Evidence map›Paper›PMID 41112654›Full record

ArticleFrontiers in public health2025

The relationship between structural characteristics of long-term care institutions and their initial operating budgets.

Xiaojing Wang, Peter C Coyte

Abstract read
In one paragraph

Article in Frontiers in public health, 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

2 authors.

Xiaojing WangDepartment of Business Administration, School of Management, Shanghai University of Engineering Science, Shanghai, China.
Peter C CoyteInstitute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: In the context of a rapidly aging population, this study focuses on an important issue concerning long-term care institutions, attempting to explore the relationship between structural characteristics and initial operating budgets. Methods: Data analysis was performed based on 581 long-term care institutions collected from the Shanghai Municipal Civil Affairs Bureau. Statistical analyses were conducted using IBM SPSS Statistics 24.0 with the PROCESS macro (version 3.5) for moderation analyses and Stata 16.0 for endogeneity tests. Results: The analyses revealed a significant U-shaped relationship between the gross floor areas of long-term care institutions and their initial operating budgets. Industry competition negatively moderated the effect of gross floor area on initial operating budget and also significantly exerted a direct negative effect on budgets. In addition, staffing arrangement showed a positive effect on initial operating budgets. Ownership type mattered: publicly constructed institutions had significantly lower initial operating budget compared to privately constructed institutions, whereas publicly operated institutions were associated with significantly higher initial operating budgets than privately operated ones. Institutions with leased property reported lower initial operating budgets than those with self-owned property. Conclusion: This study demonstrates that the initial operating budgets of long-term care institutions are significantly associated with their structural characteristics.

Indexed as

BudgetsFacility Design and ConstructionLong-Term CareNursing HomesChinaHumansOwnershipPublic Sectoreconomicsindustry competitioninitial operating budgetslong-term care institutionsolder adultsownershipstructural characteristics

Identifiers

PMID41112654
PMCPMC12528046

What OpenQuestion holds

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LicenceCC BY
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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.