• Mary Ersek, Keela Herr, Michelle M Hilgeman, Moni Blazej Neradilek, Nayak Polissar, Karon F Cook, Princess Nash, A Lynn Snow, Meghan McDarby, and Francis X Nelson.
• Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania.
• Pain Med. 2019 Jun 1; 20 (6): 1078-1092.

ObjectiveThe 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.MethodsThrough 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.SettingFour government-owned nursing homes and 12 community nursing homes in Alabama and Southeastern Pennsylvania.ParticipantsNinety-five residents (mean age = 84.9 years) with moderate to severe cognitive impairment.ResultsUsing 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.ConclusionsWe 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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