The development of indirect search strategies

Search filters for systematic reviews and meta-analyses in sleep medicine.

Background: In an era of explosive growth in biomedical evidence, improving systematic review (SR) search processes is increasingly critical. Text-mining tools (TMTs) are a potentially powerful resource to improve and streamline search strategy development. Two types of TMTs are especially of interest to searchers: word frequency (useful for identifying most used keyword terms, e.g., PubReminer) and clustering (visualizing common themes, e.g., Carrot2). Objectives: The objectives of this study were to compare the benefits and trade-offs of searches with and without the use of TMTs for evidence synthesis products in real world settings. Specific questions included: (1) Do TMTs decrease the time spent developing search strategies? (2) How do TMTs affect the sensitivity and yield of searches? (3) Do TMTs identify groups of records that can be safely excluded in the search evaluation step? (4) Does the complexity of a systematic review topic affect TMT performance? In addition to quantitative data, we collected librarians' comments on their experiences using TMTs to explore when and how these new tools may be useful in systematic review search¬¬ creation. Methods: In this prospective comparative study, we included seven SR projects, and classified them into simple or complex topics. The project librarian used conventional “usual practice” (UP) methods to create the MEDLINE search strategy, while a paired TMT librarian simultaneously and independently created a search strategy using a variety of TMTs. TMT librarians could choose one or more freely available TMTs per category from a pre-selected list in each of three categories: (1) keyword/phrase tools: AntConc, PubReMiner; (2) subject term tools: MeSH on Demand, PubReMiner, Yale MeSH Analyzer; and (3) strategy evaluation tools: Carrot2, VOSviewer. We collected results from both MEDLINE searches (with and without TMTs), coded every citation’s origin (UP or TMT respectively), deduplicated them, and then sent the citation library to the review team for screening. When the draft report was submitted, we used the final list of included citations to calculate the sensitivity, precision, and number-needed-to-read for each search (with and without TMTs). Separately, we tracked the time spent on various aspects of search creation by each librarian. Simple and complex topics were analyzed separately to provide insight into whether TMTs could be more useful for one type of topic or another. Results: Across all reviews, UP searches seemed to perform better than TMT, but because of the small sample size, none of these differences was statistically significant. UP searches were slightly more sensitive (92% [95% confidence intervals (CI) 85–99%]) than TMT searches (84.9% [95% CI 74.4–95.4%]). The mean number-needed-to-read was 83 (SD 34) for UP and 90 (SD 68) for TMT. Keyword and subject term development using TMTs generally took less time than those developed using UP alone. The average total time was 12 hours (SD 8) to create a complete search strategy by UP librarians, and 5 hours (SD 2) for the TMT librarians. TMTs neither affected search evaluation time nor improved identification of exclusion concepts (irrelevant records) that can be safely removed from the search set. Conclusion: Across all reviews but one, TMT searches were less sensitive than UP searches. For simple SR topics (i.e., single indication–single drug), TMT searches were slightly less sensitive, but reduced time spent in search design. For complex SR topics (e.g., multicomponent interventions), TMT searches were less sensitive than UP searches; nevertheless, in complex reviews, they identified unique eligible citations not found by the UP searches. TMT searches also reduced time spent in search strategy development. For all evidence synthesis types, TMT searches may be more efficient in reviews where comprehensiveness is not paramount, or as an adjunct to UP for evidence syntheses, because they can identify unique includable citations. If TMTs were easier to learn and use, their utility would be increased.

In this chapter we present data on trends in innovation in climate mitigation technologies. The data have been generated using newly developed search strategies to extract data from a worldwide database of patent documents (PATSTAT). In comparison with previous reports, this chapter draws upon the more detailed European Classification System (ECLA) and, most significantly, draws upon the expertise of patent examiners at the European Patent Office (EPO) in the development of search strategies. We present data on invention, technology transfer and research co-operation for a broad cross-section of countries over the last three decades. We also review some of the relevant empirical evidence on the determinants of innovation in these fields.

