Evidence map›Paper›PMID 38233782›Full record

ArticleBMC geriatrics2024

Racial and ethnic differences in predictors of participation in an intergenerational social connectedness intervention for older adults.

Omolola E Adepoju, Chinedum O Ojinnaka, Jason Pieratt, Jessica Dobbins

Open access · goldAbstract read
In one paragraph

Article in BMC geriatrics, 2024. 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
2.1field-weighted citation impact, top 14% of its field
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, 4 citations in OpenAlex.

  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

4 authors at 3 institutions in 1 country.

Omolola E AdepojuHumana Integrated Health Systems Sciences Institute, University of Houston, Houston, USA. oadepoju@central.uh.edu.
Chinedum O OjinnakaCollege of Health Solutions, Arizona State University, Phoenix, USA.
Jason PierattHumana Inc, Louisville, USA.
Jessica DobbinsTilman J Fertitta Family College of Medicine, Department of Health Systems and Population Health Sciences, University of Houston, Houston, USA.
Humana (United States) · USArizona State University · USUniversity of Houston · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSocial connectedness is a key determinant of health and interventions have been developed to prevent social isolation in older adults. However, these interventions have historically had a low participation rate amongst minority populations. Given the sustained isolation caused by the COVID-19 pandemic, it is even more important to understand what factors are associated with an individual's decision to participate in a social intervention. To achieve this, we used machine learning techniques to model the racial and ethnic differences in participation in social connectedness interventions.

methodsData were obtained from a social connectedness intervention that paired college students with Houston-area community-dwelling older adults (> 65 yo) enrolled in Medicare Advantage plans. Eligible participants were contacted telephonically and asked to complete the 3-item UCLA Loneliness Scale. We used the following machine-learning methods to identify significant predictors of participation in the program: k-nearest neighbors, logistic regression, decision tree, gradient-boosted decision tree, and random forest.

resultsThe gradient-boosted decision tree models yielded the best parameters for all race/ethnicity groups (96.1% test accuracy, 0.739 AUROC). Among non-Hispanic White older adults, key features of the predictive model included Functional Comorbidity Index (FCI) score, Medicare prescription risk score, Medicare risk score, and depression and anxiety indicators within the FCI. Among non-Hispanic Black older adults, key features included disability, Medicare prescription risk score, FCI and Medicare risk scores. Among Hispanic older adults, key features included depression, FCI and Medicare risk scores.

conclusionsThese findings offer a substantial opportunity for the design of interventions that maximize engagement among minority groups at greater risk for adverse health outcomes.

Indexed as

EthnicityIntergenerational RelationsRacial GroupsSocial ParticipationAgedHumansMedicareUnited StatesOlder adultsRace/ethnicitySocial connectednessSocial isolation

Identifiers

PMID38233782
PMCPMC10795227
OpenAlexW4390938169

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.