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Original article

Non-medical prescription drug use in Serbia: results from the national survey on lifestyles – substance abuse and gambling

Zorica Terzić-Šupić1, Jovana Todorović1, Biljana Kilibarda2, Viktor Mravčik3,4,5
  • University of Belgrade, Faculty of Medicine, Institute of Social Medicine, Belgrade, Serbia
  • Institute of Public Health of Serbia Dr Milan Jovanovic Batut, Belgrade, Serbia
  • National Monitoring Centre for Drugs and Addiction, Office of the Government, Prague, Czech Republic
  • Department of Addictology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
  • Centre for Epidemiological and Clinical Research on Addictions, National Institute of Mental Health, Klecany, Czech Republic

ABSTRACT

Background: Non-medical prescription drug use (NMPDU) of anti-anxiety medications is a growing public health concern. The aim of this study was to examine the prevalence of the use of anti-anxiety medications, as well as the factors associated with the NMPDU of these medications among adults in Serbia.

Materials and methods: The study is a secondary analysis of the data from the National Survey on Lifestyles in Serbia – Substance Abuse and Gambling, conducted in 2014 and 2018, with 7,385 participants.

Results: The prevalence of prescription only use of anti-anxiety medications was 13.5% (995/7,385), while the prevalence of the non-medical prescription drug use was 5.04% (372/7,385). Multinomial logistic regression analysis showed an association between non-medical prescription use of anti-anxiety medications and the female sex (OR: 3.23), the age between 35 and 44 years (OR: 1.91), the age between 45 and 54 years (OR: 2.40), or the age between 55 and 64 years (OR: 2.97), reporting a low (OR: 2.40) or average (OR:1.67) satisfaction with health status, being a smoker (OR: 1.62), having moderate (OR: 2.35) or high (OR: 4.56) psychological distress, and having a low/moderate risk for pathological gambling (OR: 1.86).

Conclusion: There is a clear need for the inclusion of health care professionals and media in the education of patients on the risks of self-medication, medication exchange, or illegal purchase of these medications.


INTRODUCTION

Non-medical prescription drug use (NMPDU), especially of anti-anxiety medications is a growing problem worldwide [1]. NMPDU is most commonly defined as the use of prescription medication in any way other than instructed by a physician, including the use of medication without having a prescription in one’s own name, using medication in doses higher than prescribed, as well as using medication more frequently or for a longer period than prescribed [2]. The World Health Organization (WHO) defines NMPDU as any use of prescription medication in a form or at a time other than prescribed by a physician. NMPDU has reached epidemic proportions in the United States of America (USA) [3].

NMPDU is the most frequent for opiates, opiate substitute medications, and anti-anxiety medications. Previous studies have shown that the most frequently prescribed medications from the group of anti-anxiety medications are benzodiazepines, which, along with Z-drugs, have the highest NMPDU in this group of medications [4]. Prescription use and NMPDU of anti-anxiety medications have risen over the past 10 years, in USA and Europe [5],[6]. The National Survey on Drug Use and Health has shown that almost half a million Americans reported NMPDU of these medications in 2016 [7], with the prevalence among young adults, aged 18 to 25 years, being 6.5%, in 2018 [8]. The prevalence of NMPDU of anti-anxiety medications has been reported for only a small number of European countries, varying between 2.8%, in Germany, and 9.2%, in Spain, in 2016, and between 1%, in Germany and the UK, and 4%, in Spain, in 2017 [5].

Studies published so far have shown that the factors associated with NMPDU of anti-anxiety medications are the following: age, sex, culture, lifestyle characteristics and risk behaviors, as well as easy access to these medications [9]. Young adults, aged between 18 and 35 years, elderly individuals, and women have been shown to be at a higher risk of NMPDU of sedatives and hypnotics [10]. In some studies, NMPDU of anti-anxiety medications was associated with other substance use/ abuse, such as tobacco smoking, alcohol consumption, and the use of psychoactive substances [11]. Anti-anxiety medications are commonly used for self-medication. In these cases, medication is taken for the main pharmaceutical indication which excludes taking the medication with alcohol, other medications or by alternative ways of administration [12].