Background and rationale:Obesity is a metabolic condition brought on by the interplay of hereditary and environmental factors, making it one of the most common diseases in the world. Insulin resistance (IR) and obesity have a close connection and can both be advantageous. One of the main methods of epigenetic regulation is DNA methylation modification. Studies have demonstrated over the past few years that DNA methylation is crucial to the emergence of obesity and DNA methylation can lead to IR. Adipose tissue participates in the physiopathological processes of obesity and IR and functions as an endocrine organ controlling the body’s balanced metabolism, thus, adipose tissue-associated gene DNA methylation affects the development of obesity and IR by influencing the function of adipose tissue. Hence, an explanation of current research on DNA methylation, IR, and obesity, following the most recent developments, exploring changes in DNA methylation in different types of adipose tissue in insulin-resistant patients and obese patients may enable the identification of novel targets in clinical obesity prevention and treatment.Method and analysis:The following electronic bibliographic databases will be searched from inception for peer-reviewed original research published: MEDLINE (through PubMed), Scopus, and EMBASE. Cochrane Library, Cochrane Clinical Trials Registry, the National Institutes for Health Clinical Trials Registry, and the WHO International Clinical Trials Registry Platform from inception to December 31, 2021 will be conducted. Systematic reviews will adhere to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses reporting guidelines. The development of search strategies will make use of medical issue phrases and keywords associated with DNA methylation, Adipose tissue DNA methylation, obesity, and IR. Identified citations will be independently reviewed by two authors to determine eligibility at the title and abstract level, and then at the full text and data extraction phases. Disagreements and conflicts will be resolved through discussion with a third author. Two authors will extract the necessary data from the included studies independently, and The Cochrane Risk of Bias Assessment Tool will be used to assess the bias of randomized controlled studies, and the Newcastle–Ottawa scale for nonrandomized controlled studies. If the interventions and outcomes evaluated are sufficiently homogeneous, results from subgroups of studies will be pooled together in a meta-analysis.

A brief review has been provided with regard to some approaches to information retrieval that are now under development in the United States. These developments are discussed in terms of the unit operations of documentation: acquisition; analysis (abstracting, indexing, classifying, extracting); terminology control; recording of results of analysis on searchable medium; storage of source documents; question analysis and development of search strategy;conductingofsearch;anddelivery of search results.At the present time efforts in this field are largely uncoordinated, with decisions on depth of analysis of documents and philosophy of coding system left largely to the desires and opinions of individuals or separate organizations.Two programs in medjcal documentation at Western Reserve University are discussed: one in communicable diseases; and the other in diabetes. Both programs involve the analysis of the literature in considerable detail, using roles and links, and the control of the meaning of terminology using the technique , of semantic factoring.

Question analysis and search strategy development, two major components in the process of answering reference questions, were characterized as nine decision making steps. Twenty‐eight reference questions were analyzed in terms of these nine steps. The answers to each step were examined to determine whether rules for performing the individual steps by machine could be developed. Reasons are given for concluding that it would be very difficult, if not impossible, to have these reference process steps performed by machine.

Spatial navigation is a universal behavior that varies depending on goals, experience and available sensory stimuli. Spatial navigational tasks are routinely used to study learning, memory and goal-directed behavior, in both animals and humans. One popular paradigm for testing spatial memory is the Morris water maze, where subjects learn the location of a hidden platform that offers escape from a pool of water. Researchers typically express learning as a function of the latency to escape, though this reveals little about the underlying navigational strategies. Recently, a number of studies have begun to classify water maze search strategies in order to clarify the precise spatial and mnemonic functions of different brain regions, and to identify which aspects of spatial memory are disrupted in disease models. However, despite their usefulness, strategy analyses have not been widely adopted due to the lack of software to automate analyses. To address this need we developed Pathfinder, an open source application for analyzing spatial navigation behaviors. In a representative dataset, we show that Pathfinder effectively characterizes the development of highly-specific spatial search strategies as male and female mice learn a standard spatial water maze. Pathfinder can read data files from commercially- and freely-available software packages, is optimized for classifying search strategies in water maze paradigms, and can also be used to analyze 2D navigation by other species, and in other tasks, as long as timestamped xy coordinates are available. Pathfinder is simple to use, can automatically determine pool and platform geometry, generates heat maps, analyzes navigation with respect to multiple goal locations, and can be updated to accommodate future developments in spatial behavioral analyses. Given these features, Pathfinder may be a useful tool for studying how navigational strategies are regulated by the environment, depend on specific neural circuits, and are altered by pathology.

