It takes longer than you think: librarian time spent on systematic review tasks

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

Systematic reviews and meta-analyses are increasingly common in sleep research, although the methodological quality level has been a matter of concern. Efforts towards methodological standardization are needed to ensure the reliability of sleep-related systematic reviews. The development of search strategies is a critical step in a systematic review, which often lead to methodological biases. Standardized search filters have been used to facilitate the development of search strategies. However, such filters have not been developed for sleep medicine. The current study aimed at developing a list of PubMed search filters related to sleep medicine, including specific search strategies for different sleep disorders and sleep conditions. First, a list of sleep disorders and conditions was created for which search filters would be developed. This included most conditions listed in the International Classification of Sleep Disorders - 3rd edition. Additional search filters were developed for proposed disorders not recognized as independent clinical entities, and for other sleep-related conditions. All search strategies were designed specifically for PubMed, by combining relevant MeSH terms and free terms. Nine fully independent and unrelated MeSH terms related to sleep were identified. In total, 91 search filters were developed, related to 71 different sleep-related conditions. With the current work, we aimed to provide a list of reliable search filters organized to cover the field in a broad manner, therefore being useful for different types of systematic reviews within sleep medicine, ranging from narrow-focused meta-analyses to broader scoping reviews, mapping reviews, and meta-epidemiological studies.

Librarian involvement on knowledge synthesis articles and its relationship to article citation count and Journal Impact Factor

Introduction

Our aim was to determine if there is a relationship between librarian involvement on a knowledge synthesis project and the synthesis's citation count or the Journal Impact Factor (JIF) of its publication venue.

Methods

A total of 551 knowledge syntheses published during a one-year period (2020) from a single category, "Psychology, Clinical", in Clarivate's Journal Citation Reports were exported from Web of Science along with the citation counts for each synthesis and the JIF of its publication venue. The full-text of each article was examined in order to code each as either co-author, acknowledged, or unknown to reflect the level of librarian involvement in the synthesis. The Wilcoxon Rank Sum test on bootstrapped samples was used to determine the significance of the results.

Results

Librarians were co-authors or acknowledged in 80 (15%) of the syntheses examined. Analyzing two levels of librarian involvement (involved, unknown) indicated no relationship between the level of librarian involvement and the JIF of the journal nor the citation count the synthesis received since publication.

Discussion

There is no evidence of a relationship between librarian involvement in knowledge syntheses and the JIF of the publication or citation count of documents published in journals falling in the JCR category of "Psychology, Clinical" in the year 2020. Repeating this methodology in a different JCR category could help determine whether this lack of a relationship extends beyond the "Psychology, Clinical" category.

The optimal approach for retrieving systematic reviews was achieved when searching MEDLINE and Epistemonikos in addition to reference checking: a methodological validation study

BACKGROUND

Systematic reviews (SRs) are used to inform clinical practice guidelines and healthcare decision making by synthesising the results of primary studies. Efficiently retrieving as many relevant SRs as possible is challenging with a minimum number of databases, as there is currently no guidance on how to do this optimally. In a previous study, we determined which individual databases contain the most SRs, and which combination of databases retrieved the most SRs. In this study, we aimed to validate those previous results by using a different, larger, and more recent set of SRs.

METHODS

We obtained a set of 100 Overviews of Reviews that included a total of 2276 SRs. SR inclusion was assessed in MEDLINE, Embase, and Epistemonikos. The mean inclusion rates (% of included SRs) and corresponding 95% confidence intervals were calculated for each database individually, as well as for combinations of MEDLINE with each other database and reference checking. Features of SRs not identified by the best database combination were reviewed qualitatively.