The prevalence of the use of anti-anxiety medications in Serbia has been examined as a part of different national health surveys, and has been shown to vary from 13.7%, in 2000, to 13.4%, in 2006, and 18.1%, in 2013 [13] among adults, i.e., persons above the age of 15 years.

Research conducted in Serbia so far has examined only the prevalence of the use of anti-anxiety medications, while, to the best of our knowledge, no study has examined the prevalence of NMPDU of anti-anxiety medications and the factors associated with the use of anti-anxiety medications and with NMPDU of anti-anxiety medications, among the adults in Serbia. Our study aimed to examine the prevalence of the use of anti-anxiety medications and the factors associated with the use and with NMPDU of these medications, among the adults in Serbia.

MATERIALS AND METHODS

The study is a secondary analysis of the two national surveys conducted in Serbia regarding the use of medications: the National Survey on Lifestyles in Serbia 2014 – Substance Abuse and Gambling and the National Survey on Lifestyles in Serbia 2018 – Substance Abuse and Gambling. The total number of participants was 7,385 [14].

Adults aged between 18 and 64 years comprised the population included in the study. The exclusion criteria were as follows: age under 18 years, persons serving prison sentences or persons institutionalized in other ways, such as patients in hospitals, people living in therapeutic communities or in social care centers, as well as homeless persons and persons living in illegal settlements.

Probability-proportional-to-size sampling (PPS) was applied in both studies. In the first step of PPS, territorial units were randomly chosen based on the likelihood which was proportional to the population size. In the second step, households were randomly chosen in each territorial unit, with the national household registry used as a sampling frame. The third step was the random selection of one participant from each household with the use of Kish grids. The national representative sample was obtained by using weighting by sex, age, education, region, and type of settlement.

The instrument used was a questionnaire composed of 158 questions, of which 35 questions were used for this study. The questions referred to socio-demographic characteristics (10 questions), the Kessler psychological distress scale – K6 (6 questions) [15] which we refer to as the K10 and K6, were constructed from the reduced set of questions based on Item Response Theory models. The scales were subsequently validated in a two-stage clinical reappraisal survey (N = 1000 telephone screening interviews in the first stage followed by N = 153 face-to-face clinical interviews in the second stage that oversampled first-stage respondents who screened positive for emotional problems, gambling assessed with the Problem Gambling Severity Index (9 questions) [16] non-problem, low-risk, moderate-risk and problem gamblers, only the latter category underwent any validity testing during the scale’s development, despite the fact that over 95% of gamblers fall into one of the remaining three categories. Using Canadian population data on over 25,000 gamblers, we conducted a comprehensive validity and reliability analysis of the four PGSI gambler types. The temporal stability of PGSI subtype over a 14-month interval was modest but adequate (intraclass correlation coefficient = 0.63, alcohol and tobacco use (3 questions), psychoactive substance use (1 question), opiate use (1 question), and the use of anti-anxiety medications (5 questions).

Self-perceived financial status was assessed with the question: “How would you describe your financial status?” (Possible answers: very poor, poor, average, good, very good). Alcohol consumers were all participants who reported alcohol consumption during the previous 12 months, which was determined with the question: “Did you consume any alcoholic beverages during the previous 12 months?” (Possible answers: Yes/No). Binge drinking was defined as consuming a total of 60 g of pure alcohol, on one occasion, at least once during the previous 12 months. (Details on the definition of binge drinking in this research have been published elsewhere) [17].

A total of 13 variables were analyzed: age, sex, year of survey, type of residence, education, marital status, employment status, religion, satisfaction with health status, self-perceived financial status, Kessler distress score, alcohol consumption, binge drinking, smoking status, high risk gambling.

