Activity

RR1-10.2196/22511.

DERR1-10.2196/22511.

To optimize their use of a new Health Information System (HIS), supporting health care providers require effective HIS education. Failure to provide this education can significantly hinder an organization’s HIS implementation and sustainability efforts.

The aim of this review is to understand the most effective educational strategies and approaches to enable health care providers to optimally use an HIS.

Ovid MEDLINE, Ovid Embase, EBSCO Cumulative Index to Nursing and Allied Health Literature, and EBSCO Education Resources Information Center were searched to identify relevant papers. Relevant studies were systematically reviewed and analyzed using a qualitative thematic analysis approach.

Of the 3539 studies screened, 17 were included for data extraction. The literature on the most effective approaches to enable health care providers to optimally use an HIS emphasized the importance of investing in engaging and understanding learners in the clinical context, maximizing the transfer of learning to care, and designing continuous and agile evaluation to meet the emerging demands of the clinical environment.

This review supports the advancement of a new HIS learning framework that organizational leaders and educators can use to guide HIS education design and development. Future research should examine how this framework can be translated into practice.

This review supports the advancement of a new HIS learning framework that organizational leaders and educators can use to guide HIS education design and development. Future research should examine how this framework can be translated into practice.

Identifying cognitive impairment early enough could support timely intervention that may hinder or delay the trajectory of cognitive impairment, thus increasing the chances for successful cognitive aging.

We aimed to build a prediction model based on machine learning for cognitive impairment among Chinese community-dwelling elderly people with normal cognition.

A prospective cohort of 6718 older people from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) register, followed between 2008 and 2011, was used to develop and validate the prediction model. Participants were included if they were aged 60 years or above, were community-dwelling elderly people, and had a cognitive Mini-Mental State Examination (MMSE) score ≥18. They were excluded if they were diagnosed with a severe disease (eg, cancer and dementia) or were living in institutions. Cognitive impairment was identified using the Chinese version of the MMSE. Several machine learning algorithms (random forest, XGBoost, naïve Bayes, and logisent.

This simple and feasible cognitive impairment prediction model could identify community-dwelling elderly people at the greatest 3-year risk for cognitive impairment, which could help community nurses in the early identification of dementia.

This simple and feasible cognitive impairment prediction model could identify community-dwelling elderly people at the greatest 3-year risk for cognitive impairment, which could help community nurses in the early identification of dementia.

In the United States, abortion access is restricted by numerous logistical, financial, social, and policy barriers. Most studies on abortion-seeking experiences in the United States have recruited participants from abortion clinics. However, clinic-based recruitment strategies fail to capture the experiences of people who consider an abortion but do not make it to an abortion clinic. Research indicates that many people search for abortion information on the web; however, web-based recruitment remains underutilized in abortion research.

This study aims to establish the feasibility of using Facebook, Google Ads, and Reddit as recruitment platforms for a study on abortion-seeking experiences in the United States.

From August to September 2018, we posted recruitment advertisements for a survey about abortion-seeking experiences through Facebook, Google Ads, and Reddit. Eligible participants were US residents aged 15-49 years who had been pregnant in the past 5 years and had considered abortion for a pregnant. ALK inhibitor A total of 84% (66/79) of those who screened eligible from Facebook completed the short survey compared with 73% (8/11) of those who screened eligible from Reddit and 13% (7/53) of those who screened eligible from Google Ads.

These results suggest that Facebook advertisements may be the most time- and cost-effective strategy to recruit people who considered but did not obtain an abortion in the United States. Adapting and implementing Facebook-based recruitment strategies for research on abortion access could facilitate a more complete understanding of the barriers to abortion care in the United States.

These results suggest that Facebook advertisements may be the most time- and cost-effective strategy to recruit people who considered but did not obtain an abortion in the United States. Adapting and implementing Facebook-based recruitment strategies for research on abortion access could facilitate a more complete understanding of the barriers to abortion care in the United States.

Ecological momentary assessment (EMA) is a promising tool in the management of psychiatric disorders and particularly depression. It allows for a real-time evaluation of symptoms and an earlier detection of relapse or treatment efficacy. The generalization of the smartphone in the modern world offers a new, large-scale support for EMA.

The main objective of this study was twofold (1) to assess patients’ compliance with an EMA smartphone app defined by the number of EMAs completed, and (2) to estimate the external validity of the EMA using a correlation between self-esteem/guilt/mood variables and Hamilton Depression Rating Scale (HDRS) score.

Eleven patients at the Pitié-Salpêtrière Hospital, Paris, France, were monitored for 28 days by means of a smartphone app. Every patient enrolled in the study had two types of assessment (1) three outpatient consultations with a psychiatrist at three different time points (days 1, 15, and 28), and (2) real-time data collection using an EMA smartphone app with a single, fixed notification per day at 3 pm for 28 days.