Dataset Information

Is Barthel Index Suitable for Assessing Activities of Daily Living in Patients With Dementia?

ABSTRACT: Objectives:To evaluate application of the Barthel Index (BI) in assessing basic activities of daily living (ADL) of patients with dementia using Rasch analysis. Design:A multi-country cross-sectional study. Setting and Participants:Nineteen long-term care facilities located in China, Japan, South Korea, and Thailand. A total of 644 patients with dementia were included. Methods:Unidimensionality, global and item fit, local dependence, person-item targeting, threshold disordering, and differential item functioning (DIF) were examined. Negative correlations between scores for DIF items and Neuropsychiatric Inventory Nursing Home version (NPI-NH) were evaluated. Results:Item reliability (1.0) and person reliability (.88) were acceptable. The Rasch dimension explained 72.9% of the variance (Eigenvalue = 27), while the first contrast explained 6.6% (Eigenvalue = 2.4). The "mobility" was misfitting to the Rasch model (infit mean square = 1.86). The overall difficulty of the BI exceeded patients' ability (person location = -2.27 logits). The "stairs climbing" and "mobility" showed narrow category thresholds (< 1.4 logits). The location of "controlling bladder" and "toilet use" overlapped. Removing "stairs climbing", collapsing categories with narrow threshold widths in "mobility", and combining "controlling bowel" and "controlling bladder" into one item, improved unidimensionality, and item fit of the scale. Only three items ("grooming", "dressing", and "toilet use") were free from DIF across countries. The scores for "feeding" were negatively related to scores for "disinhibition" (r = -0.46, P < 0.01), and scores for "controlling bowel" were negatively related to scores for "disinhibition" (r = -0.44, P < 0.01), "agitation" (r = -0.32, P < 0.05), and "aggression" (r = -0.27, P < 0.01) in Japanese samples. Conclusions and Implications:The performance of the BI for assessing patients with dementia might be compromised by misfit items, person-item mistargeting, measurement gaps, redundant items, narrow threshold width, and item bias. Mobility ability might not be helpful for determining capability of basic ADL in the patients. Comparisons of BI scores between countries should be undertaken with caution due to item bias. Neuropsychiatric symptoms might interact with basic ADL abilities of the patients. We will not suggest using the instrument in patients with dementia, without future refining to improve its performance.

SUBMITTER: Yi Y

PROVIDER: S-EPMC7225343 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Is Barthel Index Suitable for Assessing Activities of Daily Living in Patients With Dementia?

Yi Yayan Y Ding Lin L Wen Huangliang H Wu Jialan J Makimoto Kiyoko K Liao Xiaoyan X

Frontiers in psychiatry 20200508

<h4>Objectives</h4>To evaluate application of the Barthel Index (BI) in assessing basic activities of daily living (ADL) of patients with dementia using Rasch analysis.<h4>Design</h4>A multi-country cross-sectional study.<h4>Setting and participants</h4>Nineteen long-term care facilities located in China, Japan, South Korea, and Thailand. A total of 644 patients with dementia were included.<h4>Methods</h4>Unidimensionality, global and item fit, local dependence, person-item targeting, threshold ...[more]

PMID: 32457659

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Project description:BackgroundDrug Burden Index (DBI), a measure of exposure to medications with anticholinergic and sedative activity, has been associated with poorer physical function in older adults in the general population. While extensive study has been conducted on associations between DBI and physical function in older adults in the general population, little is known about associations in older adults with intellectual disabilities (ID). This is the first study which aims to examine the association between DBI score and its two sub-scores, anticholinergic and sedative burden, with two objective measures of physical performance, grip strength and timed up and go, and a measure of dependency, Barthel Index activities of daily living, in older adults with ID.MethodsData from Wave 2 (2013/2014) of the Intellectual Disability Supplement to the Irish Longitudinal Study on Ageing (IDS-TILDA) was analysed. Analysis of Covariance (ANCOVA) was used to detect associations and produce adjusted means for the physical function and dependency measures with respect to categorical DBI scores and the anticholinergic and sedative sub-scores (DBA and DBS).ResultsAfter adjusting for confounders (age, level of ID, history of falls, comorbidities and number of non-DBI medications, Down syndrome (grip strength only) and gender (timed up and go and Barthel Index)), neither grip strength nor timed up and go were significantly associated with DBI, DBA or DBS score > 0 (p > 0.05). Higher dependency in Barthel Index was associated with DBS exposure (p < 0.001).ConclusionsDBI, DBA or DBS scores were not significantly associated with grip strength or timed up and go. This could be as a result of established limitations in physical function in this cohort, long-term exposure to these types of medications or lifelong sedentary lifestyles. Higher dependency in Barthel Index activities of daily living was associated with sedative drug burden, which is an area which can be examined further for review.

Project description:BACKGROUND:There has been an increasing interest in understanding the usefulness of wrist-based accelerometer data for physical activity (PA) assessment due to the ease of use and higher user compliance than other body placements. PA assessment studies have relied on machine learning methods which take accelerometer data in forms of variables, or feature vectors. METHODS:In this work, we introduce automated shape feature derivation methods to transform epochs of accelerometer data into feature vectors. As the first step, recurring patterns in the collected data are identified and placed in a codebook. Similarities between epochs of accelerometer data and codebook's patterns are the basis of feature calculations. In this paper, we demonstrate supervised and unsupervised approaches to learn codebooks. We evaluated these methods and compared them with the standard statistical measures for PA assessment. The experiments were performed on 146 participants who wore an ActiGraph GT3X+ accelerometer on the right wrist and performed 33 activities of daily living. RESULTS:Our evaluations show that the shape feature derivation methods were able to perform comparably with the standard wrist model (F1-score: 0.89) for identifying sedentary PAs (F1-scores of 0.86 and 0.85 for supervised and unsupervised methods, respectively). This was also observed for identifying locomotion activities (F1-scores: 0.87, 0.83, and 0.81 for the standard wrist, supervised, unsupervised models, respectively). All the wrist models were able to estimate energy expenditure required for PAs with low error (rMSE: 0.90, 0.93, and 0.90 for the standard wrist, supervised, and unsupervised models, respectively). CONCLUSION:The automated shape feature derivation methods offer insights into the performed activities by providing a summary of repeating patterns in the accelerometer data. Furthermore, they could be used as efficient alternatives (or additions) for manually engineered features, especially important for cases where the latter fail to provide sufficient information to machine learning methods for PA assessment.

Dataset Information

Is Barthel Index Suitable for Assessing Activities of Daily Living in Patients With Dementia?

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Is Barthel Index Suitable for Assessing Activities of Daily Living in Patients With Dementia?

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