The data are presented with absolute numbers and frequencies. Based on the answer to the question: “During the past 12 months, when you used anti-anxiety medications, how did you obtain them?”, participants were divided into the three groups. The first group was composed of participants who reported no use of anti-anxiety medications in the past 12 months, i.e., the ‘no use group’ (N = 6,018 participants). The second group included participants who reported prescription only use (N = 995). The final group was the group with participants who reported the use of these medications without a prescription, i.e., the ‘NMPDU group’ (N = 372).

The ethics committee of the Institute of Public Health of Serbia approved the National Survey on Lifestyle – Substance Abuse and Gambling 2014 (No. 178/1, January 16, 2014).

The chi-square test was used to examine the differences in characteristics of the participants in the three groups. The multinomial logistic regression model included all variables which were shown to be significant in the type of sedative and hypnotics use as an outcome variable, with the ‘no use of sedatives and hypnotics’ as a reference group. Statistical analyses were done in the Statistical Package for Social Science, SPSS 22.0.

RESULTS

The prevalence of prescription only use of anti-anxiety medications was 13.5% (995/7,385), while the prevalence of non-medical prescription drug use was 5.04% (372/7,385).

There were significant differences between the sexes in the frequency of prescription only use and non-medical prescription drug use (p < 0.001). Among the participants who reported prescription only use, there were 71.7% women, while among the participants who reported non-medical use of anti-anxiety medications, 68.8% were women.

The prevalence of non-medical prescription use of anti-anxiety medications was the highest among the participants aged between 45 and 54 years. The socio-demographic, socio-economic, and lifestyle characteristics of the participants from all three groups are presented in Table 1.

Table 1. Characteristics of the participants from all three groups

nemedicinska upotreba 1 1

nemedicinska upotreba 1 2

A majority of the participants who reported non-medical prescription use of anti-anxiety medications reported obtaining them from a friend or family member (129: 1.7%), followed by the combination of prescription use and buying the anti-anxiety medications in a pharmacy without a prescription (88; 1.2%). The modalities of obtaining anti-anxiety medications are presented in Table 2.

Table 2. The modality of obtaining anti-anxiety medications

 nemedicinska upotreba 2

Multinomial logistic regression analysis showed that there was an association between prescription only use and the female sex (OR: 2.85, 95%CI: 2.28 – 3.56); the age between 25 and 34 years (OR: 2.82, 95% CI: 1.67 – 4.77), the age between 35 and 44 years (OR: 6.46, 95% CI: 3.76 – 11.09), the age between 45 and 54 years (OR: 6.68, 95%CI: 3.38 – 11.47), and the age between 55 and 64 years (OR: 16.26, 95% CI: 9.73 – 27.16), as compared to the age between 18 and 24 years; being unemployed (OR: 0.71, 95% CI: 0.53 – 0 .96), as compared to being a student/retired; reporting low (OR: 4.29, 95% CI: 3.22 – 5.72) or average (OR: 2.73, 95% CI: 2.14 – 3.48) satisfaction with health status; reporting no binge drinking in the past 30 days (1.69, 95% CI: 1.30 – 2.53); being a smoker (OR: 1.48, 95 % CI: 1.21 – 1.81); and having moderate (OR: 2.08, 95% CI: 1.62 – 2.65) or high (OR: 3.57, 95% CI: 2.45 – 5.20) psychological distress (Table 3).

Table 3. The multinomial logistic regression analysis with the type of use of anti-anxiety medications as an outcome variable

nemedicinska upotreba 3

Multinomial logistic regression analysis showed an association between non-medical prescription use of anti-anxiety medications and the female sex (OR: 3.23, 95% CI: 2.33 – 4.41); the age between 35 and 44 years (OR: 1.91, 95% CI: 1.10 – 3.30), the age between 45 and 54 years (OR: 2.40, 95% CI: 1.39 – 4.13), and the age between 55 and 64 years (OR: 2.97, 95% CI: 1.73 – 5.10); reporting low (OR: 2.40 95% CI: 1.60 – 3.61) or average (OR: 1.67, 95% CI: 1.17 – 2.36) satisfaction with health status; being a smoker (OR: 1.62, 95% CI: 1.23 – 2.13); having moderate (OR: 2.35, 95% CI: 1.71 – 3.24) or high (OR: 4.56, 95% CI: 2.87 – 7.25) psychological distress; and having a low/moderate risk of pathological gambling (OR: 1.86, 95% CI: 1.20 – 3.14).

