Evidence map›Paper›PMID 38884455›Full record

ArticleJournal of primary care & community health

Subjective Well-Being and Burnout Among the Maternal and Child Health Workforce.

Carolyn Brown-Kaiser, Amita Vyas

Abstract read
In one paragraph

Article in Journal of primary care & community health. 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

2 authors.

Carolyn Brown-KaiserGeorge Washington University, Washington, DC, USA.ORCID 0009-0001-3136-2528
Amita VyasGeorge Washington University, Washington, DC, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThis study investigates burnout and subjective well-being among the Maternal and Child Health (MCH) workforce, considering recent events such as the

methodsAn anonymous web-based, cross-sectional survey was conducted among 313 MCH professionals in the United States. Data were collected using validated measures, including the Maslach Burnout Inventory-Human Services Survey (MBI-HSS) and the Oxford Happiness Questionnaire (OHQ) short scale. Sociodemographic characteristics and factors associated with burnout and subjective well-being were examined using univariate statistics and multivariable models.

resultsAnalysis revealed moderate levels of burnout among MCH professionals, particularly in emotional exhaustion. However, subjective well-being levels were relatively high. After controlling for covariates, significant associations were found between subjective well-being and burnout dimensions, as well as sociodemographic factors such as sex and race.

conclusionsThe study's findings indicate that higher subjective well-being is significantly associated with lower burnout, emotional exhaustion, and higher personal accomplishment. Variations in burnout and well-being are also influenced by sociodemographic factors such as age, sex, race, and occupation. Tailored interventions addressing the specific needs of MCH professionals are essential for building a resilient workforce. Organizational reforms and legislative measures are crucial for fostering supportive workplace environments and ensuring access to care and services amidst workforce challenges.

Indexed as

Burnout, ProfessionalAdultCOVID-19Cross-Sectional StudiesFemaleHealth PersonnelHumansJob SatisfactionMaleMiddle AgedSARS-CoV-2Surveys and QuestionnairesUnited Statesburnoutmaternal and child healthresiliencesubjective well-beingworkforce development

Identifiers

PMID38884455
PMCPMC11185010

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.