Evidence map›Paper›PMID 38263150›Full record

ArticleBMC health services research2024

The impact of public leadership on collaborative administration and public health delivery.

Muhammad Zia Ud Din, Xu Yuan Yuan, Naqib Ullah Khan, Christophe Estay

Abstract read
In one paragraph

Article in BMC health services research, 2024. 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

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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. 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

4 authors.

Muhammad Zia Ud DinSchool of Public Administration, Central South University, Yuelu District, Changsha, Hunan, 410017, China.ORCID http://orcid.org/0009-0003-8675-0557
Xu Yuan YuanSchool of Public Administration, Central South University, Yuelu District, Changsha, Hunan, 410017, China. xuyuanyuanj@163.com.
Naqib Ullah KhanSchool of Public Administration, Central South University, Yuelu District, Changsha, Hunan, 410017, China. naqibkhan05@csu.edu.cn.ORCID http://orcid.org/0000-0002-6023-4066
Christophe EstayFERRANDI Paris (France), Lirsa, Cnam, Hesam Université, Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis research depicts the linkage of public leadership on public health delivery (PHD) and collaborative administration. The research is also focused to examine the effect of public leadership on public health delivery through the intervening variable of collaborative administration by using both social information processing theory and collaboration theory.

methodsThis research is based on quantitative method. Data was collected from 464 public hospital administration in the context of Pakistan. This study evaluated data using SPSS, AMOS, and PROCESS Macro.

resultsPublic leadership has a positive profound effect on public health delivery and collaborative administration, and that collaborative administration significantly promotes public health delivery. The outcomes also exposed that public leadership has substantial influence on public health delivery through intervening collaborative administration.

conclusionsWhilst public leadership demonstrated positive outcomes on public health delivery and collaborative administration, there is a need for more rigor studies on collaborative governance leadership, collaborative ethics and collaborative norms in the public health service.

Indexed as

LeadershipPublic HealthCognitionHumansPakistanSocial TheoryCollaboration theoryCollaborative administrationPublic health deliveryPublic leadershipSocial information processing theory

Identifiers

PMID38263150
PMCPMC10807078

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.