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Preventing mental illness: closing the evidence-practice gap through workforce and services planning

Overview of attention for article published in BMC Health Services Research, July 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (58th percentile)

Mentioned by

twitter
3 tweeters
facebook
1 Facebook page

Citations

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17 Dimensions

Readers on

mendeley
97 Mendeley
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Title
Preventing mental illness: closing the evidence-practice gap through workforce and services planning
Published in
BMC Health Services Research, July 2015
DOI 10.1186/s12913-015-0954-5
Pubmed ID
Authors

Gareth Furber, Leonie Segal, Matthew Leach, Catherine Turnbull, Nicholas Procter, Mark Diamond, Stephanie Miller, Patrick McGorry

Abstract

Mental illness is prevalent across the globe and affects multiple aspects of life. Despite advances in treatment, there is little evidence that prevalence rates of mental illness are falling. While the prevention of cardiovascular disease and cancers are common in the policy dialogue and in service delivery, the prevention of mental illness remains a neglected area. There is accumulating evidence that mental illness is at least partially preventable, with increasing recognition that its antecedents are often found in infancy, childhood, adolescence and youth, creating multiple opportunities into young adulthood for prevention. Developing valid and reproducible methods for translating the evidence base in mental illness prevention into actionable policy recommendations is a crucial step in taking the prevention agenda forward. Building on an aetiological model of adult mental illness that emphasizes the importance of intervening during infancy, childhood, adolescence and youth, we adapted a workforce and service planning framework, originally applied to diabetes care, to the analysis of the workforce and service structures required for best-practice prevention of mental illness. The resulting framework consists of 6 steps that include identifying priority risk factors, profiling the population in terms of these risk factors to identify at-risk groups, matching these at-risk groups to best-practice interventions, translation of these interventions to competencies, translation of competencies to workforce and service estimates, and finally, exploring the policy implications of these workforce and services estimates. The framework outlines the specific tasks involved in translating the evidence-base in prevention, to clearly actionable workforce, service delivery and funding recommendations. The framework describes the means to deliver mental illness prevention that the literature indicates is achievable, and is the basis of an ongoing project to model the workforce and service structures required for mental illness prevention.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 97 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%
Unknown 95 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 21%
Student > Master 19 20%
Student > Bachelor 11 11%
Student > Doctoral Student 9 9%
Other 5 5%
Other 18 19%
Unknown 15 15%
Readers by discipline Count As %
Psychology 24 25%
Medicine and Dentistry 18 19%
Nursing and Health Professions 15 15%
Social Sciences 9 9%
Agricultural and Biological Sciences 5 5%
Other 11 11%
Unknown 15 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 24 October 2020.
All research outputs
#9,154,085
of 16,649,729 outputs
Outputs from BMC Health Services Research
#3,392
of 5,737 outputs
Outputs of similar age
#100,355
of 242,297 outputs
Outputs of similar age from BMC Health Services Research
#1
of 1 outputs
Altmetric has tracked 16,649,729 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,737 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one is in the 40th percentile – i.e., 40% of its peers scored the same or lower than it.
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 242,297 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them