The power of integrating data: advancing pain research using meta-analysis
<p>Publications related to pain research have increased significantly in recent years. The abundance of new evidence creates challenges staying up to date with the latest information. A comprehensive understanding of the literature is important for both clinicians and investigators involved in...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Lippincott, Williams & Wilkins
2022
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| _version_ | 1797108460791267328 |
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| author | Fundaun, J Thomas, ET Schmid, AB Baskozos, G |
| author_facet | Fundaun, J Thomas, ET Schmid, AB Baskozos, G |
| author_sort | Fundaun, J |
| collection | OXFORD |
| description | <p>Publications related to pain research have increased significantly in recent years. The abundance of new evidence creates challenges staying up to date with the latest information. A comprehensive understanding of the literature is important for both clinicians and investigators involved in pain research. One commonly used method to combine and analyse data in health care research is meta-analysis. The primary aim of a meta-analysis is to quantitatively synthesise the results of multiple studies focused on the same research question. Meta-analysis is a powerful tool that can be used to advance pain research. However, there are inherent challenges when combining data from multiple sources. There are also numerous models and statistical considerations when undertaking a meta-analysis. This review aims to discuss the planning and preparation for completing a meta-analysis, review commonly used meta-analysis models, and evaluate the clinical implications of meta-analysis in pain research.</p> |
| first_indexed | 2024-03-07T07:29:35Z |
| format | Journal article |
| id | oxford-uuid:e2719dc3-49fd-4354-b599-0ecd9e3dbfa7 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T07:29:35Z |
| publishDate | 2022 |
| publisher | Lippincott, Williams & Wilkins |
| record_format | dspace |
| spelling | oxford-uuid:e2719dc3-49fd-4354-b599-0ecd9e3dbfa72022-12-14T09:49:31ZThe power of integrating data: advancing pain research using meta-analysisJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:e2719dc3-49fd-4354-b599-0ecd9e3dbfa7EnglishSymplectic ElementsLippincott, Williams & Wilkins2022Fundaun, JThomas, ETSchmid, ABBaskozos, G<p>Publications related to pain research have increased significantly in recent years. The abundance of new evidence creates challenges staying up to date with the latest information. A comprehensive understanding of the literature is important for both clinicians and investigators involved in pain research. One commonly used method to combine and analyse data in health care research is meta-analysis. The primary aim of a meta-analysis is to quantitatively synthesise the results of multiple studies focused on the same research question. Meta-analysis is a powerful tool that can be used to advance pain research. However, there are inherent challenges when combining data from multiple sources. There are also numerous models and statistical considerations when undertaking a meta-analysis. This review aims to discuss the planning and preparation for completing a meta-analysis, review commonly used meta-analysis models, and evaluate the clinical implications of meta-analysis in pain research.</p> |
| spellingShingle | Fundaun, J Thomas, ET Schmid, AB Baskozos, G The power of integrating data: advancing pain research using meta-analysis |
| title | The power of integrating data: advancing pain research using meta-analysis |
| title_full | The power of integrating data: advancing pain research using meta-analysis |
| title_fullStr | The power of integrating data: advancing pain research using meta-analysis |
| title_full_unstemmed | The power of integrating data: advancing pain research using meta-analysis |
| title_short | The power of integrating data: advancing pain research using meta-analysis |
| title_sort | power of integrating data advancing pain research using meta analysis |
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