Methamphetamine Use and Psychiatric Morbidity in Sri Lanka: Sociodemographic Insights from a Tertiary Care Clinic

Abstract

Background:

Methamphetamine use is increasing across South and Southeast Asia, yet evidence on user characteristics and psychiatric morbidity remains limited. This study examines the sociodemographic features, psychiatric symptoms, and their associations among methamphetamine users in Sri Lanka.

Methods:

A cross-sectional study was conducted among 245 consecutive patients attending the professorial psychiatry unit of a tertiary hospital in Sri Lanka. Data were collected using a structured questionnaire, Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) diagnostic criteria, and the Brief Psychiatric Rating Scale (BPRS).

Results:

Most participants were male (97.6%) with a mean age of 31.3 years (SD = 9.7). The mean age of initiation was 29.2 years (SD = 10.0), and 86.9% were introduced by friends. Methamphetamine dependence was 60.8%. Frequent concurrent substance use included nicotine (93.1%) and heroin (73.9%). Psychiatric comorbidities included substance-induced psychosis (10.6%) and major depression (4.9%). The mean BPRS score was 24.25 (SD = 8.0), with prevalent symptoms: suspiciousness (86%), hostility (82.5%), and depression (61.6%). Higher BPRS scores linked to younger age, family history, unemployment, recent use, and dependence; dependence predicted higher symptoms (adjusted odds ratio [AOR] = 3.62, confidence intervals [CI]: 1.82–7.19).

Conclusion:

The methamphetamine users in Sri Lanka are predominantly young males with high rates of dependence, concurrent substance use, and significant psychiatric morbidity. These findings highlight the urgent need for integrated mental health and substance use interventions and provide data relevant for national, regional, and global public health strategies.

Keywords

Concurrent substance use methamphetamine psychiatric morbidity sociodemographic characteristics substance-induced psychosis

Key Messages:

Question: What are the sociodemographic characteristics and psychiatric symptoms, and how are they related among methamphetamine users in Sri Lanka?

Finding: Methamphetamine users are mostly young men with dependence, often using multiple drugs. Common comorbidities include psychosis and depression. Symptoms are linked to dependence, youth, unemployment, and recent use.

Meaning: There is an urgent need for integrated mental health and substance use interventions in Sri Lanka.

Methamphetamine is the second most widely used illicit psychoactive substance globally.¹ Its use is associated with a spectrum of psychotic presentations, ranging from brief intoxication-related states to persistent substance-induced psychotic disorders resembling schizophrenia.² Studies conducted in Southeast and East Asia have documented a wide array of health problems related to methamphetamine use.¹ Beyond direct psychiatric effects, methamphetamine-induced psychosis contributes to social and occupational dysfunction, violence, and poor treatment outcomes.^3,4 Evidence suggests a bidirectional relationship between methamphetamine use and psychotic symptoms, where each can exacerbate the other.⁵ In Sri Lanka, a survey of 50 methamphetamine users reported a mean age of initiation of 19 years, with common concurrent use of heroin, cannabis, alcohol, cigarettes, and other stimulants.⁶ A recent study conducted at the National Institute of Mental Health, Sri Lanka, reported that the most common physical consequences were weight loss (38.8%) and loss of appetite (37.2%).⁷ Among the perceived psychological and social effects, irritability (28.8%) and interpersonal relationship difficulties (50.8%) were the most frequently reported.⁷ The highest number of methamphetamine-related arrests (1762) was reported in the Colombo District in 2022.⁸ Methamphetamine use and offense-related arrests have increased over the last few years, since 2017 in Sri Lanka.⁶ However, data on the psychiatric characterization of methamphetamine users in Sri Lanka remain limited, and no previous studies have described psychiatric symptom severity using the Brief Psychiatric Rating Scale (BPRS) in this setting. Understanding the characteristics of high-risk populations is essential for prevention and intervention strategies. This study aimed to describe the sociodemographic characteristics and psychiatric morbidity of methamphetamine users attending a tertiary hospital in Sri Lanka and to examine the associations between these factors. The secondary objectives were to determine the prevalence of methamphetamine dependence, substance-induced psychosis, and other psychiatric comorbidities; to identify factors associated with greater psychiatric symptom severity; and to determine independent predictors of higher psychiatric symptom severity.