DISCUSSION

Our study showed that almost one in four adults in Serbia used anti-anxiety medications in the past 12 months, and one-quarter of them reported NMPDU. The lifetime prevalence of NMPDU of anti-anxiety medications in the USA varies from 2.3% to 18% [18]. NMPDU of anti-anxiety medications has received increasing attention in European countries as well, and our prevalence is within the reported range for European countries (2.8% – 9.2%) [5] and is similar to the prevalence reported in the United Kingdom (5.7%) [5].

The most common modality for obtaining anti-anxiety medications among patients with NMPDU was from friends and family members and buying medication in a pharmacy along with prescription use, or without prescription use. Other studies have also shown that a majority of NMPD users obtain medication from family and friends, which calls for the implementation of population educational interventions [19],[20]. The Internet was not commonly used for obtaining anti-anxiety medications in our study, and only three participants reported this modality of acquiring these medications. Internet purchase of anti-anxiety medications has received increasing attention in the past few years, but online purchasing is still not developed in Serbia [21].

In our study, multinomial logistic regression analysis showed that women had more than a three times higher likelihood for NMPDU and almost a three times higher likelihood for prescription only use, as compared to men. The results from previous studies related to the differences regarding sex in NMPDU are inconsistent, as some have shown no difference between the sexes, some have shown a higher prevalence among men [22], and in some, as is the case with our study, the prevalence was higher among women [23] 837 individuals, aged 12 to 64 year, completed anonymously a computer-assisted self-interview. Past-year prescription drug use was divided into medical use only (MUO. The higher likelihood of prescription only use among women is in keeping with the growing concern among researchers studying anti-anxiety medication use. Researchers have expressed concerns about the increase in the number of prescriptions issued to women for anti-anxiety medications, as well as about the disparity in the diagnoses of anxiety disorders among sexes [24]. The overprescribing of anti-anxiety medications can subsequently lead to NMPDU, as some patients do not stop taking the medication prescribed after the end of treatment, which is a cause for concern, as women are often prescribed anti-anxiety medications [19]. The characteristic of female NMPD users is that the most common reason for NMPDU is self-medication [25].

In our study, participants older than 35 years had almost a twice higher likelihood of NMPDU, as compared to younger adults (aged 18 to 24 years), and the likelihood of NMPDU increased with age. There was also a higher likelihood of prescription only use among all age groups, as compared to the adults aged 18 to 24 years. This result is in contrast with the results from previous studies, as they showed a higher risk of NMPDU among adults younger than 35 years. However, this finding is not surprising, as it is to be expected that older adults are more likely to be prescribed anti-anxiety medications, which later leads to continuous treatment with these medications and NMPDU [19]. Additionally, Serbia went through international sanctions, embargo, and war during the 1990s, all of which may have influenced the mental health of the population that was over 35 years of age at the time of our study. Many were prescribed anti-anxiety medications during the 1990s and may have just continued using them without a prescription.

