Notes

CRISPR/Cas9 mediated age group of an iPSC line EHTJUi005-A-1 together with homozygous knockout with the SUV39H1 gene.
ring the cost of insulin.
The rising prevalence of gestational diabetes mellitus (GDM) calls for the use of innovative methods to inform and empower these pregnant women. An information chatbot, Dina, was developed for women with GDM and is Norway's first health chatbot, integrated into the national digital health platform.

The aim of this study is to investigate what kind of information users seek in a health chatbot providing support on GDM. Furthermore, we sought to explore when and how the chatbot is used by time of day and the number of questions in each dialogue and to categorize the questions the chatbot was unable to answer (fallback). The overall goal is to explore quantitative user data in the chatbot's log, thereby contributing to further development of the chatbot.

An observational study was designed. We used quantitative anonymous data (dialogues) from the chatbot's log and platform during an 8-week period in 2018 and a 12-week period in 2019 and 2020. Dialogues between the user and the chatbot were the unit of anal that the chatbot is used to quickly access information already provided for them by the health care service but providing a low-threshold way to access that information. Our results underline the need to actively promote and integrate the chatbot into antenatal care as well as the importance of continuous content improvement in order to provide relevant information.
Frequently asked questions seem to mirror the cornerstones of GDM treatment and may indicate that the chatbot is used to quickly access information already provided for them by the health care service but providing a low-threshold way to access that information. Our results underline the need to actively promote and integrate the chatbot into antenatal care as well as the importance of continuous content improvement in order to provide relevant information.
Early detection of dementia is critical for intervention and care planning but remains difficult. Computerized cognitive testing provides an accessible and promising solution to address these current challenges.

The aim of this study was to evaluate a computerized cognitive testing battery (BrainCheck) for its diagnostic accuracy and ability to distinguish the severity of cognitive impairment.

A total of 99 participants diagnosed with dementia, mild cognitive impairment (MCI), or normal cognition (NC) completed the BrainCheck battery. Statistical analyses compared participant performances on BrainCheck based on their diagnostic group.

BrainCheck battery performance showed significant differences between the NC, MCI, and dementia groups, achieving 88% or higher sensitivity and specificity (ie, true positive and true negative rates) for separating dementia from NC, and 77% or higher sensitivity and specificity in separating the MCI group from the NC and dementia groups. Three-group classification found true positive rates of 80% or higher for the NC and dementia groups and true positive rates of 64% or higher for the MCI group.

BrainCheck was able to distinguish between diagnoses of dementia, MCI, and NC, providing a potentially reliable tool for early detection of cognitive impairment.
BrainCheck was able to distinguish between diagnoses of dementia, MCI, and NC, providing a potentially reliable tool for early detection of cognitive impairment.
In obesity management, whether patients lose ≥5% of their initial weight is a critical factor in clinical outcomes. However, evaluations that take only this approach are unable to identify and distinguish between individuals whose weight changes vary and those who steadily lose weight. Evaluation of weight loss considering the volatility of weight changes through a mobile-based intervention for obesity can facilitate understanding of an individual's behavior and weight changes from a longitudinal perspective.

The aim of this study is to use a machine learning approach to examine weight loss trajectories and explore factors related to behavioral and app use characteristics that induce weight loss.

We used the lifelog data of 13,140 individuals enrolled in a 16-week obesity management program on the health care app Noom in the United States from August 8, 2013, to August 8, 2019. We performed k-means clustering with dynamic time warping to cluster the weight loss time series and inspected the quality of ct app. Overall adherence and early adherence related to self-monitoring emerged as potential predictors of these trajectories.
Using a machine learning approach and clustering shape-based time series similarities, we identified 5 weight loss trajectories in a mobile weight management app. Overall adherence and early adherence related to self-monitoring emerged as potential predictors of these trajectories.[This corrects the article DOI 10.2196/32165.].
Children with acute and chronic illness undergo frequent, painful, and distressing procedures.

This randomized controlled trial was used to evaluate the effectiveness of guided imagery (GI) versus virtual reality (VR) on the procedural pain and state anxiety of children and young adults undergoing unsedated procedures. We explored the role of trait anxiety and pain catastrophizing in intervention response.

Children and young adults were recruited from the hematology, oncology, and blood and marrow transplant clinics at a children's hospital. Each study participant completed the GI and VR intervention during separate but consecutive unsedated procedures. Self-report measures of pain and anxiety were completed before and after the procedures.