Methods

This cross-sectional study was conducted among methamphetamine users attending the substance use disorder management clinic, outpatient psychiatry services, and liaison psychiatry referrals to the professorial psychiatry unit of the hospital from September 2020 to February 2021. Ethics committee approval was obtained from the Institutional Ethics Review Committee. Participants were recruited using a convenience sampling method from patients attending the hospital for various reasons, including psychiatric symptoms, substance-related problems, or other health concerns. Some participants were initially referred from other departments for physical health issues; however, only those with a history of methamphetamine use within the preceding year were included. All eligible participants subsequently underwent psychiatric assessment. Inclusion criteria were individuals aged over 15 years who attended the above settings and reported methamphetamine use at least once during the preceding year. Only medically stable patients were included in the study. Exclusion criteria included individuals who had been receiving antipsychotic or antidepressant treatment for more than one month, those with a pre-existing mental illness before the initiation of methamphetamine use, and those who were critically ill with acute medical conditions requiring immediate life-saving intervention. Medication history was obtained through participant self-report and review of available medical records.

The sample size was calculated using the formula for estimating a single population proportion (n = Z²P(1 – P)/d²). As precise prevalence estimates of methamphetamine-induced psychosis vary widely across studies,^9,10 a conservative estimate of 15% was used for sample size calculation. The sample size was initially estimated using the expected prevalence of methamphetamine-induced psychosis reported in previous literature as a proxy indicator of psychiatric morbidity, due to the lack of prior data on BPRS-based symptom severity in this population. However, the primary outcome of the present analysis was psychiatric symptom severity measured using the BPRS. This discrepancy is acknowledged as a methodological limitation. With a 5% margin of error, a 95% confidence level, and a 10% allowance for non-response, the required sample size was estimated to be 215. The principal investigator carried out data collection. Informed written consent was obtained from participants. Demographic data and substance use details were collected using a pretested interviewer-administered questionnaire. Occupations were categorized into four predefined groups based on skill level and type of employment: Group I (laborers, service workers, and semiskilled workers), Group II (clerical, sales, skilled, agricultural, and protective service workers), Group III (small business owners, managers, and administrators), and Group IV (professionals with or without doctoral qualifications). This categorization was developed for this study to reflect increasing levels of occupational skill and responsibility. The interviewer-administered questionnaire was available in Sinhala and Tamil. The original English version was translated independently by two bilingual experts. A separate bilingual translator, blinded to the original questionnaire, performed a back-translation into English. Discrepancies were reviewed and resolved by the research team to ensure conceptual equivalence. The translated versions were pre-tested in a small group of participants to ensure clarity and cultural appropriateness before the main study. Clinical assessments were conducted by a consultant psychiatrist using the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) diagnostic criteria for substance use disorder.¹¹ Major mental illnesses, including major depressive disorder, substance-induced psychotic disorder, schizophrenia, and other relevant psychiatric conditions, were diagnosed through independent clinical assessment using DSM-5 criteria by the same clinician. Psychiatric symptoms were assessed using the BPRS, a semi-structured clinical interview tool.¹² BPRS is considered a sensitive and specific measure for assessing psychiatric symptoms; one study reported a sensitivity of 71.4% and a specificity of 69.1% for conceptual disorganization.¹³ Its brevity and clinical practicality make it well-suited for busy tertiary care settings in Sri Lanka.¹⁴ The primary outcome of the study was psychiatric symptom severity, assessed using the BPRS. Psychiatric symptom severity was dichotomized using a BPRS cut-off of 25, which approximated the sample mean (24.25), to enable comparative and regression analyses. Psychiatric diagnoses, including substance-induced psychotic disorder, major depressive disorder, and schizophrenia, were recorded as secondary descriptive outcomes. Individuals identified with mental illnesses received treatment in suitable clinical settings. The manuscript was prepared in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology guidelines.^15,16 Sociodemographic characteristics were analyzed in terms of frequencies and percentages. Dichotomous variables were compared using Pearson’s chi-square test. Variables that showed statistical significance in bivariate analysis (Table 2) were entered into a multivariable binary logistic regression model to identify factors independently associated with higher psychiatric symptom severity (defined as BPRS ≥ 25). Adjusted odds ratios (AORs) with 95% confidence intervals (CIs) were calculated. A two-tailed p value of <.05 was considered statistically significant. Statistical analyses were performed using IBM SPSS Statistics.

