Evidence map›Paper›PMID 22166907›Full record

ArticleNursing research

Jurisdiction over nursing care systems in nursing homes: latent class analysis.

Kirsten N Corazzini, Ruth A Anderson, Christine Mueller, Joshua M Thorpe, Eleanor S McConnell

Abstract read
In one paragraph

Article in Nursing research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

4 citing papers in PubMed.

  1. Resource Factors Associated With Avoidable Transfers in Nursing Homes.Journal of the American Medical Directors Association · 2026
    Article
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  4. Review
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

5 authors.

Kirsten N CorazziniDuke University School of Nursing, Duke University Medical Center, Durham, NC 27710, USA. kirsten.corazzini@duke.edu
Ruth A Anderson
Christine Mueller
Joshua M Thorpe
Eleanor S McConnell

Funding

Translation CoreP30NR003979 · NINR · UNIVERSITY OF IOWA · PI REIMER, TONI TRIPP · 1994 to 2008
$3.8M
NINR NIH HHS 5P30NR003979-13NINR NIH HHS P30 NR003979
6 · The paper itself

Abstract

backgroundIn the context of declining registered nurse (RN) staffing levels in nursing homes, professional nursing jurisdiction over nursing care systems may erode.

objectiveThe aim of this study was to develop a typology of professional nursing jurisdiction in nursing homes in relation to characteristics of RN staffing, drawing upon Abbott's tasks and jurisdictions framework.

methodsThe study was a cross-sectional, observational study using the 2004 National Nursing Home Survey (n = 1,120 nursing homes). Latent class analysis was used to test whether RN staffing indicators differentiated facilities in a typology of RN jurisdiction and compared classes on key organizational environment characteristics. Multiple logistic regression analysis related the emergent classes to presence or absence of specialty care programs in eight clinical areas.

resultsThree classes of capacity for jurisdiction were identified, including low capacity (41% of homes) with low probabilities of having any indicators of RN jurisdiction, mixed capacity (26% of homes) with moderate to high probabilities of having higher RN education and staffing levels, and high capacity (32% of homes) with moderate to high probabilities of having almost all indicators of RN jurisdiction. High-capacity homes were more likely to have specialty care programs relative to low-capacity homes; such homes were less likely to be chain-owned and more likely to be larger, provide higher technical levels of patient care, have unionized nursing assistants, have a lower ratio of licensed practical nurses to RNs, and have an administrator with higher education level. DISCUSSION: Findings provide preliminary support for the theoretical framework as a starting point to move beyond extensive reliance on staffing levels and mix as indicators of quality. Furthermore, findings indicate the importance of RN specialty certification.

Indexed as

Personnel Staffing and SchedulingCross-Sectional StudiesHumansLogistic ModelsNursing HomesNursing StaffQuality of Health CareUnited StatesWorkforce

Identifiers

PMID22166907
PMCPMC4360952

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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.