You are here

Article Text

Article menu

Download PDFPDF

XML
Mental health
Original research
Risks of psychosis in methamphetamine users: cross-sectional study in Thailand
  1. Warot Lamyai1,
  2. Kitkawee Pono1,
  3. Danai Indrakamhaeng2,
  4. Apichat Saengsin3,
  5. Nartya Songhong4,
  6. Panu Khuwuthyakorn5,
  7. Pongruk Sribanditmongkol6,
  8. Anongphan Junkuy6,
  9. Manit Srisurapanont7
  1. 1 Nakhon Phanom Rajanagarindra Psychiatric Hospital, Department of Mental Health, Ministry of Public Health, Nakhon Phanom, Thailand
  2. 2 Thanyarak Chiang Mai Hospital, Department of Medical Services, Ministry of Public Health, Chiang Mai, Thailand
  3. 3 Galyarajanagarindra Institute, Department of Mental Health, Ministry of Public Health, Nakorn Prathom, Thailand
  4. 4 Songkhla Rajanagarindra Psychiatric Hospital, Department of Mental Health, Ministry of Public Health, Songkhla, Thailand
  5. 5 Suanprung Psychiatric Hospital, Department of Mental Health, Ministry of Public Health, Chiang Mai, Thailand
  6. 6 Department of Forensic Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
  7. 7 Department of Psychiatry, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
  1. Correspondence to Dr Manit Srisurapanont; manit.s{at}cmu.ac.th

Abstract

Objective To determine factors related to recent methamphetamine-associated psychosis (MAP) among individuals recently using methamphetamine (MA).

Design Cross-sectional study carried out between July 2015 and June 2017.

Setting Four mental health hospitals and one substance abuse treatment centre in Thailand.

Participants Individuals recruited onto the study included those aged 18 years or over, of both sexes, who reported MA use in the month prior to admission.

Measures Any recent psychosis was confirmed using the Mini International Neuropsychiatric Interview-Plus psychotic module. The Timeline Follow Back was used to determine days of MA use. The severity of MA dependence was assessed using the Severity of Dependence Scale. Quantitative hair analysis was carried out to confirm recent use of MA and to measure the amount of MA use. We compared several characteristics between those who had recently experienced psychosis and those who had not.

Results This study included 120 participants without MAP and 113 participants with MAP. The mean age was 28 years and the mean abstinence was 17 days. The levels of MA concentration in hair were not significantly different between groups (p=0.115). Based on the final logistic regression model, the independent factors associated with MAP (OR and 95% CI) included being male (OR 4.03, 95% CI 1.59 to 10.20), ≥16 days of MA use in the past month (OR 2.35, 95% CI 1.22 to 4.52), MA dependence (OR 9.41, 95% CI 2.01 to 44.00) and hospitalisation history related to substance abuse (OR 3.85, 95% CI 2.03 to 7.28).

Conclusions Health professionals should closely monitor the development of MAP in MA-dependent men who frequently use MA and have a history of hospitalisation for substance abuse. The measure of MA concentration levels in the hair may add no benefit for the prediction of the development of MAP.

  • schizophrenia and psychotic disorders
  • substance misuse
  • adult psychiatry
  • amphetamine
  • stimulant
  • psychotic disorder

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

http://dx.doi.org/10.1136/bmjopen-2019-032711

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    Strengths and limitations of this study

    • This study examined risks of recent methamphetamine-associated psychosis (MAP) in a clinical sample in which there was recent use of methamphetamine (MA).

    • This study used MA concentration levels in the hair to confirm recent MA use and to determine the amount of MA use.

    • This study used a structure clinical interview for diagnosis to confirm a recent diagnosis of substance-induced psychotic disorder.

    • This is a cross-sectional study.

    • Some risks of MAP were not included in the study, for example, polydrug use; history of conduct disorder, depressive and anxiety disorders; premorbid schizoid/schizotypal personality trait; family history of psychotic disorders; family history of schizophrenia; and bipolar disorder.

    Introduction

    Methamphetamine-associated psychosis (MAP) is an increasing health problem. Amphetamines are one of the most common drugs used in East and Southeast Asia. In 2016, an estimated 34.2 million people worldwide used amphetamines in the past year.1 In its class, methamphetamine (MA), a very potent amphetamine derivative, is the most frequently used substance.2 Between 21% and 46% of MA users are likely to develop psychosis at least once in a lifetime.3 Based on these estimations, MAP may currently affect millions of people around the world.

