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Introducing Core Smart Tags
Introducing Core Smart Tags If you are familiar with Tagging in Nested Knowledge, you know how integral the process of setting up a tagging hierarchy
August 27, 2024
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Initially designed as a comprehensive tool for completing systematic literature reviews, Nested Knowledge has evolved into a versatile platform for conducting a diverse range of review types. See below for a summary of different review types available in Nested Knowledge, as well as example projects and a flowchart of key choices in study design.
Systematic Literature Review (SLR)
The first review type we have to mention is the glorious SLR. A comprehensive and careful approach, SLRs systematically gather, appraise, and synthesize existing literature to answer specific research questions based on all available evidence, with quality-controlled screening and data gathering. Nested Knowledge provides a structured framework to facilitate the rigorous process of SLRs, ensuring clarity and transparency in evidence synthesis. See our Systematic Review Guide for more info.
Suggested Nest Setup:
1. Comprehensive search query built for Literature Search – it may be worth involving a professional medical librarian for SLR searches.
Optionally, Run automatic search on a schedule for a living SLR
2. For maximum screening quality control, turn on Dual Two-Pass Screening mode in Settings
3. Optionally, turn on Robot Screener in Settings when recall reaches appropriate threshold, and if you do so, make sure to report this in your Methods!
4. Set up Tag Hierarchy with pre-specified Population, Intervention, Comparator, and Outcome concepts (PICOs)
5. Optionally, turn on Smart Tag Recommendations for assistance in Tagging/evidence collection, and then tag all Included studies
6. As appropriate, use a Critical Appraisal system to assess Risk of Bias
7. Download Exports: Tags in Study Inspector
8. Assess and present evidence in Qualitative Synthesis and Dashboard
View an example of a published SLR in Nested Knowledge.
Meta-analysis, including Network Meta-analysis (NMA)
A meta-analysis uses statistical methods to summarize the results of a systematic review. After completing your systematic review in Nested Knowledge, you can utilize Meta-Analytical Extraction to pool quantitative data from multiple studies to compare therapies. If study quality allows, the software’s capabilities extend to Network Meta-analysis, as Quantitative Synthesis is automatically generated. This interactive output enables in-depth examination of treatment comparisons within a broader network of evidence, using indirect treatment comparison where needed.
Suggested Nest Setup:
1. Follow above steps to build an SLR
2. After completing Tagging, toggle on Meta-Analytical Extraction in Settings
3. Configure Interventions and Data Elements
4. Complete MA Extraction to generate Quantitative Synthesis
5. As appropriate, use a Critical Appraisal system to assess Risk of Bias
6. Download Exports: Meta-Analytical Extracted Data in Study Inspector
7. Assess and present evidence in Quantitative Synthesis for NMA outputs
View an example of a published SLR & NMA in Nested Knowledge.
HTA Submissions
Nested Knowledge supports the Health Technology Assessment (HTA) process, largely catering to the clinical, epidemiological, and economic evaluation/cost-effectiveness aspects of submissions. Researchers can navigate these intricate components with ease, ensuring a comprehensive and well-rounded evaluation of healthcare technologies.
Clinical Effectiveness: This part of the HTA submission focuses on the clinical efficacy and safety of the health technology.
View an example of Clinical Effectiveness HTA assessment in Nested Knowledge.
Epidemiology: This part of the HTA submission addresses the broader population-level impact of the health technology, exploring the prevalence and incidence of the health condition targeted by the technology.
View an example of Epidemiological HTA assessment in Nested Knowledge.
Economic evaluation/Cost-effectiveness: This part of the HTA submission evaluates the economic aspects of the health technology, including considerations of direct costs, indirect costs, quality-adjusted life years (QALYs), and other economic metrics.
View an example of incorporating Economic Evaluations as part of an HTA assessment in Nested Knowledge.
Suggested Nest Setup:
1. Topic-specific search queries should be built for Literature Search
2. Either one nest covering all HTA topics, or separate searches by topic, are possible; if one search is used, Tagging is recommended as a method for distinguishing studies included for Clinical, Epidemiology, and Economic topics
3. Toggle on Dual Two-Pass Screening mode in Settings
4. Set up Tag Hierarchy with pre-determined PICOs regardless of review type
5. Clinical reviews may involve MA Extraction and NMA, but Epidemiology and Cost-effectiveness reviews only involve Tagging
6. Turn on Smart Tag Recommendations for assistance in Tagging/evidence collection
7. As appropriate, use a Critical Appraisal system to assess Risk of Bias
8. Download Exports/Spreadsheets in Study Inspector
9. Assess and present evidence in Synthesis outputs
Targeted Literature Reviews (TLRs)/Rapid Review
When time is of the essence, Nested Knowledge facilitates targeted literature reviews and rapid reviews. Efficient and streamlined, these review strategies are ideal for quickly synthesizing relevant evidence to inform time-sensitive decisions and interventions. In comparison to SLRs, TLRs may be less comprehensive and use fewer quality-control strategies, but give far more immediate evidence.
