Bayesian analysis of the association between effective strategies of multimodal nonpharmacological intervention and characteristics of cognitive function in nursing home residents with cognitive impairment: A cross-sectional study. Issue 37 (11th September 2020)

• Record Type: Journal Article
• Authors: Yorozuya, Kyosuke; Yamane, Shingo; Nobuhisa, Misako; Owaki, Hiroko; Suzuki, Takeaki; Okahara, Hikaru; Iwamori, Wataru; Hanaoka, Hideaki
• Other Names: Zhan. Frank Y section editor.
• Is Part Of: Medicine. Volume 99:Issue 37(2020)
• Publication Date: 2020-09-11
• Subjects: Bayesian analysis -- cognitive function -- multimodal -- non-pharmacological interventions -- nursing home residents with cognitive impairment; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000022154
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : Abstract: The cognitive function of nursing home (NH) residents with cognitive impairment (CI) tends to decline over time. An effective multimodal non-pharmacological intervention (MNPI) strategy is needed to improve the cognitive function of NH residents with CI. The aim of this study was to clarify the cognitive function characteristics of NH residents with CI in whom a non-pharmacological intervention (NPI) can be implemented, consisting of MNPI using a Bayesian analysis, and to incorporate suggestions to make the MNPI strategy as effective as possible. This study had a cross-sectional design. The 61 subjects were selected from the residents of 5 NHs, of whom 90.16% were female, and the mean (standard deviation) age was 87.20 ± 6.90. Analyses were performed using a hierarchical Bayesian model, and the global and specific cognitive functions as assessed by the Japanese version of the Neurobehavioral Cognitive Status Examination were the response variables. Three types of NPI (cognitive enhancement NPI, physical NPI, psychological and psychosocial NPI), and activities of daily living (ADL), as assessed by the Barthel index, were the explanatory variables. Cognitive enhancement NPI was revealed to have no association with any cognitive function. Physical NPI was negatively associated with orientation [OR 0.31 (95% credible interval (95% CI) –2.33, –0.10)], comprehension [OR 0.16 (95% CI –2.78, –0.95)] and naming [OR 0.49 (95% CI –1.47, –0.02)]. Psychological and psychosocial NPI was positively associated with comprehension [OR 3.67 (95% CI 0.52, 2.13)]. Barthel index was positively associated with total Japanese version of the Neurobehavioral Cognitive Status Examination [OR 1.74 (95% CI 0.08, 2.12)], comprehension [OR 3.49 (95% CI 0.45, 4.67)], repetition [OR 10.07 (95% CI 0.53, 9.01)], naming [OR 2.24 (95% CI 0.07, 3.20)], and calculations [OR 18.82 (95% CI 2.71, 9.40)]. The implementation of MNPI should be preceded by cognitive enhancement NPI and physical NPI. Providing ADL enhancing NPI in response to cognitive improvement may be an effective strategy. Providing cognitive enhancement NPI, physical NPI, psychological, and psychosocial NPI, as well as ADL-enhancing NPI at the same time, is also an effective strategy for subjects with mild dementia who are considered to have relatively high cognitive functions.