RESULTS

Inclusion rates of SRs were similar in all three databases (mean inclusion rates in % with 95% confidence intervals: 94.3 [93.9-94.8] for MEDLINE, 94.4 [94.0-94.9] for Embase, and 94.4 [93.9-94.9] for Epistemonikos). Adding reference checking to MEDLINE increased the inclusion rate to 95.5 [95.1-96.0]. The best combination of two databases plus reference checking consisted of MEDLINE and Epistemonikos (98.1 [97.7-98.5]). Among the 44/2276 SRs not identified by this combination, 34 were published in journals from China, four were other journal publications, three were health agency reports, two were dissertations, and one was a preprint. When discounting the journal publications from China, the SR inclusion rate in the recommended combination (MEDLINE, Epistemonikos and reference checking) was even higher than in the previous study (99.6 vs. 99.2%).

CONCLUSIONS

A combination of databases and reference checking was the best approach to searching for biomedical SRs. MEDLINE and Epistemonikos, complemented by checking the references of the included studies, was the most efficient and produced the highest recall. However, our results point to the presence of geographical bias, because some publications in journals from China were not identified.

STUDY REGISTRATION

https://doi.org/10.17605/OSF.IO/R5EAS (Open Science Framework).

Large-scale systematic review support for guideline development in diabetes precision medicine

Background

Involving librarians as team members can lead to better quality in reviews. To improve their search results, an international diabetes project involved two medical librarians in a large-scale project planning of a series of systematic reviews for clinical guidelines in diabetes precision medicine.

Case Presentation

The precision diabetes project was divided into teams. Four diabetes mellitus types (type 1, type 2, gestational, and monogenic) were divided into teams focusing on diagnostics, prevention, treatment, or prognostics. A search consultation plan was set up for the project to help organize the work. We performed searches in Embase and PubMed for 14 teams, building complex searches that involved non-traditional search strategies. Our search strategies generated very large amounts of records that created challenges in balancing sensitivity with precision. We also performed overlap searches for type 1 and type 2 diabetes search strategies; and assisted in setting up reviews in the Covidence tool for screening.

Conclusions

This project gave us opportunities to test methods we had not used before, such as overlap comparisons between whole search strategies. It also gave us insights into the complexity of performing a search balancing sensitivity and specificity and highlights the need for a clearly defined communication plan for extensive evidence synthesis projects.

Machine learning models for abstract screening task - A systematic literature review application for health economics and outcome research

OBJECTIVE

Systematic literature reviews (SLRs) are critical for life-science research. However, the manual selection and retrieval of relevant publications can be a time-consuming process. This study aims to (1) develop two disease-specific annotated corpora, one for human papillomavirus (HPV) associated diseases and the other for pneumococcal-associated pediatric diseases (PAPD), and (2) optimize machine- and deep-learning models to facilitate automation of the SLR abstract screening.

METHODS

This study constructed two disease-specific SLR screening corpora for HPV and PAPD, which contained citation metadata and corresponding abstracts. Performance was evaluated using precision, recall, accuracy, and F1-score of multiple combinations of machine- and deep-learning algorithms and features such as keywords and MeSH terms.

RESULTS AND CONCLUSIONS

The HPV corpus contained 1697 entries, with 538 relevant and 1159 irrelevant articles. The PAPD corpus included 2865 entries, with 711 relevant and 2154 irrelevant articles. Adding additional features beyond title and abstract improved the performance (measured in Accuracy) of machine learning models by 3% for HPV corpus and 2% for PAPD corpus. Transformer-based deep learning models that consistently outperformed conventional machine learning algorithms, highlighting the strength of domain-specific pre-trained language models for SLR abstract screening. This study provides a foundation for the development of more intelligent SLR systems.

Validation of an interprofessional education search strategy in PubMed to optimize IPE literature searching

Objective

With exponential growth in the publication of interprofessional education (IPE) research studies, it has become more difficult to find relevant literature and stay abreast of the latest research. To address this gap, we developed, evaluated, and validated search strategies for IPE studies in PubMed, to improve future access to and synthesis of IPE research. These search strategies, or search hedges, provide comprehensive, validated sets of search terms for IPE publications.

