Traditional Systematic Review Research Articles

Veterinary Evidence: moving forward

Unrecognised and unknown information needs can significantly impact on the quality of decision making, advice, and patient care. In the practice of veterinary medicine, additional information may be required in one or more of epidemiology, diagnosis, treatment, prognosis, control (risk reduction), and prevention (risk avoidance), in order to optimise patient care. Veterinary Evidence publishes Knowledge Summaries, which aim to answer a specific and focused clinical query by appraising the best available evidence published in peer-reviewed scientific journals. By presenting the evidence in a structured and easily digestible format, Knowledge Summaries enable veterinary professionals to stay informed and apply the best available evidence to their decision-making. To assist in the identification of unrecognised deficits and the generation of clinical queries Veterinary Evidence has developed a list of common conditions for each species, alongside the different categories of information. The aim is to prompt and support the generation of new clinical queries in a more systematic format. This resource sits alongside our species-based lists of clinical queries that have already been suggested by practicing veterinarians, veterinary nurses, and other paraprofessionals (see veterinaryevidence.org/index.php/ve/clinical-queries). We hope readers and prospective authors will use these resources to generate new clinical queries or as a starting point for writing their own Knowledge Summaries. Most of the papers published in Veterinary Evidence are Knowledge Summaries, but the journal has always accepted and will continue to accept and encourage other types of reviews and original research that provide evidence to inform clinical practice. For example, in this issue we have published a commentary paper by Professor Jonathan Elliott regarding the processes and evidence required for the registration of veterinary medicinal products which provides some important insights and debate into the publication of evidential information (Elliott, 2024). A Knowledge Summary may not always be the best format to synthesise and summarise evidence on a multifaceted topic; scoping reviews, systematic reviews, or narrative reviews maybe more appropriate. Munn et al. (2018) provide a useful account of scoping reviews and how they differ from traditional literature and systematic reviews. In particular, we are keen to receive articles on artificial intelligence applications, sustainability, and quality improvement in clinical practice, as the impact and importance of these topics grows. We are also making some changes to the presentation of Knowledge Summaries in Veterinary Evidence, to help readers more easily understand the details and context of the summarised evidence. In order to support everyone in appraising and understanding quantitative clinical studies, we will be publishing a glossary and guidance on basic statistical terms and tests on the journal website.

Global Research on Pandemics or Epidemics and Mental Health: A Natural Language Processing Study.

The global research on pandemics or epidemics and mental health has been growing exponentially recently, which cannot be integrated through traditional systematic review. Our study aims to systematically synthesize the evidence using natural language processing (NLP) techniques. Multiple databases were searched using titles, abstracts, and keywords. We systematically identified relevant literature published prior to Dec 31, 2023, using NLP techniques such as text classification, topic modelling and geoparsing methods. Relevant articles were categorized by content, date, and geographic location, outputting evidence heat maps, geographical maps, and narrative synthesis of trends in related publications. Our NLP analysis identified 77,915 studies in the area of pandemics or epidemics and mental health published before Dec 31, 2023. The Covid pandemic was the most common, followed by SARS and HIV/AIDS; Anxiety and stress were the most frequently studied mental health outcomes; Social support and healthcare were the most common way of coping. Geographically, the evidence base was dominated by studies from high-income countries, with scant evidence from low-income counties. Co-occurrence of pandemics or epidemics and fear, depression, stress was common. Anxiety was one of the three most common topics in all continents except North America. Our findings suggest the importance and feasibility of using NLP to comprehensively map pandemics or epidemics and mental health in the age of big literature. The review identifies clear themes for future clinical and public health research, and is critical for designing evidence-based approaches to reduce the negative mental health impacts of pandemics or epidemics.

