Predicting actual weight from self-report data

Meni Koslowsky, Zvi Scheinberg, Avi Bleich, Mordechai Mark, Alan Apter, Yehuda Danon, Zahava Solomon

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Due to reasons of economy of time and ease of data collection, researchers increasingly use self-report weight as a substitute for measured or actual weight. Little research has been done on the inclusion of attitudinal scales and other self-report data in improving prediction of actual weight. The present study examined self-report data as well as actual weight for a sample of 946 young women inductees to the Israel Defense Forces. The results showed that self-reported weight is the best predictor of actual weight, but indicators such as the Eating Attitudes Scale (EAT), body image, and ideal weight are significant predictors also. In addition, the correlation between actual weight and difference weight (reported weight-actual weight) was negative (-.37) indicating that the heavier people tend to underreport their weight.

Original languageEnglish
Pages (from-to)168-173
Number of pages6
JournalEducational and Psychological Measurement
Volume54
Issue number1
DOIs
StatePublished - Mar 1994
Externally publishedYes

Fingerprint

Dive into the research topics of 'Predicting actual weight from self-report data'. Together they form a unique fingerprint.

Cite this