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A Social-Ecological Framework of Theory, Assessment, and Prevention of Suicide

Overview of attention for article published in Frontiers in Psychology, October 2017
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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 (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
36 X users
googleplus
1 Google+ user

Citations

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174 Dimensions

Readers on

mendeley
280 Mendeley
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Title
A Social-Ecological Framework of Theory, Assessment, and Prevention of Suicide
Published in
Frontiers in Psychology, October 2017
DOI 10.3389/fpsyg.2017.01756
Pubmed ID
Authors

Robert J. Cramer, Nestor D. Kapusta

Abstract

The juxtaposition of increasing suicide rates with continued calls for suicide prevention efforts begs for new approaches. Grounded in the Centers for Disease Control and Prevention (CDC) framework for tackling health issues, this personal views work integrates relevant suicide risk/protective factor, assessment, and intervention/prevention literatures. Based on these components of suicide risk, we articulate a Social-Ecological Suicide Prevention Model (SESPM) which provides an integration of general and population-specific risk and protective factors. We also use this multi-level perspective to provide a structured approach to understanding current theories and intervention/prevention efforts concerning suicide. Following similar multi-level prevention efforts in interpersonal violence and Human Immunodeficiency Virus (HIV) domains, we offer recommendations for social-ecologically informed suicide prevention theory, training, research, assessment, and intervention programming. Although the SESPM calls for further empirical testing, it provides a suitable backdrop for tailoring of current prevention and intervention programs to population-specific needs. Moreover, the multi-level model shows promise to move suicide risk assessment forward (e.g., development of multi-level suicide risk algorithms or structured professional judgments instruments) to overcome current limitations in the field. Finally, we articulate a set of characteristics of social-ecologically based suicide prevention programs. These include the need to address risk and protective factors with the strongest degree of empirical support at each multi-level layer, incorporate a comprehensive program evaluation strategy, and use a variety of prevention techniques across levels of prevention.

X Demographics

X Demographics

The data shown below were collected from the profiles of 36 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 280 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 280 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 40 14%
Student > Ph. D. Student 35 13%
Researcher 29 10%
Student > Doctoral Student 28 10%
Student > Bachelor 24 9%
Other 36 13%
Unknown 88 31%
Readers by discipline Count As %
Psychology 55 20%
Social Sciences 37 13%
Medicine and Dentistry 34 12%
Nursing and Health Professions 20 7%
Business, Management and Accounting 5 2%
Other 28 10%
Unknown 101 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 40. 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 August 2023.
All research outputs
#1,033,600
of 25,466,764 outputs
Outputs from Frontiers in Psychology
#2,155
of 34,531 outputs
Outputs of similar age
#21,308
of 333,940 outputs
Outputs of similar age from Frontiers in Psychology
#60
of 600 outputs
Altmetric has tracked 25,466,764 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 34,531 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.3. 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 333,940 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 93% of its contemporaries.
We're also able to compare this research output to 600 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 90% of its contemporaries.