Restraint, weight suppression, and self-report reliability: how much do you really weigh?

P J Morgan1, D B Jeffrey

  • 1Department of Psychology, The University of Montana, Missoula 59812-1041, USA.

Addictive Behaviors
|November 26, 1999
PubMed

Insights

Weight suppression did not significantly affect eating behaviors in restrained female eaters during an ice cream taste test. This suggests restraint is not uniform and questions self-report weight suppression measures.

Area of Science:

  • Psychology
  • Behavioral Science
  • Nutrition Science

Background:

  • Weight suppression, the difference between a person's lowest adult weight and current weight, is thought to influence eating behaviors.
  • Restrained eaters, individuals who consciously restrict their food intake, may be particularly susceptible to weight suppression effects.
  • Previous research suggests a link between weight suppression and altered eating patterns, but findings are not always consistent.

Purpose of the Study:

  • To investigate the impact of weight suppression on the eating behaviors of female restrained eaters.
  • To examine whether a milkshake preload moderates the relationship between weight suppression and subsequent food consumption.
  • To explore the homogeneity of dietary restraint as a construct.

Main Methods:

  • A taste-test paradigm using ice cream was employed with 58 female restrained eaters.
  • Participants were categorized as high or low weight suppressors based on self-report.
  • A 2x2 between-subjects design included a milkshake preload or no preload condition.

Main Results:

  • No significant differences in ice cream consumption were found between high and low weight suppressors.
  • The preload condition did not significantly alter ice cream intake in either weight suppression group.
  • These findings contrast with prior studies showing preload effects in restrained eaters.

Conclusions:

  • Dietary restraint may not be a monolithic construct, as weight suppression did not predictably influence eating behavior in this sample.
  • The study questions the reliability of self-report measures for accurately assessing an individual's degree of weight suppression.
  • Further research is needed to clarify the complex interplay between weight suppression, dietary restraint, and eating behaviors.

Related Concept Videos

Regression Toward the Mean01:52

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...
Self-Discrepancy Theory02:45

Self-Discrepancy Theory

One influential perspective on what motivates people's behavior is detailed in Tory Higgin's self-discrepancy theory (Higgins, 1987). He proposed that people hold disagreeing internal representations of themselves that lead to different emotional states.
Self-Presentation: Self-Monitoring and Self-Handicapping02:05

Self-Presentation: Self-Monitoring and Self-Handicapping

People can go to great lengths to protect their self-image and present themselves in ways that they want others to see them. Sociologist Erving Goffman presented the idea that a person is like an actor on a stage. Calling his theory dramaturgy, Goffman believed that we use “impression management” to present ourselves to others as we hope to be perceived. Each situation is a new scene, and individuals perform different roles depending on who is present (Goffman, 1959). Think about the way you...
Weighted Mean00:57

Weighted Mean

While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...