There was no significant association between employment status and NMPDU, but we found a significant association between employment status and prescription only use. Unemployed participants had a lower likelihood of prescription only use in our study. Previously, unemployment was shown as a detrimental factor for mental well-being [26] the psychological mechanisms involved are not very clear. This study examines the roles of social support and coping strategies as mediators of the association between employment status and mental health, as well as gender and age differences as moderators. Residents from the epidemiological catchment area of southwest Montreal responded to a randomized household survey for adults in 2009. A follow-up was conducted based on participants’ employment status 2 and 4 years later. ANOVAs tests were computed with SPSS to evaluate group differences, and structural equation modeling was performed with AMOS to test mediation effects. At baseline, among participants between 18 and 64 years old (n = 2325, while employed individuals were reported to have more social support and less exposure to distress [26] the psychological mechanisms involved are not very clear. This study examines the roles of social support and coping strategies as mediators of the association between employment status and mental health, as well as gender and age differences as moderators. Residents from the epidemiological catchment area of southwest Montreal responded to a randomized household survey for adults in 2009. A follow-up was conducted based on participants’ employment status 2 and 4 years later. ANOVAs tests were computed with SPSS to evaluate group differences, and structural equation modeling was performed with AMOS to test mediation effects. At baseline, among participants between 18 and 64 years old (n = 2325. Multinomial logistic regression analysis did not show any significant association between prescription only use or NMPDU and religiousness. Previous studies have found an association between being religious and lower substance use [27]we question whether religious culture impacts the veracity of self-reported substance use. The primary aim of this study of low-income pregnant women in South Central Appalachia was to determine the accuracy of self-reported substance use in pregnant women as well as to determine whether there were differences in use rates and/or differences in the degree to which women would accurately report substance use depending on their religiousness. Self-reported use and toxicology screening results taken from a larger prospective, longitudinal, smoking cessation study were compared for five substances (cannabinoids [marijuana or other cannabinoids], benz/ barb/sed [including benzodiazepines, barbiturates, or any sedative], opioids [including heroin, methadone or other medication-assisted treatment medications, or other opiates], crack/cocaine [crack or cocaine], and meth/amph [including methamphetamine or any other amphetamine].

In our study, smokers had an almost two times higher likelihood of reporting NMPDU in the previous year, as compared to those who did not use anti-anxiety medications, which has also been reported previously [19]. The previously reported association with poor mental health [19] was proven in our study as well, as participants from the NMPDU group had more than a two times higher likelihood of moderate psychological distress and an almost five times higher likelihood of high psychological distress. These findings support the assumption that anti-anxiety medications are often used for self-medicating of perceived mental health problems [19].

Prescription only users of anti-anxiety medications in our study had a lower likelihood of binge drinking, while the association between NMPDU and alcohol consumption and binge drinking was not significant, which might also support the assumption that NMPDU among the general population of Serbia is associated with self-medication rather than with euphoria seeking or non-therapeutic effects of anti-anxiety medications. The association between gambling and sedative use was proven for adolescents [28], while our study showed the association between low/moderate gambling and NMPDU. Mood disorders and anxiety disorders are associated with problem gambling and were shown to predict future problem gambling. The association between prescription only use and highrisk gambling can support the relationship with existing psychiatric comorbidities, predicting the gambling problem and directing prevention efforts [29].

One of the limitations of this study is its crosssectional design as it does not allow the establishing of causal relationships. We did not have the data on the frequency or dose of anti-anxiety medications used, either for prescribed medications or for NMPDU, which would have allowed a better understanding of the doseresponse relationship. The data were self-reported, and there might have been a recall bias. Although the study was anonymous, participants might have given socially acceptable answers, which would have lowered the prevalence of NMPDU. Another limitation may be that we did not include the questions to assess the possible misuse of one’s own prescription, which may have underestimated the prevalence of NMPDU in our sample. Also, we did not include people in prisons, or persons institutionalized in other ways, such as patients in hospitals, people living in therapeutic communities, or in social care centers, as well as homeless persons and persons living in illegal settlements, who may be at higher risk of NMPDU. Nevertheless, this seems, to the best of our knowledge, to be the first study on NMPDU of anti-anxiety medications on a large, nationally representative sample of adults in Serbia, and the first to examine the factors associated with it.

