Characterizing Episodes of Lucidity in Dementia Using Observational and Applied Computational Linguistics Approaches
使用观察和应用计算语言学方法表征痴呆症的清醒发作
基本信息
- 批准号:10094836
- 负责人:
- 金额:$ 19.42万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-09-30 至 2022-08-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAffectAlzheimer&aposs DiseaseAlzheimer&aposs disease related dementiaAttitudeCaringClinicalCodeCognitiveCommunicationComputational LinguisticsDataData CollectionData SourcesDementiaDevelopmentDisease ProgressionEnrollmentEpidemiologyEthicsEventEyeFamily CaregiverFeasibility StudiesFocus GroupsFoundationsFrequenciesFutureGoalsGroup InterviewsIndividualInpatientsInvestigationLanguageLegalLinguisticsMeasurementMeasuresMethodologyMethodsMissionNonverbal CommunicationOutputPersonsPhasePhenotypePopulationPrivacyProceduresReportingResearchResearch PrioritySecureSourceSpeechStandardizationStructureTarget PopulationsUnited StatesValidationVariantWorkadvanced diseasebasebehavioral responsecognitive functioncommunication behaviorcomplex data data infrastructuredata sharingdata warehouseend of lifeend of life caregazehospice environmentinterestprospectiveprototyperecruitrepositorysharing platformusability
项目摘要
PROJECT SUMMARY/ABSTRACT
Individuals with Alzheimer’s disease and related dementias (ADRD) demonstrate heterogeneous cognitive,
functional, and behavioral responses to disease progression, yet underlying sources of these variations remain
poorly understood. Fluctuations in communication abilities in particular have important implications for care and
attitudes toward individuals with ADRD. Of particular interest is the occurrence of episodes of lucidity (EL) in
advanced disease stages, which are characterized by the manifestation of spontaneous, meaningful, and
relevant communication abilities that were previously believed to be irretrievable. Reports suggest EL are
transient and most likely to occur near end of life, yet empiric evidence documenting these events is extremely
limited. Efforts to better understand, and ultimately define EL, are hindered by underdeveloped methodological
approaches for capturing and characterizing these events. While underutilized in ADRD research, audiovisual
observation is well-suited to addressing these gaps, as these data provide an objective data source and enable
a robust assessment of verbal and nonverbal communication, the primary means through which EL are
observed. Our long-term objective is to clarify conceptual, operational and epidemiologic understandings of EL
in ADRD. Our short-term objective is to establish the necessary foundational data and infrastructure to accelerate
systematic investigation of EL. To advance these goals, we will develop feasible and acceptable procedures to
enable capture of longitudinal audiovisual data of targeted populations and timeframes to maximize opportunities
for detecting EL; these rich data sources will then be analyzed via computational linguistic and sequential
analysis (timed-event) methods, to assemble a robust, fully characterized understanding of the linguistic, non-
linguistic, and non-verbal communication features of EL along with the specific temporal qualities of these events.
In the R21 Phase, we will demonstrate the feasibility of collecting and sharing longitudinal audiovisual data
among PLWD near end of life through a mixed-methods feasibility study to determine key ethical and practical
considerations (R21 Aim 1); and evaluate usability, reliability and capture rate for coding of verbal/nonverbal
indicators of EL from collected audiovisual data using computational linguistic and timed-event methods (R21
Aim 2). The R33 Phase will harness procedures optimized in the R21 phase to expand data collection and
develop more robust estimates of EL frequency. Specifically, we will expand longitudinal audiovisual
observations of persons with ADRD near the end of life to obtain initial estimates of EL frequency, describe event
attributes, and inform the development of definitions for EL (R33 Aim1); and establish a repository of longitudinal
audiovisual observational data and a secure data sharing platform (R33 Aim 2). Impact: Findings from this
research will set the stage for extension and validation of urgently needed objective measurement for EL in
ADRD and provide a critically needed foundation for future systematic investigation of lucidity in ADRD. The
objectives of this proposal are directly responsive to national ADRD research priorities and the NIA mission.
项目总结/文摘
项目成果
期刊论文数量(0)
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Andrea L Gilmore-Bykovskyi其他文献
Andrea L Gilmore-Bykovskyi的其他文献
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{{ truncateString('Andrea L Gilmore-Bykovskyi', 18)}}的其他基金
Characterizing Episodes of Lucidity in Dementia Using Observational and Applied Computational Linguistics Approaches
使用观察和应用计算语言学方法表征痴呆症的清醒发作
- 批准号:
10266124 - 财政年份:2020
- 资助金额:
$ 19.42万 - 项目类别:
Characterizing Episodes of Lucidity in Dementia Using Observational and Applied Computational Linguistics Approaches
使用观察和应用计算语言学方法表征痴呆症的清醒发作
- 批准号:
10677987 - 财政年份:2020
- 资助金额:
$ 19.42万 - 项目类别:
Characterizing Episodes of Lucidity in Dementia Using Observational and Applied Computational Linguistics Approaches
使用观察和应用计算语言学方法表征痴呆症的清醒发作
- 批准号:
10704748 - 财政年份:2020
- 资助金额:
$ 19.42万 - 项目类别:
Novel Approaches to Identifying and Engaging Disadvantaged Patients with Alzheimer’s Disease (AD) in Clinical Research
识别弱势阿尔茨海默病 (AD) 患者并使之参与临床研究的新方法
- 批准号:
9770763 - 财政年份:2018
- 资助金额:
$ 19.42万 - 项目类别:
Novel Approaches to Identifying and Engaging Disadvantaged Patients with Alzheimer’s Disease (AD) in Clinical Research
识别弱势阿尔茨海默病 (AD) 患者并使之参与临床研究的新方法
- 批准号:
10228043 - 财政年份:2018
- 资助金额:
$ 19.42万 - 项目类别:
Novel Approaches to Identifying and Engaging Disadvantaged Patients with Alzheimer’s Disease (AD) in Clinical Research
识别弱势阿尔茨海默病 (AD) 患者并使之参与临床研究的新方法
- 批准号:
9977895 - 财政年份:2018
- 资助金额:
$ 19.42万 - 项目类别:
Novel Approaches to Identifying and Engaging Disadvantaged Patients with Alzheimer’s Disease (AD) in Clinical Research
识别弱势阿尔茨海默病 (AD) 患者并使之参与临床研究的新方法
- 批准号:
10448269 - 财政年份:2018
- 资助金额:
$ 19.42万 - 项目类别:
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