Methods

The search strategies were created for PubMed using relative recall methodology. The research methods followed the guidance of previous search hedge and search filter validation studies in creating a gold standard set of relevant references using systematic reviews, having expert searchers identify and test search terms, and using relative recall calculations to validate the searches' performance against the gold standard set.

Results

The three recommended search hedges for IPE studies presented had recall of 71.5%, 82.7%, and 95.1%; the first more focused for efficient literature searching, the last with high recall for comprehensive literature searching, and the remaining hedge as a middle ground between the other two options.

Conclusion

These validated search hedges can be used in PubMed to expedite finding relevant scholarships, staying up to date with IPE research, and conducting literature reviews and evidence syntheses.

How do search systems impact systematic searching? A qualitative study

Objective

Systematic reviews and other evidence synthesis projects require systematic search methods. Search systems require several essential attributes to support systematic searching; however, many systems used in evidence synthesis fail to meet one or more of these requirements. I undertook a qualitative study to examine the effects of these limitations on systematic searching and how searchers select information sources for evidence synthesis projects.

Methods

Qualitative data were collected from interviews with twelve systematic searchers. Data were analyzed using reflexive thematic analysis.

Results

I used thematic analysis to identify two key themes relating to search systems: systems shape search processes, and systematic searching occurs within the information market. Many systems required for systematic reviews, in particular sources of unpublished studies, are not designed for systematic searching. Participants described various workarounds for the limitations they encounter in these systems. Economic factors influence searchers' selection of sources to search, as well as the degree to which vendors prioritize these users.

Conclusion

Interviews with systematic searchers suggest priorities for improving search systems, and barriers to improvement that must be overcome. Vendors must understand the unique requirements of systematic searching and recognize systematic searchers as a distinct group of users. Better interfaces and improved functionality will result in more efficient evidence synthesis.

Are ChatGPT and large language models "the answer" to bringing us closer to systematic review automation?

In this commentary, we discuss ChatGPT and our perspectives on its utility to systematic reviews (SRs) through the appropriateness and applicability of its responses to SR related prompts. The advancement of artificial intelligence (AI)-assisted technologies leave many wondering about the current capabilities, limitations, and opportunities for integration AI into scientific endeavors. Large language models (LLM)-such as ChatGPT, designed by OpenAI-have recently gained widespread attention with their ability to respond to various prompts in a natural-sounding way. Systematic reviews (SRs) utilize secondary data and often require many months and substantial financial resources to complete, making them attractive grounds for developing AI-assistive technologies. On February 6, 2023, PICO Portal developers hosted a webinar to explore ChatGPT's responses to tasks related to SR methodology. Our experience from exploring the responses of ChatGPT suggest that while ChatGPT and LLMs show some promise for aiding in SR-related tasks, the technology is in its infancy and needs much development for such applications. Furthermore, we advise that great caution should be taken by non-content experts in using these tools due to much of the output appearing, at a high level, to be valid, while much is erroneous and in need of active vetting.

Why do researchers co-author evidence syntheses with librarians? A mixed-methods study

Librarians and information specialists are experts in designing comprehensive literature searches, such as those needed for Evidence Syntheses (ES). The contributions of these professionals to ES research teams have several documented benefits, especially when they collaborate on the project. However, librarian co-authorship is relatively rare. This study explores researcher motivations for working with librarians at the co-author level through a mixed methods design. Interviews with researchers identified 20 potential motivations that were then tested through an online questionnaire sent to authors of recently published ES. Consistent with previous findings, most respondents did not have a librarian co-author on their ES, though 16% acknowledged one in their manuscript and 10% consulted one but did not document the contribution. Search expertise was the most common motivation both to and not to co-author with librarians. Those that had or were interested in co-authoring stated that they wanted the librarians' search expertise, while those who had not or were not interested stated that they already had the necessary search expertise. Researchers who were motivated by methodological expertise and availability were more likely to have co-authored their ES with a librarian. No motivations were negatively associated with librarian co-authorship. These findings provide an overview of the motivations that influence researchers to bring a librarian into an ES investigatory team. More research is needed to substantiate the validity of these motivations.

