Background The global COVID-19 pandemic has led to the need for educators to explore online platforms in delivering lessons to students. Home-based learning is one of the most commonly-used teaching methods that allow learning to take place despite a physical separation between the students and the educators. Methods A descriptive qualitative approach was used to explore the experiences of nursing undergraduates when using home-based learning as a pedagogy during the COVID-19 pandemic. Data were collected from twenty-three nursing students (n = 14 in year one; n = 9 in year two) of their full-time pre-registration nursing program in a public-funded university in Singapore. Semi-structured interviews using an interview guide was conducted through Zoom-based video-conferencing from November 2020 to January 2021. The interview lasted between 45 and 65 min (median = 45 min). Data collection took place concurrently with thematic analysis through Braun and Clarke’s six-step approach. This study was reported according to the Consolidated Criteria for Reporting Qualitative Research. Results Three main themes identified during the data analysis were: (1) challenges of home-based learning, where students detailed their experiences and difficulties encountered during the process; (2) the effectiveness of home-based learning, which explored the pedagogy’s impact on the students’ learning experience; and (3) students’ motivation to learn, where the effects on student morale and motivation in partaking in learning tasks were discussed. Conclusions Results from this study suggested that universities should incorporate more home-based learning opportunities as home-based learning to continue playing a crucial role in the foreseeable future. Universities should continue to incorporate more home-based learning opportunities into the existing nursing curriculaa in order to test their capacities and address technical challenges in online learning. Future studies should also consider incorporating other pedagogical strategies when conducting lessons online.

Globally, around half (55%) of the population live in fast‐paced urban settings where many people find it challenging to manage their stress and respond to crises with a positive mindset. This resulted in prolonged distress where anxiety and fatigue caused physical and mental health concerns. Nature walks involving immersive exposure in the forest, and green spaces have been posited to offer physiological and psychological benefits. Therefore, in this systematic review, we evaluated the effects of forest bathing on psychological and physiological outcomes. We searched four English and five non‐English databases (Chinese and Korean) for peer‐reviewed studies published between January 2000 and March 2021. This review adhered to the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta‐analysis Statement 2020. The primary outcomes explored in this review were mainly psychological, including anxiety, depression, mood and quality of life. The secondary outcomes were physiological outcomes such as blood pressure and heart rate. We conducted a meta‐analysis on each outcome using the random‐effects model. Heterogeneity was assessed by the I2 statistic. Thirty‐six articles (21 in English, 3 in Chinese and 12 in Korean) with 3554 participants were included in this review. Our meta‐analysis suggested that forest bathing can significantly reduce symptoms of depression and anxiety. However, we did not observe as many benefits in physiological outcomes. Against the background of the negative effects of urbanization on mental well‐being, this review highlighted the potential therapeutic role of forests in the contemporary world, lending further evidence‐based support for forest conservation.

Background Despite health behavioral change interventions targeting modifiable lifestyle factors underlying chronic diseases, dropouts and nonadherence of individuals have remained high. The rapid development of machine learning (ML) in recent years, alongside its ability to provide readily available personalized experience for users, holds much potential for success in health promotion and behavioral change interventions. Objective The aim of this paper is to provide an overview of the existing research on ML applications and harness their potential in health promotion and behavioral change interventions. Methods A scoping review was conducted based on the 5-stage framework by Arksey and O’Malley and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews) guidelines. A total of 9 databases (the Cochrane Library, CINAHL, Embase, Ovid, ProQuest, PsycInfo, PubMed, Scopus, and Web of Science) were searched from inception to February 2021, without limits on the dates and types of publications. Studies were included in the review if they had incorporated ML in any health promotion or behavioral change interventions, had studied at least one group of participants, and had been published in English. Publication-related information (author, year, aim, and findings), area of health promotion, user data analyzed, type of ML used, challenges encountered, and future research were extracted from each study. Results A total of 29 articles were included in this review. Three themes were generated, which are as follows: (1) enablers, which is the adoption of information technology for optimizing systemic operation; (2) challenges, which comprises the various hurdles and limitations presented in the articles; and (3) future directions, which explores prospective strategies in health promotion through ML. Conclusions The challenges pertained to not only the time- and resource-consuming nature of ML-based applications, but also the burden on users for data input and the degree of personalization. Future works may consider designs that correspondingly mitigate these challenges in areas that receive limited attention, such as smoking and mental health.

