Notes

Within search of genomic cherish.
gaps. The Advancing American Kidney Health initiative has the potential to usher in a new era of value-based care for nephrology.
Modern lifestyle is associated with a high prevalence of physical inactivity.

This study aims to investigate the effect of a wearable tracking device on cardiorespiratory fitness among inactive adults and to explore if personal characteristics and health outcomes can predict adoption of the device.

In total, 62 inactive adults were recruited for this study. A control period (4 weeks) was followed by an intervention period (8 weeks) where participants were instructed to register and follow their physical activity (PA) behavior on a wrist-worn tracking device. Data collected included estimated cardiorespiratory fitness, body composition, blood pressure, perceived stress levels, and self-reported adoption of using the tracking device.

In total, 50 participants completed the study (mean age 48, SD 13 years, 84% women). Relative to the control period, participants increased cardiorespiratory fitness by 1.52 mL/kg/minute (95% CI 0.82-2.22; P<.001), self-reported PA by 140 minutes per week (95% CI 93.3-187.1; P<.001), daily step count by 982 (95% CI 492-1471; P<.001), and participants' fat percentage decreased by 0.48% (95% CI -0.84 to -0.13; P=.009). No difference was observed in blood pressure (systolic 95% CI -2.16 to 3.57, P=.63; diastolic 95% CI -0.70 to 2.55; P=.27) or perceived stress (95% CI -0.86 to 1.78; P=.49). No associations were found between adoption of the wearable tracking device and age, gender, personality, or education. selleck chemical However, participants with a low perceived stress at baseline were more likely to rate the use of a wearable tracking device highly motivating.

Tracking health behavior using a wearable tracking device increases PA resulting in an improved cardiorespiratory fitness among inactive adults.
Tracking health behavior using a wearable tracking device increases PA resulting in an improved cardiorespiratory fitness among inactive adults.
Adolescents (10-19 years) are a big segment of the Nigerian population, and they face serious risks to their health and well-being. Maternal mortality is very high in Nigeria, and rates of pregnancy and maternal deaths are high among female adolescents. Rates of HIV infection are rising among adolescents, gender violence and sexual abuse are common, and knowledge about sexual and reproductive health risks is low. Adolescent sexual and reproductive health (ASRH) indicators are worse in the north of the country.

In Bauchi State, northern Nigeria, the project will document the nature and extent of ASRH outcomes and risks, discuss the findings and codesign solutions with local stakeholders, and measure the short-term impact of the discussions and proposed solutions.

The participatory research project is a sequential mixed-methods codesign of a pragmatic cluster randomized controlled trial. Focus groups of local stakeholders (female and male adolescents, parents, traditional and religious leaders, service prssess its impact qualitatively.

Focus groups to explore ASRH concerns of stakeholders began in October 2021. Baseline data collection in the household survey is expected to take place in mid-2022. The study was approved by the Bauchi State Health Research Ethics Committee, approval number NREC/03/11/19B/2021/03 (March 1, 2021), and by the Faculty of Medicine and Health Sciences Institutional Review Board McGill University (September 13, 2021).

Evidence about factors related to ASRH outcomes in Nigeria and implementation and testing of a dialogic intervention to improve these outcomes will fill a gap in the literature. The project will document and test the effectiveness of a participatory approach to ASRH intervention research.

ISRCTN Registry ISRCTN18295275; https//www.isrctn.com/ISRCTN18295275.

DERR1-10.2196/36060.
DERR1-10.2196/36060.
The digital divide refers to technological disparities based on demographic characteristics (eg, race and ethnicity). Lack of physical access to the internet inhibits online health information seeking (OHIS) and exacerbates health disparities. Research on the digital divide examines where and how people access the internet, whereas research on OHIS investigates how intersectional identities influence OHIS. We combine these perspectives to explicate how unique context-device access pairings operate differently across intersectional identities-particularly racial and ethnic groups-in the domain of OHIS.

This study aims to examine how different types of internet access relate to OHIS for different racial and ethnic groups. We investigate relationships among predisposing characteristics (ie, age, sex, education, and income), internet access (home computer, public computer, work computer, and mobile), health needs, and OHIS.

Analysis was conducted using data from the 2019 Health Information National Trends Serventions with an intersectional approach to access to ameliorate the impact of the digital divide.
Similar to many low- and middle-income countries, Botswana has identified eHealth as a means of improving health care service provision and delivery. The National Malaria Programme (NMP) in Botswana has implemented the District Health Information System version 2 (DHIS2) to support timely malaria case reporting across its 27 health districts; however, the implementation of an eHealth system is never without challenges. Barriers to the implementation of eHealth innovations within health care settings may arise at the individual or organizational levels. As such, the evaluation of user perceptions of the technology is an important step that can inform its sustainable implementation. The DHIS2 was implemented without evaluating user perceptions beforehand; therefore, the Botswana Ministry of Health and Wellness was uncertain about the likelihood of acceptance and use of the platform.

