A Multiple Indicators Multiple Causes (MIMIC) model of internal barriers to drug treatment in China

Developing and validating a measurement tool to self-report perceived barriers in substance use treatment: the substance use treatment barriers questionnaire (SUTBQ)

BACKGROUND

Substance using often cause a wide range of social, health, and psychological problems. This study aimed to develop and validate a questionnaire of barriers of treatment in substance users.

METHODS

In this cross-sectional study, the initial questionnaire was designed based on the evaluation of previous studies. The preliminary tool including 35 Likert-scaled items. After assuring the face validity of the questionnaire, 13 experts' opinions were obtained for assessing or improving the content validity. The reliability was investigated by internal consistency methods using Cronbach's alpha. For measuring the structural validity, the exploratory factor analysis was performed to determine the dimensionality of the questionnaire using principal components extraction and Varimax rotation.

RESULTS

The preliminary questionnaire consisted of 35 items. After completing the face validity and summarizing the experts' suggestions, 8 items were removed. By calculating the content validity ratio and coefficient, 11 questions were deleted. The internal consistency was calculated to be 0.84 using Cronbach's alpha. In the last stage and according to the results of the factor analysis, three factors fear of or unawareness of treatment, doubt or inefficiency, and social stigma were identified from the 10-items questionnaire, which explained 67.34% of the total variance.

CONCLUSION

Considering the necessity of using a validated tool for planning and evaluating effective interventions on people who use substance is inevitable. The Substance use Treatment Barriers Questionnaire is designed with 10 items and 3 dimensions, which has appropriate validity and reliability and can be used to determine the obstacles for treatment or factors that lead to discontinuing treatment.

The Effect of Small Sample Size on Measurement Equivalence of Psychometric Questionnaires in MIMIC Model: A Simulation Study

Evaluating measurement equivalence (also known as differential item functioning (DIF)) is an important part of the process of validating psychometric questionnaires. This study aimed at evaluating the multiple indicators multiple causes (MIMIC) model for DIF detection when latent construct distribution is nonnormal and the focal group sample size is small. In this simulation-based study, Type I error rates and power of MIMIC model for detecting uniform-DIF were investigated under different combinations of reference to focal group sample size ratio, magnitude of the uniform-DIF effect, scale length, the number of response categories, and latent trait distribution. Moderate and high skewness in the latent trait distribution led to a decrease of 0.33% and 0.47% power of MIMIC model for detecting uniform-DIF, respectively. The findings indicated that, by increasing the scale length, the number of response categories and magnitude DIF improved the power of MIMIC model, by 3.47%, 4.83%, and 20.35%, respectively; it also decreased Type I error of MIMIC approach by 2.81%, 5.66%, and 0.04%, respectively. This study revealed that power of MIMIC model was at an acceptable level when latent trait distributions were skewed. However, empirical Type I error rate was slightly greater than nominal significance level. Consequently, the MIMIC was recommended for detection of uniform-DIF when latent construct distribution is nonnormal and the focal group sample size is small.