Introduction Given the diversity of the scope for inquiry and methodologies used in nursing research, the synthesis of primary research may not be as straightforward as conducting a meta‐analysis or systematic review on clinical trials. Scoping reviews offer an option to nursing academics for inquiries involving a range of applications and interpretations. Given the continual advances in evidence‐based research, it is, therefore, crucial for nursing to constantly substantiate its research capabilities and uphold standards in its research inquiry. Accordingly, an updated overview would be timely to characterize scoping reviews in the nursing literature. Hence this review aimed to examine the characteristics of scoping reviews published in nursing journals and evaluate the methodological and reporting quality of the scoping reviews. Design A systematic review. Methods A comprehensive search of three electronic databases (PubMed, CINAHL, and Embase) were conducted. Scoping reviews published in English on or before December 31, 2020 were included, with the criterion that their publication had been in nursing journals indexed in the Journal Citation Reports (2020 Science Edition) of the Web of Science. Two reviewers independently screened the titles and abstracts for eligibility. A standardized data extraction form was used for data collection, and a 29‐item checklist was developed to assess the methodological and reporting quality of the scoping reviews. The methodological and reporting quality was assessed independently by four reviewers and subsequently counter‐checked by another two reviewers. Descriptive statistics were used to characterize the included papers, and narrative synthesis was undertaken to explain the results. Results This review included 422 papers from 88 nursing journals. They were published between 2008 and 2021 (median year 2019). Only 15 (3.5%) reviews reported accessible protocols, and 63 (15.0%) presented data on their critical appraisal of the included sources of evidence. Poor reporting of the selection of sources of evidence and data extraction was also identified. Overall, the 422 included reviews had complied with 20 (median [range: 9–27]) of the 29 items on the checklist. Conclusions Scoping reviews have garnered wider acceptance in nursing research, of which the scopes and methodologies exhibit much diversity. Our systematic review has provided insights into existing scoping reviews published in nursing journals through our characterization of them and appraisal of their methodological and reporting quality. However, our findings underline several areas needing improvement: the lack of transparency, the absence of critical appraisal, non‐compliance to established checklists, and inconsistencies in the data processing. Clinical Relevance Appraising included sources of evidence and maintaining transparency in the conduct and reporting of scoping reviews increases the practical utility of scoping reviews.

BACKGROUND Despite health behavioral change interventions targeting modifiable lifestyle factors underlying chronic diseases, dropouts and nonadherence of individuals have remained high. The rapid development of machine learning (ML) in recent years, alongside its ability to provide readily available personalized experience for users, holds much potential for success in health promotion and behavioral change interventions. OBJECTIVE The aim of this paper is to provide an overview of the existing research on ML applications and harness their potential in health promotion and behavioral change interventions. METHODS A scoping review was conducted based on the 5-stage framework by Arksey and O’Malley and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews) guidelines. A total of 9 databases (the Cochrane Library, CINAHL, Embase, Ovid, ProQuest, PsycInfo, PubMed, Scopus, and Web of Science) were searched from inception to February 2021, without limits on the dates and types of publications. Studies were included in the review if they had incorporated ML in any health promotion or behavioral change interventions, had studied at least one group of participants, and had been published in English. Publication-related information (author, year, aim, and findings), area of health promotion, user data analyzed, type of ML used, challenges encountered, and future research were extracted from each study. RESULTS A total of 29 articles were included in this review. Three themes were generated, which are as follows: (1) enablers, which is the adoption of information technology for optimizing systemic operation; (2) challenges, which comprises the various hurdles and limitations presented in the articles; and (3) future directions, which explores prospective strategies in health promotion through ML. CONCLUSIONS The challenges pertained to not only the time- and resource-consuming nature of ML-based applications, but also the burden on users for data input and the degree of personalization. Future works may consider designs that correspondingly mitigate these challenges in areas that receive limited attention, such as smoking and mental health.