Measuring Adolescent Attitudes Towards Abortion
Abstract
Background
Measurement scales seeking to quantify latent traits like attitudes, are often developed using traditional psychometric approaches. Application of the Rasch unidimensional measurement model may complement or replace these techniques, as the model can be used to construct scales and check their psychometric properties. If data fit the model, then a scale with invariant measurement properties, including interval-level scores, will have been developed. Aims This paper highlights the unique properties of the Rasch model. Items developed to measure adolescent attitudes towards abortion are used to exemplify the process.
Method
Ten attitude and intention items relating to abortion were answered by 406 adolescents aged 12 to 19 years, as part of the “Teen Relationships Study”. The sampling framework captured a range of sexual and pregnancy experiences. Items were assessed for fit to the Rasch model including checks for Differential Item Functioning (DIF) by gender, sexual experience or pregnancy experience.
Results
Rasch analysis of the original dataset initially demonstrated that some items did not fit the model. Rescoring of one item (B5) and removal of another (L31) resulted in fit, as shown by a non-significant item-trait interaction total chi-square and a mean log residual fit statistic for items of -0.05 (SD=1.43). No DIF existed for the revised scale. However, items did not distinguish as well amongst persons with the most intense attitudes as they did for other persons. A person separation index of 0.82 indicated good reliability.
Conclusion
Application of the Rasch model produced a valid and reliable scale measuring adolescent attitudes towards abortion, with stable measurement properties. The Rasch process provided an extensive range of diagnostic information concerning item and person fit, enabling changes to be made to scale items. This example shows the value of the Rasch model in developing scales for both social science and health disciplines.