Enhancing data quality for cross-national harmonization: Assessment of cognitive function in the CHARLS HCAP by language, literacy, and visual impairment
Enhancing data quality for cross-national harmonization: Assessment of cognitive function in the CHARLS HCAP by language, literacy, and visual impairment
批准号:
10759798
负责人:
Alden L. Gross
金额:
$41.85万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-04-01 至 2026-01-31
关键词:
AddressAffectAgeAlzheimer&aposs disease related dementiaChinaCognitionCognitiveConsultationsCountryDataDecontaminationDetectionDiffuseEducationElderlyEnglandExclusionFundingFutureGoalsHealthHigh PrevalenceIndiaInternationalInterviewInterviewerInvestmentsLanguageLinguisticsLongitudinal StudiesMeasurementMeasuresMethodsMexicoOlder PopulationParentsParticipantPerformancePopulationPrevalenceProtocols documentationPublic HealthPublic PolicyReadingRecommendationRespondentRetirementSouth AfricaStimulusTestingTimeTranslatingTranslationsVisionVisualVisual impairmentWorkWritingagedcognitive abilitycognitive functioncognitive testingcognitive trainingdata qualityexperiencehealth goalsilliteracyimprovedinnovationinstrumentliteracylongitudinal analysisnovelparent grantperformance testspilot testrate of changeresponserural residencesextheoriestoolverbal
中文摘要
点击翻译按钮获取中文摘要
英文摘要
Alzheimer’s disease and related dementias (ADRD) are a major global public health and policy challenge. The
NIA has invested in addressing the global ADRD burden through funding the Harmonized Cognitive Assessment
Protocol (HCAP) sub-studies of the US Health and Retirement and its International Partner Studies. The HCAP
is an innovation that aims to allow, for the first time, comparable measurement of cognitive function among older
adults around the world. The HCAP in the China Health and Retirement Longitudinal Study (CHARLS) was first
deployed in Wave 4 of CHARLS in 2018 to participants aged ≥60 years. China is a large, diverse country with at
least nine languages and seven dialects of Mandarin spoken amongst its population. Illiteracy (35.3%
prevalence) and uncorrected visual impairment (18.3% prevalence) are also common in the older population.
However, interview materials for the CHARLS HCAP were prepared and administered assuming fluency in
spoken and written standard Mandarin and were not systematically adapted to account for illiteracy or visual
impairment. If performance on a cognitive test item is affected by these extraneous features rather than a
respondent’s true level of cognition, then differential item functioning (DIF) is said to be present for that cognitive
test item. While DIF can lead to biased cognitive scores, we have tools that can, given assumptions, adjust for
such DIF to improve measurement of cognition. The goal of this supplemental application is to decontaminate
measurement differences in the CHARLS HCAP cognitive test battery due to spoken language or dialect, written
literacy, and visual ability from true underlying levels of cognitive function. The parent R01 (R01AG070953) aims
to statistically harmonize HCAP measures and test for DIF at the country-level across five different countries
(US, Mexico, England, South Africa, and India). The present supplemental application is an extension of the
statistical machinery and scientific scope of the parent grant. We propose to 1) identify and adjust for potential
DIF in measurement of cognitive function in CHARLS HCAP due to language or dialect, literacy, and visual
ability; and 2) Identify and adjust for potential DIF in measurement of cognitive function in prior waves of CHARLS
(Waves 1, 2, 3), by language or dialect, literacy, and visual ability. After performing DIF analysis and adjusting
cognitive scores as needed for DIF, we will examine whether the associations of each of age, sex, education,
and urban/rural residence with DIF-adjusted cognitive scores will differ from the non-DIF-adjusted scores in ways
that suggest reduction of bias due to language or dialect, illiteracy, and vision impairment in the DIF-adjusted
scores. Successful completion of this proposed supplement will help improve the quality of existing CHARLS
cognitive data, and will produce recommendations for the content, administration, and interviewer training for the
cognitive test battery in future planned waves of CHARLS HCAP. We anticipate that this work will enable us to
recommend additional information to collect alongside cognitive measures to enhance data quality and assist
interpretations, such as objective measurement of language, literacy, and visual ability.
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会议论文
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批准号:10586126
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项目类别:
-
资助金额:$49.2万
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财政年份:2021
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负责人:Alden L. Gross
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依托单位:
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批准号:10379328
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项目类别:
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资助金额:$48.46万
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财政年份:2021
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负责人:Alden L. Gross
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批准号:10661154
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项目类别:
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资助金额:$32.53万
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财政年份:2021
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负责人:Alden L. Gross
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批准号:9889017
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项目类别:
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资助金额:$12.76万
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财政年份:2016
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负责人:Alden L. Gross
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Big Questions in Cognitive Aging: An Integrative Analysis Approach
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批准号:8573064
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负责人:Alden L. Gross
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依托单位:
海外基金