Mary Ersek1,2, Keela Herr3, Michelle M Hilgeman4,5,6, Moni Blazej Neradilek7, Nayak Polissar7, Karon F Cook8, Princess Nash4, A Lynn Snow4,5, Meghan McDarby9, Francis X Nelson1. 1. Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania. 2. University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania. 3. University of Iowa College of Nursing, Iowa City, Iowa. 4. Tuscaloosa VA Medical Center, Tuscaloosa, Alabama. 5. Alabama Research Institute on Aging and Department of Psychology, University of Alabama, Tuscaloosa, Alabama. 6. Division of Gerontology, Geriatrics, and Palliative Care, University of Alabama at Birmingham, Birmingham, Alabama. 7. The Mountain-Whisper-Light Statistics, Seattle, Washington. 8. Northwestern University Feinberg School of Medicine, Chicago, Illinois. 9. Washington University, St. Louis, Missouri, USA.
Abstract
OBJECTIVE: The goal of this study was to identify a limited set of pain indicators that were most predicive of physical pain. We began with 140 items culled from existing pain observation tools and used a modified Delphi approach followed by statistical analyses to reduce the item pool. METHODS: Through the Delphi Method, we created a candidate item set of behavioral indicators. Next, trained staff observed nursing home residents and rated the items on scales of behavior intensity and frequency. We evaluated associations among the items and expert clinicians' assessment of pain intensity. SETTING: Four government-owned nursing homes and 12 community nursing homes in Alabama and Southeastern Pennsylvania. PARTICIPANTS: Ninety-five residents (mean age = 84.9 years) with moderate to severe cognitive impairment. RESULTS: Using the least absolute shrinkage and selection operator model, we identified seven items that best predicted clinicians' evaluations of pain intensity. These items were rigid/stiff body or body parts, bracing, complaining, expressive eyes, grimacing, frowning, and sighing. We also found that a model based on ratings of frequency of behaviors did not have better predictive ability than a model based on ratings of intensity of behaviors. CONCLUSIONS: We used two complementary approaches-expert opinion and statistical analysis-to reduce a large pool of behavioral indicators to a parsimonious set of items to predict pain intensity in persons with dementia. Future studies are needed to examine the psychometric properties of this scale, which is called the Pain Intensity Measure for Persons with Dementia. 2018 American Academy of Pain Medicine. This work is written by US Government employees and is in the public domain in the US.
OBJECTIVE: The goal of this study was to identify a limited set of pain indicators that were most predicive of physical pain. We began with 140 items culled from existing pain observation tools and used a modified Delphi approach followed by statistical analyses to reduce the item pool. METHODS: Through the Delphi Method, we created a candidate item set of behavioral indicators. Next, trained staff observed nursing home residents and rated the items on scales of behavior intensity and frequency. We evaluated associations among the items and expert clinicians' assessment of pain intensity. SETTING: Four government-owned nursing homes and 12 community nursing homes in Alabama and Southeastern Pennsylvania. PARTICIPANTS: Ninety-five residents (mean age = 84.9 years) with moderate to severe cognitive impairment. RESULTS: Using the least absolute shrinkage and selection operator model, we identified seven items that best predicted clinicians' evaluations of pain intensity. These items were rigid/stiff body or body parts, bracing, complaining, expressive eyes, grimacing, frowning, and sighing. We also found that a model based on ratings of frequency of behaviors did not have better predictive ability than a model based on ratings of intensity of behaviors. CONCLUSIONS: We used two complementary approaches-expert opinion and statistical analysis-to reduce a large pool of behavioral indicators to a parsimonious set of items to predict pain intensity in persons with dementia. Future studies are needed to examine the psychometric properties of this scale, which is called the Pain Intensity Measure for Persons with Dementia. 2018 American Academy of Pain Medicine. This work is written by US Government employees and is in the public domain in the US.
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