STRUCTURED INTERVIEW FOR ASSESSING CHILD SEXUAL ABUSE

DESCRIPTION (adapted from applicant's abstract): The present research describes the development of a protocol for the assessment of the occurrence of child sexual abuse that is designed to facilitate the evaluation of its psychometric properties by using a hypothesis testing model and a structured format of administration. The Sexual Abuse Structured Interview for Children (SASIC) aims to provide the field with an efficient, practical, empirically sound assessment device. The proposed research is a feasibility study and will accomplish the evaluation of the SASIC by experts in child information processing, child structured interviewing, legal utility, minority appropriateness, and appropriateness for child sexual abuse. The second goal is to demonstrate that the SASIC can be functionally administered by trained interviewers. This will be accomplished by training SASIC interviewers and evaluating their format adherence during a subsequent SASIC administration. According to the applicant, after these studies have been completed, the SASIC will be content valid, administrable and free from the effects of leading or suggestive questioning (a claim made possible by the structured format). Phase II studies will further investigate the SASIC's reliability and validity in non-analog settings, as well as increase its ethnic diversity (e.g., create a Spanish language version). $ = TOTAL AWARD AMTS & NOT LIMITED TO PORTION OF PROJECT RELATED TO SUBJECT OF SEARCH SUBPROJECT $ = TOTAL AWARD AMOUNT DIVIDED BY NUMBER OF SUBPROJECTS SOURCE: CRISP FORMAT F FY 97 LAST UPDATE 04-07-98 1QUERY 1536 ID SEARCH 06/01/98 PAGE 475 --PROJECT NUMBER......1 R43 MH57200-01 INVESTIGATOR NAME/ADDRESS FY 97 ETTINGER, GIL J IRG/INTRAMURAL UNIT..MHSB ALPHATECH, INC AWARD AMOUNT......... $99,752 50 MALL ROAD BURLINGTON, MA 01803-4562 PERFORMING ORGANIZATION: ALPHATECH, INC. TITLE QUANTITATIVE 3D IMAGE AIDED ANATOMIC CHANGE DETECTION ABSTRACT: This research develops quantitative image analysis software tools for detecting and precisely measuring anatomic changes in sequences of 3D medical image data, such as MRI or CT scans taken over time. Accurate structural change detection and identification will improve several medical applications, such as the experimental evaluation of drugs and treatments, precise monitoring of disease progression, and early disease diagnosis. The key objective of this research is to demonstrate that practical automated registration tools can be developed for handling the problems encountered in medical change detection applications: structures of complex 3D shape, tissue deformation, varying image resolution, and sensor distortion. This Phase I research program proposes to demonstrate the feasibility of automated image registration tools for detecting anatomic changes by: l) establishing bounds on attainable performance of the image-based anatomic change detection technique as a function of sensor resolution and other image acquisition parameters; 2) assessing the performance of our approach through extensive experimentation with phantom models and controlled imagery; and 3) identifying impact on specific applications. Following a successful validation study in Phase I, a proposed Phase II effort will continue with animal studies and increased interaction with clinicians to refine the change detection capabilities.