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Developing an RAI-MDS Behavior-Based Pain Scale for Long-Term Care Residents With Advanced Dementia

In Canadian and many international long-term care (LTC) facilities, pain assessment frequently relies on data from the Resident Assessment Instrument – Minimum Data Set 2.0 (RAI-MDS). The RAI-MDS produces a two-item scale, measuring both pain frequency and pain intensity. This scale correlates well...

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Autores principales: Knopp-Sihota, Jennifer, Hoben, Matthias, Poss, Jeff, Estabrooks, Carole
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7740963/
http://dx.doi.org/10.1093/geroni/igaa057.658
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author Knopp-Sihota, Jennifer
Hoben, Matthias
Poss, Jeff
Estabrooks, Carole
author_facet Knopp-Sihota, Jennifer
Hoben, Matthias
Poss, Jeff
Estabrooks, Carole
author_sort Knopp-Sihota, Jennifer
collection PubMed
description In Canadian and many international long-term care (LTC) facilities, pain assessment frequently relies on data from the Resident Assessment Instrument – Minimum Data Set 2.0 (RAI-MDS). The RAI-MDS produces a two-item scale, measuring both pain frequency and pain intensity. This scale correlates well with self-reported pain in cognitively intact LTC residents, but despite repeated testing, is less valid for use in residents with more advanced cognitive impairment who are unable to self-report their pain. In this study we aimed to develop and validate a behaviour-based pain assessment scale for long-term care residents using data available in the RAI-MDS. To construct our initial scale, we reviewed the literature and compiled a list of observable indicators of pain (e.g., grimacing) and linked these with 28 similar items available in the RAI-MDS. Using Delphi techniques, we further refined this to 20 items. We then evaluated the psychometric properties of our scale using two independent, representative samples, of urban LTC residents in Western Canada. Exploratory factor analyses were conducted in sample one (n=16,282) and confirmatory factor analyses (CFA) were then conducted in sample two (n=15,785) in order to test, and confirm, our model. A two-factor solution was identified grouping RAI-MDS items into subscales 1) change in status (e.g., new onset restlessness) and 2) behaviours (e.g., crying). Commonly recognized model fit indices were acceptable suggesting the adequacy of the two-factor solution. Results provide preliminary support for the use of behavioural-based pain assessment scale using RAI-MDS data. Further evaluation and validation of our scale is warranted.
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spelling pubmed-77409632020-12-21 Developing an RAI-MDS Behavior-Based Pain Scale for Long-Term Care Residents With Advanced Dementia Knopp-Sihota, Jennifer Hoben, Matthias Poss, Jeff Estabrooks, Carole Innov Aging Abstracts In Canadian and many international long-term care (LTC) facilities, pain assessment frequently relies on data from the Resident Assessment Instrument – Minimum Data Set 2.0 (RAI-MDS). The RAI-MDS produces a two-item scale, measuring both pain frequency and pain intensity. This scale correlates well with self-reported pain in cognitively intact LTC residents, but despite repeated testing, is less valid for use in residents with more advanced cognitive impairment who are unable to self-report their pain. In this study we aimed to develop and validate a behaviour-based pain assessment scale for long-term care residents using data available in the RAI-MDS. To construct our initial scale, we reviewed the literature and compiled a list of observable indicators of pain (e.g., grimacing) and linked these with 28 similar items available in the RAI-MDS. Using Delphi techniques, we further refined this to 20 items. We then evaluated the psychometric properties of our scale using two independent, representative samples, of urban LTC residents in Western Canada. Exploratory factor analyses were conducted in sample one (n=16,282) and confirmatory factor analyses (CFA) were then conducted in sample two (n=15,785) in order to test, and confirm, our model. A two-factor solution was identified grouping RAI-MDS items into subscales 1) change in status (e.g., new onset restlessness) and 2) behaviours (e.g., crying). Commonly recognized model fit indices were acceptable suggesting the adequacy of the two-factor solution. Results provide preliminary support for the use of behavioural-based pain assessment scale using RAI-MDS data. Further evaluation and validation of our scale is warranted. Oxford University Press 2020-12-16 /pmc/articles/PMC7740963/ http://dx.doi.org/10.1093/geroni/igaa057.658 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of The Gerontological Society of America. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Abstracts
Knopp-Sihota, Jennifer
Hoben, Matthias
Poss, Jeff
Estabrooks, Carole
Developing an RAI-MDS Behavior-Based Pain Scale for Long-Term Care Residents With Advanced Dementia
title Developing an RAI-MDS Behavior-Based Pain Scale for Long-Term Care Residents With Advanced Dementia
title_full Developing an RAI-MDS Behavior-Based Pain Scale for Long-Term Care Residents With Advanced Dementia
title_fullStr Developing an RAI-MDS Behavior-Based Pain Scale for Long-Term Care Residents With Advanced Dementia
title_full_unstemmed Developing an RAI-MDS Behavior-Based Pain Scale for Long-Term Care Residents With Advanced Dementia
title_short Developing an RAI-MDS Behavior-Based Pain Scale for Long-Term Care Residents With Advanced Dementia
title_sort developing an rai-mds behavior-based pain scale for long-term care residents with advanced dementia
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7740963/
http://dx.doi.org/10.1093/geroni/igaa057.658
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