Results

Sociodemographic Characteristics

Of 245 participants, 239 (97.6%) were males, and 147 (60%) were single. The mean age was 31.30 years (SD = 9.74), ranging from 15 to 63 years. The majority (173, 70.6%) were educated up to Grade 11, and 108 (44.1%) had an income of less than LKR 50,000 per month. Most participants were recruited from the substance use disorder management clinic (196, 80%), followed by the outpatient psychiatry clinic (32, 13.06%) and inpatient psychiatry referrals (17, 6.9%). Most referrals were by self or family members (142, 58%), while 68 (27.5%) were referred through courts.

Among methamphetamine users, 23 (9.4%) were in job Group III. A total of 112 (45.7%) had a history of imprisonment. Most users resided within the Colombo District; 83 (33.9%) were from districts outside Colombo. The highest numbers were from Colombo (52, 21.1%), Thimbirigasyaya (28, 11.4%), and Kolonnawa (23, 9.4%) divisional secretariat areas. Figure 1 illustrates the distribution of participating methamphetamine users within the Colombo District.

Figure 1.

Map Showing the Distribution of Methamphetamine Users According to GN Divisions in the Colombo District (Drawn Using a Geographic Information System).

Clinical and Psychiatric Characteristics

Among the participants, 76 (31%) reported a family history of substance use, while 9.8% had a family history of major mental illness. The most commonly identified psychiatric comorbidities, other than methamphetamine use disorder, were substance-induced psychotic disorder (26, 10.6%), major depressive disorder (12, 4.9%), and schizophrenia (9, 3.7%).

Substance Use Characteristics

Substance use characteristics are presented in Table 1. The mean age of onset of methamphetamine use was 29.16 (SD = 10.02), and 149 (60.8%) met DSM-5 criteria for dependence. For the majority of participants, the initial use of methamphetamine occurred at a friend’s place, while eight participants (3.3%) reported initiating use at funeral gatherings. The most common concurrent drugs were nicotine and heroin. They were used weekly or more often by 228 (93.1%) and 181 (73.9%), respectively. Other common drugs included cannabis (116, 47.3%), pregabalin (74, 30.2%), and alcohol (26, 10.6%).

Table 1.

Sociodemographic Characteristics Among All Methamphetamine Users.

Sociodemographic Characteristic		Number (%)
Mean age of onset of use (SD), (min–max)		31.30 years (SD = 9.74) (min = 15, max = 63)
Gender	Male	239(97.6%)
Gender	Female	06(2.4%)
Setting of first use	Workplace	24(9.8%)
	Friend’s place	96(39.2%)
	Home or a place near the home	47(19.1%)
	Party	39(15.9%)
	Prison	6(2.4%)
	Any other	12(4.9%)
	Can not remember	8(3.3%)
	School	1(0.4%)
	Rented room	4(1.6%)
	Funeral house	8(3.3%)
Frequency of methamphetamine use	Daily	39(15.9%)
	Once a week or more but less than daily	108(44.1%)
	Once a month or more but less than once a week	27(11.0%)
	Less than once a month	55(22.4%)
First introducer	Friend	213(86.9%)
	Workmate	5(2.0%)
	Relation/spouse/partner	5(2.4%)
	Prison inmate	5(2.0%)
	Any other	10(4.1%)
	Can not remember	5(2.0%)
Last use	Within the last 24 hours	9(3.7%)
	1–7 days duration	55(22.4%)
	8–30 days duration	37(15.1%)
	One month to one year duration	141(57.6%)
Duration of use	Less than 30 days	47(19.2%)
	31–90 days	13(5.3%)
	91 days to one year	74(30.2%)
	More than one year	111(45.3%)
Mode of administration	Snorting by heating on a glass plate	241(98.4%)
	Smoking through a bong	3(1.2%)
	Aluminum coil and cylinder	1(0.4%)
	Intravenous	0(0.00%)
	Oral	0 (0.00%)
Source of the drug	Illegal drug market	138(56.3%)
	friends or relatives	100(40.8%)
	Any other	4(1.6%)
	Not willing to reveal	1(0.4%)
The most common place of methamphetamine use	Home or nearby place	71(29%)
	Friends place	124(50.6%)
	Hotel/restaurant/dance hall	10(4.1%)
	Work place	10(4.1%)
	Funeral houses	1(0.4%)
	Three wheel/car	2(0.8%)
	Prison	1(0.4%)
	Any other place	14(5.7%)
	Not willing to reveal	3(1.2%)
DSM-5 criteria for methamphetamine dependence (at least two over the last 12 months)	Yes	149(60.8%)
	No	96(39.2%)
Concurrent use of other drugs	Yes	234(95.5%)
Concurrent use of other drugs	No	10(4.1%)

