Objective: Evidence-based practice (EBP) provides nurses with a method to use critically appraised and scientifically proven evidence for delivering quality health care to a specific population. The objective of this study was to explore nurses' awareness of, knowledge of, and attitude toward EBP and factors likely to encourage or create barriers to adoption. In addition, information sources used by nurses and their literature searching skills were also investigated.Method: A total of 2,100 copies of the questionnaire were distributed to registered nurses in 2 public hospitals in Singapore, and 1,486 completed forms were returned, resulting in a response rate of 70.8%.Results: More than 64% of the nurses expressed a positive attitude toward EBP. However, they pointed out that due to heavy workload, they cannot keep up to date with new evidence. Regarding self-efficacy of EBP-related abilities, the nurses perceived themselves to possess moderate levels of skills. The nurses also felt that EBP training, time availability, and mentoring by nurses with EBP experience would encourage them to implement EBP. The top three barriers to adopting EBP were lack of time, inability to understand statistical terms, and inadequate understanding of the jargon used in research articles. For literature searching, nurses were using basic search features and less than one-quarter of them were familiar with Boolean and proximity operators. Conclusion:Although nurses showed a positive attitude toward EBP, certain barriers were hindering their smooth adoption. It is, therefore, desirable that hospital management in Southeast Asia, particularly in Singapore, develop a comprehensive strategy for building EBP competencies through proper training. Moreover, hospital libraries should also play an active role in developing adequate information literacy skills among the nurses.

Background Conversational agents, also known as chatbots, are computer programs designed to simulate human text or verbal conversations. They are increasingly used in a range of fields, including health care. By enabling better accessibility, personalization, and efficiency, conversational agents have the potential to improve patient care. Objective This study aimed to review the current applications, gaps, and challenges in the literature on conversational agents in health care and provide recommendations for their future research, design, and application. Methods We performed a scoping review. A broad literature search was performed in MEDLINE (Medical Literature Analysis and Retrieval System Online; Ovid), EMBASE (Excerpta Medica database; Ovid), PubMed, Scopus, and Cochrane Central with the search terms “conversational agents,” “conversational AI,” “chatbots,” and associated synonyms. We also searched the gray literature using sources such as the OCLC (Online Computer Library Center) WorldCat database and ResearchGate in April 2019. Reference lists of relevant articles were checked for further articles. Screening and data extraction were performed in parallel by 2 reviewers. The included evidence was analyzed narratively by employing the principles of thematic analysis. Results The literature search yielded 47 study reports (45 articles and 2 ongoing clinical trials) that matched the inclusion criteria. The identified conversational agents were largely delivered via smartphone apps (n=23) and used free text only as the main input (n=19) and output (n=30) modality. Case studies describing chatbot development (n=18) were the most prevalent, and only 11 randomized controlled trials were identified. The 3 most commonly reported conversational agent applications in the literature were treatment and monitoring, health care service support, and patient education. Conclusions The literature on conversational agents in health care is largely descriptive and aimed at treatment and monitoring and health service support. It mostly reports on text-based, artificial intelligence–driven, and smartphone app–delivered conversational agents. There is an urgent need for a robust evaluation of diverse health care conversational agents’ formats, focusing on their acceptability, safety, and effectiveness.

The aim of this study was to review the existing literature on game-based digital interventions for depression systematically and examine their effectiveness through a meta-analysis of randomized controlled trials (RCTs). Database searching was conducted using specific search terms and inclusion criteria. A standard meta-analysis was also conducted of available RCT studies with a random effects model. The standard mean difference (Cohen's d) was used to calculate the effect size of each study. Nineteen studies were included in the review, and 10 RCTs (eight studies) were included in the meta-analysis. Four types of game interventions-psycho-education and training, virtual reality exposure therapy, exercising, and entertainment-were identified, with various types of support delivered and populations targeted. The meta-analysis revealed a moderate effect size of the game interventions for depression therapy at posttreatment (d=-0.47 [95% CI -0.69 to -0.24]). A subgroup analysis showed that interventions based on psycho-education and training had a smaller effect than those based on the other forms, and that self-help interventions yielded better outcomes than supported interventions. A higher effect was achieved when a waiting list was used as the control. The review and meta-analysis support the effectiveness of game-based digital interventions for depression. More large-scale, high-quality RCT studies with sufficient long-term data for treatment evaluation are needed.

