JMIR Publications

ABSTRACT

Background:

Public health surveillance systems should be evaluated periodically, and the evaluation should include recommendations for improving the system’s quality and efficiency. Each surveillance system could have its unique situation in which evaluating data quality depends on its methodology, aims, and other factors, such as the frequency of repeating the survey in case of survey-based surveillance.

Objective:

The aim of this article is to evaluate the Saudi Arabia Mental Health Surveillance System MHSS data quality via a scientific hypothesis testing process that follows the EPA Guidance for Data Quality Assessment.

Methods:

Assessing the data quality of the MHSS via examining (1) the consistency of the main demographical variables and (2) the changes between the two mental health screening tools used in the MHSS and between the three waves collected in three consecutive months. The assessment uses all data collected via the MHSS between May 2020 and July 2020. The first null hypothesis predicted there were differences between the same distributions of the demographical variables between the three waves. The second predicted there were no difference between the scores of the Patient Health Questionnaire 9 (PHQ-9) and the Generalized Anxiety Disorders 7 (GAD-7) between the three waves.

Results:

In terms of sampling variables (age, gender, and region), there were no significant differences between the three waves in age using one-way ANOVA nor in gender and region using the chi-square test. In addition, there were no significant differences between the three waves in all other demographical variables, except in the income variable. However, in terms of the PHQ-9 score, the one-way ANOVA (F (2, 12334) = 8.05, p < 0.01) showed significant differences between waves. Similarly, significant differences between waves were found in the GAD-7 score one-way ANOVA (F (2, 12334) = 7.09, p < 0.01).

Conclusions:

The MHSS seems to provide high-quality data based on a consistent demographical distribution of the sample, while being sensitive to the changes of mental health scores across waves.