An automated method for developing search strategies for systematic review using Natural Language Processing (NLP)

The design and implementation of systematic reviews and meta-analyses are often hampered by high financial costs, significant time commitment, and biases due to researchers' familiarity with studies. We proposed and implemented a fast and standardized method for search term selection using Natural Language Processing (NLP) and co-occurrence networks to identify relevant search terms to reduce biases in conducting systematic reviews and meta-analyses.•The method was implemented using Python packaged dubbed Ananse, which is benchmarked on the search terms strategy for naïve search proposed by Grames et al. (2019) written in "R". Ananse was applied to a case example towards finding search terms to implement a systematic literature review on cumulative effect studies on forest ecosystems.•The software automatically corrected and classified 100% of the duplicate articles identified by manual deduplication. Ananse was applied to the cumulative effects assessment case study, but it can serve as a general-purpose, open-source software system that can support extensive systematic reviews within a relatively short period with reduced biases.•Besides generating keywords, Ananse can act as middleware or a data converter for integrating multiple datasets into a database.

A Tailored Approach: A model for literature searching in complex systematic reviews

Our previous work identified that nine leading guidance documents for seven different types of systematic review advocated the same process of literature searching. We defined and illustrated this process and we named it ‘the Conventional Approach’. The Conventional Approach appears to meet the needs of researchers undertaking literature searches for systematic reviews of clinical interventions. In this article, we report a new and alternate process model of literature searching called ‘A Tailored Approach’. A Tailored Approach is indicated as a search process for complex reviews which do not focus on the evaluation of clinical interventions. The aims of this article are to (1) explain the rationale for, and the theories behind, the design of A Tailored Approach; (2) report the current conceptual illustration of A Tailored Approach and to describe a user’s interaction with the process model; and (3) situate the elements novel to A Tailored Approach (when compared with the Conventional Approach) in the relevant literature. A Tailored Approach suggests investing time at the start of a review, to develop the information needs from the research objectives, and to tailor the search approach to studies or data. Tailored Approaches should be led by the information specialist (librarian) but developed by the research team. The aim is not necessarily to focus on comprehensive retrieval. Further research is indicated to evaluate the use of supplementary search methods, methods of team-working to define search approaches, and to evaluate the use of conceptual models of information retrieval for testing and evaluation.

Resource use during systematic review production varies widely: a scoping review

OBJECTIVE

We aimed to map the resource use during systematic review (SR) production and reasons why steps of the SR production are resource intensive to discover where the largest gain in improving efficiency might be possible.

STUDY DESIGN AND SETTING

We conducted a scoping review. An information specialist searched multiple databases (e.g., Ovid MEDLINE, Scopus) and implemented citation-based and grey literature searching. We employed dual and independent screenings of records at the title/abstract and full-text levels and data extraction.

RESULTS

We included 34 studies. Thirty-two reported on the resource use-mostly time; four described reasons why steps of the review process are resource intensive. Study selection, data extraction, and critical appraisal seem to be very resource intensive, while protocol development, literature search, or study retrieval take less time. Project management and administration required a large proportion of SR production time. Lack of experience, domain knowledge, use of collaborative and SR-tailored software, and good communication and management can be reasons why SR steps are resource intensive.

CONCLUSION

Resource use during SR production varies widely. Areas with the largest resource use are administration and project management, study selection, data extraction, and critical appraisal of studies.

Addressing challenges with systematic review teams through effective communication: a case report

BACKGROUND

Every step in the systematic review process has challenges, ranging from resistance by review teams to adherence to standard methodology to low-energy commitment to full participation. These challenges can derail the project and result in significant delays, duplication of work, and failure to complete the review. Communication during the systematic review process is key to ensuring it runs smoothly and is identified as a core competency for librarians involved in systematic reviews.