2238 How can effective teaching about dementia be integrated into the undergraduate medical curriculum? A realist review

Abstract Introduction The prevalence of dementia is increasing and yet healthcare professionals (HCP) do not always have sufficient education and training to deliver optimal care for patients with dementia (PWD). There is an evidence base as to how to deliver effective undergraduate education about dementia but this is infrequently integrated into the medical curriculum. Methods We undertook a realist synthesis to review the barriers to integrating effective interventions on dementia into the medical curriculum. A realist synthesis differs from a traditional systematic review in terms of explaining how interventions might succeed (or not) in a particular context, involving iterative cycles of literature review and synthesis to develop and refine a ‘programme theory’ (PT). Results We analysed and synthesised twenty relevant studies of undergraduate educational interventions on dementia to identify common themes. We constructed an ‘initial programme theory’ (IPT) to illustrate the contexts where teaching on dementia occurs and outline four main categories of barriers to curriculum integration: culture, concern for patient welfare, student attitudes, and logistics. Conclusion We have identified key barriers to implementation of undergraduate education about dementia, and potential mechanisms to overcome them. The next stage of our realist synthesis is to gather stakeholder feedback on the validity of the IPT before returning to the next cycle of literature review to refine and finalise our PT. This model will serve as a guide for those aiming to successfully integrate effective education about dementia into the medical curriculum.

Challenges of spatio-temporal trajectory datasets

ABSTRACT The rapid evolution of wireless location technologies has significantly increased the availability of mobility data, particularly spatio-temporal trajectory data, detailing object movements and locations over time. This data holds diverse applications such as predicting travel patterns, optimizing routes, analysing social interactions, and managing urban resources. However, leveraging trajectory datasets presents challenges, including data heterogeneity, volume, velocity requiring real-time processing, privacy concerns with sensitive information, and regulatory compliance. Traditional systematic reviews of literature may not fully capture industry challenges, as professionals often do not publish research. To address this gap, industry expert input is vital. Collaborating with academia, we propose using focus group discussions to explore these challenges comprehensively. Focus groups offer a qualitative platform for professionals and academics to identify practical issues and gaps in the literature. This combined approach will inform technological advancements in creating and utilizing spatio-temporal datasets. Additionally, integrating insights from focus groups with a literature review ensures a thorough analysis of data challenges. This methodology aims to provide a holistic understanding and foster innovation in managing and exploiting trajectory data effectively.

When it comes to research on land management behavior, how are we doing? A systematic review on theory, measurement, and suggestions for improvement

AbstractWith increasing attention to climate change and biodiversity loss, conservation social science research on land management practices is burgeoning. Researchers have broadened their focus from protected areas to diverse types of land management to support conservation and climate mitigation. But, developing effective strategies for these issues requires an in‐depth understanding of both the socio‐psychological factors that guide landholders' decision‐making and global trends in land management practices and literature. To assess the trends and status of land management behavior research, we systematically reviewed research published between 2010 and 2020 in five seminal conservation journals. Of 11,607 articles reviewed, we identified 100 articles about land management behavior. We assessed theoretical groundings, measurement methodology, land‐use terminology and practices, ecosystem type, and geographic distribution. We identified strengths and significant gaps and weaknesses across land management research. For example, 52% of articles made no meaningful connection to theory, only 14% of papers used observed behavioral data, 86% of studies uses non‐experimental methods and researchers disproportionately measured land management behavior in developed nations (66%). We also find that language used to describe land management behavior is very heterogeneous, making it difficult to summarize land management research using traditional systematic review methods. Conducting a limited systematic review can help summarize research and also identify trends across disciplines that might otherwise missed. Results from our limited systematic review can guide future research and support the development of evidence‐based policies to mitigate climate change and biodiversity loss.

A Narrative Review of the Efficacy of Interventions for Emotional Dysregulation, and Underlying Bio-Psycho-Social Factors.

In this narrative, comprehensive, and updated review of the literature, we summarize evidence about the effectiveness of interventions aimed at reducing emotion dysregulation and improving emotion regulation in children, adolescents, and adults. After introducing emotion dysregulation and emotion regulation from a theoretical standpoint, we discuss the factors commonly associated with emotion regulation, including neurobiological and neuropsychological mechanisms, and the role of childhood adverse experiences and psycho-social factors in the onset of emotion dysregulation. We then present evidence about pharmacological and non-pharmacological interventions aiming at improving emotion dysregulation and promoting emotion regulation across the lifespan. Although our review was not intended as a traditional systematic review, and the search was only restricted to systematic reviews and meta-analyses, we highlighted important implications and provided recommendations for clinical practice and future research in this field.

Rapid review: A review of methods and recommendations based on current evidence.