SD = Standard deviation, DSM-5 = Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition.

The mean BPRS score was 24.25 (SD = 8.00), ranging from 1.00 to 49.00. Participants were categorized into two groups based on the mean BPRS score. Of the participants, 86 (35%) had BPRS scores above the mean. The line chart shows that the distribution of psychotic symptoms among methamphetamine users with above-mean BPRS scores differs from that of below-mean BPRS scorers. Among participants with above-mean BPRS scores, the most prominent psychiatric symptoms were suspiciousness (mean = 3.87, SD = 1.75), hostility (mean = 3.06, SD = 1.31), hallucinating behavior (mean = 2.84, SD = 1.88), depressed mood (mean = 2.70, SD = 1.67), somatic concerns (mean = 2.09, SD = 1.65), anxiety (mean = 1.96, SD = 1.14), and grandiosity (mean = 1.75, SD = 1.02), corresponding to BPRS items 1, 2, 8, 9, 10, 11, and 12 (Figure 2). This indicates that psychotic and affective symptoms were common in this subgroup. Sociodemographic analysis revealed significant associations between higher BPRS scores and younger age (p = .03), family history of mental illness (p = .04), unemployment (p = .01), use of methamphetamine within the last seven days (p = .01), and dependence (p < .001) (Table 2). In multivariable logistic regression analysis, methamphetamine dependence was significantly associated with higher psychiatric symptom severity (AOR = 3.62, 95% CI: 1.82–7.19, p < .001). Regular heroin use was associated with lower psychiatric symptom severity (AOR = 0.43, 95% CI: 0.30–0.62, p < .001). Other variables, including age, employment status, family history of mental illness, duration of methamphetamine use, and recent use, were not significantly associated after adjustment (Table 3).

Figure 2.

BPRS: Brief Psychiatric Rating Scale.

Table 2.

Distribution of Demographic and Substance Use Characteristics with BPRS Scores Among Methamphetamine Users.

