By Jacquelyn C. Campbell
This up to date variation of the vintage e-book on threat evaluate provides the most recent study concerning the prediction of interpersonal violence. In transparent and available language, the authors tackle the categorical variables focused on the prediction of kid abuse and murder, in addition to intimate accomplice violence and murder. This version additionally provides a tremendous revision of Campbell's ground-breaking intimate associate murder lethality chance software, the Danger Assessment.
All of the participants to this multidisciplinary quantity have confronted the tough job of assessing the chance of family members violence in a large choice of settings--courts, clinics, shelters, emergency rooms, protecting carrier places of work, colleges, batterer intervention courses, violence prevention courses, and extra. Their mixed event in study and perform makes this an integral source for all clinicians required to make predictions approximately violent behavior.
- Key good points of this re-creation include:
- Coverage of a large breadth of medical and courtroom events requiring probability assessments
- A evaluation of the most recent review instruments
- New findings on predicting deadly baby abuse
- Legal and moral matters in hazard assessment
Read or Download Assessing Dangerousness: Violence by Batterers and Child Abusers, 2nd Edition PDF
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Additional resources for Assessing Dangerousness: Violence by Batterers and Child Abusers, 2nd Edition
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Construct Validity Overlapping somewhat with content validity, construct validity refers to the extent to which the underlying constructs assumed to be measured by the test actually are measured. Construct data provide veriﬁcation of what initially was theoretically or intuitively assumed during the test item construction. Construct validity is supported by the accumulation of data that verify that the characteristics the instrument was designed to measure are indeed measured. In addition, development of a large array of different types of construct validity data provides a mosaic of information that allows the test user to understand what the instrument is measuring.