    The symptoms of MAP are similar to those of schizophrenia and are associated with serious negative consequences. Its common symptoms include auditory hallucinations, visual hallucinations, strange or unusual beliefs, persecutory delusion and negative psychotic symptoms, which cannot be distinguished from schizophrenic psychotic symptoms.4 5 These psychotic symptoms usually cause anxiety, fear, terror and decreased behavioural control. A case of severe psychosis can lead to unpredictable episodes of aggression and violence. Previous studies found that MA users with psychotic symptoms had a higher risk of violent behaviour than MA users who had no psychotic symptoms.6 Other than the more frequent use of health services and attempted suicide, MA users with MAP are more likely to have medical, employment and legal problems than those without MAP.7 The findings from long-term studies also suggest that 25%–38% of individuals with MAP may develop primary or persistent psychosis sometime in later life.8 9

    Because a subset of MA users may develop psychotic symptoms, important questions are raised about MA users who may have an increased risk of MAP. Previous studies suggest that MAP is associated with a number of MA use patterns and psychiatric comorbidities. In early Japanese studies in which most users exclusively used MA (1955–1992), the investigators found an association between frequent and long-term use of MA and MAP.10 Based on a recent review, replicated risks factors included early-age MA use, frequent and long-term use of MA, MA dependence, alcohol and other drug use, major depressive disorders and antisocial personality disorders.11 That review found no association between sociodemographic factors and MAP. In addition, some risk factors are not yet clear, for example, other drug use, psychiatric comorbidity, family history of psychiatric illness and childhood trauma.

    Despite the increasing evidence around risk factors of MAP, there are some limitations in previous studies. First, many studies were carried out using patients with a lifetime history of MA use and/or MAP. The results of these studies may be less reliable because the participants may not have been able to recall those experiences accurately. Second, some of them did not exclude individuals with primary psychotic disorders prior to MA use. Lastly, most studies did not use a valid method to confirm or measure the amount of MA use. For these reasons, we proposed to carry out a cross-sectional study to determine the risk of psychosis in Thai people who recently used MA and had recently experienced MAP. This studied population was chosen to minimise the problems of inaccurate recalls on MA use and MAP experience. We hypothesised that a number of patients’ characteristics, including the amount of MA in the hair of the users, should be used as predictors of MAP.

    Methods

    This cross-sectional study was carried out in MA users admitted to four mental health hospitals and one substance abuse treatment centre in Thailand. Suanprung Psychiatric Hospital and Thanyarak Chiang Mai Hospital are located in Northern Thailand. Nakhon Phanom Rajanagarindra Psychiatric Hospital is located in Northeastern Thailand. The Galyarajanagarindra Institute is located in Central Thailand. Songkhla Rajanagarindra Psychiatric Hospital is located in Southern Thailand. This study was carried out between July 2015 and June 2017.

    Participants

    We assessed 120 MA users with MAP and 120 MA users without MAP. Participants included those aged 18 years or over, of both sexes, with self-reported MA use at least once in the month prior to admission. The primary reasons for their hospitalisation were MAP and/or MA use disorders. The Mini International Neuropsychiatric Interview (MINI)-Plus psychotic module, was used to confirm a recent diagnosis of substance-induced psychotic disorder.12 Based on the data elicited from this module, participants who developed psychosis prior to substance use and due to a general medical condition were excluded from the study.

    Assessment

    All clinical assessments were completed in a single day. As a cross-sectional study, this study had no follow-up visit. We assessed the participants when they were less likely to harm themselves or others. Apart from sociodemographic data, we interviewed each participant to elicit the pattern and history of MA use. We assessed the severity of depression and MA withdrawal using the nine-item Patient Health Questionnaire (PHQ-9) and the Amphetamine Withdrawal Questionnaire (AWQ).13 14 The Timeline Follow Back was used to determine days of MA use.15 The severity of MA dependence, current psychotic symptoms and cognitive impairment were assessed using the Severity of Dependence Scale (SDS),16 the 18-item Brief Psychiatric Rating Scale (BPRS)17 and the Montreal Cognitive Assessment (MoCA),18 respectively. We confirmed any diagnosis of alcohol and other substance use disorders and antisocial personality disorder using the MINI alcohol use disorder, substance use disorder and antisocial personality disorder modules, respectively.12 In addition, the MINI suicidality module was also used to assess the level of suicidal tendency.