Variables		Below the Mean BPRS Score (BPRS ≤ 24) N = 159	Above-mean BPRS Score (BPRS ≥ 25) N = 86	Degree of Freedom	p Value
*Associations with demographic factors and the BPRS score
Gender	Male	155	84	1	.93
Gender	Female	4	2	1	.93
Age in years	≤40	129	78	1	.03
Age in years	>41	30	7	1	.03
Education level	Grade 11 or below	121	68	1	.60
Education level	Above Grade 11	38	18		.60
Monthly income	<LKR 50,000	90	58	1	.10
Monthly income	≥LKR 50,000	69	28	1	.10
Marital status	Never married or separated	100	60	1	.28
Marital status	Married	59	26	1	.28
Number of children	No children	111	58	1	.70
Number of children	One or more children	48	28	1	.70
Family history of mental illness	No history/not known	148	73	1	.04
Family history of mental illness	Present	11	13	1	.04
Family history of substance use	No history	93	45	1	.35
Family history of substance use	Present	66	41	1	.35
Conflict with law	Absent	32	16	1	.77
Conflict with law	Present	127	70
Age at first methamphetamine use	Less than 25	62	44	1	.07
Age at first methamphetamine use	More than 25	96	42	1	.07
Employment status	Unemployed	22	23	1	.01
Employment status	Employed	137	63	1	.01
Frequency of Pregabalin use	Regular users	50	24	1	.62
Frequency of Pregabalin use	Occasional/not users	108	60	1	.62
Use of methamphetamine within the last 7 days	Yes	33	31	1	.01
Use of methamphetamine within the last 7 days	No	125	53	1	.01
Methamphetamine dependence (DSM-5)	Yes	41	55	1	<.001
Methamphetamine dependence (DSM-5)	No	118	31	1	<.001
Duration of methamphetamine use	≤90 days	50	10	1	.01
Duration of methamphetamine use	>90 days	109	76	1	.01
Frequency of Heroin use	Regular	140	41	1	<.001
Frequency of Heroin use	Occasional/not use	19	43	1	<.001
Frequency of cannabis use	Regular	73	43	1	.46
Frequency of cannabis use	Occasional/not use	85	41	1	.46

DSM-5 = Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, BPRS = Brief Psychiatric Rating Scale, LKR = Sri Lankan rupees.

The mean BPRS score of 24 was used as the cut-off value to categorize participants.

*Data are presented as frequencies. Pearson’s chi-square test was used for variables with adequate expected cell counts, while Fisher’s exact test was applied when expected counts were <5.

Table 3.

Multivariable Binary Logistic Regression Analysis of Factors Associated with Higher Psychiatric Symptom Severity Among Methamphetamine Users (BPRS ≥ 25).*

Variable	Category	Adjusted OR	95% CI	p Value
Age group	>40 vs. ≤40	0.80	0.58–1.11	.18
Family history of mental illness	Present vs. Absent	2.04	0.76–5.46	.15
Employment status	Unemployed vs. Employed	0.84	0.58–1.20	.33
Recent methamphetamine use	Yes vs. no	1.01	0.95–1.07	.83
Methamphetamine dependence (DSM-5)	Yes vs. no	3.62	1.82–7.19	<.001*
Duration of methamphetamine use	>90 days vs. ≤90 days	1.17	0.83–1.64	.36
Heroin use	Regular vs. occasional/none	0.43	0.30–0.62	<.001*

*The dependent variable was psychiatric symptom severity (BPRS ≥ 25 vs. <25). Independent variables included those found to be statistically significant in bivariate analysis ( Table 2 ). AORs with 95% CIs were calculated. A p value <.05 was considered statistically significant.

Discussion

This study aimed to examine the sociodemographic characteristics and psychiatric morbidity among methamphetamine users attending a tertiary care hospital in Sri Lanka. The findings indicate that the study population consisted predominantly of young adult males with a high prevalence of unemployment, legal involvement, and concurrent substance use. Approximately one-third of participants demonstrated elevated psychiatric symptom severity, with dependence emerging as a key independent predictor. In addition to these clinical findings, this study provides one of the first structured assessments of psychiatric symptom severity using the BPRS among methamphetamine users in Sri Lanka. The detailed characterization of both sociodemographic features and symptom profiles represents an important contribution to the limited regional literature.

The demographic profile of methamphetamine users in this study was similar to findings reported in previous Sri Lankan and comparable regional studies, with a predominance of young adult males and a high proportion of unmarried individuals.¹⁷ The mean age at onset of methamphetamine use was 29.16 years, which is comparable to the age range reported in similar settings (21–30 years).⁷ Nearly half of the participants had a history of legal conflict, reflecting the growing law-enforcement action against methamphetamine use in Sri Lanka.⁸ However, the available data did not allow us to determine whether these incidents were directly related to methamphetamine use or were offenses committed under its influence.⁸ These findings underscore the need for coordinated public health and legal responses, including prevention strategies, and diversion to treatment programs. A family history of regular substance use or major mental illness was reported in 9.8% of participants, which is lower than that reported in studies from China,¹⁸ and Iran.¹⁹ This difference may reflect variations in study populations, sociocultural factors, or underreporting, rather than indicating a reduced or increased familial influence. Eight participants (3.3%) reported initiating methamphetamine use at funeral gatherings, representing a relatively uncommon context of substance initiation that has been rarely described in the literature. In the local context, funeral gatherings often involve prolonged social interactions, which may increase exposure to substance use in certain social groups. However, given the small number of cases, this finding should be interpreted cautiously and warrants further exploration in future studies.

