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Modelling job support, job fit, job role and job satisfaction for school of nursing sessional academic staff

Overview of attention for article published in BMC Nursing, May 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#48 of 763)
  • High Attention Score compared to outputs of the same age (86th percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

Mentioned by

news
2 news outlets

Citations

dimensions_citation
6 Dimensions

Readers on

mendeley
55 Mendeley
Title
Modelling job support, job fit, job role and job satisfaction for school of nursing sessional academic staff
Published in
BMC Nursing, May 2018
DOI 10.1186/s12912-018-0290-2
Pubmed ID
Authors

Leanne S. Cowin, Robyn Moroney

Abstract

Sessional academic staff are an important part of nursing education. Increases in casualisation of the academic workforce continue and satisfaction with the job role is an important bench mark for quality curricula delivery and influences recruitment and retention. This study examined relations between four job constructs - organisation fit, organisation support, staff role and job satisfaction for Sessional Academic Staff at a School of Nursing by creating two path analysis models. A cross-sectional correlational survey design was utilised. Participants who were currently working as sessional or casual teaching staff members were invited to complete an online anonymous survey. The data represents a convenience sample of Sessional Academic Staff in 2016 at a large school of Nursing and Midwifery in Australia. After psychometric evaluation of each of the job construct measures in this study we utilised Structural Equation Modelling to better understand the relations of the variables. The measures used in this study were found to be both valid and reliable for this sample. Job support and job fit are positively linked to job satisfaction. Although the hypothesised model did not meet model fit standards, a new 'nested' model made substantive sense. This small study explored a new scale for measuring academic job role, and demonstrated how it promotes the constructs of job fit and job supports. All four job constructs are important in providing job satisfaction - an outcome that in turn supports staffing stability, retention, and motivation.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 55 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 16%
Student > Doctoral Student 5 9%
Lecturer 4 7%
Student > Master 4 7%
Student > Bachelor 4 7%
Other 4 7%
Unknown 25 45%
Readers by discipline Count As %
Nursing and Health Professions 9 16%
Business, Management and Accounting 6 11%
Social Sciences 5 9%
Arts and Humanities 3 5%
Psychology 2 4%
Other 4 7%
Unknown 26 47%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 April 2019.
All research outputs
#2,033,381
of 23,094,276 outputs
Outputs from BMC Nursing
#48
of 763 outputs
Outputs of similar age
#45,477
of 330,389 outputs
Outputs of similar age from BMC Nursing
#3
of 11 outputs
Altmetric has tracked 23,094,276 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 763 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 330,389 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.