    Hair was collected from each participant during hospitalisation. Scalp hair was cut close to the scalp from the vertex posterior region, with root ends marked, and was kept in a clean plastic bag. The bag was then sealed with aluminium foil paper and shipped to the Department of Forensic Medicine, Chiang Mai University, for quantitative hair analysis. The analysis for hair MA levels followed a previously published protocol involving solid-phase microextraction in line with gas chromatography/mass spectrometry.19 Derivatising reagents for hair analysis were heptafluorobutyric chloride (98% purity) and heptafluorobutyric anhydride (99% purity). Both reagents were purchased from Sigma-Aldrich (St. Louis, MO, USA). The limit of detection and the limit of quantitation for the present analysis were 0.10 and 0.15 ng/mg of hair, respectively.

    MA concentration levels in the hair was the primary outcome measure. Other measures were considered as the secondary outcomes.

    Statistical analyses

    Our sample size calculation was based on the number of events per variable (NEV) in logistic regression analysis. We hypothesised that a maximum of 10 variables might be included in the final model of logistic regression analysis. In 1996, Peduzzi and colleagues have proposed that a logistic regression model with an NEV of 10 or more would be less biassed.20 In this study, we planned to enrol at least 100 patients with MAP and 100 patients without MAP. To compensate for some participants with incomplete data, we decided to enrol 120 patients for each group.

    All missing data were considered as not available data. We present each variable as percentage, mean and/or SD. The association between each potential factor and MAP was assessed using a univariate analysis, including the χ2 test for categorical data for all cell sizes >5, the Fisher exact test for categorical data for a cell size ≤5 and the Student t-test for continuous data. Manual backward elimination, binary logistic regression analysis was used to identify the independent risks that showed a significant correlation with MAP. The first regression model included all univariate variables significantly correlated with MAP (p≤0.05). The variable with the highest p value of each regression model was then eliminated step by step. Only the risks significantly predicting MAP (p<0.05) were included in the final regression model. ORs with corresponding 95% CIs and β’s were used to estimate the associations of nominal and continuous variables with MAP, respectively. The Hosmer and Lemeshow (H–L) test was applied, and its p value of 0.05 or higher indicated that the model fitted well with the data. The variance inflation factors (VIFs) of each variable included in the final model were computed, and a VIF of >10 indicated that multicollinearity of the corresponding variable was high.21 A p value of <0.05 indicated a significant prediction. All reported p values are two-sided.

    All statistical analyses were done using R V.3.5.1.22 We used the Rcmdr V.2.4–4 for univariate and multivariate analyses, the RcmdrPlugin.ROC V.1.0–18 for testing the H–L goodness of fit (GOF) and the rcompanion V.1.13.2 for calculating the Nagelkerke R 2.23–25

    Patient and public involvement

    Participants were not directly involved in the design of the study. The main results will be communicated to health professionals, who may need some predictors of MAP in their clinical practice.

    Results

    The total numbers of participants were 120 with MAP and 120 without MAP. Of the 120 participants with MAP, 7 were excluded because their hair tests were negative for MA.

    The data of 233 participants were included in the analysis. The whole sample included 201 men and 32 women who had a mean age (SD) of 28.3 (7.2) years, a mean of days since last use (SD) of 16.80 (9.27), a mean PHQ-9 score (SD) of 6.8 (4.5) and a mean AWQ score (SD) of 7.3 (5.4).

    The mean BPRS score (SD) of the MAP group was 25.42 (6.47). Table 1 shows the demographic data and characteristics of both groups. The mean values (SD) of MA concentration levels in the hair of the MAP group (13.68 ng/mg (25.95)) and that of the no-MAP group (8.93 ng/mg (24.66)) were not significantly different (p=0.115). The MA concentration levels in the hair and the BPRS scores were not significantly correlated in both the MAP group (Spearman’s r=0.160, p=0.091) and in the no-MAP group (Spearman’s rho=0.031, p=0.736). The mean (SD) MoCA scores of the MAP group (24.95 (2.96)) and the no-MAP group (25.77 (3.23)) were significantly different (p=0.046).

