Evidence map›Paper›PMID 41098678›Full record

ArticleFrontiers in education2025

A comparison of applicant and accepted student characteristics to research training programs with implications for recruitment and selection strategy.

Young-Hee Cho, Chi-Ah Chun, Hector Ramos, Paul Buonora, Vasanthy Narayanaswami, Kim-Phuong L Vu

Abstract read
In one paragraph

Article in Frontiers in education, 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

6 authors.

Young-Hee ChoDepartment of Psychology, California State University, Long Beach, CA, United States.
Chi-Ah ChunDepartment of Psychology, California State University, Long Beach, CA, United States.
Hector RamosCSULB BUILD Program, California State University, Long Beach, CA, United States.
Paul BuonoraCSULB BUILD Program, California State University, Long Beach, CA, United States.
Vasanthy NarayanaswamiDepartment of Chemistry and Biochemistry, California State University, Long Beach, CA, United States.
Kim-Phuong L VuDepartment of Psychology, California State University, Long Beach, CA, United States.

Funding

CSULB Building Biomedical Research Program: Overall ComponentUL1GM118979 · NIGMS · CALIFORNIA STATE UNIVERSITY LONG BEACH · PI CHUN, CHI-AH, DILLON, JESSE · 2015 to 2023
$20.7M
CSULB Building Biomedical Research Program: Student Training CoreTL4GM118980 · NIGMS · CALIFORNIA STATE UNIVERSITY LONG BEACH · PI CHUN, CHI-AH, DILLON, JESSE · 2015 to 2023
$12.3M
Research Initiative for Scientific Enhancement at CSULBR25GM071638 · NIGMS · CALIFORNIA STATE UNIVERSITY LONG BEACH · PI BUONORA, PAUL T, FRASER, DEBORAH ANN · 2004 to 2022
$10.0M
CSULB Building Biomedical Research Program: Research Enrichment CoreRL5GM118978 · NIGMS · CALIFORNIA STATE UNIVERSITY LONG BEACH · PI CHUN, CHI-AH, DILLON, JESSE · 2015 to 2023
$7.3M
Supplement for CSULB Maximizing Access to Research Careers (MARC) UNDERGRADUATE STUDENT TRAINING IN ACADEMIC RESEARCH (U-STAR)T34GM008074 · NIGMS · CALIFORNIA STATE UNIVERSITY LONG BEACH · PI NARAYANASWAMI, VASANTHY · 1985 to 2022
$4.6M
Undergraduate Research Training Initiative for Student Enhancement (U-RISE) (T34) at CSULBT34GM149378 · NIGMS · CALIFORNIA STATE UNIVERSITY LONG BEACH · PI VASANTHY NARAYANASWAMI · 2023 to 2026
$2.4M
Transendothelial transport mediated modulations to the High Density LipoproteinSC3GM105561 · NIGMS · CALIFORNIA STATE UNIVERSITY LONG BEACH · PI NARAYANASWAMI, VASANTHY · 2013 to 2021
$876k
NIGMS NIH HHS R25 GM071638NIGMS NIH HHS RL5 GM118978NIGMS NIH HHS SC3 GM105561NIGMS NIH HHS T34 GM008074NIGMS NIH HHS T34 GM149378NIGMS NIH HHS TL4 GM118980NIGMS NIH HHS UL1 GM118979
6 · The paper itself

Abstract

Introduction: Very few studies have examined the relationship between student characteristics and their acceptance to research training programs that use holistic selection. The present study addressed this question using institutional and applicant data of three NIH undergraduate training programs at California State University, Long Beach. Its first aim was to examine whether the applicants to the training programs were representative of the broader campus population. Its second aim was to investigate whether applicants who were accepted to the programs using a holistic selection process differed in academic discipline, demographics, and psychosocial characteristics from applicants who were not accepted. Methods: Information on students' majors, race/ethnicity, and gender was obtained from the university records or applications submitted by students. Majors were categorized as either biomedical or behavioral disciplines, while URM status was defined as students who self-identified their race and ethnicity as African American/Black, Native American, Native Hawaiian/Pacific Islander, or Hispanic. Applicants' psychosocial characteristics were obtained from a separate online survey. The acceptance status of applicants was obtained from the training programs' records. Results: The applicant and non-applicant groups showed similar distribution of demographic characteristics regarding URM status and gender. Moreover, students' academic discipline and other demographic variables were not associated with application status at either the lower division (LD) or upper division (UD) levels. Although psychosocial characteristics measured with the online survey were not considered in the selection process, post-hoc analyses showed that LD applicants with higher grit and UD applicants with higher science interests were more likely to be accepted to the programs. Conclusion: The equal representation of URM and female students in the applicant and non-applicant groups suggests that students from these traditionally underrepresented groups in STEM were just as likely to apply to our training programs. Furthermore, while the holistic selection process resulted in comparable acceptance rates across URM status and gender, it appeared to favor LD applicants with higher grit and UD students with higher science interests. These findings imply that research training programs can effectively recruit diverse students from underrepresented populations in STEM by using intentional outreach and recruitment efforts coupled with an objective and holistic selection process.

Indexed as

acceptanceapplicationdemographic characteristicsdiversitypsychosocial characteristicsundergraduate research training

Identifiers

PMID41098678
PMCPMC12519540

What OpenQuestion holds

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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.