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Detection of unsafety in families with parental and/or child developmental problems at the start of family support

Overview of attention for article published in BMC Psychiatry, January 2016
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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 (81st percentile)

Mentioned by

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2 policy sources
twitter
1 tweeter
facebook
2 Facebook pages

Citations

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5 Dimensions

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68 Mendeley
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Title
Detection of unsafety in families with parental and/or child developmental problems at the start of family support
Published in
BMC Psychiatry, January 2016
DOI 10.1186/s12888-016-0715-y
Pubmed ID
Authors

Claudia E. van der Put, Jo Hermanns, Loes van Rijn-van Gelderen, Frouke Sondeijker

Abstract

Risk assessment is crucial in preventing child maltreatment as it can identify high-risk cases in need of child protection intervention. Despite this importance, there have been no validated risk assessment instruments available in the Netherlands for assessing the risk of child maltreatment. Therefore, the predictive validity of the California Family Risk Assessment (CFRA) was examined in Dutch families who received family support. In addition, the added value of a number of experimental items was examined. Finally, it was examined whether the predictive value of the instrument could be improved by modifying the scoring procedure. Dutch families who experienced parenting and/or child developmental problems and were referred by the Centres for Youth and Family for family support between July 2009 and March 2011 were included. This led to a sample of 491 families. The predictive validity of the CFRA and the added value of the experimental items were examined by calculating AUC values. A CHAID analysis was performed to examine whether the scoring procedure could be improved. About half of the individual CFRA items were not related to future reports of child maltreatment. The predictive validity of the CFRA in predicting future reports of child maltreatment was found to be modest (AUC = .693). The addition of some of the experimental items and the modification of the scoring procedure by including only items that were significantly associated with future maltreatment reports resulted in a 'high' predictive validity (AUC = .795). This new set of items might be a valuable instrument that also saves time because only variables that uniquely contribute to the prediction of future reports of child maltreatment are included. Furthermore, items that are perceived as difficult to assess by professionals, such as parental mental health problems or parents' history of abuse/neglect, could be omitted without compromising predictive validity. However, it is important to examine the psychometric properties of this new set of items in a new dataset.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 68 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 22%
Student > Bachelor 9 13%
Student > Ph. D. Student 6 9%
Student > Doctoral Student 6 9%
Student > Master 5 7%
Other 12 18%
Unknown 15 22%
Readers by discipline Count As %
Psychology 22 32%
Medicine and Dentistry 8 12%
Social Sciences 8 12%
Nursing and Health Professions 4 6%
Arts and Humanities 1 1%
Other 6 9%
Unknown 19 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 13 January 2020.
All research outputs
#2,977,983
of 17,358,590 outputs
Outputs from BMC Psychiatry
#1,183
of 3,751 outputs
Outputs of similar age
#62,619
of 347,809 outputs
Outputs of similar age from BMC Psychiatry
#1
of 1 outputs
Altmetric has tracked 17,358,590 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,751 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. 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 347,809 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 81% 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