    View this table:
    Table 1

    Demographic and clinical characteristics of MA users with and without psychosis

    The univariate analysis revealed the association of MA psychosis and eight factors, including being male, MA dependence, antisocial personality disorder, history of hospitalisation for mental illnesses, history of hospitalisation for substance abuse, intravenous use in the past month, MA use for ≥16 days in the past month and younger age at first use (p<0.05) (see table 1). These eight factors were independent variables included in the first binary logistic regression analysis. After four steps of manual elimination of non-significant predictors, the final model included four risks that significantly predicted MA psychosis. These were being male, MA dependence, history of hospitalisation for substance abuse and MA use for ≥16 days in the past month (p<0.05) (see table 2). The H–L GOF test indicated no evidence of poor fit (χ2=1.39, df=8, p=0.99). The VIFs of all four predictors were between 1.02 and 1.05.

    View this table:
    Table 2

    Manual backward elimination and binary logistic regression analysis to determine the risk of MA psychosis

    Discussion

    This study examined risks of MAP in a clinical sample in which there was recent use of MA. The recent MA use and recent MAP were confirmed by using hair analysis and MINI-Plus, respectively. The low BPRS scores (mean=25.42) of the MAP group suggested that they were assessed after the recovery from psychosis. Risks of MA psychosis included being male, meeting the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) diagnosis of MA dependence, history of hospitalisation for substance abuse and using MA for ≥16 days in the past month. However, the amount of MA use measured by hair analysis was not related to experience of MA psychosis.

    Although there have been many studies on the risks of MAP, only a few of them were carried out in MA users with a recent history of psychosis.26–28 Although the mean level of hair MA in the MAP group was higher, the differences of these levels were not significant between groups. This finding was in contrast with that of a previous study reporting the association between the amount of MA use and lifetime diagnosis of MAP.29 Similar to the findings from two previous studies,27 28 we did find a correlation between the frequency of recent MA use and the development of MAP. However, the previous and the present studies differ on at least two respects. While the previous studies assessed the association between self-reported MA use and lifetime MAP, our study examined the correlation between hair MA levels and recent MAP. If any future study confirms the present findings that frequency but not the amount of MA use predicts MAP, it would mean that frequency is more important than the amount of MA use in predicting MAP.

    This study assessed MA dependence using two measures, the SDS and the DSM-IV diagnosis of MA dependence. Our finding that MA-dependent users had a higher risk of MAP than an MA abuser confirms a previous report.30 In another study, the investigators found a correlation between MAP and MA dependence, defined by using an SDS score of 4 or more.28 However, our study did not find a difference in SDS scores between groups. The discordance between the diagnosis of MA dependence and SDS scores may reflect that these two measures assess different aspects of MA dependence. The present finding that the history of hospitalisation for substance use could predict MAP appears to be in concordance with the predictability of MA dependence. Taken together, the SDS should be used with caution in future clinical studies of MAP.

    Although a literature review did not find any correlation between sociodemographic characteristics and MAP,11 our study and previous studies did find that male MA users were more likely to experience MAP.27 As two diseases in the same continuum,31 the higher risk of MAP in men appears to be in line with the findings that men are more likely than women to develop schizophrenia.32

    To our knowledge, this is the first study using hair analysis to confirm recent MA use and to determine the amount of MA use. By using this objective test, we excluded the data of 11 participants with negative results of hair analysis. The amount of MA use measured by hair analysis in this study should be more accurate than that calculated based on self-reporting.29 The recent MAP diagnosed in this study was also confirmed using the MINI-Plus psychotic module, which is a structure clinical interview widely used for diagnosis. By using the logistic regression, the predictors found in this study had already been adjusted by multiple variables.

