Database selection in systematic reviews: an insight through clinical neurology

Vassar, Matt; Yerokhin, Vadim; Sinnett, Philip; Weiher, Matthew; Muckelrath, Halie D.; Carr, Branden; Varney, Laura; Cook, Gregory

doi:10.1111/hir.12176

Cited by 41 publications

(42 citation statements)

References 23 publications

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“…The audiences for tech mining follow a structure similar to that of corporate R&D, but with a stronger focus on funding and strategy. Data sources are selected, and the inclusion criteria used reflect those audiences and purposes, with tech mining pulling data largely from the patent and engineering and technical databases, while systematic reviews extract data from a variety of health, life science, and social science databases, depending on the specific topic . Both of these bibliometric methods appropriately focus on data sources that match the domain of the question and target audience.…”

Section: Discussionmentioning

confidence: 99%

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Systematic reviews and tech mining: A methodological comparison with case study

Anderson

Shannon

Bickett

et al. 2018

Research Synthesis Methods

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When the Medical Library Association identified questions critical for the future of the profession, it assigned groups to use systematic reviews to find the answers to these questions. Group 6, whose question was on emerging technologies, recognized early on that the systematic review process would not work well for this question, which looks forward to predict future trends, whereas the systematic review process looks back in time. We searched for new methodologies that were more appropriate to our question, developing a process that combined systematic review, text mining, and visualization techniques. We then discovered tech mining, which is very similar to the process we had created. In this paper, we describe our research design and compare tech mining and systematic review methodologies. There are similarities and differences in each process: Both use a defined research question, deliberate database selection, careful and iterative search strategy development, broad data collection, and thoughtful data analysis. However, the focus of the research differs significantly, with systematic reviews looking to the past and tech mining mainly to the future. Our comparison demonstrates that each process can be enhanced from a purposeful consideration of the procedures of the other. Tech mining would benefit from the inclusion of a librarian on their research team and a greater attention to standards and collaboration in the research project. Systematic reviews would gain from the use of tech mining tools to enrich their data analysis and corporate management communication techniques to promote the adoption of their findings.

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Section: Discussionmentioning

confidence: 99%

“…and technical databases, 4,10,25-27 while systematic reviews extract data from a variety of health, life science, and social science databases, depending on the specific topic. 28,29 Both of these bibliometric methods appropriately focus on data sources that match the domain of the question and target audience.…”

Section: Primary Purposesmentioning

confidence: 99%

Systematic reviews and tech mining: A methodological comparison with case study

Anderson

Shannon

Bickett

et al. 2018

Research Synthesis Methods

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“…The search was modified for the following eight electronic databases: MEDLINE, CINAHL, AMED, CENTRAL, Embase, PsycINFO, Scopus, and Web of Science (see Table SII, online supporting information for MEDLINE search strategy). The number and type of databases were chosen to minimize selection bias and increase the generalizability of this systematic review . Preliminary searching began in February 2017 and the final search was completed on June 2nd, 2017.…”

Section: Methodsmentioning

confidence: 99%

“…The number and type of databases were chosen to minimize selection bias and increase the generalizability of this systematic review. 29 Preliminary searching began in February 2017 and the final search was completed on June 2nd, 2017. All of the retrieved articles were imported into the bibliographic database, EndNote X8 (Thomas Reuters [Scientific] LLC, Philadelphia, PA, USA) and then exported into the Covidence database for screening and management.…”

Section: Search Strategymentioning

confidence: 99%

Behavioural interventions to treat drooling in children with neurodisability: a systematic review

McInerney

Reddihough

Carding

et al. 2018

Develop Med Child Neuro

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Aim To review the evidence for behavioural interventions to reduce drooling in children with neurodisability. Method A detailed search in eight databases sought studies that: (1) included participants aged 0 to 18 years with neurodisability and drooling; (2) provided behavioural interventions targeting drooling or a drooling‐related behaviour; and (3) used experimental designs. Two reviewers extracted data from full‐text papers independently. Results were tabulated for comparison. The Risk of Bias assessment in N‐of‐1 Trials scale for single case experimental designs (SCEDs) and the Cochrane risk of bias assessment tool for randomized controlled trials (RCTs) were applied. Results Of an initial yield of 763, seven SCEDs and one RCT were included. Behavioural interventions included the use of reinforcement, prompting, self‐management, instruction, extinction, overcorrection, and fading. Each assessed body functions or structures’ outcomes (drooling frequency and severity); three included activity outcomes (mouth drying, head control, eye contact, and vocalizations) and none assessed participation or quality of life. While each study reported positive effects of intervention, risk of bias was high. Interpretation Low‐level evidence suggests behavioural interventions may be useful for treatment of drooling in children with neurodisability. Well‐designed intervention studies are urgently needed to determine effectiveness. What this paper adds Behavioural interventions used to treat drooling included reinforcement, prompting, self‐management, extinction, overcorrection, instruction, and fading. Interventions targeted body structures and function‐level outcomes and activity‐level outcomes. Low‐level evidence supports the use of behavioural intervention to treat drooling.

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“…Several factors play a role in the quality of searches for primary studies to be included in SRs (3). Involvement of an information specialist or librarian in the search process seems to play a role for the quality of searches (4,5).…”

Section: Introductionmentioning

confidence: 99%

PubMed coverage varied across specialties and over time: a large-scale study of included studies in Cochrane reviews

Frandsen

Eriksen

Hammer

et al. 2019

Journal of Clinical Epidemiology

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Objective: PubMed is one of the most commonly used search tools in Biomedical and Life Sciences. Existing studies on database coverage generally conclude that searching PubMed may not be sufficient although some find that the contributions from other databases are modest at best. However, generalizability of the studies of the coverage of PubMed is typically restricted. The objective of this study is to analyze the coverage of PubMed across specialties and over time. Study Design and Setting: We use the more than 50,000 included studies in all Cochrane reviews published from 2012 to 2016 as our population and examine if the studies as well as resulting publications can be identified in PubMed. Results: The results show that PubMed has a coverage of 70.9, 95% CI [68.40,73.30] of all the included publications and 82.8%, 95% CI [80.9, 84.7] of the included studies. There are huge differences in coverage across as well as within specialties. In addition, coverage varies within groups over time. Conclusion: Databases used for searching topics within the groups with highly varying or low coverage should be chosen with care as PubMed may have a relatively low coverage.

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Database selection in systematic reviews: an insight through clinical neurology

Abstract: Systematic reviewers should aim to search a sufficient number of databases to minimise selection bias. Additionally, systematic reviewers should include information specialists in designing SR methodology, as this may improve systematic review quality.

Cited by 41 publications

References 23 publications

Systematic reviews and tech mining: A methodological comparison with case study

Systematic reviews and tech mining: A methodological comparison with case study

Behavioural interventions to treat drooling in children with neurodisability: a systematic review

PubMed coverage varied across specialties and over time: a large-scale study of included studies in Cochrane reviews

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