OBJECTIVEInjury is a major cause of morbidity and mortality in the world. The assessment of patterns and severity of injury in high-risk groups is crucial for planning and service development. On a large scale national household survey, we estimated the annual incidence and the patterns of injury, the demographics of the injured people, as well as the service use for all injuries in Iran. The current study aims at assessing the reliability of the questionnaire before carrying out a national survey.

METHODSIn a pilot study using cluster random sampling approach, 73 people were interviewed. The interviewers asked the participants to report all injuries occurred in them and the care provided during the previous 12 months, based on "Short Form Injury Questionnaire 7" About two weeks later, the interview was repeated by another interviewer.

RESULTSIn our test-retest reliability, Kappa score was good for three and moderate for four questions. The question on the injured organ had the highest test-retest reliability with a Kappa score of 0.84.

CONCLUSIONSThe reliability of the questionnaire and the procedure of questioning are confirmed. The ques-tionnire is proper for utilization in large national surveies.

Humans ; Incidence ; Iran ; epidemiology ; Pilot Projects ; Reproducibility of Results ; Surveys and Questionnaires

Latent class analysis (LCA) is a method of assessing and correcting measurement error in surveys. The local independence assumption in LCA assumes that indicators are independent from each other condition on the latent variable. Violation of this assumption leads to unreliable results. We explored this issue by using LCA to estimate the prevalence of illicit drug use in the Iranian Mental Health Survey. The following three indicators were included in the LCA models: five or more instances of using any illicit drug in the past 12 months (indicator A), any use of any illicit drug in the past 12 months (indicator B), and the self-perceived need of treatment services or having received treatment for a substance use disorder in the past 12 months (indicator C). Gender was also used in all LCA models as a grouping variable. One LCA model using indicators A and B, as well as 10 different LCA models using indicators A, B, and C, were fitted to the data. The three models that had the best fit to the data included the following correlations between indicators: (AC and AB), (AC), and (AC, BC, and AB). The estimated prevalence of illicit drug use based on these three models was 28.9%, 6.2% and 42.2%, respectively. None of these models completely controlled for violation of the local independence assumption. In order to perform unbiased estimations using the LCA approach, the factors violating the local independence assumption (behaviorally correlated error, bivocality, and latent heterogeneity) should be completely taken into account in all models using well-known methods.
Bias (Epidemiology) ; Mental Health* ; Methods ; Prevalence ; Self Report ; Substance-Related Disorders ; Surveys and Questionnaires