Evidence map›Paper›PMID 42685658›Full record

ArticleJournal of the American Medical Directors Association2026

Effect of Staffing and Wages on Turnover of Nonclinical Support Staff in Nursing Homes.

Hari Sharma

Abstract read
In one paragraph

Article in Journal of the American Medical Directors Association, 2026. 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

1 author.

Hari SharmaDepartment of Health Management and Policy, The University of Iowa, Iowa City, IA, USA. Electronic address: hari-sharma@uiowa.edu.

Funding

NIOSH CDC HHS R03 OH012519
6 · The paper itself

Abstract

objectivesHousekeeping, dietary, laundry, and maintenance workers play a critical role in nursing home quality and safety. High turnover among these workers disrupts care, increases costs, and undermines facility stability. However, little is known about the role of staffing and wages on turnover for these roles. The objective of this study is to estimate the effect of staffing and wages on the turnover of housekeeping, dietary, laundry, and maintenance workers.

designRetrospective study. SETTING AND

participantsA total of 418 unique nursing homes with 4428 observations in Iowa from 2011 to 2022.

methodsWe define turnover rates using the number of employees in a given job type who left during the year, divided by the average number of employees in that job type at the facility. Our main predictor variables were average staff size and hourly wage rates. We used robust facility-fixed effects linear regressions to estimate the impact of staffing and wages on turnover.

resultsEach additional dollar in hourly wages was associated with a reduction in turnover of 3.50 percentage points for dietary staff, 3.83 for housekeeping, 1.17 for maintenance, and 3.12 for laundry (all P < .001). Similarly, increasing average staff size by 1 worker was associated with a reduction in turnover of 0.95 percentage points for dietary staff, 2.06 for housekeeping, and 2.99 for laundry. Effects were broadly consistent but larger in for-profit and urban facilities. CONCLUSIONS AND IMPLICATIONS: Our findings suggest that improving wages and staffing levels may be effective strategies for reducing turnover among nursing home support staff, particularly in for-profit and urban facilities.

Indexed as

Nursing HomesPersonnel Staffing and SchedulingPersonnel TurnoverSalaries and Fringe BenefitsHumansIowaRetrospective Studiesfinancialnon-nurse staffQualityretention

Identifiers

PMID42685658
PMCPMC13651776

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.