Methamphetamine dependence rates were similar to those in studies in Australia,²⁰ although assessment scales differed. This finding suggests that severe methamphetamine use occurs across different socioeconomic settings, and that the clinical burden of dependence is significant even in low- and middle-income countries such as Sri Lanka. Commonly concurrently used substances were tobacco, alcohol, and heroin.²¹ This pattern is consistent with previous studies, which have shown that concurrent use is highly prevalent among methamphetamine users, with alcohol and tobacco being among the most frequently co-used substances.²² In particular, tobacco use is often highly prevalent in substance-using populations, with some studies reporting use in the majority of individuals with substance use disorders.²³ Alcohol is also commonly used alongside stimulants, either to enhance or modulate their psychoactive effects.²² In this study, approximately three-quarters of methamphetamine users reported using heroin every week or more frequently; however, heroin dependence was not formally assessed using standard diagnostic criteria, as the study focused on methamphetamine use. The frequent co-use of heroin and methamphetamine may reflect attempts by users to modulate stimulant and opioid effects.²⁴ In particular, some individuals may use methamphetamine to counteract the sedative effects of heroin. Such patterns complicate treatment and may increase both psychiatric and physical health risks.²⁵ These findings also underscore the importance of routine screening for multiple substance use in clinical settings.

Substance-induced psychosis, major depressive disorder, and schizophrenia were the most frequently identified psychiatric comorbidities, and these findings were similar to those of other studies.⁵ Previous studies have also reported higher rates of psychotic disorders among individuals dependent on methamphetamine.¹⁸ The structured assessment using the BPRS provided further insight into the symptom profile of these individuals. The predominance of suspiciousness and hostility suggests that paranoid symptom clusters may be particularly characteristic of methamphetamine-related psychiatric presentations. However, the prevalence of diagnosed schizophrenia in this study was relatively low, suggesting that many psychotic symptoms may be transient or substance-related rather than indicative of primary psychotic disorders. These symptom patterns are consistent with the known neuropsychiatric effects of methamphetamine,²⁶ which include dopaminergic dysregulation, heightened paranoia, and mood disturbance.²⁷ The presence of both psychotic and affective symptoms highlights the complex clinical presentation of methamphetamine users and the need for comprehensive psychiatric assessment.

Approximately one-third of participants demonstrated elevated psychiatric symptom severity, highlighting the substantial mental health burden among methamphetamine users. The observed association between recent methamphetamine use and psychotic symptoms may reflect transient effects of intoxication rather than persistent psychotic disorder.²⁸ In methamphetamine-induced psychotic disorder, symptoms must last beyond the expected effects of intoxication or withdrawal.²⁸ Previous longitudinal studies have demonstrated that although methamphetamine-related psychotic symptoms are often transient, a proportion of individuals may go on to develop persistent or recurrent psychotic disorders.^28,29

In multivariable analysis, methamphetamine dependence was independently associated with higher psychiatric symptom severity. Interestingly, regular heroin use was associated with lower psychiatric symptom severity in this study. This finding should be interpreted cautiously, as it may reflect differences in patterns of substance use, timing of use, or other unmeasured confounders. Some previous studies have reported similar observations, suggesting that concomitant opioid use may be associated with lower apparent severity of stimulant-related psychiatric symptoms; however, the underlying mechanisms remain unclear.³⁰ It is also possible that the sedative effects of opioids may transiently mask or attenuate observable psychotic symptoms, rather than reducing the underlying psychopathology. These findings highlight the complexity of polysubstance use and warrant further investigation in longitudinal and mechanistic studies.

