Validating a Scalable, Open Science Framework for Collecting Laboratory-Grade Data Remotely in Specialized Populations
Validating a Scalable, Open Science Framework for Collecting Laboratory-Grade Data Remotely in Specialized Populations
批准号:
10289016
负责人:
Bridgette Lynne Kelleher
金额:
$23.05万
依托单位:
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:
已结题
起止时间:
2021-09-01 至 2023-08-31
关键词:
AcuteAddressAssessment toolAttentionBehavioralBiological AssayCOVID-19 pandemicCalibrationCaregiversChildClinicClinicalClinical ResearchClinical SciencesClinical TrialsCognitiveComputer softwareDataData CollectionDevelopmentE-learningEnsureEquipmentFailureFloorFragile X SyndromeFundingHeart RateHuman ResourcesIndividualIntellectual functioning disabilityLaboratoriesMeasuresMethodsModelingMonitorMulti-Institutional Clinical TrialNatural HistoryOutcomeOutcome MeasureOutputParentsParticipantPatient MonitoringPatientsPharmaceutical PreparationsPopulationPositioning AttributeProceduresProcessProtocols documentationPsychophysiologyPublishingResearchResearch PersonnelResourcesScienceSignal TransductionSiteStandardizationSymptomsTechniquesTestingTimeTrainingTranslatingTravelUnited States National Institutes of Healthbaseclinical outcome measurescohortcostcost effectivedata analysis pipelinedata standardsefficacy validationgraphical user interfacehigh risk populationimprovedinnovationnetwork modelsopen datapatient responsepeerprogramsremote deliveryself-directed learningskillssustained attentiontelehealthtooltreatment trialuser friendly softwareuser-friendlyvirtual
中文摘要
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英文摘要
PROJECT SUMMARY
The limited repertoire of clinical outcome measures suitable for children with intellectual and
developmental disabilities (IDD) is compromising the promise of clinical trials. Non-standardized
laboratory techniques that capture “spectral” signals – such as psychophysiological assays –
are increasingly recognized as promising methods for monitoring patient responses over time.
However these tools require specialized equipment and personnel to administer and are not
easily deployed via telehealth, biasing spectral studies toward patients who are able and willing
to travel to clinics. Thus, there is a significant gap in available telehealth-based protocols for
collecting laboratory-grade data remotely in IDD populations. The present study addresses this
gap by developing a comprehensive training protocol for PANDABox (Parent Assisted
Neurodevelopmental Assessment), an open-science, telehealth-based assessment protocol that
PI Kelleher developed for remotely collecting high quality, integrated clinical, behavioral, and
spectral assays from participants with IDD. Published findings indicate that PANDABox is highly
feasible and acceptable to caregivers and generates high quality, integrated, “laboratory-grade”
data at low cost. Already, PANDABox is being deployed in a variety of treatment and natural
history studies across IDD populations and is being translated to Spanish to promote
accessibility. The present study aims to enhance the scalability of PANDABox by accomplishing
two specific aims. First, we will develop and validate an open-science training protocol and
peer-to-peer reliability network to facilitate standardized, cross-laboratory implementation of the
PANDABox protocol in IDD. This protocol will include both a virtual training hub for self-paced
training, as well as a reliability network to facilitate cross-site calibration. Second, we will create
user-friendly software program to support users to efficiently process the PANDABox attention
assay, which has produced promising outcomes in clinical trials but requires computational
expertise to analyze, limiting its scalability. Addressing these gaps would shift the status quo of
clinical science in IDD by (1) providing a scalable, accessible protocol for collecting laboratory-
grade data remotely in IDD populations and (2) producing standardized data outputs necessary
for large scale, multi-site, collaborative science.
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会议论文
Optimizing a Personalized Health Approach for Virtually Treating High-Risk Caregivers During COVID-19 and Beyond
-
批准号:10363469
-
项目类别:
-
资助金额:$102.84万
-
财政年份:2022
-
负责人:Bridgette Lynne Kelleher
-
依托单位:
Optimizing a Personalized Health Approach for Virtually Treating High-Risk Caregivers During COVID-19 and Beyond
-
批准号:10709470
-
项目类别:
-
资助金额:$97.63万
-
财政年份:2022
-
负责人:Bridgette Lynne Kelleher
-
依托单位:
Telehealth Assessment of Syndromic Autism Risk in Infants
-
批准号:10181077
-
项目类别:
-
资助金额:$18.22万
-
财政年份:2017
-
负责人:Bridgette Lynne Kelleher
-
依托单位:
Telehealth Assessment of Syndromic Autism Risk in Infants
-
批准号:9386578
-
项目类别:
-
资助金额:$18.27万
-
财政年份:2017
-
负责人:Bridgette Lynne Kelleher
-
依托单位:
Predicting Autism through Behavioral and Biomarkers of Attention in Infants
-
批准号:8575340
-
项目类别:
-
资助金额:$2.64万
-
财政年份:2011
-
负责人:Bridgette Lynne Kelleher
-
依托单位:
Predicting Autism through Behavioral and Biomarkers of Attention in Infants
-
批准号:8254642
-
项目类别:
-
资助金额:$3.55万
-
财政年份:2011
-
负责人:Bridgette Lynne Kelleher
-
依托单位:
Predicting Autism through Behavioral and Biomarkers of Attention in Infants
-
批准号:8391338
-
项目类别:
-
资助金额:$3.47万
-
财政年份:2011
-
负责人:Bridgette Lynne Kelleher
-
依托单位:
海外基金