Evidence map›Paper›PMID 40267084›Full record

ArticlePloS one2025

Testing job wellbeing indicators among community behavioral health workers: Community-based participatory research.

Sadaaki Fukui, Wei Wu, Jennifer Garabrant, Michelle P Salyers, Nathaniel Dell, Emily Bass, Jaime Greenfield, Gary Morse

Abstract read
In one paragraph

Article in PloS one, 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

8 authors.

Sadaaki FukuiSchool of Social Work, Indiana University, Indianapolis, Indiana, United States of America.ORCID 0000-0002-4484-2109
Wei WuDepartment of Psychology, Indiana University Indianapolis, Indiana, United States of America.
Jennifer GarabrantDepartment of Psychology, Indiana University Indianapolis, Indiana, United States of America.
Michelle P SalyersDepartment of Psychology, Indiana University Indianapolis, Indiana, United States of America.
Nathaniel DellDepartment of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, United States of America.
Emily BassDepartment of Psychology, Indiana University Indianapolis, Indiana, United States of America.
Jaime GreenfieldBJC Healthcare, St. Louis, Missouri, United States of America.
Gary MorsePlaces for People, Inc., St. Louis, Missouri, United States of America.

Funding

Developing a Data-Driven Management System Using Machine Learning and Mixed-Methods Research to Predict Job Turnover Among MentalHealth ProfessionalsR34MH119411 · NIMH · INDIANA UNIVERSITY INDIANAPOLIS · PI FUKUI, SADAAKI · 2020 to 2022
$845k
NIMH NIH HHS R34 MH119411
6 · The paper itself

Abstract

Many community behavioral health organizations (CBHOs) continue to struggle with their employees' reduced job wellbeing and job disengagement (i.e., turnover intentions, actual turnover). Understanding employees' job wellbeing priorities in their organizational contexts is essential to address the challenges, especially for workers in diverse work settings such as CBHOs. We used community-based participatory research (CBPR) strategies to develop and test job wellbeing indicators. The current study implemented 11 indicators with 168 people employed at a CBHO through initial and 6-month follow-up surveys. Positive endorsement of job wellbeing indicators differed based on employees' demographic (e.g., race, education, marital status) and job (e.g., exempt status, clinical positions) characteristics. Several indicators declined from the initial to the follow-up surveys (e.g., communication, job fairness, decision-making involvement, expectation alignment, supervisory support, career development opportunities). The change rates also varied by employee characteristics (e.g., work years, race, exempt status, full-time). The current study illustrates the utility of CBPR strategies to implement job wellbeing indicators based on employees' priorities and diverse job wellbeing experiences among employee subpopulations. Further, the developed indicators revealed job wellbeing heterogeneity by employee subpopulations within an organization that is often overlooked. Efforts to understand varying job wellbeing characteristics among diverse employees may eventually help develop organization-tailored interventions to improve job wellbeing and reduce turnover.

Indexed as

Community-Based Participatory ResearchCommunity Health WorkersJob SatisfactionAdultFemaleHumansMaleMiddle AgedPersonnel TurnoverSurveys and Questionnaires

Identifiers

PMID40267084
PMCPMC12017500

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.