CASE PRESENTATION

This case report presents effective communication approaches that our librarians employ to address challenges encountered while working with systematic review teams. The communication strategies we describe engage teams through information, questions, and action items and lead to productive collaborations with publishable systematic reviews.

CONCLUSIONS

Effective communication with review teams keeps systematic review projects moving forward. The techniques covered in this case study strive to minimize misunderstandings, educate collaborators, and, in our experience, have led to multiple successful collaborations and publications. Librarians working in the systematic review space will recognize these challenges and can adapt these techniques to their own environments.

Adopting a toolkit to manage time, resources, and expectations in the systematic review process: a case report

BACKGROUND

The proliferation of systematic reviews has impacted library operations and activities as librarians support, collaborate, and perform more tasks in the systematic review process. This case report describes a toolkit that librarians with extensive experience in supporting multiple review teams use to manage time, resources, and expectations in the systematic review process.

CASE PRESENTATION

The toolkit is a compilation of documents that we use to effectively communicate with and help review teams understand and navigate each stage of the systematic review process. Elements included in the toolkit and discussed in this case report are intake forms, communication templates and memoranda, a process flow diagram, library guides on tools for retrieval and data appraisal, and established standards for guidance during the write-up stage. We describe the use of the toolkit for both education and project management, with a focus on its use in helping manage team time, resources, and expectations.

DISCUSSION

The systematic review toolkit helps librarians connect systematic review steps and tasks to actionable items. The content facilitates and supports discussion and learning by both librarians and team members. This toolkit helps librarians share important information and resources for each stage of the process.

An environmental scan of librarian involvement in systematic reviews at Queen's University: 2020 update

Introduction

Systematic reviews are a growing research methodology in the health sciences, and in other disciplines, having a significant impact on librarian workload. In a follow up to an earlier study, an environmental scan was conducted at Queen's University to determine what has changed, if anything, since the introduction of a tiered service for knowledge synthesis by examining review publications where at least one co-author was from Queen's University.

Methods

A search was conducted in PubMed and the Joanna Briggs database to find systematic reviews and meta-analyses with at least one author from Queen's University for the five-year time since the last environmental scan. Reviews were categorized by the degree of involvement of the librarian(s) regardless of their institutional affiliation: librarian as co-author, librarian named in the acknowledgements, no known librarian involvement in the review.

Results

Of 453 systematic reviews published in the five-year time frame, nearly 20% (89) had a librarian named as co-author. A further 24.5% (110) acknowledged the role of a librarian in the search, either in the acknowledgements section or in the body of the text of the article. In just over half of reviews (235 or 51.8%) a librarian was either not involved, or was not explicitly acknowledged. More librarians and more institutions were represented in the period of 2016-2020 than in 2010-2015.

Conclusion

In the five years since the last environmental scan, an increasing number of reviews recognized the role of the librarian in publishing systematic reviews, either through co-authorship or named acknowledgement. This also suggests that as more librarians have become involved in systematic reviews, librarian capacity for this work has increased compared to five years ago.

Updating search strategies for literature reviews with OUR2D2: an open-source computer application

Background:

While writing a scoping review, we needed to update our search strategy. We wanted to capture articles generated by our additional search terms and articles published since our original search. Simultaneously, we strove to optimize project resources by not rescreening articles that had been captured in our original results.

Case presentation:

In response, we created Open Update Re-run Deduplicate (OUR2D2), a computer application that allows the user to compare search results from a variety of library databases. OUR2D2 supports extensible markup language (XML) files from EndNote and comma-separated values (CSV) files using article titles for comparisons. We conducted unit tests to ensure appropriate functionality as well as accurate data extraction and analysis. We tested OUR2D2 by comparing original and updated search results from PubMed, Embase, Clarivate Web of Science, CINAHL, Scopus, ProQuest Dissertation and Theses, and Lens and estimate that this application saved twenty-one hours of work during the screening process.