Background: People with dementia often require full-time caregivers especially in the later stages of their condition. People with dementia and caregivers' access to reliable information on dementia is essential as it may have an important impact on patient care and quality of life. This study aims to provide an overview of the information needs and information seeking behaviour of people with dementia and their non-professional caregivers. Methods: We conducted a scoping review of the literature and searched four electronic databases for eligible studies published up to August 2018. Two reviewers independently screened studies and extracted data. Information needs were classified according to emerging themes in the literature, and information seeking behaviour was categorized using Wilson's model of information behaviour. Results: Twenty studies with a total of 4140 participants, were included in this review. Reported information needs focused on: (i) disease; (ii) patient care provision; (iii) healthcare services; and (iv) caregiver self-care. The most commonly reported information need was on healthcare service-related information. Characteristics found to influence information needs were the severity of dementia as well as patient and caregiver status. People with dementia and non-professional caregivers mainly displayed active searching, information seeking behaviour and preferred using electronic sources to obtain health information. Conclusion: Current dementia information sources available in English are extensive in the information they offer, but more emphasis needs to be placed on healthcare service-related information. All studies originated from high income countries and focused on information needs of non-professional caregivers only. The only variables found to be associated to information needs were severity of dementia condition as well as patient/caregiver status. The information needs identified in this review can be used to inform development and design of future dementia resources for people with dementia and their non-professional caregivers.

Increased demand for medical or healthcare services has meant that nurses are to take on a more proactive and independent role intending to patients, providing basic treatment and deciding relevant clinical practice. This, in turn, translates into the need for nurses to be able to translate research and evidence into their practice more efficiently and effectively. Hence, competencies in looking for, evaluating, synthesizing and applying documented information or evidence-based practice becomes crucial. This article presents a quantitative study that involved more than 300 nurses from a large government hospital in Singapore. A self-reporting questionnaire was developed to collect data pertaining to evidence-based practice and activities, including those that demonstrate information literacy competencies. Results seem to suggest that the nurses preferred to use print and human information sources compared to electronic information sources; were not proactive in looking up research or evidence-based information and, instead, preferred such information to be fed to them; and that they perceived they lacked the ability to evaluate research papers or effectively search electronic information related to nursing or evidence-based practice. It was also found that more than 80% of the nurses have not had any training related to evidence-based practice.

BackgroundRecently, many studies have been conducted to investigate the effects of exergames on the social well-being of older adults.ObjectiveThe aim of this paper is to synthesize existing studies and provide an overall picture on the social effects of exergames on older adults.MethodsA comprehensive literature search with inclusive criteria was conducted in major social science bibliographic databases. The characteristics of exergames, participants, methodology, as well as outcome measurements were extracted from the relevant studies included in the review. The bibliometric and altmetric outreach of the included studies were also investigated.ResultsA total of 10 studies were included in the review, with 8 studies having used the Nintendo Wii platform. Most of the studies recruited healthy older adults from local communities or senior activity centers. Three groups of social-related outcomes have been identified, including emotion-related, behavior-related, and attitude-related outcomes. A metric analysis has shown that the emotion-related and behavior-related outcomes received high attention from both the academic community and social media platforms.ConclusionsOverall, the majority of exergame studies demonstrated promising results for enhanced social well-being, such as reduction of loneliness, increased social connection, and positive attitudes towards others. The paper also provided implications for health care researchers and exergame designers.

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Most existing studies on next location recommendation propose to model the sequential regularity of check-in sequences, but suffer from the severe data sparsity issue where most locations have fewer than five following locations. To this end, we propose an Attentional Recurrent Neural Network (ARNN) to jointly model both the sequential regularity and transition regularities of similar locations (neighbors). In particular, we first design a meta-path based random walk over a novel knowledge graph to discover location neighbors based on heterogeneous factors. A recurrent neural network is then adopted to model the sequential regularity by capturing various contexts that govern user mobility. Meanwhile, the transition regularities of the discovered neighbors are integrated via the attention mechanism, which seamlessly cooperates with the sequential regularity as a unified recurrent framework. Experimental results on multiple real-world datasets demonstrate that ARNN outperforms state-of-the-art methods.