    This study has several limitations. First, only few women, intravenous users, and those with a history of hospitalisation for mental illnesses participated in this study. The present findings, therefore, could not apply in these populations. Second, the Nagelkerke R 2 (Cragg and Uhler) of 0.26 suggested that these four variables could explain 26% of the variance, which implied that some risks of MAP were not included in the study. Examples of risks reported in previous studies but not included in the present study are polydrug use26; history of conduct disorder, depressive and anxiety disorders27; premorbid schizoid/schizotypal personality trait29; family history of psychotic disorders27; and family history of schizophrenia and bipolar disorder.33 Not only patients with transient MAP but also the relatives of patients with persistent MAP had a higher prevalence rate of schizophrenia compared with relatives of patients with transient MAP.34 Third, as a cross-sectional study, we could not confirm that the group without MAP would not develop a psychotic illness at a later point in time. Fourth, the group without MAP that participated in this study included MA users who were hospitalised due to MA use disorder. As heavy users of MA, this comparison group, therefore, might not be much different from the MAP group. Fifth, some important data were not recorded, for example, the frequency of hospitalisations, the period of time between last MA use and the hair collection. Finally, based on the MoCA scores, the participants in this sample appeared to have mild cognitive impairment, which might affect the accuracy of reported data. Although the MoCA scores of the MAP group were significantly lower than those of the no-MAP group, we did not include this variable in the logistic regression model. This decision was made because the poorer cognition in the MAP group might not be a risk but might be a consequence of MAP.

    Health professionals should closely monitor the development of MAP in MA-dependent men who frequently use MA and have a history of hospitalisation for substance abuse. The measure of MA concentration levels in the hair may add no benefit for the prediction of the development of MAP. Future studies on the correlation between the amount of MA use and the development of MAP are warranted.

    Acknowledgments

    We are grateful to Dr Phunnapa Kittirattanapaiboon and Dr Boonsiri Jansirimongkol for giving advice on this work, and Dr Wiranpat Kittitharaphan for her administrative support.