Conclusions:

OUR2D2 could be useful for individuals seeking to update literature review strategies across fields without rescreening articles from previous searches. Because the OUR2D2 source code is freely available with a permissive license, we recommend this application for researchers conducting literature reviews who need to update their search results over time, want a powerful and flexible analysis framework, and may not have access to paid subscription tools.

The decisions and processes involved in a systematic search strategy: a hierarchical framework

OBJECTIVE

The decisions and processes that may compose a systematic search strategy have not been formally identified and categorized. This study aimed to (1) identify all decisions that could be made and processes that could be used in a systematic search strategy and (2) create a hierarchical framework of those decisions and processes.

METHODS

The literature was searched for documents or guides on conducting a literature search for a systematic review or other evidence synthesis. The decisions or processes for locating studies were extracted from eligible documents and categorized into a structured hierarchical framework. Feedback from experts was sought to revise the framework. The framework was revised iteratively and tested using recently published literature on systematic searching.

RESULTS

Guidance documents were identified from expert organizations and a search of the literature and Internet. Data were extracted from 74 eligible documents to form the initial framework. The framework was revised based on feedback from 9 search experts and further review and testing by the authors. The hierarchical framework consists of 119 decisions or processes sorted into 17 categories and arranged under 5 topics. These topics are "Skill of the searcher," "Selecting information to identify," "Searching the literature electronically," "Other ways to identify studies," and "Updating the systematic review."

CONCLUSIONS

The work identifies and classifies the decisions and processes used in systematic searching. Future work can now focus on assessing and prioritizing research on the best methods for successfully identifying all eligible studies for a systematic review.

Overlaps of multiple database retrieval and citation tracking in dementia care research: a methodological study

OBJECTIVE

We aimed to determine overlaps and optimal combination of multiple database retrieval and citation tracking for evidence synthesis, based on a previously conducted scoping review on facilitators and barriers to implementing nurse-led interventions in dementia care.

METHODS

In our 2019 scoping review, we performed a comprehensive literature search in eight databases (CENTRAL, CINAHL, Embase, Emcare, MEDLINE, Ovid Nursing Database, PsycINFO, and Web of Science Core Collection) and used citation tracking. We retrospectively analyzed the coverage and overlap of 10,527 retrieved studies published between 2015 and 2019. To analyze database overlap, we used cross tables and multiple correspondence analysis (MCA).

RESULTS

Of the retrieved studies, 6,944 were duplicates and 3,583 were unique references. Using our search strategies, considerable overlaps can be found in some databases, such as between MEDLINE and Web of Science Core Collection or between CINAHL, Emcare, and PsycINFO. Searching MEDLINE, CINAHL, and Web of Science Core Collection and using citation tracking were necessary to retrieve all included studies of our scoping review.

CONCLUSIONS

Our results can contribute to enhancing future search practice related to database selection in dementia care research. However, due to limited generalizability, researchers and librarians should carefully choose databases based on the research question. More research on optimal database retrieval in dementia care research is required for the development of methodological standards.

Improving the translation of search strategies using the Polyglot Search Translator: a randomized controlled trial

Background

Searching for studies to include in a systematic review (SR) is a time- and labor-intensive process with searches of multiple databases recommended. To reduce the time spent translating search strings across databases, a tool called the Polyglot Search Translator (PST) was developed. The authors evaluated whether using the PST as a search translation aid reduces the time required to translate search strings without increasing errors.

Methods

In a randomized trial, twenty participants were randomly allocated ten database search strings and then randomly assigned to translate five with the assistance of the PST (PST-A method) and five without the assistance of the PST (manual method). We compared the time taken to translate search strings, the number of errors made, and how close the number of references retrieved by a translated search was to the number retrieved by a reference standard translation.