This study represents one of the first structured assessments of psychiatric symptom severity among methamphetamine users in Sri Lanka, thereby making a significant contribution to the limited body of regional literature. It provides important data on methamphetamine use in a low- and middle-income South Asian setting. A key strength of this study is its relatively large clinical sample and the use of standardized diagnostic criteria (DSM-5) and a validated symptom rating scale (BPRS), enabling a robust assessment of psychiatric morbidity among methamphetamine users in Sri Lanka. However, it was conducted at a substance use disorder management clinic in the Western Province of Sri Lanka during the COVID-19 pandemic, when the number of methamphetamine users presenting was lower than expected. As such, the sample may not adequately represent users at the community level. The use of convenience sampling introduces selection bias and limits the generalizability of the findings. Patients with primary heroin dependence who also used methamphetamine may have been underrepresented, as recruitment was based on methamphetamine use as the presenting concern. Reliance on self-reported data and possible effects of other psychoactive substances may have influenced the assessment of psychiatric symptoms. Using a cut-off value approximating the sample mean to categorize psychiatric symptom severity may not correspond to a clinically validated threshold, potentially limiting the clinical interpretability of the findings. Additionally, the sample size was calculated based on the expected prevalence of methamphetamine-induced psychosis rather than the primary outcome of BPRS-based symptom severity, due to the lack of prior data. This may affect the statistical power of analyses related to the primary outcome. The use of different street names for substances could have led to misclassification. Finally, the cross-sectional design restricts causal inference between methamphetamine use and psychosis, as well as duration of psychotic symptoms.

Conclusions

This study describes the sociodemographic characteristics and psychiatric morbidity of methamphetamine users attending a tertiary care center in Sri Lanka. The majority of the participants were young men exhibiting high rates of dependence, multiple substance use, and psychiatric comorbidity. The most frequently reported psychiatric symptoms were suspiciousness, hostility, and depression. Dependence was independently associated with a greater burden of psychiatric symptoms. These findings emphasize the urgent need for early detection, integrated treatment models, and targeted prevention strategies to address methamphetamine-related psychiatric morbidity.

Supplemental Material

Supplemental material for this article is available online.

Footnotes

Acknowledgements

We want to thank the staff of the Substance Use Disorder Clinic of NHSL, Dr Sumal Nandasena (Managing Director of the Department of Health for Geographic Information System Mapping), and Dr A. Pubudu De Silva for their statistical support.

Reporting Guideline

Name: The STROBE reporting checklist

Citation: von Elm E, Altman DG, Egger M, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: Guidelines for reporting observational studies. PLoS Med 2007; 4(10): e296.

Appropriate Permissions from the Concerned Authorities

Permission was obtained from the Director of the hospital and the Head of the Department of Psychiatry, Faculty of Medicine, University of Colombo.

Data Sharing Statements

De-identified individual participant data will not be made available.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Declaration Regarding the Use of Generative AI

No part of this article was written or generated by a generative AI tool. The authors take full responsibility for the accuracy, integrity, and originality of the published article.

Ethical Approval

Name of the Institutional Ethics Committee/Independent Review Board:

Institutional Ethics Review Committee of the National Hospital of Sri Lanka.

Approval Ref. No: AAJ/ETH/COM/2020/JULY.

Date: July 21, 2020.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Informed Consent/Assent

Informed written consent was obtained from all participants prior to study participation.

Prior Presentations

Submitted as an abstract at the annual academic sessions of the Sri Lanka College of Psychiatrists in 2023.

PROSPERO/CTRI Details

Nil.

Registration

Not relevant.

Trial registry name:

URL:

Registration number:

Simultaneous Submission to Another Journal or Resource

Submitted as a preprint to medRxiv.

Status of Your Study (for Study Protocol)

Nil.

Citation Diversity Statement

The authors made a conscious effort to include citations that reflect diversity in geography, gender, and academic perspectives, where relevant to the topic. Reference selection was primarily guided by scientific relevance, methodological quality, and contribution to the field.

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