    References

    1. ↵
      1. United Nations Office on Drugs and Crime
      . World drug report 2018: global overview of drug demand and supply (booklet 2). Vienna, Austria: United Nation Publication, 2018.
    2. ↵
      1. United Nations Office on Drugs and Crime
      . World drug report 2013. Vienna: United Nations, 2013.
    3. ↵
      2. Alharbi F ,
      3. el-Guebaly N
      . Cannabis and amphetamine-type stimulant-induced psychoses: a systematic overview. Addict Disord Their Treat 2016;15:190–200.
      OpenUrl
    4. ↵
      2. Srisurapanont M ,
      3. Ali R ,
      4. Marsden J , et al
      . Psychotic symptoms in methamphetamine psychotic in-patients. Int J Neuropsychopharmacol 2003;6:347–52.doi:10.1017/S1461145703003675
      OpenUrlCrossRefPubMed
    5. ↵
      2. Srisurapanont M ,
      3. Arunpongpaisal S ,
      4. Wada K , et al
      . Comparisons of methamphetamine psychotic and schizophrenic symptoms: a differential item functioning analysis. Prog Neuropsychopharmacol Biol Psychiatry 2011;35:959–64.doi:10.1016/j.pnpbp.2011.01.014
      OpenUrlCrossRefPubMed
    6. ↵
      2. McKetin R ,
      3. Lubman DI ,
      4. Najman JM , et al
      . Does methamphetamine use increase violent behaviour? Evidence from a prospective longitudinal study. Addiction 2014;109:798–806.doi:10.1111/add.12474
      OpenUrlCrossRefPubMed
    7. ↵
      2. Glasner-Edwards S ,
      3. Mooney LJ ,
      4. Marinelli-Casey P , et al
      . Clinical course and outcomes of methamphetamine-dependent adults with psychosis. J Subst Abuse Treat 2008;35:445–50.doi:10.1016/j.jsat.2007.12.004
      OpenUrlPubMed
    8. ↵
      2. Caton CLM ,
      3. Drake RE ,
      4. Hasin DS , et al
      . Differences between early-phase primary psychotic disorders with concurrent substance use and substance-induced psychoses. Arch Gen Psychiatry 2005;62:137–45.doi:10.1001/archpsyc.62.2.137
      OpenUrlCrossRefPubMedWeb of Science
    9. ↵
      2. Kittirattanapaiboon P ,
      3. Mahatnirunkul S ,
      4. Booncharoen H , et al
      . Long-term outcomes in methamphetamine psychosis patients after first hospitalisation. Drug Alcohol Rev 2010;29:456–61.doi:10.1111/j.1465-3362.2010.00196.x
      OpenUrlCrossRefPubMedWeb of Science
    10. ↵
      2. Ujike H ,
      3. Sato M
      . Clinical features of sensitization to methamphetamine observed in patients with methamphetamine dependence and psychosis. Ann N Y Acad Sci 2004;1025:279–87.doi:10.1196/annals.1316.035
      OpenUrlCrossRefPubMedWeb of Science
    11. ↵
      2. Arunogiri S ,
      3. Foulds JA ,
      4. McKetin R , et al
      . A systematic review of risk factors for methamphetamine-associated psychosis. Aust N Z J Psychiatry 2018;52:514–29.doi:10.1177/0004867417748750
      OpenUrl
    12. ↵
      2. Sheehan DV ,
      3. Lecrubier Y ,
      4. Sheehan KH , et al
      . The Mini-International neuropsychiatric interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry 1998;59(Suppl 20):22–33.
      OpenUrl
    13. ↵
      2. Kroenke K ,
      3. Spitzer RL ,
      4. Williams JB
      . The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med 2001;16:606–13.doi:10.1046/j.1525-1497.2001.016009606.x
      OpenUrlCrossRefPubMedWeb of Science
    14. ↵
      2. Srisurapanont M ,
      3. Jarusuraisin N ,
      4. Jittiwutikan J
      . Amphetamine withdrawal: I. reliability, validity and factor structure of a measure. Aust N Z J Psychiatry 1999;33:89–93.doi:10.1046/j.1440-1614.1999.00517.x
      OpenUrlCrossRefPubMedWeb of Science
    15. ↵
      pp Sobell LC , Sobell MB . Timeline follow-back. In: Measuring alcohol consumption. Totowa, NJ: Humana Press, 1992: 41–72.
    16. ↵
      2. Gossop M ,
      3. Darke S ,
      4. Griffiths P , et al
      . The severity of dependence scale (SDS): psychometric properties of the SDS in English and Australian samples of heroin, cocaine and amphetamine users. Addiction 1995;90:607–14.doi:10.1046/j.1360-0443.1995.9056072.x
      OpenUrlCrossRefPubMedWeb of Science
    17. ↵
      2. Overall JE ,
      3. Gorham DR
      . The brief psychiatric rating scale. Psychol Rep 1962;10:799–812.doi:10.2466/pr0.1962.10.3.799
      OpenUrlCrossRef
    18. ↵
      2. Nasreddine ZS ,
      3. Phillips NA ,
      4. Bédirian V , et al
      . The Montreal cognitive assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc 2005;53:695–9.doi:10.1111/j.1532-5415.2005.53221.x
      OpenUrlCrossRefPubMedWeb of Science
    19. ↵
      2. Suwannachom N ,
      3. Thananchai T ,
      4. Junkuy A , et al
      . Duration of detection of methamphetamine in hair after abstinence. Forensic Sci Int 2015;254:80–6.doi:10.1016/j.forsciint.2015.06.030
      OpenUrl
    20. ↵
      2. Peduzzi P ,
      3. Concato J ,
      4. Kemper E , et al
      . A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol 1996;49:1373–9.doi:10.1016/S0895-4356(96)00236-3
      OpenUrlCrossRefPubMedWeb of Science
    21. ↵
      2. Sheather S
      . A modern approach to regression with R. New York: Springer-Verlag, 2009. www.springer.com/gp/book/9780387096070
    22. ↵
      1. R Core Team
      . A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing, 2018. https://www.R-project.org/
    23. ↵
      2. Daniel-Corneliu L
      . RcmdrPlugin.ROC: Rcmdr Receiver Operator Characteristic Plug-In PACKAGE. R package version 1.0-18, 2015. Available: https://CRAN.R-project.org/package=RcmdrPlugin.ROC
    24. ↵
      2. Fox J
      . The R Commander: a basic statistics graphical user interface to R. J STAT Softw 2005;14:1–42.
    25. ↵
      2. Salvatore M
      . Rcompanion: Functions to Support Extension Education Program Evaluation. R package version 1.13.2, 2018. Available: https://CRAN.R-project.org/package=rcompanion
    26. ↵
      2. McKetin R ,
      3. Hickey K ,
      4. Devlin K , et al
      . The risk of psychotic symptoms associated with recreational methamphetamine use. Drug Alcohol Rev 2010;29:358–63.doi:10.1111/j.1465-3362.2009.00160.x
      OpenUrlCrossRefPubMedWeb of Science
    27. ↵
      2. McKetin R ,
      3. Lubman DI ,
      4. Baker AL , et al
      . Dose-related psychotic symptoms in chronic methamphetamine users: evidence from a prospective longitudinal study. JAMA Psychiatry 2013;70:319–24.doi:10.1001/jamapsychiatry.2013.283
      OpenUrl
    28. ↵
      2. McKetin R ,
      3. McLaren J ,
      4. Lubman DI , et al
      . The prevalence of psychotic symptoms among methamphetamine users. Addiction 2006;101:1473–8.doi:10.1111/j.1360-0443.2006.01496.x
      OpenUrlCrossRefPubMedWeb of Science
    29. ↵
      2. Chen CK ,
      3. Lin SK ,
      4. Sham PC , et al
      . Pre-morbid characteristics and co-morbidity of methamphetamine users with and without psychosis. Psychol Med 2003;33:1407–14.doi:10.1017/S0033291703008353
      OpenUrlCrossRefPubMedWeb of Science
    30. ↵
      2. Smith MJ ,
      3. Thirthalli J ,
      4. Abdallah AB , et al
      . Prevalence of psychotic symptoms in substance users: a comparison across substances. Compr Psychiatry 2009;50:245–50.doi:10.1016/j.comppsych.2008.07.009
      OpenUrlCrossRefPubMedWeb of Science
    31. ↵
      2. Bramness JG ,
      3. Gundersen Øystein Hoel ,
      4. Guterstam J , et al
      . Amphetamine-induced psychosis--a separate diagnostic entity or primary psychosis triggered in the vulnerable? BMC Psychiatry 2012;12:221.doi:10.1186/1471-244X-12-221
    32. ↵
      2. McGrath J ,
      3. Saha S ,
      4. Chant D , et al
      . Schizophrenia: a Concise overview of incidence, prevalence, and mortality. Epidemiol Rev 2008;30:67–76.doi:10.1093/epirev/mxn001
      OpenUrlCrossRefPubMedWeb of Science
    33. ↵
      2. Hides L ,
      3. Dawe S ,
      4. McKetin R , et al
      . Primary and substance-induced psychotic disorders in methamphetamine users. Psychiatry Res 2015;226:91–6.doi:10.1016/j.psychres.2014.11.077
      OpenUrl
    34. ↵
      2. Chen C-K ,
      3. Lin S-K ,
      4. Sham PC , et al
      . Morbid risk for psychiatric disorder among the relatives of methamphetamine users with and without psychosis. Am J Med Genet B Neuropsychiatr Genet 2005;136B:87–91.doi:10.1002/ajmg.b.30187
      OpenUrl

