Evidence map›Paper›PMID 40200452›Full record

ArticleStudies in health technology and informatics2025

Using C4.5 Algorithm to Gain Insights on Stakeholder Engagement and Use of Artificial Intelligence on Social Media in Dementia Caregiving Disparity Research.

Sunmoo Yoon, Frederick Sun, Peter Broadwell, Robert Crupi, Melissa Patterson, Tess D Pottinger, Milea Kim, Ncole Davis

Abstract read
In one paragraph

Article in Studies in health technology and informatics, 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

8 authors.

Sunmoo YoonGeneral Medicine, Columbia University, New York, NY.
Frederick SunNew York Presbyterian Hospital, New York, NY.
Peter BroadwellCenter for Interdisciplinary Digital Research, Stanford University, Stanford, CA.
Robert CrupiNew York Presbyterian Hospital, New York, NY.
Melissa PattersonDivision of Geriatric Medicine and Aging, Columbia University, New York, NY.
Tess D PottingerGeneral Medicine, Columbia University, New York, NY.
Milea KimNew York Presbyterian Hospital, New York, NY.
Ncole DavisSchool of Nursing, Clemson University, Clemson, SC.

Funding

Using Twitter to Enhance the Social Support of Hispanic and Black Dementia Caregivers (Tweet-SS)R01AG060929 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI YOON, SUNMOO · 2019 to 2023
$3.0M
NIA NIH HHS R01 AG060929
6 · The paper itself

Abstract

We applied machine learning techniques to build models that predict perceived risks and benefits of using artificial intelligence (AI) algorithms to recruit African American informal caregivers for clinical trials and general health disparity research via social media platforms. In a U.S. sample of 572 family caregivers of a person with Alzheimer's disease and related dementias (ADRD), our application of the J48 algorithm (C4.5) revealed an interesting trend. African American family members of a person with ADRD were more likely to see the benefits of using AI on social media to ease the burden of recruitment, regardless of age, ethnicity, gender, and level of education. However, white family caregivers, particularly those aged 25-34 with graduate degrees, were more cautious and prone to perceive risks of using AI on social media for recruitment in research. This caution underscores the need for further research and understanding in this area.

Indexed as

AlgorithmsArtificial IntelligenceCaregiversDementiaSocial MediaStakeholder ParticipationAdultAgedAlzheimer DiseaseBlack or African AmericanFemaleHumansMaleMiddle AgedUnited StatesWhiteAIdementia caregivinghealth disparitysocial media

Identifiers

PMID40200452
PMCPMC11984627

What OpenQuestion holds

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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.