Rapid review (RR) could accelerate the traditional systematic review (SR) process by simplifying or omitting steps using various shortcuts. With the increasing popularity of RR, numerous shortcuts had emerged, but there was no consensus on how to choose the most appropriate ones. This study conducted a literature search in PubMed from inception to December 21, 2023, using terms such as "rapid review" "rapid assessment" "rapid systematic review" and "rapid evaluation". We also scanned the reference lists and performed citation tracking of included impact studies to obtain more included studies. We conducted a narrative synthesis of all RR approaches, shortcuts and studies assessing their effectiveness at each stage of RRs. Based on the current evidence, we provided recommendations on utilizing certain shortcuts in RRs. Ultimately, we identified 185 studies focusing on summarizing RR approaches and shortcuts, or evaluating their impact. There was relatively sufficient evidence to support the use of the following shortcuts in RRs: limiting studies to those published in English-language; conducting abbreviated database searches (e.g., only searching PubMed/MEDLINE, Embase, and CENTRAL); omitting retrieval of grey literature; restricting the search timeframe to the recent 20 years for medical intervention and the recent 15 years for reviewing diagnostic test accuracy; conducting a single screening by an experienced screener. To some extent, the above shortcuts were also applicable to SRs. This study provided a reference for future RR researchers in selecting shortcuts, and it also presented a potential research topic for methodologists.

A methodological framework for rigorous systematic reviews: Tailoring comprehensive analyses to clinicians and healthcare professionals

Systematic reviews represent a fundamental study design, providing the highest level of evidence across diverse research inquiries, encompassing both public health and clinical research and practice. However, for healthcare professionals, the process of selecting, synthesizing, and interpreting evidence can be challenging, and requires specialized skills. Therefore, it is imperative to explore innovative solutions aimed at simplifying and making the traditional systematic review process more accessible while ensuring the validity and reliability of results.In this perspective, our research objective is to develop a systematic review framework that, while maintaining a rigorous methodological approach, streamlines the process for healthcare professionals. This study describes such approach in every phase, from the collection of evidence to the writing of the text, creating a guide for the healthcare professional who approaches this type of research. The qualitative and organizational analysis tools are also described, providing useful information for the use of non-paid programs.This systematic review aims to develop a framework with a rigorous methodological approach that allows simplify the process for clinicians and healthcare professionals. The implementation of this methodology in clinical practice offers new perspectives to ensure a thoughtful consideration and application of scientific evidence and opens the way to innovative and easily accessible solutions to facilitate the conduct of systematic reviews in the clinical care setting.

Teachers’ digital literacy overview in secondary school

<span lang="EN-US">This study explored the teachers’ digital literacy in secondary school and deciphered the most suggested way of enhancing secondary teachers’ digital literacy, overview levels, and the trends factors in the last five years of research. The methodologies in this study employed the traditional systematic literature review (SLR), which compiled some previous studies to be examined. The initial studies were only selected from an article published in a reputable journal indexed by Scopus. Of the 118 articles reviewed, 46 were selected to be included in the analysis. Significant findings summarize the fact that most of the last five-year research about teachers in secondary schools was impacted by the rapid development of technology and the demand for 21st-century skills. To summarize, as it is at the intermediate level, most secondary school teachers are digitally literate. However, future research may evaluate digital literacy training programs for teachers to assess what improvements should be made to delivery as well as existing frameworks used to test teachers’ digital literacy.</span>

APPLICATIONS OF TALENT MANAGEMENT IN THE TRAVEL AND TOURISM SECTOR : A SYSTEMATIC REVIEW OF THE LITERATURE

The fourth industrial revolution's revolutionary changes to the business environment and skill sets, along with increased global mobility, global demographic and economic trends, and a more diverse workforce, are creating the ideal storm for strategic human resource management (SHRM). A tough corporate climate that requires constant advancement and innovation has been identified as the hallmark of the knowledge-based economy. Organizations' capacity is significantly impacted by the caliber of knowledge they apply to succeed in the increasingly competitive knowledge-based market economy.
 The methodologies of this study employed the traditional Systematic Literature Review (SLR), which compiled some previous studies to be examined. The initial studies were only selected from the article published in a reputable journal indexed by Scopus. Of the 207 reviewed articles, 31 articles were selected to be included in the analysis.
 Talent management is the methodical planning, acquisition, development, performance management, engagement, and retention of workers who have been identified as having talent within the company. In order to establish an evidence-based comprehensive multilevel framework, this review intends to compile empirical evidence on the components of talent management. The crucial components are talent management practices, determinants, and results. This evaluation attempts to describe the majority of talent management practices as well as the best suggestions for enhancing talent management in the tourism industry

An Automated Literature Review Tool (LiteRev) for Streamlining and Accelerating Research Using Natural Language Processing and Machine Learning: Descriptive Performance Evaluation Study.