    Footnotes

    • Contributors WL conceived the idea of this work, collected the data, analysed/interpreted the data and drafted the article. KP, DI, AS and NS conceived the idea for this work and collected the data. PK, PS and AJ conceived the idea for this work, collected the data and drafted the article. MS conceived the idea for this work, analysed/interpreted the data and drafted the article. All authors critically revised the article and approved the final manuscript.

    • Funding This study was supported by a grant from the Department of Mental Health, Ministry of Public Health, Thailand and partially supported by a grant from Chiang Mai University. The sponsor had no role in the analysis and interpretation of data, the manuscript preparation or writing and the decision to submit the manuscript.

    • Competing interests MS has received a speaker honorarium from Lundbeck and Sumitomo Dainippon Pharma.

    • Patient consent for publication Not required.

    • Ethics approval Approval for this study was obtained from the local medical ethics committee (EC) of Nakhon Phanom Rajanagarindra Psychiatric Hospital under project number 102/2558 on 25 June 2015. The EC for human research of the Ministry of Public Health approved the study protocol for Thanyarak Chiang Mai Hospital, Nakhon Phanom Rajanagarindra Psychiatric Hospital and Songkhla Rajanagarindra Psychiatric Hospital. Each EC for Human Research of Suanprung Psychiatric Hospital and Galyarajanagarindra Institute approved the study protocol at its site. All the participants provided written informed consent prior to participation in the study. All methods used in the study were performed in accordance with the guidelines given, and the regulation agreed with the ECs.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data availability statement Data are available upon reasonable request.