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Child Abuse Negl ; 29(11): 1281-96, 2005 Nov.
Article in English | MEDLINE | ID: mdl-16263167

ABSTRACT

OBJECTIVE: According to mandatory reporting laws for professionals, the relationship between initial recognition that a child may have been abused and the subsequent reporting of that suspected case of child abuse to the responsible agency would, at first glance, appear to be clear. However, this relationship has developed into one of the major social policy controversies of the recent past. Our major goal is to present research findings that address this social policy debate concerning the problems of underreporting and overreporting, focusing specifically on teachers. METHOD: A factorial survey design, that combines the advantages of the factorial experiment with those of surveys, was employed in a probability sample of teachers (N=480) who responded to vignettes in which case characteristics were systematically manipulated. Teachers responded with judgments about whether the vignette was child abuse and the likelihood that they would report this suspected case. Characteristics of the teachers and their work setting (school) were also measured. RESULTS: When comparing the teachers' recognition and reporting scores, we found that they gave the same score for 63% of the vignettes they judged, gave higher reporting than recognition scores (overreporting) for 4% of the vignettes, and gave higher recognition than reporting scores (underreporting) for 33% of the vignettes. Discrepancies between recognition and reporting (over and under reporting) were related to characteristics of the case, teacher, and school where the teacher was employed. CONCLUSIONS: Teachers in our Ohio sample evidence the use of professional discretion in making judgments about the recognition and reporting of child abuse and do not appear to make these judgments with equal certainty. Their use of discretion is more likely to result in underreporting than overreporting.


Subject(s)
Child Abuse/diagnosis , Faculty , Mandatory Reporting , Adult , Aged , Child , Data Collection , Female , Humans , Male , Middle Aged , Ohio
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