Literature reviews (LRs) identify, evaluate, and synthesize relevant papers to a particular research question to advance understanding and support decision-making. However, LRs, especially traditional systematic reviews, are slow, resource-intensive, and become outdated quickly. LiteRev is an advanced and enhanced version of an existing automation tool designed to assist researchers in conducting LRs through the implementation of cutting-edge technologies such as natural language processing and machine learning techniques. In this paper, we present a comprehensive explanation of LiteRev's capabilities, its methodology, and an evaluation of its accuracy and efficiency to a manual LR, highlighting the benefits of using LiteRev. Based on the user's query, LiteRev performs an automated search on a wide range of open-access databases and retrieves relevant metadata on the resulting papers, including abstracts or full texts when available. These abstracts (or full texts) are text processed and represented as a term frequency-inverse document frequency matrix. Using dimensionality reduction (pairwise controlled manifold approximation) and clustering (hierarchical density-based spatial clustering of applications with noise) techniques, the corpus is divided into different topics described by a list of the most important keywords. The user can then select one or several topics of interest, enter additional keywords to refine its search, or provide key papers to the research question. Based on these inputs, LiteRev performs a k-nearest neighbor (k-NN) search and suggests a list of potentially interesting papers. By tagging the relevant ones, the user triggers new k-NN searches until no additional paper is suggested for screening. To assess the performance of LiteRev, we ran it in parallel to a manual LR on the burden and care for acute and early HIV infection in sub-Saharan Africa. We assessed the performance of LiteRev using true and false predictive values, recall, and work saved over sampling. LiteRev extracted, processed, and transformed text into a term frequency-inverse document frequency matrix of 631 unique papers from PubMed. The topic modeling module identified 16 topics and highlighted 2 topics of interest to the research question. Based on 18 key papers, the k-NNs module suggested 193 papers for screening out of 613 papers in total (31.5% of the whole corpus) and correctly identified 64 relevant papers out of the 87 papers found by the manual abstract screening (recall rate of 73.6%). Compared to the manual full text screening, LiteRev identified 42 relevant papers out of the 48 papers found manually (recall rate of 87.5%). This represents a total work saved over sampling of 56%. We presented the features and functionalities of LiteRev, an automation tool that uses natural language processing and machine learning methods to streamline and accelerate LRs and support researchers in getting quick and in-depth overviews on any topic of interest.

The Eclectic Approach in English Language Teaching Applications: A Qualitative Synthesis of the Literature

This paper proposes a study of the methodologies used to teach English as a second language through computer applications. It reviews the different methodologies used in language teaching in order to contrast them with different fundamental approaches. It examines the applications used for teaching English online, especially those in line with personalised learning environments and learner-centred autonomy. The use of a mixed methodology is reported, allowing the selection of papers from both a traditional systematic review and the search engine elicit.org. Finally, it is concluded that Blended Learning is the most appropriate method, highlighting that current applications are mainly based on the Audio-Lingual method, which limits their practical use in wider contexts. Further research is needed on software applications that prioritise personalised learning environments with learner-centred autonomy, incorporating technologies based on Blended Learning and artificial intelligence (AI). To this end, it is proposed in the future to develop an application using Automatic Speech Recognition (ASR), Text To Speech (TTS), Natural Language Understanding (NLU) and Dialog Management (DM) algorithms, focusing on the above and simulating the capabilities of a teacher. This may lead to innovations in the development of software applications capable of integrating different methods, teaching modalities and learning methods.

Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions

Systematic reviews (SR) are crucial in synthesizing and analyzing existing scientific literature to inform evidence-based decision-making. However, traditional SR methods often have limitations, including a lack of automation and decision support, resulting in time-consuming and error-prone reviews. To address these limitations and drive the field forward, we harness the power of the revolutionary language model, ChatGPT, which has demonstrated remarkable capabilities in various scientific writing tasks. By utilizing ChatGPT’s natural language processing abilities, our objective is to automate and streamline the steps involved in traditional SR, explicitly focusing on literature search, screening, data extraction, and content analysis. Therefore, our methodology comprises four modules: (1) Preparation of Boolean research terms and article collection, (2) Abstract screening and articles categorization, (3) Full-text filtering and information extraction, and (4) Content analysis to identify trends, challenges, gaps, and proposed solutions. Throughout each step, our focus has been on providing quantitative analyses to strengthen the robustness of the review process. To illustrate the practical application of our method, we have chosen the topic of IoT applications in water and wastewater management and quality monitoring due to its critical importance and the dearth of comprehensive reviews in this field. The findings demonstrate the potential of ChatGPT in bridging the gap between traditional SR methods and AI language models, resulting in enhanced efficiency and reliability of SR processes. Notably, ChatGPT exhibits exceptional performance in filtering and categorizing relevant articles, leading to significant time and effort savings. Our quantitative assessment reveals the following: (1) the overall accuracy of ChatGPT for article discarding and classification is 88%, and (2) the F-1 scores of ChatGPT for article discarding and classification are 91% and 88%, respectively, compared to expert assessments. However, we identify limitations in its suitability for article extraction. Overall, this research contributes valuable insights to the field of SR, empowering researchers to conduct more comprehensive and reliable reviews while advancing knowledge and decision-making across various domains.

Systematic online living evidence summaries: emerging tools to accelerate evidence synthesis.

Systematic reviews and meta-analysis are the cornerstones of evidence-based decision making and priority setting. However, traditional systematic reviews are time and labour intensive, limiting their feasibility to comprehensively evaluate the latest evidence in research-intensive areas. Recent developments in automation, machine learning and systematic review technologies have enabled efficiency gains. Building upon these advances, we developed Systematic Online Living Evidence Summaries (SOLES) to accelerate evidence synthesis. In this approach, we integrate automated processes to continuously gather, synthesise and summarise all existing evidence from a research domain, and report the resulting current curated content as interrogatable databases via interactive web applications. SOLES can benefit various stakeholders by (i) providing a systematic overview of current evidence to identify knowledge gaps, (ii) providing an accelerated starting point for a more detailed systematic review, and (iii) facilitating collaboration and coordination in evidence synthesis.

The role of smoking in COVID-19 progression: a comprehensive meta-analysis.

The association between current smoking and coronavirus disease 2019 (COVID-19) progression remains uncertain. We aim to provide up-to-date evidence of the role of cigarette smoking in COVID-19 hospitalisation, severity and mortality. On 23 February 2022 we conducted an umbrella review and a traditional systematic review via PubMed/Medline and Web of Science. We used random-effects meta-analyses to derive pooled odds ratios of COVID-19 outcomes for smokers in cohorts of severe acute respiratory syndrome coronavirus 2 infected individuals or COVID-19 patients. We followed the Meta-analysis of Observational Studies in Epidemiology reporting guidelines. PROSPERO: CRD42020207003. 320 publications were included. The pooled odds ratio for current versus never or nonsmokers was 1.08 (95% CI 0.98-1.19; 37 studies) for hospitalisation, 1.34 (95% CI 1.22-1.48; 124 studies) for severity and 1.32 (95% CI 1.20-1.45; 119 studies) for mortality. Estimates for former versus never-smokers were 1.16 (95% CI 1.03-1.31; 22 studies), 1.41 (95% CI: 1.25-1.59; 44 studies) and 1.46 (95% CI 1.31-1.62; 44 studies), respectively. Estimates for ever- versus never-smokers were 1.16 (95% CI 1.05-1.27; 33 studies), 1.44 (95% CI 1.31-1.58; 110 studies) and 1.39 (95% CI 1.29-1.50; 109 studies), respectively. We found a 30-50% excess risk of COVID-19 progression for current and former smokers compared with never-smokers. Preventing serious COVID-19 outcomes, including death, seems the newest compelling argument against smoking.

