Background and Objectives: Different methods to examine research gaps have been described, but there are still no standard methods for identifying, prioritizing, or reporting research gaps. This study aimed to describe the methods used to identify, prioritize, and display gaps in health research. Methods: A scoping review using the Arksey and O'Malley methodological framework was carried out. We included all study types describing or reporting on methods to identify, prioritize, and display gaps or priorities in health research. Data synthesis is both quantitative and qualitative. Results: Among 1,938 identified documents, 139 articles were selected for analysis; 90 (65%) aimed to identify gaps, 23 (17%) aimed to determine research priorities, and 26 (19%) had both aims. The most frequent methods in the review were aimed at gap identification and involved secondary research, which included knowledge synthesis (80/116 articles, 69%), specifically systematic reviews and scoping reviews (58/80, 73%). Among 49 studies aimed at research prioritization, the most frequent methods were both primary and secondary research, accounting for 24 (49%) reports. Finally, 52 (37%) articles described methods for displaying gaps and/or priorities in health research. Conclusion: This study provides a mapping of different methods used to identify, prioritize, and display gaps or priorities in health research.
Background: Participation in randomized controlled trials (RCTs) may be quite demanding and could represent an important burden for patients. We aimed to explore this research burden (i.e., the psychological, physical, and financial burdens) experienced by patients through their participation in a RCT. Methods: We conducted a systematic review of qualitative studies exploring adult patients' experiences with RCT participation. We searched MEDLINE (PubMed), CINAHL, PSYCHINFO, and Embase (search date March 2018) for eligible reports. Qualitative data coding and indexing were assisted by NVivo. The quality of reports was assessed by using the Critical Appraisal Skills Program (CASP) tool. Results: We included 45 qualitative studies that involved 1732 RCT participants. Important psychological burdens were identified at every stage of the trial process. Participants reported feeling anxiety and being afraid of "being a 'guinea pig'" and described undergoing randomization and allocation to a placebo as particularly difficult resulting in disappointment, anger, and depression. Patients' follow-up and trial closure were also responsible for a wide range of psychological, physical, and financial burdens. Furthermore, factors related to burdensome impacts and consequences were discerned. These factors involved trial information, poorly organized and too-demanding follow-up, and lack of appropriate management when the patient's participation ended. Trial participation was also associated with beneficial effects such as the satisfaction of feeling "useful," gaining "a sense of control," and receiving special attention. Conclusions: Our finding provides a detailed description of research burden across the whole RCT process. Many of the burdens described could be anticipated, and some avoided in a movement toward minimally disruptive clinical research. Such an approach could improve trial recruitment and retention. Review registration: PROSPERO CRD42018098994
Background Researchers worldwide are actively engaging in research activities to search for preventive and therapeutic interventions against COVID-19. Our aim was to describe the planning of randomized controlled trials (RCTs) in terms of timing related to the course of the COVID-19 epidemic and research question evaluated. Method We performed a living mapping of RCTs registered in the WHO International Clinical Trials Registry Platform. We systematically search the platform every week for all RCTs evaluating preventive interventions and treatments for COVID-19 and created a publicly available interactive mapping tool at https://covid-nma.com to visualize all trials registered. Results By August 12, 2020, 1,568 trials for COVID-19 were registered worldwide. Overall, the median ([Q1-Q3]; range) delay between the first case recorded in each country and the first RCT registered was 47 days ([33-67]; 15-163). For the 9 countries with the highest number of trials registered, most trials were registered after the peak of the epidemic (from 100% trials in Italy to 38% in the United States). Most trials evaluated treatments (1,333 trials; 85%); only 223 (14%) evaluated preventive strategies and 12 post-acute period intervention. A total of 254 trials were planned to assess different regimens of hydroxychloroquine with an expected sample size of 110,883 patients. Conclusion This living mapping analysis showed that COVID-19 trials have relatively small sample size with certain redundancy in research questions. Most trials were registered when the first peak of the pandemic have passed.
