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Nonstandard working schedules and health: the systematic search for a comprehensive model

Overview of attention for article published in BMC Public Health, October 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

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10 news outlets
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2 X users

Citations

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27 Dimensions

Readers on

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96 Mendeley
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Title
Nonstandard working schedules and health: the systematic search for a comprehensive model
Published in
BMC Public Health, October 2015
DOI 10.1186/s12889-015-2407-9
Pubmed ID
Authors

Suzanne L. Merkus, Kari Anne Holte, Maaike A. Huysmans, Willem van Mechelen, Allard J. van der Beek

Abstract

Theoretical models on shift work fall short of describing relevant health-related pathways associated with the broader concept of nonstandard working schedules. Shift work models neither combine relevant working time characteristics applicable to nonstandard schedules nor include the role of rest periods and recovery in the development of health complaints. Therefore, this paper aimed to develop a comprehensive model on nonstandard working schedules to address these shortcomings. A literature review was conducted using a systematic search and selection process. Two searches were performed: one associating the working time characteristics time-of-day and working time duration with health and one associating recovery after work with health. Data extracted from the models were used to develop a comprehensive model on nonstandard working schedules and health. For models on the working time characteristics, the search strategy yielded 3044 references, of which 26 met the inclusion criteria that contained 22 distinctive models. For models on recovery after work, the search strategy yielded 896 references, of which seven met the inclusion criteria containing seven distinctive models. Of the models on the working time characteristics, three combined time-of-day with working time duration, 18 were on time-of-day (i.e. shift work), and one was on working time duration. The model developed in the paper has a comprehensive approach to working hours and other work-related risk factors and proposes that they should be balanced by positive non-work factors to maintain health. Physiological processes leading to health complaints are circadian disruption, sleep deprivation, and activation that should be counterbalanced by (re-)entrainment, restorative sleep, and recovery, respectively, to maintain health. A comprehensive model on nonstandard working schedules and health was developed. The model proposes that work and non-work as well as their associated physiological processes need to be balanced to maintain good health. The model gives researchers a useful overview over the various risk factors and pathways associated with health that should be considered when studying any form of nonstandard working schedule.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 96 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
United States 1 1%
Portugal 1 1%
Canada 1 1%
Unknown 92 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 21 22%
Researcher 12 13%
Student > Bachelor 12 13%
Student > Ph. D. Student 11 11%
Student > Doctoral Student 5 5%
Other 18 19%
Unknown 17 18%
Readers by discipline Count As %
Medicine and Dentistry 21 22%
Psychology 13 14%
Nursing and Health Professions 9 9%
Social Sciences 9 9%
Business, Management and Accounting 5 5%
Other 18 19%
Unknown 21 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 84. 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 27 August 2019.
All research outputs
#425,238
of 22,831,537 outputs
Outputs from BMC Public Health
#372
of 14,872 outputs
Outputs of similar age
#6,995
of 283,600 outputs
Outputs of similar age from BMC Public Health
#5
of 267 outputs
Altmetric has tracked 22,831,537 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 14,872 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.9. This one has done particularly well, scoring higher than 97% 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 283,600 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 267 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.