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--- wiki:guide:research:tag [2022/02/01 22:27]
erin.sheffels Added info on hierarchical vs nonhierarchical tagging structures
+++ wiki:guide:research:tag [2023/06/07 00:31] (current)
jthurnham [Building Tagging Systems]
@@ Line 1: / Line 1: @@
-====== Tagging ======
+====== Best Practices for Tagging ======
 Tagging is a process of applying a set of labels to the included studies in a review. AutoLit offers a [[:wiki:autolit:tagging|built-in hierarchical tagging system]] connected to the data element set up for extraction. Hierarchical or non-hierarchical tagging systems can be implemented in other systematic review setups.
@@ Line 8: / Line 8: @@
 ===== Building Tagging Systems =====
-To start building a tagging system, lay out tags related to your study's PICO elements. In order for the tags to be useful, tagging hierarchies need to be kept simple. If every study has a completely unique tag, then using the organization systems and drawing a synthesis from the tagging becomes more difficult. This issue can often be solved by removing the lowest conceptual level of tags. For example, in the tagging hierarchy below, if only a few studies report each individual drug, tagging with the drug class (outlined in blue) may be more useful, and the individual drug tags (outlined in red) can be deleted.
-{{ :wiki:guide:research:tagging-hierarchy-example.png?400 |Example of tagging hierarchy levels}}
+To start building a tagging system, lay out tags related to your study's PICO elements. In order for the tags to be useful, tagging hierarchies need to be kept simple. If every study has a completely unique tag, then using the organization systems and drawing a synthesis from the tagging becomes more difficult. This issue can often be solved by removing the lowest conceptual level of tags. For example, in the tagging hierarchy below, if only a few studies report each individual drug, tagging with the drug class (outlined in blue) may be more useful, and the individual drug tags (outlined in red) can be deleted.
+{{ :undefined:tagging-hierarchy-example.png?nolink |}}
 ==== Tagging Hierarchies ====
-In hierarchical tagging systems, tags can be nested under broader umbrella tags. For example, tags for interventions of interest can be grouped together under an "Interventions" tag (highlighted purple in the hierarchy below). This structure makes organization more intuitive and allows for easy sorting and synthesis of information from study tags.
+In hierarchical tagging systems, tags can be nested under broader umbrella tags. For example, tags for interventions of interest can be grouped together under an "Interventions" tag (highlighted purple in the hierarchy below). This structure makes organization more intuitive and allows for easy sorting and synthesis of information from study tags.
 When applying tags from a hierarchical tagging structure, it's important to apply tags from the lowest level possible. For example, when using the hierarchy above, studies reporting patients treated with remdesivir should be tagged with "remdesivir", not with "Antivirals". They will automatically be sorted under "Antivirals" due to the defined tag structure.
-{{https://t2321303.p.clickup-attachments.com/t2321303/e1c0d686-cddc-42fe-9a7f-6de29ec592d4/Screen Shot 2021-05-14 at 9.47.21 AM.png?nolink&|Example complete tagging hierarchy}}
+{{ :wiki:guide:research:00.png?nolink |}}
+===== Applying Tags =====
+When applying a tag, it's useful to note the text, figure, or table in the study that supports the application of that tag. For example, the text supporting the tag "adult patients only" on a study might read "We excluded pediatric patients." These sentences should be copied directly from the study text where possible to make it easy to search the study and find the context. Referencing a figure or table may be appropriate in some cases, especially for tagging outcomes. For example, if the number of patients that died during the study is given in Table 2, the text associated with the tag may simply read "Table 2". Again, this allows team members to easily locate the information in the study.
+===== Recommendation: The PICO Framework: =====
+When tagging and data gathering, the PICO framework (Patients/population, Interventions/Comparators, and Outcomes) often makes sense as an organizational framework for your hierarchy. You can make PICO "Root nodes" and then nest appropriate concepts underneath:
+=== Patient Characteristics: ===
+Patient characteristics can make up of age, gender, comorbidities, medication use history, and other information. We suggest limiting characteristics to age and sex unless other data is critical.
+  * Age
+  * Sex
+=== Interventions (Therapies/Treatments): ===
+  * Treatment (e.g. Tocilizumab, Remdesivir)
+  * Control arms (e.g. Placebo or Standard of Care)
+  * Adjunctive/Comparator therapies (e.g. Aspirin, guide devices, etc).
+  * Dosages or other treatment details
+=== Outcomes: ===
+  * Efficacy Outcomes (e.g. Mortality, Length of Hospital Stay)
+  * Safety outcomes
+      * Complications/adverse events
+=== Study Design Information ===
+  * Study Type (randomized controlled trial, retrospective cohort, etc)
+  * Inclusion and exclusion criteria (*only if relevant)
+Nested Knowledge automatically gathers study metadata, which is bibliographic information about the included studies. Do not worry about creating tags for any of the following information:
+  * Title
+  * Authors
+  * Date
+  * URL
+  * DOI
+  * PubMed ID
+==== Where to find information in studies ====
+While tagging, where can you usually find the information within studies? See this figure to guide you!
+{{:wiki:guide:research:screenshot_2022-08-11_150637.png|}}

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