Epidemiology of illicit drug use disorders in Iran: prevalence, correlates, comorbidity and service utilization results from the Iranian Mental Health Survey

Addiction ◽  
2016 ◽  
Vol 111 (10) ◽  
pp. 1836-1847 ◽  
Author(s):  
Masoumeh Amin-Esmaeili ◽  
Afarin Rahimi-Movaghar ◽  
Vandad Sharifi ◽  
Ahmad Hajebi ◽  
Reza Radgoodarzi ◽  
...  
Keyword(s):  
Mental Health ◽  
Drug Use ◽  
Service Utilization ◽  
Health Survey ◽  
Illicit Drug ◽  
Illicit Drug Use ◽  
Drug Use Disorders ◽  
Mental Health Survey

An ad hoc method for dual adjusting for measurement errors and nonresponse bias for estimating prevalence in survey data: Application to Iranian mental health survey on any illicit drug use

2017 ◽  
Vol 27 (10) ◽  
pp. 3062-3076 ◽  
Author(s):  
Kazem Khalagi ◽  
Mohammad Ali Mansournia ◽  
Seyed-Abbas Motevalian ◽  
Keramat Nourijelyani ◽  
Afarin Rahimi-Movaghar ◽  
...  
Keyword(s):  
Mental Health ◽  
Drug Use ◽  
Measurement Errors ◽  
Latent Class ◽  
Illicit Drug ◽  
Illicit Drug Use ◽  
Nonresponse Bias ◽  
Missing Not At Random ◽  
Mental Health Survey ◽  
Log Linear

Purpose The prevalence estimates of binary variables in sample surveys are often subject to two systematic errors: measurement error and nonresponse bias. A multiple-bias analysis is essential to adjust for both biases. Methods In this paper, we linked the latent class log-linear and proxy pattern-mixture models to adjust jointly for measurement errors and nonresponse bias with missing not at random mechanism. These methods were employed to estimate the prevalence of any illicit drug use based on Iranian Mental Health Survey data. Results After jointly adjusting for measurement errors and nonresponse bias in this data, the prevalence (95% confidence interval) estimate of any illicit drug use changed from 3.41 (3.00, 3.81)% to 27.03 (9.02, 38.76)%, 27.42 (9.04, 38.91)%, and 27.18 (9.03, 38.82)% under “missing at random,” “missing not at random,” and an intermediate mode, respectively. Conclusions Under certain assumptions, a combination of the latent class log-linear and binary-outcome proxy pattern-mixture models can be used to jointly adjust for both measurement errors and nonresponse bias in the prevalence estimation of binary variables in surveys.

scholarly journals Assessing measurement error in surveys using latent class analysis: application to self-reported illicit drug use in data from the Iranian Mental Health Survey

2016 ◽  
Vol 38 ◽  
pp. e2016013
Author(s):  
Kazem Khalagi ◽  
Mohammad Ali Mansournia ◽  
Afarin Rahimi-Movaghar ◽  
Keramat Nourijelyani ◽  
Masoumeh Amin-Esmaeili ◽  
...  
Keyword(s):  
Mental Health ◽  
Measurement Error ◽  
Drug Use ◽  
Latent Class Analysis ◽  
Health Survey ◽  
Latent Class ◽  
Illicit Drug ◽  
Class Analysis ◽  
Analysis Application ◽  
Mental Health Survey

Epidemiology of Illicit Drug Use Disorders

2011 ◽  
pp. 381-399
Author(s):  
Wilson M. Compton ◽  
Marsha F. Lopez ◽  
Kevin P. Conway ◽  
Yonette F. Thomas
Keyword(s):  
Drug Use ◽  
Illicit Drug ◽  
Illicit Drug Use ◽  
Drug Use Disorders

scholarly journals Cannabis use, subsequent other illicit drug use and drug use disorders: A 16-year follow-up study among Swedish adults

2020 ◽  
Vol 106 ◽  
pp. 106390 ◽  
Author(s):  
Rynaz Rabiee ◽  
Andreas Lundin ◽  
Emilie Agardh ◽  
Yvonne Forsell ◽  
Peter Allebeck ◽  
...  
Keyword(s):  
Drug Use ◽  
Illicit Drug ◽  
Illicit Drug Use ◽  
Cannabis Use ◽  
Follow Up Study ◽  
Drug Use Disorders

Prevalence and socio-demographic correlates of drug use among adolescents: results from the Mexican Adolescent Mental Health Survey

Addiction ◽  
2007 ◽  
Vol 102 (8) ◽  
pp. 1261-1268 ◽  
Author(s):  
Corina Benjet ◽  
Guilherme Borges ◽  
Maria Elena Medina-Mora ◽  
Clara Fleiz ◽  
Jeronimo Blanco ◽  
...  
Keyword(s):  
Mental Health ◽  
Drug Use ◽  
Health Survey ◽  
Adolescent Mental Health ◽  
Demographic Correlates ◽  
Mental Health Survey
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