Evidence map›Paper›PMID 39707813›Full record

ArticleWestern journal of nursing research2025

Understanding Daily Care Experience Preferences Across the Lifespan of Older Adults: Application of Natural Language Processing.

Se Hee Min, Kyungmi Woo, Jiyoun Song, Gregory L Alexander, Terrence O'Malley, Maria D Moen, Maxim Topaz

Abstract read
In one paragraph

Article in Western journal of nursing research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Se Hee MinUniversity of Pennsylvania School of Nursing, Philadelphia, PA, USA.ORCID 0000-0003-2722-6627
Kyungmi WooSeoul National University College of Nursing, Seoul, South Korea.
Jiyoun SongUniversity of Pennsylvania School of Nursing, Philadelphia, PA, USA.
Gregory L AlexanderColumbia University School of Nursing, New York, NY, USA.ORCID 0000-0003-4500-8797
Terrence O'MalleyHarvard University, Cambridge, MA, USA.
Maria D MoenADVault Inc., Richardson, TX, USA.ORCID 0009-0001-9984-4582
Maxim TopazColumbia University School of Nursing, New York, NY, USA.

Funding

Reducing Health Disparities Through Informatics - Genomics SupplementT32NR007969 · NINR · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SUZANNE BAKKEN, Rebecca Schnall · 2002 to 2026
$7.9M
NINR NIH HHS T32 NR007969
6 · The paper itself

Abstract

introductionOlder adults are a heterogeneous group, and their care experience preferences are likely to be diverse and individualized. Thus, the aim of this study was to identify categories of older adults' care experience preferences and to examine similarities and differences across different age groups.

methodsThe initial categories of older adults' care experience preferences were identified through a qualitative review of narrative text (n = 3134) in the ADVault data set. A natural language processing (NLP) algorithm was used to automatically and accurately define older adults' care experience preference categories. Descriptive statistics were used to examine similarities and differences in care experience preference categories across different age groups.

resultsThe overall average performance of NLP algorithms was relatively high (average

conclusionClinicians must understand the distinct categories of care experience preferences and incorporate them into personalized care planning.

Indexed as

Natural Language ProcessingPatient PreferenceAgedAged, 80 and overAlgorithmsFemaleHumansMaleMiddle AgedQualitative Researchagingcare preferenceolder adultspatient-centeredness

Identifiers

PMID39707813
PMCPMC11742706

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.