Results

Sixteen participants performed 174 translations using the PST-A method and 192 translations using the manual method. The mean time taken to translate a search string with the PST-A method was 31 minutes versus 45 minutes by the manual method (mean difference: 14 minutes). The mean number of errors made per translation by the PST-A method was 8.6 versus 14.6 by the manual method. Large variation in the number of references retrieved makes results for this outcome inconclusive, although the number of references retrieved by the PST-A method was closer to the reference standard translation than the manual method.

Conclusion

When used to assist with translating search strings across databases, the PST can increase the speed of translation without increasing errors. Errors in search translations can still be a problem, and search specialists should be aware of this.

A Microsoft Excel Approach to Reduce Errors and Increase Efficiency in Systematic Searching

Developing a search strategy for a systematic review is a time-consuming process in which small errors around the formatting and compilation of terms can have large consequences. Microsoft Excel was identified as a potentially useful software to streamline the process and reduce manual errors. Ultimately a spreadsheet was created that largely automates the process of creating a single-line search string with correctly formatted terms, Boolean operators and parentheses.

Novel citation-based search method for scientific literature: a validation study

Background

We recently developed CoCites, a citation-based search method that is designed to be more efficient than traditional keyword-based methods. The method begins with identification of one or more highly relevant publications (query articles) and consists of two searches: the co-citation search, which ranks publications on their co-citation frequency with the query articles, and the citation search, which ranks publications on frequency of all citations that cite or are cited by the query articles.

Methods

We aimed to reproduce the literature searches of published systematic reviews and meta-analyses and assess whether CoCites retrieves all eligible articles while screening fewer titles.

Results

A total of 250 reviews were included. CoCites retrieved a median of 75% of the articles that were included in the original reviews. The percentage of retrieved articles was higher (88%) when the query articles were cited more frequently and when they had more overlap in their citations. Applying CoCites to only the highest-cited article yielded similar results. The co-citation and citation searches combined were more efficient when the review authors had screened more than 500 titles, but not when they had screened less.

Conclusions

CoCites is an efficient and accurate method for finding relevant related articles. The method uses the expert knowledge of authors to rank related articles, does not depend on keyword selection and requires no special expertise to build search queries. The method is transparent and reproducible.

Burnout among medical and health sciences information professionals who support systematic reviews: an exploratory study

Objective

The aim of this exploratory study was to assess personal, work-related, and client-related burnout among information professionals who support systematic review (SR) work.

Methods

The Copenhagen Burnout Inventory, a validated tool for assessing burnout, was administered to information professionals who support SR work. A broad range of health sciences or medical librarians and information professionals were targeted via professional email discussion lists and news outlets. Questionnaire responses were captured electronically using Qualtrics Survey Software and quantitatively analyzed.

Results

Respondents experienced an average personal burnout score of 48.6, work-related score of 46.4, and client-related score of 32.5 out of 100. Respondents who reported spending >80% of their job duties on SR work had significantly lower personal burnout scores than those who reported spending <10% of their job duties on SR work (average, 31.5 versus 50.9, respectively). Also, respondents who reported using an SR support tool had significantly lower personal burnout scores than those who reported sometimes using a tool (average, 43.7 versus 54.7, respectively).

Conclusion

The results suggest that information professionals who dedicate more time to SR work or who consistently use an SR support tool experience less burnout. This study provides groundwork for further investigation with the aim of developing approaches to prevent or combat SR-related burnout among information professionals.

Building the Systematic Review Core in an academic health sciences library

BACKGROUND

The authors present efforts to build capacity at our institution for conducting systematic reviews and other forms of evidence synthesis through partnerships and a recharge model. This report describes how we successfully created and launched a for-fee systematic review core at our library.

