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Age-related differences in working hours among male and female GPs: an SMS-based time use study

Overview of attention for article published in Human Resources for Health, December 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

blogs
1 blog
twitter
5 tweeters

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
29 Mendeley
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Title
Age-related differences in working hours among male and female GPs: an SMS-based time use study
Published in
Human Resources for Health, December 2017
DOI 10.1186/s12960-017-0258-4
Pubmed ID
Authors

Daniël van Hassel, Lud van der Velden, Dinny de Bakker, Ronald Batenburg

Abstract

In several countries, the number of hours worked by general practitioners (GPs) has decreased, raising concern about current and impending workforce shortages. This shorter working week has been ascribed both to the feminisation of the workforce and to a younger generation of GPs who prefer more flexible working arrangements. There is, however, limited insight into how the impact of these determinants interact. We investigated the relative importance of differences in GPs' working hours in relation to gender, age, and employment position. An analysis was performed on real-time monitoring data collected by sending SMS text messages to 1051 Dutch GPs, who participated during a 1-week time use study. We used descriptive statistics, independent sample t-tests, and one-way ANOVA analysis to compare the working time of different GP groups. A path analysis was conducted to examine the difference in working time by gender, age, employment position, and their combinations. Female GPs worked significantly fewer hours than their male peers. GPs in their 50s worked the highest number of hours, followed by GPs age 60 and older. GPs younger than 40 worked the lowest number of hours. This relationship between working hours and age was not significantly different for women and men. As shown by path analysis, female GPs consistently worked fewer hours than their male counterparts, regardless of their age and employment position. The relationship between age and working hours was largely influenced by gender and employment position. The variation in working hours among GPs can be explained by the combination of gender, age, and employment position. Gender appears to be the most important predictor as the largest part of the variation in working hours is explained by a direct effect of this variable. It has previously been reported that the difference in working hours between male and female GPs had decreased over time. However, our findings suggest that gender remains a critical factor for variation in time use and for policy instruments such as health workforce planning.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 29 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 24%
Other 5 17%
Researcher 2 7%
Student > Doctoral Student 2 7%
Professor 2 7%
Other 4 14%
Unknown 7 24%
Readers by discipline Count As %
Medicine and Dentistry 10 34%
Nursing and Health Professions 4 14%
Business, Management and Accounting 2 7%
Social Sciences 2 7%
Economics, Econometrics and Finance 1 3%
Other 3 10%
Unknown 7 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 17 February 2020.
All research outputs
#1,908,465
of 17,366,233 outputs
Outputs from Human Resources for Health
#234
of 945 outputs
Outputs of similar age
#62,211
of 416,333 outputs
Outputs of similar age from Human Resources for Health
#28
of 73 outputs
Altmetric has tracked 17,366,233 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 945 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one has done well, scoring higher than 75% 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 416,333 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 85% of its contemporaries.
We're also able to compare this research output to 73 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 61% of its contemporaries.