Evidence map›Paper›PMID 40192556›Full record

ArticlePopulation health management2025

Enhancing Machine Learning Explainability of Disaster Preparedness Models from the FEMA National Household Survey to Inform Tailored Population Health Interventions.

Taryn Amberson, Wenhui Zhang, Samuel E Sondheim, Wanda Spurlock, Jessica Castner

Abstract read
In one paragraph

Article in Population health management, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Taryn AmbersonDepartment of Health Systems and Population Health, University of Washington, Seattle, Washington, USA.ORCID 0000-0001-7088-2545
Wenhui ZhangNell Hodgson Woodruff School of Nursing, Emory University, Atlanta, Georgia, USA.
Samuel E SondheimMount Sinai Morningside Department of Emergency Medicine, Department of Emergency Medicine, and Innovations Lead Faculty, Center for Healthcare Readiness, Icahn, New York, New York, USA.
Wanda SpurlockCollege of Nursing and Allied Health, Southern University and A&M College, Baton Rouge, Louisiana, USA.
Jessica CastnerCastner Incorporated, University at Albany, Grand Island, New York, USA.

Funding

Environmental Health Research Institute for Nurse and Clinician Scientists (EHRI-NCS)R25ES033452 · NIEHS · CASTNER INCORPORATED · PI CASTNER, JESSICA · 2021 to 2025
$1.0M
Precision Assessment Algorithm for Reducing Disaster-related Respiratory Health DisparitiesR43MD017188 · NIMHD · CASTNER INCORPORATED · PI CASTNER, JESSICA · 2021 to 2023
$283k
NIEHS NIH HHS R25 ES033452NIMHD NIH HHS R43 MD017188NIOSH CDC HHS T42 OH008433
6 · The paper itself

Abstract

Devastating mortality, morbidity, economic, and quality of life impacts have resulted from disasters in the United States. This study aimed to validate a preexisting machine learning (ML) model of household disaster preparedness. Data from 2021 to 23 Federal Emergency Management Agency's National Household Surveys (

Indexed as

Disaster PlanningMachine LearningPopulation HealthAdultAgedFamily CharacteristicsFemaleHumansMaleMiddle AgedSurveys and QuestionnairesUnited Statesdata sciencedisaster planningdisparitiesmachine learninguse case

Identifiers

PMID40192556
PMCPMC12419149

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.