CASE PRESENTATION

Throughout 2014 and 2015, library leadership proposed different models for getting institutional and financial support for librarians and staff to better support university researchers conducting systematic reviews. Though well received, initial requests for financial support were not funded. The executive director of the Health Sciences Library released two years' worth of salary and benefits to fund an evidence synthesis and retrieval librarian position. With this new position, the team formed a charge-back core facility in partnership with our university's Clinical Translation and Science Award hub. A series of procedural decisions and operational changes helped the group achieve success. Within eighteen months after launching the Systematic Review Core, we reached maximum capacity with more than twenty ongoing reviews.

DISCUSSION

Assigning a dollar value to our expertise put us on par with other subject matter experts on campus and actually drove demand. We could act as paid consultants in research projects and shifted the perception of librarians from service providers to research partners. Affiliating with our partners was key to our success and boosted our ability to strengthen our campus' research infrastructure.

Rapid reviews may produce different results to systematic reviews: a meta-epidemiological study

OBJECTIVE

To simulate possible changes in systematic review results if rapid review methods were used.

STUDY DESIGN AND SETTING

We recalculated meta-analyses for binary primary outcomes in Cochrane systematic reviews, simulating rapid review methods. We simulated searching only PubMed, excluding older articles (5, 7, 10, 15, and 20 years before the search date), excluding smaller trials (<50, <100, and <200 participants), and using the largest trial only. We examined percentage changes in pooled odds ratios (ORs) (classed as no important change [<5%], small [<20%], moderate [<30%], or large [≥30%]), statistical significance, and biases observed using rapid methods.

RESULTS

Two thousand five hundred and twelve systematic reviews (16,088 studies) were included. Rapid methods resulted in the loss of all data in 3.7-44.7% of meta-analyses. Searching only PubMed had the smallest risk of changed ORs (19% [477/2,512] were small changes or greater; 10% [260/2,512] were moderate or greater). Changes in ORs varied substantially with each rapid review method; 8.4-21.3% were small, 1.9-8.8% were moderate, and 4.7-34.1% were large. Changes in statistical significance occurred in 6.5-38.6% of meta-analyses. Changes from significant to nonsignificant were most common (2.1-13.7% meta-analyses). We found no evidence of bias with any rapid review method.

CONCLUSION

Searching PubMed only might be considered where a ∼10% risk of the primary outcome OR changing by >20% could be tolerated. This could be the case in scoping reviews, resource limitation, or where syntheses are needed urgently. Other situations, such as clinical guidelines and regulatory decisions, favor more comprehensive systematic review methods.

Rapid reviews may produce different results to systematic reviews: a meta-epidemiological study

Objective

To simulate possible changes in systematic review results if rapid review methods were used.

Study Design and Setting

We recalculated meta-analyses for binary primary outcomes in Cochrane systematic reviews, simulating rapid review methods. We simulated searching only PubMed, excluding older articles (5, 7, 10, 15, and 20 years before the search date), excluding smaller trials (<50, <100, and <200 participants), and using the largest trial only. We examined percentage changes in pooled odds ratios (ORs) (classed as no important change [<5%], small [<20%], moderate [<30%], or large [≥30%]), statistical significance, and biases observed using rapid methods.

Results

Two thousand five hundred and twelve systematic reviews (16,088 studies) were included. Rapid methods resulted in the loss of all data in 3.7–44.7% of meta-analyses. Searching only PubMed had the smallest risk of changed ORs (19% [477/2,512] were small changes or greater; 10% [260/2,512] were moderate or greater). Changes in ORs varied substantially with each rapid review method; 8.4–21.3% were small, 1.9–8.8% were moderate, and 4.7–34.1% were large. Changes in statistical significance occurred in 6.5–38.6% of meta-analyses. Changes from significant to nonsignificant were most common (2.1–13.7% meta-analyses). We found no evidence of bias with any rapid review method.

Conclusion

Searching PubMed only might be considered where a ∼10% risk of the primary outcome OR changing by >20% could be tolerated. This could be the case in scoping reviews, resource limitation, or where syntheses are needed urgently. Other situations, such as clinical guidelines and regulatory decisions, favor more comprehensive systematic review methods.