| Abstract: | Most research investigating the effects of physical child abuse on children's development has been based on uncontrolled or poorly controlled studies having small samples, no long-term follow-up, and weak instrumentation. These studies, as well as some which have been more carefully designed, have generally suggested seriously detrimental developmental consequences in physical, intellectual, behavioral, and emotional areas. Some recent controlled follow-up studies challenge such a negative picture of abuse. In particular, a study by Elmer, which is probably the most carefully conducted study yet done, found that the harmful effects of abuse dissipated years after the abusive incident and that socioeconomic status (SES) and related factors may be more important than abuse in determining the course of child development. To improve the quality and clarity of future research on developmental effects of child abuse, this paper discusses, in four major areas, problems which plague the research. Definition: The extent, type, and frequency of abuse should be more carefully defined to allow studies to be compared. The types and amounts of social service interventions should also be specified. Generalization: Research should include more middle and upper SES children, more of the mildly and moderately abused, and more neglected children to allow generalization to the total population of maltreated children. Causality: Since developmental deficits may be the cause as well as the effects of abuse and because outside factors such as SES may lead to both the abuse and the deficits, there is a need for large-scale longitudinal studies which can untangle the cause and effect web of abuse by following children from birth and measuring many factors which might affect development (e.g., SES, birth abnormalities, abuse). Statistical Analysis: Future studies should always use statistical analysis and should obtain larger samples and utilize outcome and classification measures with demonstrated reliability and validity to increase statistical power. |