CONCLUSION

Our study showed that one out of twenty adults in Serbia reported NMPDU of anti-anxiety medications during the previous 12 months and that these medications were most commonly obtained through friends or family members. The prevalence of NMPDU of anti-anxiety medications and the modalities of obtaining these medications suggest that there is a need for including health care professionals and media in the education of patients regarding the risks of self-medication, medication exchange or illegal purchase of these medications. Improvement of the system for monitoring the prescription and especially the distribution of anti-anxiety medications is urgently needed.

Submission declaration and verification

This article has not been published elsewhere and is not under consideration for publication elsewhere.

  • Conflict of interest:
    Authors declare no conflict of interest.

Informations

Volume 4 No 3

September 2023

Pages 209-221
  • Keywords:
    NMPDU, anti-anxiety medications, Serbia, factors
  • Received:
    15 May 2023
  • Revised:
    19 June 2023
  • Accepted:
    22 June 2023
  • Online first:
    25 September 2023
  • DOI:
  • Cite this article:
    Terzić Šupić Z, Todorović J, Kilibarda B, Mravčik V. Non-medical prescription drug use in Serbia: Results from the national survey on lifestyles: Substance abuse and gambling. Serbian Journal of the Medical Chamber. 2023;4(3):209-21. doi: 10.5937/smclk4-44519
Corresponding author

Zorica Terzić-Šupic
University of Belgrade, Faculty of Medicine, Institute of Social Medicine
15 Dr Subotića Street, 11000 Belgrade, Serbia
E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.


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REFERENCES

1. Cunliffe J, Décary-Hêtu D, Pollak TA. Nonmedical prescription psychiatric drug use and the darknet: A cryptomarket analysis. Int J Drug Policy. 2019;73:263–72. [CROSSREF]

2. Substance Abuse and Mental Health Services Administration Center for Behavioral Health Statistics and Quality. RESULTS FROM THE 2016 NATIONAL SURVEY ON DRUG USE AND HEALTH: DETAILED TABLES. Rockville; 2017.

3. Casati A, Sedefov R, Pfeiffer-Gerschel T. Misuse of medicines in the European union: A systematic review of the literature. Eur Addict Res. 2012;18(5):228– 45. [CROSSREF]

4. Gomez AF, Barthel AL, Hofmann SG. Comparing the Efficacy of Benzodiazepines and Serotonergic Anti-Depressants for Adults with Generalized Anxiety Disorder: A meta-analytic review. Expert Opin Pharmacother. 2018;19(8):883–94. [CROSSREF]

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6. Mathews B, Yang C, Lehman EB, Mincemoyer C, Verdiglione N, Levi BH. Educating early childhood care and education providers to improve knowledge and attitudes about reporting child maltreatment : A randomized controlled trial. PlosOne. 2017;1–20. [CROSSREF]

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12. Boyd CJ, McCabe SE. Coming to terms with the nonmedical use of prescription medications. Subst Abus Treat Prev Policy. 2008;3:1–3. [CROSSREF]

13. Republic Institute of Public Health of Serbia “Dr Milan Jovanovic Batut.” National Health Survey 2013. 2014.

14. Kilibarda Biljana NN. Istraživanje o stilovima života stanovništva Srbije 2018. godine. 2018.

15. Kessler RC, Andrews G, Colpe LJ, Hiripi E, Mroczek DK, Normand SLT, et al. Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol Med [Internet]. 2002;32(6):959– 76. Dostupno: http://www.ncbi.nlm.nih.gov/pubmed/12214795 [CROSSREF]

16. Currie SR, Hodgins DC, Casey DM. Validity of the Problem Gambling Severity Index Interpretive Categories. J Gambl Stud. 2013;29(2):311–27. [CROSSREF]

17. Pakovic L, Todorovic J, Santric-Milicevic M, Bukumiric D, Terzic-Supic Z. The association between social characteristics, alcoholic beverage preferences, and binge drinking in a Serbian adult population. Nord Stud Alcohol Drugs [Internet]. 2018;145507251880328. Dostupno: http://journals.sagepub.com/ doi/10.1177/1455072518803281 [CROSSREF]