We aimed to determine the acceptance of the DHIS2 platform by the NMP in Botswana to gauge whether adoption would be successfuram in Botswana.
Participants' responses indicated their acceptance of the DHIS2 platform; however, the consideration of factors related to organizational readiness could further enhance successful acceptance, and consequently, successful adoption of the platform by the malaria program in Botswana.
The full potential of eHealth technologies to support self-management and disease management for patients with chronic diseases is not being reached. A possible explanation for these lacking results is that during the development process, insufficient attention is paid to the needs, wishes, and context of the prospective end users. To overcome such issues, the user-centered design practice of creating personas is widely accepted to ensure the fit between a technology and the target group or end users throughout all phases of development.

In this study, we integrate several approaches to persona development into the Persona Approach Twente to attain a more holistic and structured approach that aligns with the iterative process of eHealth development.

In 3 steps, a secondary analysis was carried out on different parts of the data set using the Partitioning Around Medoids clustering method. First, we used health-related electronic patient record data only. Second, we added person-related data that were gatenges lie in data quality and fitness for (quantitative) clustering.
Concomitant psychological and cognitive impairments modulate nociceptive processing and contribute to chronic low back pain (CLBP) maintenance, poorly correlated with radiological findings. Clinical practice guidelines recommend self-management and multidisciplinary educational and exercise-based interventions. However, these recommendations are based on self-reported measurements, which lack evidence of related electrophysiological changes. Furthermore, current mobile health (mHealth) tools for self-management are of low quality and scarce evidence. Thus, it is necessary to increase knowledge on mHealth and electrophysiological changes elicited by current evidence-based interventions.

The aim of this study is to investigate changes elicited by a self-managed educational and exercise-based 4-week mHealth intervention (BackFit app) in electroencephalographic and electrocardiographic activity, pressure pain thresholds (PPTs), pain, disability, and psychological and cognitive functioning in CLBP versus the sarch will be needed. Nevertheless, to the best of our knowledge, this is the first study reporting electroencephalographic changes in patients with CLBP after an mHealth intervention.

ClinicalTrials.gov NCT04576611; https//clinicaltrials.gov/ct2/show/NCT04576611.
ClinicalTrials.gov NCT04576611; https//clinicaltrials.gov/ct2/show/NCT04576611.
Artificial intelligence and digital health care have substantially advanced to improve and enhance medical diagnosis and treatment during the prolonged period of the COVID-19 global pandemic. In this study, we discuss the development of prediction models for the self-diagnosis of polycystic ovary syndrome (PCOS) using machine learning techniques.

We aim to develop self-diagnostic prediction models for PCOS in potential patients and clinical providers. For potential patients, the prediction is based only on noninvasive measures such as anthropomorphic measures, symptoms, age, and other lifestyle factors so that the proposed prediction tool can be conveniently used without any laboratory or ultrasound test results. For clinical providers who can access patients' medical test results, prediction models using all predictor variables can be adopted to help health providers diagnose patients with PCOS. We compare both prediction models using various error metrics. We call the former model the patient model and It will enable women to conveniently access the platform at home without delay before they seek further medical care. Clinical providers can also use the proposed prediction tool to help diagnose PCOS in women.
Sick leave due to common mental disorders (CMDs) is a public health problem in several countries, including Sweden. Given that symptom relief does not necessarily correspond to return to work, health care interventions focusing on factors that have proven important to influence the return to work process, such as self-efficacy, are warranted. Self-efficacy is also a central concept in person-centered care.

The aim of this study is to evaluate the effects of a person-centered eHealth intervention for patients on sick leave due to CMDs.

A randomized controlled trial of 209 patients allocated to either a control group (107/209, 51.2%) or an intervention group (102/209, 48.8%) was conducted. The control group received usual care, whereas the intervention group received usual care with the addition of a person-centered eHealth intervention. The intervention was built on person-centered care principles and consisted of telephone support and a web-based platform. The primary outcome was a composite score of chd not affect the level of sick leave.

A person-centered eHealth intervention for patients on sick leave due to CMDs improved GSE but did not affect the level of sick leave.

ClinicalTrials.gov NCT03404583; https//clinicaltrials.gov/ct2/show/NCT03404583.
ClinicalTrials.gov NCT03404583; https//clinicaltrials.gov/ct2/show/NCT03404583.
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