A total of 50 participants (median age 13 years) completed both interventions. GI and VR performed similarly in the management of procedural pain. click here Those with high pain catastrophizing reported experiencing less nervousness about pain during procedures that used VR than those using GI. State anxiety declined pre- to postprocedure in both interventions; however, the decrease reached the level of significance during the VR intervention only. Those with high trait anxiety had less pain during GI.

In our sample, VR worked as well as GI to manage the pain and distress associated with common procedures experienced by children with acute or chronic illnesses. Children who are primed for pain based on beliefs about pain or because of their history of chronic pain had a better response to VR. GI was a better intervention for those with high trait anxiety.

ClinicalTrials.gov NCT04892160; https//clinicaltrials.gov/ct2/show/NCT04892160.
ClinicalTrials.gov NCT04892160; https//clinicaltrials.gov/ct2/show/NCT04892160.
Shared decision-making is an essential principle for the prevention of cardiovascular disease (CVD), where asymptomatic people consider lifelong medication and lifestyle changes.

This study aims to develop and evaluate the first literacy-sensitive CVD prevention decision aid (DA) developed for people with low health literacy, and investigate the impact of literacy-sensitive design and heart age.

We developed a standard DA based on international standards. The standard DA was based on our existing general practitioner DA. The literacy-sensitive DA included simple language, supporting images, white space, and a lifestyle action plan. The control DA used Heart Foundation materials. A randomized trial included 859 people aged 45-74 years using a 3 (DA standard, literacy-sensitive, control) ×2 (heart age heart age + percentage risk, percentage risk only) factorial design, with outcomes including prevention intentions and behaviors, gist and verbatim knowledge of risk, credibility, emotional response, and dece lifestyle change intentions or behavior but did affect psychological outcomes, consistent with previous findings. This tool will be integrated with additional resources to improve other lifestyle outcomes.

Australian New Zealand Clinical Trials Registry ACTRN12620000806965; https//tinyurl.com/226yhk8a.
Australian New Zealand Clinical Trials Registry ACTRN12620000806965; https//tinyurl.com/226yhk8a.
Health care access issues have long plagued rural Americans. One approach to alleviating the challenges and poor health outcomes for rural individuals is through the use of telemedicine, sometimes called telehealth. It is important to understand factors that may be related to telemedicine adoption or nonadoption, particularly in underserved rural settings.

This pilot study examines telemedicine perceptions among rural, underserved populations using the Technology Acceptance Model, which serves as a framework to explore the adoption of telemedicine services by those who have used it. This study also explores the differences between user and nonuser perceptions of telemedicine.

Paper surveys and phone interviews were conducted in rural Northern Lower Michigan.

Perceived usefulness and perceived ease of use explained 91% of the variability in attitude toward telemedicine (R
=0.91; F
=73.406; P<.001). Ease of use was a significant predictor (mean 2.36, SD 1.20; P<.001), but usefulness (mean 3.16, SD 0.81; P=.20) was not. Furthermore, there were significant differences in individual perception of telemedicine between users and nonusers. For example, nonusers believed they would receive better care in person (users mean 3.30, SD 1.22; nonusers mean 1.91, SD 1.14; F
=10.126; P=.003). The quantitative findings were reinforced by the qualitative results from the phone interviews.

Overall, the Technology Acceptance Model is an appropriate model to understand the attitudes toward telemedicine that may lead to its adoption by rural Americans.
Overall, the Technology Acceptance Model is an appropriate model to understand the attitudes toward telemedicine that may lead to its adoption by rural Americans.
Clinicians need to be able to assess the quality of the available information to aid clinical decision-making. The internet has become an important source of health information for consumers and their families.

This study aimed to rate the quality of websites with psychosis-related information (to provide clinicians with a basis for recommending material to guide clinical decision-making with consumers and their families), using a validated instrument as well as a purpose-developed checklist, and consider improvement in quality over a 4-year period.

Two measures of website quality were used the DISCERN scale and the Psychosis Website Quality Checklist (PWQC). Terms related to psychosis, including "psychotic," "psychosis," "schizophrenia," "delusion," and "hallucination," were entered into Google, and the first 25 results were analyzed. In total, 6 raters with varying health professional backgrounds were used to evaluate the websites across two time points January-March 2014 and January-March 2018.

Of ite quality. While sites generally provided basic clinical information, most lacked material addressing weighing up risks and benefits of medication and alternatives, the role of coercive treatment and other more contentious issues. Insufficient emphasis is placed on detailed information on early intervention and importance of lifestyle modifications or how families and friends can contribute. These are likely to be the very answers that consumers and carers are seeking and this gap contributes to unmet needs among this group. We suggest that clinicians should be aware of what is available and where there are gaps.
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