Objectives: New forms of research involving collective intelligence (CI) of diverse individuals mobilized through crowdsourcing is successfully emerging in various fields. This scoping review aimed to describe these methods across different fields and propose a framework for implementation. Study Design and Setting: We searched seven electronic databases for reports describing projects that had mobilized CI with crowdsourcing. We used content analysis to develop themes and categories of the methods. Results: We identified 145 reports. CI was mobilized to generate ideas, conduct evaluations, solve problems, and create intellectual outputs. Most projects (n 5 110, 76%) were open to the public without restrictions on participants' expertise. Participants contributed to projects by independent contribution (i.e., no interaction with other participants) (n 5 50, 34%), collaboration (n 5 41, 28%), competitions (n 5 33, 23%), and playing games (n 5 16, 11%). In total, 61% of articles (n 5 89) reported methods to evaluate participants' contribution and decision-making process: 43% used an independent panel of experts and 18% involved end users. We identified challenges in implementation and sustainability of CI and proposed solutions. Conclusion: New research methods based on CI through crowdsourcing could transform clinical research. This framework facilitates the implementation of these methods.
Background: As the rate of opioid use in pregnancy escalates, there are a growing number of women diagnosed with opioid use disorder (OUD) and their newborns being cared for in inpatient settings. Purpose: In this study, we sought to better understand the experiences of nurses and nursing assistants working with women diagnosed with OUD and their newborns. By identifying the needs of nurses and nursing assistants, the findings from this study may contribute to reductions in stigma and improved patient care. Methods: Nurses and nursing assistants were recruited from a postpartum unit at a large urban hospital in Utah. Participants (n = 30) attended up to 4 semistructured focus groups. We utilized Braun and Clarke's 6-phase approach to thematic analysis to analyze transcribed interviews. Findings/Results: Themes identified during the data analysis process included negative feelings and reactions toward patients; preferential concern for the newborn over maternal well-being; and identification of organizational and training needs to overcome these challenges. Implications for Practice: These findings identify strategies for addressing challenges faced by nurses and nursing assistants in caring for women diagnosed with OUD and their newborns. Implications for Research: Future research should examine the effectiveness of approaches to reduce behaviors influenced by stigma among nurses and nursing assistants working with women diagnosed with OUD and their newborns, as well as employee and patient satisfaction, and long-term health outcomes.
Background Innovative ways of planning and conducting research have emerged recently, based on the concept of collective intelligence. Collective intelligence is defined as shared intelligence emerging when people are mobilized within or outside an organization to work on a specific task that could result in more innovative outcomes than those when individuals work alone. Crowdsourcing is defined as “the act of taking a job traditionally performed by a designated agent and outsourcing it to an undefined, generally large group of people in the form of an open call.” Objective This qualitative study aimed to identify the barriers to mobilizing collective intelligence and ways to overcome these barriers and provide good practice advice for planning and conducting collective intelligence projects across different research disciplines. Methods We conducted a multinational online open-ended question survey and semistructured audio-recorded interviews with a purposive sample of researchers who had experience in running collective intelligence projects. The questionnaires had an interactive component, enabling respondents to rate and comment on the advice of their fellow respondents. Data were analyzed thematically, drawing on the framework method. Results A total of 82 respondents from various research fields participated in the survey (n=65) or interview (n=17). The main barriers identified were the lack of evidence-based guidelines for implementing collective intelligence, complexity in recruiting and engaging the community, and difficulties in disseminating the results of collective intelligence projects. We drew on respondents’ experience to provide tips and good practice advice for governance, planning, and conducting collective intelligence projects. Respondents particularly suggested establishing a diverse coordination team to plan and manage collective intelligence projects and setting up common rules of governance for participants in projects. In project planning, respondents provided advice on identifying research problems that could be answered by collective intelligence and identifying communities of participants. They shared tips on preparing the task and interface and organizing communication activities to recruit and engage participants. Conclusions Mobilizing collective intelligence through crowdsourcing is an innovative method to increase research efficiency, although there are several barriers to its implementation. We present good practice advice from researchers with experience of collective intelligence across different disciplines to overcome barriers to mobilizing collective intelligence.
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