Suggested Nest Setup:
1. Rapidly check the PICOs of a preliminary search and build out strategy in Search Exploration,
2. Toggle on Standard, Single Screening mode in Settings
3. Turn on Automatic Training of the Screening model in Settings, which will activate once 50 records are screened
4. As appropriate, apply bulk actions based on topical filters in Inspector or based on the Inclusion Predictions scores from the Screening model
5. Configure Tag Hierarchy with a specific set of questions
6. Turn on Abstract and/or Full Text Smart Tag Recommendations
7. Review tags, and as appropriate, apply a bulk action of accepting tag recommendations to create preliminary, non-quality-controlled outputs
8. Download Exports/Spreadsheets in Study Inspector
9. Assess and present evidence in Synthesis outputs, especially Qualitative Synthesis and Dashboard
View an example of a TLR/Rapid Review in Nested Knowledge.
Scoping Review
For researchers aiming to map the landscape of existing literature on a particular topic, but desiring to understand the general contents in advance, Nested Knowledge provides tools for conducting scoping reviews. This approach helps define the breadth and depth of available evidence, setting the stage for more focused investigations such as an SLR.
Suggested Nest Setup:
1. Enter broad PICO terms and build out initial search query in Search Exploration
2. Set searches to run on a schedule to ensure comprehensive research import
3. Toggle Single Standard or Single Two Pass Screening mode in Settings
4. Turn on Automatic Training of the Screening Model in Settings, which will activate once 50 records are screened
5. As appropriate, apply bulk actions based on topical filters in Inspector or based on the Inclusion Predictions scores from the Screening model
6. Configure tag hierarchy with General PICO template to encompass overarching, scoping questions
7. Turn on Abstract or Full Text Smart Tag Recommendations
8. Either manually accept/reject recommendations or apply a bulk action of accepting all tag recommendations to create preliminary, non-quality-controlled outputs
9. Use a Critical Appraisal system to assess Risk of Bias
10. Download Exports/Spreadsheets in Study Inspector
11. Assess and present evidence in Synthesis outputs
12. Depending on your project, you may wish to use Dashboard or Manuscript
View an example of a Scoping Review in Nested Knowledge.
Narrative Review
For researchers aiming to conduct an extensive description and interpretation of previously published writing on a chosen topic. Narrative reviews provide a flexible and rigorous approach to analyzing and interpreting the literature where research questions address qualitative concepts that may not fit into conventional meta-analysis–especially, if multiple related questions are being addressed.
Suggested Nest Setup:
1. Enter broad terms and build out initial search query in Search Exploration
2. Toggle Dual Standard or Dual Two-Pass Screening mode in Settings
3. As appropriate, turn on Robot Screener in Settings, once 50 records are screened
4. Auto-adjudicate Screening agreements and adjudicate disagreements
5. Configure tag hierarchy with general questions to encompass overarching, qualitative questions
6. Turn on Abstract or Full Text Smart Tag Recommendations
7. Manually accept/reject recommendations and extract text related to the research questions of interest
8. Download Exports/Spreadsheets in Study Inspector
9. Assess and present evidence in Synthesis outputs
10. Depending on your project, you may wish to use Dashboard or Manuscript to display and discuss your findings.
View an example of a Narrative Review in Nested Knowledge.
Gap Analysis
Nested Knowledge supports researchers in identifying gaps in existing literature through comprehensive gap analyses. Using a quick, overarching reviewing the current state of knowledge, researchers can pinpoint areas where further research is needed, contributing to the advancement of their respective fields.
Suggested Nest Setup:
1. Enter broad PICO terms and build out initial search query in Search Exploration
2. Toggle Standard, Single Screening mode in Settings
3. Turn on Automatic Training of the Screening model in Settings, which will activate once 50 records are screened
4. If appropriate, apply a bulk action including records above assigned threshold and excluding below assigned threshold
5. Configure Tag hierarchy with high specificity to identify gaps
6. Turn on Abstract or Full Text Smart Tag Recommendations
7. Either manually accept/reject recommendations or apply a bulk action of accepting all tag recommendations to create preliminary, non-quality-controlled outputs
8. If necessary, use a Critical Appraisal system to assess Risk of Bias
9. Download Exports/Spreadsheets in Study Inspector
10. Assess and present evidence in Synthesis outputs
View an example of a Gap Analysis in Nested Knowledge.
As shown in these methods, there is a spectrum of rapidity and quality control possible in Nested Knowledge, depending on whether you want quick answers (TLR), scope a future SLR (scoping review), or going fully toward an SLR with NMA. The platform has multiple settings (e.g., Screening modes) and strategies (e.g., bulk actions on Smart Tag recommendations, if appropriate) that should be evaluated and employed based on your goals and intended methods, and if you have any questions along the way or encounter difficulties, “Ask AI” in the software directly or reach out to us at support@nested-knowledge.com!
Yep, you read that right. We started making software for conducting systematic reviews because we like doing systematic reviews. And we bet you do too.
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Introducing Core Smart Tags If you are familiar with Tagging in Nested Knowledge, you know how integral the process of setting up a tagging hierarchy