18. Schmitz A. Benzodiazepine use, misuse, and abuse: A review. Ment Heal Clin. 2016;6(3):120–6. [CROSSREF]

19. Abrahamsson T, Hakansson A. Nonmedical Prescription Drug Use (NMPDU) in the Swedish General Population—Correlates of Analgesic and Sedative Use. Subst Use Misuse [Internet]. 2015;50(2):148–55. Dostupno: http://www.tandfonline.com/doi/full/10.3109/10826084.2014.962047 [HTTP]

20. Boyd CJ, West B, McCabe SE. Does misuse lead to a disorder? The misuse of prescription tranquilizer and sedative medications and subsequent substance use disorders in a U.S. longitudinal sample. Addict Behav. 2018;79(November 2017):17–23. [CROSSREF]

21. Norbutas L. Offline constraints in online drug marketplaces: An exploratory analysis of a cryptomarket trade network. Int J Drug Policy. 2018;56(March):92–100. [CROSSREF]

22. National Institute on Drug Abuse. Misuse of Prescription Drugs. 2018. p. 1–39.

23. Chen LY, Chen YL, Tsay WI, Wu SC, Chen YT, Hsiao PC, et al. Nonmedical prescription drug use of analgesics and sedatives/hypnotics in Taiwan: Results from the 2014 National Survey of Substance Use. Prev Med Reports. 2019;15(March):100900. [CROSSREF]

24. Knight KR. Women on the Edge: Opioids, Benzodiazepines, and the Social Anxieties Surrounding Women’s Reproduction in the U.S. “Opioid Epidemic.” Contemp Drug Probl. 2017;44(4):301–20. [CROSSREF]

25. Cutler KA. Beauty and Care Versus Fun and Flair: Applying a Gendered Theory of Offending to College Students’ NMPDU. Deviant Behav. 2016;37(10):1132– 51. [CROSSREF]

26. Perreault M, Touré EH, Perreault N, Caron J. Employment Status and Mental Health: Mediating Roles of Social Support and Coping Strategies. Psychiatr Q. 2017;88(3):501–14. [CROSSREF]

27. Clements AD, Cyphers NA. Prenatal substance use: Religious women report lower use rates, but do they use less? J Prev Interv Community. 2020;48(1):47–63. [CROSSREF]

28. Grant JE, Lust K, Christenson GA, Redden SA, Chamberlain SR. Gambling and its clinical correlates in university students. Int J Psychiatry Clin Pract. 2019;23(1):33–9. [CROSSREF]

29. Sundqvist K, Rosendahl I. Problem Gambling and Psychiatric Comorbidity-Risk and Temporal Sequencing Among Women and Men: Results from the Swelogs Case-Control Study. J Gambl Stud. 2019;35(3):757–71. [CROSSREF]

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8. Substance Abuse and Mental Health Services Administration. Key substance use and mental health indicators in the United States: Results from the 2018 National Survey on Drug Use and Health. HHS Publ No PEP19-5068, NSDUH Ser H-54. 2019;170:51–8.

9. Wheeler P, Stevens-Watkins D, Knighton J. Pre-Incarceration Rates of Nonmedical Use of Prescription Drugs among Black Men from Urban Counties. 2018;95(4):444–53. [CROSSREF]

10. Drazdowski TK. A systematic review of the motivations for the non-medical use of prescription drugs in young adults. Drug Alcohol Depend. 2016;162(2016):3–25. [CROSSREF]

11. Nattala P, Murthy P, Thennarasu K, Cottler L. Nonmedical use of sedatives in urban Bengaluru. Indian J Psychiatry [Internet]. 2014;56(3):246. Dostupno: http://www.indianjpsychiatry.org/text.asp?2014/56/3/246/140619 [HTTP]

12. Boyd CJ, McCabe SE. Coming to terms with the nonmedical use of prescription medications. Subst Abus Treat Prev Policy. 2008;3:1–3. [CROSSREF]