Spatial navigation is a universal behavior that varies depending on goals, experience and available sensory stimuli. Spatial navigational tasks are routinely used to study learning, memory and goal-directed behavior, in both animals and humans. One popular paradigm for testing spatial memory is the Morris water maze, where subjects learn the location of a hidden platform that offers escape from a pool of water. Researchers typically express learning as a function of the latency to escape, though this reveals little about the underlying navigational strategies. Recently, a number of studies have begun to classify water maze search strategies in order to clarify the precise spatial and mnemonic functions of different brain regions, and to identify which aspects of spatial memory are disrupted in disease models. However, despite their usefulness, strategy analyses have not been widely adopted due to the lack of software to automate analyses. To address this need we developed Pathfinder, an open source application for analyzing spatial navigation behaviors. In a representative dataset, we show that Pathfinder effectively characterizes the development of highly-specific spatial search strategies as male and female mice learn a standard spatial water maze. Pathfinder can read data files from commercially- and freely-available software packages, is optimized for classifying search strategies in water maze paradigms, and can also be used to analyze 2D navigation by other species, and in other tasks, as long as timestamped xy coordinates are available. Pathfinder is simple to use, can automatically determine pool and platform geometry, generates heat maps, analyzes navigation with respect to multiple goal locations, and can be updated to accommodate future developments in spatial behavioral analyses. Given these features, Pathfinder may be a useful tool for studying how navigational strategies are regulated by the environment, depend on specific neural circuits, and are altered by pathology.

Evidence of the effectiveness of health promotion to support decision-making has become increasingly important to health promotion practitioners and policy-makers. Primary research on effectiveness, however, is not always easily accessible. This study aimed to contribute to strategies for facilitating access to this research by exploring the development and implementation of search strategies for identifying effectiveness research, in the area of sexual health promotion, on five commonly used electronic databases. Firstly, search stra tegies to locate all available research were developed; secondly, the implications of restrictions on the extent of searcliing were investigated. Undertaking sys tematic searching was complex and time-consuming. Although useful ways to reduce the effort involved were identified, in the context of conducting sys tematic reviews, these came with 'trade-offs' in terms of the number of poten tially important studies missed. These findings suggest an urgent need for wide dissemination of search strategies and specialised registers of health promotion studies. This study is part of an ongoing programme of work on facilitating evidence-based health promotion, and this the third and final paper in a series published in three consecutive issues of the HEJ.

The main sources of citation injustice are the collective biases in the scientific community, including literature retrieval bias, which has direct effects on citation inequality. In this commentary I focus on index bias in literature databases, inherent/unconscious bias during search strategy development, and systematic bias of controlled vocabularies. Exemplar literature search strategies and/or retrieval analyses comparing Web of Science and OpenAlex are used to demonstrate these biases. Moreover, this commentary offers steps to consider during literature search preparation, search query building, and the search itself, which can lead to a more inclusive representation of the literature in the topic of interest and reduce citation inequity.

SPAPT: Search Problems in Automatic Performance Tuning

Objective To evaluate and synthesise current applications of large language models (LLMs) in systematic reviews and meta-analyses (SRMAs), identify key limitations and propose an enhanced theoretical framework to improve the efficiency, scalability and reliability of evidence synthesis. Methods and analysis We conducted a narrative review of recent studies applying LLMs across key SRMA stages. A total of 21 publications were analysed for model type, task application, accuracy metrics and workflow impact. Building on this evidence base, we designed a comprehensive LLM-enhanced SRMA framework that categorises LLM roles as consultants and assistants, integrates human-in-the-loop strategies and uses retrieval-augmented generation (RAG) and agent-based architectures to address critical challenges including hallucinations, bias and workflow inefficiency. Results The reviewed literature demonstrated that LLMs can support various SRMA tasks with reported accuracy ranging from 61% to 99%, showing particular promise in literature screening and data extraction. Our proposed framework conceptualises modular integration of LLMs across all six SRMA stages, with LLMs serving as consultants for research question formulation and search strategy development and as assistants for task automation including abstract screening and structured data extraction. The framework incorporates RAG technology to reduce hallucinations by grounding outputs in retrieved literature and employs agent-based orchestration for complex analytical workflows. Theoretical analysis suggests potential for significant efficiency gains while maintaining methodological rigour through strategic human oversight. Conclusion LLMs offer substantial theoretical potential to transform evidence synthesis by improving efficiency, scalability and consistency across SRMA workflows. The proposed LLM-enhanced framework provides a systematic, theoretically grounded approach for integrating advanced artificial intelligence capabilities into existing SRMA methodologies while preserving essential human oversight and analytical integrity. Future empirical studies are needed to validate the framework’s practical effectiveness, establish implementation protocols and demonstrate real-world benefits in evidence-based medicine.