Methodological Investigation: Traditional and Systematic Reviews as Preliminary Findings for Delphi Technique

The Delphi method has been used as a way to reach consensus among experts established in the 1950s. The method was originally conceived to be used as a forecasting instrument for business in a mixed-method study. The Delphi method is usually conducted with elements of anonymity, iteration, controlled feedback and statistical group response. Delphi method had traditionally used expert opinions through methods such as interviews and brainstorming for the initial point of studies conducted. However, with the expanding volumes of research papers and articles in this age, can techniques such as Traditional Literature Review (TLR) and Systematic Literature Review (SLR) also be viable technique to be an initial point of studies for a Delphi study. As such this study aims 1) to examine and discover whether TLR and SLR are appropriate techniques to be used in a Delphi study and 2) construct a Delphi study process overview. This study adopts a methodology in which seven articles that have used TLR and SLR in their Delphi study will be analyzed. The results shows that TLR and SLR are appropriate techniques to be used in a Delphi study and that there are two types of processes to incorporate them into the study. We have also constructed a Delphi process overview through our analysis. We hope that the results of this study will be able help researchers who are interested in doing a Delphi study to know on what are the benefits of TLR and SLR in these studies along with how to incorporate them.

The Future of INCOG (Is Now).

The Future of INCOG (Is Now).

Searching the chemical content of drug sibutramin hydrochloride in herbal slimming products

Sibutramine hydrochloride as an additive in herbal slimming products is prohibited by the Ministry of Health in accordance with the Regulation of the Minister of Health of the Republic of Indonesia number 007 of 2012 concerning Registration of Traditional Medicines. The purpose of this review is to determine the content, the highest concentration value, the identification method and the distribution area of ​​herbal slimming products containing sibutramine hydrochloride. The method used is a traditional systematic review with inclusion criteria in the form of the year of publication of the journal with a period of the last 10 years, which uses both English and Indonesian, full text, articles that contain methods and methods of identifying sibutramine hydrochloride, and articles that list the number of positive samples. contains sibutramine hydrochloride and contains levels of sibutramine hydrochloride in herbal slimming products, the article lists the research location or the location of the herbal product sampling. The presentation of data from the results of the review in descriptive form includes the percentage of products containing sibutramine hydrochloride and the highest content of sibutramine hydrochloride. The results of the article review, herbal slimming products from different research locations contain sibutramine hydrochloride by 52.17% (36). Sibutramine hydrochloride analysis methods include TLC- Densitometry, UV-Vis Spectrophotometry, HPLC, and GC-MS. The herbal slimming product with the highest concentration comes from the city of Depok with a concentration of 26.24 mg/pill, China with a concentration of 78 mg/capsule.

Information and communications technology use to prevent and respond to sexual and gender-based violence in low- and middle-income countries: An evidence and gap map.

Information and communications technology use to prevent and respond to sexual and gender-based violence in low- and middle-income countries: An evidence and gap map.

Identifying Hyper-Heuristic Trends through a Text Mining Approach on the Current Literature

Hyper-heuristics have arisen as methods that increase the generality of existing solvers. They have proven helpful for dealing with complex problems, particularly those related to combinatorial optimization. Their recent growth in popularity has increased the daily amount of text in the related literature. This information is primarily unstructured, mainly text that traditional computer data systems cannot process. Traditional systematic literature review studies exhibit multiple limitations, including high time consumption, lack of replicability, and subjectivity of the results. For this reason, text mining has become essential for researchers in recent years. Therefore, efficient text mining techniques are needed to extract meaningful information, patterns, and relationships. This study adopts a literature review of 963 journal and conference papers on hyper-heuristic-related works. We first describe the essential text mining techniques, including text preprocessing, word clouds, clustering, and frequent association rule learning in hyper-heuristic publications. With that information, we implement visualization tools to understand the most frequent relations and topics in the hyper-heuristic domain. The main findings highlight the most dominant topics in the literature. We use text mining analysis to find widespread manifestations, representing the significance of the different areas of hyper-heuristics. Furthermore, we apply clustering to provide seven categories showing the associations between the topics related to hyper-heuristic literature. The vast amount of data available that we find opens up a new opportunity for researchers to analyze the status of hyper-heuristics and help create strategic plans regarding the scope of hyper-heuristics. Lastly, we remark that future work will address the limitations of collecting information from multiple data sources and analyze book chapters related to hyper-heuristics.