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Serious juvenile offenders: classification into subgroups based on static and dynamic charateristics

Overview of attention for article published in Child and Adolescent Psychiatry and Mental Health, December 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

Mentioned by

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10 tweeters

Citations

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21 Dimensions

Readers on

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84 Mendeley
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Title
Serious juvenile offenders: classification into subgroups based on static and dynamic charateristics
Published in
Child and Adolescent Psychiatry and Mental Health, December 2017
DOI 10.1186/s13034-017-0201-4
Pubmed ID
Authors

Sanne L. Hillege, Eddy F. J. M. Brand, Eva A. Mulder, Robert R. J. M. Vermeiren, Lieke van Domburgh

Abstract

The population in juvenile justice institutions is heterogeneous, as juveniles display a large variety of individual, psychological and social problems. This variety of risk factors and personal characteristics complicates treatment planning. Insight into subgroups and specific profiles of problems in serious juvenile offenders is helpful in identifying important treatment indicators for each subgroup of serious juvenile offenders. To identify subgroups with combined offender characteristics, cluster-analyses were performed on data of 2010 adolescents from all juvenile justice institutions in the Netherlands. The study included a wide spectrum of static and dynamic offender characteristics and was a replication of a previous study, in order to replicate and validate the identified subgroups. To identify the subgroups that are most useful in clinical practice, different numbers of subgroup-solutions were presented to clinicians. Combining both good statistical fit and clinical relevance resulted in seven subgroups. Most subgroups resemble the subgroups found in the previous study and one extra subgroups was identified. Subgroups were named after their own identifying characteristics: (1) sexual problems, (2) antisocial identity and mental health problems, (3) lack of empathy and conscience, (4) flat profile, (5) family problems, (6) substance use problems, and (7) sexual, cognitive and social problems. Subgroups of offenders as identified seem rather stable. Therefore risk factor scores can help to identify characteristics of serious juvenile offenders, which can be used in clinical practice to adjust treatment to the specific risk and needs of each subgroup.

Twitter Demographics

The data shown below were collected from the profiles of 10 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 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 84 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 13 15%
Student > Master 9 11%
Student > Doctoral Student 9 11%
Researcher 8 10%
Student > Postgraduate 6 7%
Other 11 13%
Unknown 28 33%
Readers by discipline Count As %
Psychology 31 37%
Social Sciences 7 8%
Medicine and Dentistry 7 8%
Nursing and Health Professions 2 2%
Arts and Humanities 1 1%
Other 4 5%
Unknown 32 38%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 February 2018.
All research outputs
#2,996,734
of 15,922,193 outputs
Outputs from Child and Adolescent Psychiatry and Mental Health
#153
of 484 outputs
Outputs of similar age
#97,780
of 409,038 outputs
Outputs of similar age from Child and Adolescent Psychiatry and Mental Health
#15
of 47 outputs
Altmetric has tracked 15,922,193 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 484 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.5. This one has gotten more attention than average, scoring higher than 68% 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 409,038 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 76% of its contemporaries.
We're also able to compare this research output to 47 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 68% of its contemporaries.