BackgroundIn response to the high burden of disease among sex workers and their position as a population heavily affected by the HIV epidemic, there has been a growing body of literature investigating the prevalence and risk factors associated with HIV risk among sex workers. To contextualize and summarize the existing research evidence base, a systematic review was conducted to synthesize the epidemiological literature on sex workers in Uganda.MethodsDatabase selection and search strategy development followed the Cochrane Collaboration’s standards for conducting systematic review searches. All studies that included sex workers as the primary research participants were included in the review. The search was then geographically restricted to the country of Uganda. Items were identified from 18 databases (grey and peer-review) on March 10–11, 2015.ResultsA total of 484 articles were retrieved from the database search. After removal of duplicates, a total of 353 articles were screened for eligibility and 64 full-text articles were assessed. The final review included 24 studies with quantitative methodology conducted among sex workers in Uganda. The HIV prevalence among female sex workers ranged from 32.4–52.0 % and between 8.2–9.0 % had multiple HIV infections. Both multi-drug resistance to antiretroviral therapy (2.6 %) and antibiotics (83.1 %) were observed. Between 33.3–55.1 % reported inconsistent condom use in the past month. In the previous 6 months, over 80 % of sex workers experienced client-perpetrated violence and 18 % experienced intimate partner violence. Over 30 % had a history of extreme war-related trauma.ConclusionsThere was limited information on socio-structural factors that affect sex workers’ commercial working environments in Uganda, including the role of policing and criminalization, as well as the prevalence and factors associated with violence. The majority of the existing evidence is based in Kampala, highlighting a need for information on sex work in other regions of Uganda. Additionally, there is limited information on features of the non-commercial components of sex workers’ lives as well as the services needed to reduce risks outside of the sex industry.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-015-2553-0) contains supplementary material, which is available to authorized users.

This paper describes the search approach for preprints for a post COVID-19 condition (i.e., long COVID) scoping review, including source selection, search strategy development, challenges, and insights throughout a project life cycle. With the growth of medical preprints since the COVID-19 pandemic, information professionals and researchers should be aware that preprints are possible sources of evidence and be prepared to manage them in evidence reviews for COVID-19 topics and beyond. Preprints are not peer-reviewed but can include important evidence about emerging topics. Because of the importance of preprints to the scoping review, a preprint search of Europe PubMed Central (PMC) was added. Europe PMC and similar aggregators combine multiple preprint servers and often have Boolean search, but sometimes limited search functionalities or few export options. Strategy translation encountered challenges such as varying and inconsistent terminology for post-COVID-19 condition, a complex search, and negotiating large numbers of preprints with resource constraints. Europe PMC identified additional preprints for inclusion due to additional preprint server coverage. It was helpful to limit the preprint search to the title and abstract fields, and to run an extra Internet search for publication of included study preprints. Challenges and potential solutions are summarized to support those conducting preprint searches for COVID-19 and other topics.

Suicide has become a serious public health concern and international research has shown that the majority of individuals who die by suicide had receive healthcare in the year prior to their death. This presents an opportunity for suicide prevention by strategically training healthcare students in suicide prevention knowledge and skills. The objective of this scoping review is to identify literature that describes the design, development, implementation and/or evaluation of suicide prevention training for healthcare and/or social care students in higher education settings. Studies will only be considered eligible for inclusion if they describe the design, development, implementation and/or evaluation of suicide prevention curricula being delivered to healthcare or social care degree students in higher education. Quantitative, qualitative, and mixed method studies published between 2011 and 2023 (inclusive) and in the English language will be considered eligible. This scoping review will be conducted according to the PRISMA guidelines for scoping reviews (PRISMA-ScR). The developed search strategy will be implemented across six databases: PubMed, ERIC (Education Resources Information Center), PsycINFO, Embase, CINAHL and Web of Science. Several grey literature sources will also be consulted. Further potential results will be located by hand-searching the reference lists of included articles. The search strategy will include variations of the terms: 'student', 'suicide prevention' and 'education'. The search will be limited to titles, abstracts, and keywords in databases that allow it. Two reviewers will complete the screening using the predefined inclusion criteria. A third reviewer will resolve any conflicts during the screening and eligibility appraisal processes. Results will be presented in the form of tabulated results and an accompanying narrative summary, describing key findings and context related to learning outcomes, methodologies employed and implementation of the identified programmes.