Predicting attitudes related to stuttering from an international database

Abstract

Purpose

A vast number of studies over the past 50 years have explored public and professional attitudes toward stuttering, and many of them have identified variables that predict more—or less—positive attitudes. Part I of this study summarized 91 studies in terms of consistency of prediction of stuttering attitudes. Part II sought to compare a considerable number of potential predictors and to quantify their prediction strengths.

Method

Thirty-seven predictors were analyzed in linear regression models using a retrospective analysis of a database consisting of 22,413 respondents from 44 countries who had filled out the Public Opinion Survey of Human Attributes–Stuttering (POSHA–S) in 26 different languages. Dependent variables were two POSHA–S subscores, Beliefs about stuttering and Self Reactions to people who stutter, as well as the mean of these two subscores, the Overall Stuttering Score.

Results

All 37 predictors were statistically significant for most—but at least one—of the three scores. The strongest predictors related to regions of the world and related variables of countries and languages, with greater strength for Beliefs than for Self Reactions. Knowing persons who stutter, or knowing about stuttering, were moderate predictors of Self Reactions but weak predictors of Beliefs. Different populations, such as the public, students, or speech-language pathologists, moderately predicted attitudes on all three dependent variables while education level and self-ratings of ability to speak were weak predictors. Sex (gender), age, income, parental or marital status, and most of 12 life priorities (e.g., get things done; be safe and secure) had very weak and practically insignificant predictive potential.

Conclusions

The study confirmed previous research showing ambiguous results for such predictors as sex and age but consistent differences from various geographic regions. Beliefs and Self Reactions measure different constructs that are often predicted differently by variables.