13. Republic Institute of Public Health of Serbia “Dr Milan Jovanovic Batut.” National Health Survey 2013. 2014.

14. Kilibarda Biljana NN. Istraživanje o stilovima života stanovništva Srbije 2018. godine. 2018.

15. Kessler RC, Andrews G, Colpe LJ, Hiripi E, Mroczek DK, Normand SLT, et al. Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychol Med [Internet]. 2002;32(6):959– 76. Dostupno: http://www.ncbi.nlm.nih.gov/pubmed/12214795 [CROSSREF]

16. Currie SR, Hodgins DC, Casey DM. Validity of the Problem Gambling Severity Index Interpretive Categories. J Gambl Stud. 2013;29(2):311–27. [CROSSREF]

17. Pakovic L, Todorovic J, Santric-Milicevic M, Bukumiric D, Terzic-Supic Z. The association between social characteristics, alcoholic beverage preferences, and binge drinking in a Serbian adult population. Nord Stud Alcohol Drugs [Internet]. 2018;145507251880328. Dostupno: http://journals.sagepub.com/ doi/10.1177/1455072518803281 [CROSSREF]

18. Schmitz A. Benzodiazepine use, misuse, and abuse: A review. Ment Heal Clin. 2016;6(3):120–6. [CROSSREF]

19. Abrahamsson T, Hakansson A. Nonmedical Prescription Drug Use (NMPDU) in the Swedish General Population—Correlates of Analgesic and Sedative Use. Subst Use Misuse [Internet]. 2015;50(2):148–55. Dostupno: http://www.tandfonline.com/doi/full/10.3109/10826084.2014.962047 [HTTP]

20. Boyd CJ, West B, McCabe SE. Does misuse lead to a disorder? The misuse of prescription tranquilizer and sedative medications and subsequent substance use disorders in a U.S. longitudinal sample. Addict Behav. 2018;79(November 2017):17–23. [CROSSREF]

21. Norbutas L. Offline constraints in online drug marketplaces: An exploratory analysis of a cryptomarket trade network. Int J Drug Policy. 2018;56(March):92–100. [CROSSREF]

22. National Institute on Drug Abuse. Misuse of Prescription Drugs. 2018. p. 1–39.

23. Chen LY, Chen YL, Tsay WI, Wu SC, Chen YT, Hsiao PC, et al. Nonmedical prescription drug use of analgesics and sedatives/hypnotics in Taiwan: Results from the 2014 National Survey of Substance Use. Prev Med Reports. 2019;15(March):100900. [CROSSREF]

24. Knight KR. Women on the Edge: Opioids, Benzodiazepines, and the Social Anxieties Surrounding Women’s Reproduction in the U.S. “Opioid Epidemic.” Contemp Drug Probl. 2017;44(4):301–20. [CROSSREF]

25. Cutler KA. Beauty and Care Versus Fun and Flair: Applying a Gendered Theory of Offending to College Students’ NMPDU. Deviant Behav. 2016;37(10):1132– 51. [CROSSREF]

26. Perreault M, Touré EH, Perreault N, Caron J. Employment Status and Mental Health: Mediating Roles of Social Support and Coping Strategies. Psychiatr Q. 2017;88(3):501–14. [CROSSREF]

27. Clements AD, Cyphers NA. Prenatal substance use: Religious women report lower use rates, but do they use less? J Prev Interv Community. 2020;48(1):47–63. [CROSSREF]

28. Grant JE, Lust K, Christenson GA, Redden SA, Chamberlain SR. Gambling and its clinical correlates in university students. Int J Psychiatry Clin Pract. 2019;23(1):33–9. [CROSSREF]

29. Sundqvist K, Rosendahl I. Problem Gambling and Psychiatric Comorbidity-Risk and Temporal Sequencing Among Women and Men: Results from the Swelogs Case-Control Study. J Gambl Stud. 2019;35(3):757–71. [CROSSREF]


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