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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Results and their implications from comparing respondents and proxy responses for non-respondents with cognitive
1On Target Health Data LLC, 247 N Stone Street, West Suffield, CT 06093, USA.
Background:
Limited study has been done on proxy responses for non-respondents with subjective cognitive decline (SCD) on the Behavioral Risk Factor Surveillance System (BRFSS).
Objective:
To directly compare results for survey respondents with SCD with those for proxies provided for non-respondents with SCD.
Methods:
Publicly available 2011 BRFSS data from 120,485 households in 21 states were analyzed using Stata. Respondents ages 40 and older with SCD (n = 10,831) were compared with proxy responses for non-respondents ages 40 and older with SCD (n = 4296) living in households where the respondent did not have SCD. Outcome measures included functional difficulties associated with their SCD, needing help, receiving informal care, talking with a healthcare provider about their SCD, getting treatment, and having a dementia diagnosis. Logistic regression for each outcome controlled for age, household income, state of residence, and number of household adults.
Results:
Non-respondents were significantly more likely than respondents by Pearson chi square tests with alpha = 0.05 to report all 6 outcomes. Adjusted odds ratios comparing non-respondents with respondents ranged from 2.61 (95% confidence interval: 2.22-3.07) for needing help, to 8.99 (6.60-12.24) for a dementia diagnosis and confirmed unadjusted results.
Conclusion:
Respondent results only represent adults capable of answering a telephone survey. To represent all household adults and avoid nonresponse bias that may under-represent the true population parameters by as much as 70%, results must include both respondents and non-respondents. Other measures may be similarly affected if they inhibit one's ability to respond to a telephone survey (e.g. disability, stroke).
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