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dc.contributor.authorNunes, Anthony P
dc.contributor.authorZhao, Danni
dc.contributor.authorJesdale, William M.
dc.contributor.authorLapane, Kate L.
dc.date2022-08-11T08:10:36.000
dc.date.accessioned2022-08-23T17:14:21Z
dc.date.available2022-08-23T17:14:21Z
dc.date.issued2021-06-26
dc.date.submitted2021-09-23
dc.identifier.citation<p>Nunes AP, Zhao D, Jesdale WM, Lapane KL. Multiple imputation to quantify misclassification in observational studies of the cognitively impaired: an application for pain assessment in nursing home residents. BMC Med Res Methodol. 2021 Jun 26;21(1):132. doi: 10.1186/s12874-021-01327-5. PMID: 34174838; PMCID: PMC8235835. <a href="https://doi.org/10.1186/s12874-021-01327-5">Link to article on publisher's site</a></p>
dc.identifier.issn1471-2288 (Linking)
dc.identifier.doi10.1186/s12874-021-01327-5
dc.identifier.pmid34174838
dc.identifier.urihttp://hdl.handle.net/20.500.14038/46936
dc.description.abstractBACKGROUND: Despite experimental evidence suggesting that pain sensitivity is not impaired by cognitive impairment, observational studies in nursing home residents have observed an inverse association between cognitive impairment and resident-reported or staff-assessed pain. Under the hypothesis that the inverse association may be partially attributable to differential misclassification due to recall and communication limitations, this study implemented a missing data approach to quantify the absolute magnitude of misclassification of pain, pain frequency, and pain intensity by level of cognitive impairment. METHODS: Using the 2016 Minimum Data Set 3.0, we conducted a cross-sectional study among newly admitted US nursing home residents. Pain presence, severity, and frequency is assessed via resident-reported measures. For residents unable to communicate their pain, nursing home staff document pain based on direct resident observation and record review. We estimate a counterfactual expected level of pain in the absence of cognitive impairment by multiply imputing modified pain indicators for which the values were retained for residents with no/mild cognitive impairment and set to missing for residents with moderate/severe cognitive impairment. Absolute differences () in the presence and magnitude of pain were calculated as the difference between documented pain and the expected level of pain. RESULTS: The difference between observed and expected resident reported pain was greater in residents with severe cognitive impairment ( = -10.2%, 95% Confidence Interval (CI): -10.9% to -9.4%) than those with moderate cognitive impairment ( = -4.5%, 95% CI: -5.4% to -3.6%). For staff-assessed pain, the magnitude of apparent underreporting was similar between residents with moderate impairment ( = -7.2%, 95% CI: -8.3% to -6.0%) and residents with severe impairment ( = -7.2%, 95% CI: -8.0% to -6.3%). Pain characterized as "mild" had the highest magnitude of apparent underreporting. CONCLUSIONS: In residents with moderate to severe cognitive impairment, documentation of any pain was lower than expected in the absence of cognitive impairment. This finding supports the hypothesis that an inverse association between pain and cognitive impairment may be explained by differential misclassification. This study highlights the need to develop analytic and/or procedural solutions to correct for recall/reporter bias resulting from cognitive impairment.
dc.language.isoen_US
dc.relation<p><a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=34174838&dopt=Abstract">Link to Article in PubMed</a></p>
dc.rightsCopyright © The Author(s) 2021. Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectMisclassification
dc.subjectMultiple imputation
dc.subjectNursing homes
dc.subjectPain
dc.subjectEpidemiology
dc.subjectGeriatrics
dc.subjectHealth Services Administration
dc.subjectNervous System Diseases
dc.subjectPain Management
dc.subjectPsychiatry and Psychology
dc.titleMultiple imputation to quantify misclassification in observational studies of the cognitively impaired: an application for pain assessment in nursing home residents
dc.typeJournal Article
dc.source.journaltitleBMC medical research methodology
dc.source.volume21
dc.source.issue1
dc.identifier.legacyfulltexthttps://escholarship.umassmed.edu/cgi/viewcontent.cgi?article=2420&amp;context=qhs_pp&amp;unstamped=1
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/qhs_pp/1416
dc.identifier.contextkey25084012
refterms.dateFOA2022-08-23T17:14:21Z
html.description.abstract<p>BACKGROUND: Despite experimental evidence suggesting that pain sensitivity is not impaired by cognitive impairment, observational studies in nursing home residents have observed an inverse association between cognitive impairment and resident-reported or staff-assessed pain. Under the hypothesis that the inverse association may be partially attributable to differential misclassification due to recall and communication limitations, this study implemented a missing data approach to quantify the absolute magnitude of misclassification of pain, pain frequency, and pain intensity by level of cognitive impairment.</p> <p>METHODS: Using the 2016 Minimum Data Set 3.0, we conducted a cross-sectional study among newly admitted US nursing home residents. Pain presence, severity, and frequency is assessed via resident-reported measures. For residents unable to communicate their pain, nursing home staff document pain based on direct resident observation and record review. We estimate a counterfactual expected level of pain in the absence of cognitive impairment by multiply imputing modified pain indicators for which the values were retained for residents with no/mild cognitive impairment and set to missing for residents with moderate/severe cognitive impairment. Absolute differences () in the presence and magnitude of pain were calculated as the difference between documented pain and the expected level of pain.</p> <p>RESULTS: The difference between observed and expected resident reported pain was greater in residents with severe cognitive impairment ( = -10.2%, 95% Confidence Interval (CI): -10.9% to -9.4%) than those with moderate cognitive impairment ( = -4.5%, 95% CI: -5.4% to -3.6%). For staff-assessed pain, the magnitude of apparent underreporting was similar between residents with moderate impairment ( = -7.2%, 95% CI: -8.3% to -6.0%) and residents with severe impairment ( = -7.2%, 95% CI: -8.0% to -6.3%). Pain characterized as "mild" had the highest magnitude of apparent underreporting.</p> <p>CONCLUSIONS: In residents with moderate to severe cognitive impairment, documentation of any pain was lower than expected in the absence of cognitive impairment. This finding supports the hypothesis that an inverse association between pain and cognitive impairment may be explained by differential misclassification. This study highlights the need to develop analytic and/or procedural solutions to correct for recall/reporter bias resulting from cognitive impairment.</p>
dc.identifier.submissionpathqhs_pp/1416
dc.contributor.departmentGraduate School of Biomedical Sciences
dc.contributor.departmentDivision of Epidemiology, Department of Population and Quantitative Health Sciences
dc.source.pages132


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Copyright © The Author(s) 2021. Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Except where otherwise noted, this item's license is described as Copyright © The Author(s) 2021. Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.