This is referred to as an “open window” where the immune function is temporarily suppressed and there is an elevated risk of infection of primarily URTI. Conclusions: Our results not only suggest that exercise is more efficient out of doors such that more exercise/effort is obtained but also that recovery outdoors may be a way to decrease t