Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2018 Feb 1.
Published in final edited form as: Addict Behav. 2016 Aug 30;65:236–241. doi: 10.1016/j.addbeh.2016.08.033

Prescription opioid use disorder and heroin use among youth nonmedical prescription opioid users from 2002 to 2014

Silvia S Martins a,*, Luis E Segura a, Julian Santaella-Tenorio a, Alexander Perlmutter a, Miriam C Fenton b, Magdalena Cerdá d, Katherine M Keyes a, Lilian A Ghandour f, Carla L Storr e, Deborah S Hasin a,c
PMCID: PMC5140701  NIHMSID: NIHMS816880  PMID: 27614657

1. Introduction

Trend analyses of prescription opioids in the U.S. indicate use, especially use of prescription opioids stronger than morphine, has more than doubled among adults since the early 1990’s (Frenk, Porter, & Paulozzi, 2015). Prescription opioids, like Oxycontin®, are effective pharmacological treatments for acute and chronic pain (Fitzcharles & Shir, 2009; Gallagher & Rosenthal, 2008). When used as indicated, these medications can be an important component of pain management. However, their high abuse potential presents concerns regarding their nonmedical use, which can be defined as ‘use of a prescription opioid that was not prescribed, or taken for the experience or feeling it caused’ (SAMHSA, 2014). In the United States, nonmedical use of prescription opioids (NMPO) is increasingly recognized as a serious public health problem among adults (Blanco et al., 2007; Han et al., 2015; Huang et al., 2006). Nonmedical prescription drug use, specifically nonmedical use of prescription opioids, is also a growing problem in other countries such as Canada (Fischer, Gooch, Goldman, Kurdyak, & Rehm, 2014; Fischer, Ialomiteanu, Kurdyak, Mann, & Rehm, 2013) and Australia (Degenhardt et al., 2006; Rintoul, Dobbin, Drummer, & Ozanne-Smith, 2011).

Repeated NMPO use increases the risk of developing an opioid use disorder. Studies have shown that adults using prescription opioids as prescribed by a doctor to treat chronic pain are less likely to develop DSM-IV dependence (Minozzi, Amato, & Davoli, 2013) compared to nonmedical opioid users (Compton, Dawson, Goldstein, & Grant, 2013; Huang et al., 2006; Peer et al., 2013; SAMHSA, 2009). Thus, it is important to detect NMPO use early before clinical problems emerge. Nearly 80% of 12–21 year olds who reported initiation of heroin use had previously initiated NMPO between the ages 13–18 (Cerdá et al., 2015). In general household population samples of past-year NMPO users in the U.S., approximately 7% and 9% adolescents met criteria for prescription opioid abuse and dependence, respectively (Wu et al., 2011), and 11% of the past-year NMPO users between ages 18–34 met criteria for prescription opioid use disorder (Becker et al., 2008).

Given this and the high probability of nonmedical use among adolescents and young adults, the potential development of prescription opioid use disorder secondary to nonmedical use among youth represents an important and growing public health concern. Still, no study has investigated time trends, specifically if prescription opioid use disorder has increased in the past decade among adolescents, emerging adults and young adults who are nonmedical users of prescription opioids.

Heavy use of prescription opioids can affect neurodevelopment during critical periods from in utero through adolescence and into young adulthood (Chambers, Taylor, & Potenza, 2003; Uebel et al., 2015). Data from Monitoring the Future (MTF) have shown that late high school (12th grade) medical PO use is associated with adult onset of NMPO use (Miech, Johnston, O’Malley, et al., 2013), while other MTF research has shown declining NMPO use into young adulthood after NMPO use in high school (McCabe, Schulenberg, O’Malley et al., 2014). Further, opioid use disorders can impact all aspects of adolescents’ and young adults’ lives, including family, school, and the acquisition of adult roles and responsibilities (Boyd, McCabe, & Teter, 2006; Wu, Blazer, Li, & Woody, 2011; Wu, Ringwalt, Mannelli, & Patkar, 2008). Despite research findings that young adulthood is a period of high vulnerability to drug effects (Hwang et al., 2013), adolescent susceptibility to drug effects might be even greater due to adolescent physiological and social transitions (Rudolph, Lambert, Clark, & Kurlakowsky, 2001). Thus, it is important to examine patterns of prescription opioid use disorder in different developmental periods including adolescence, the transition from adolescence to adulthood and early adulthood.

In addition, previous studies have shown that NMPO use is a risk factor for subsequent heroin use (Becker, Sullivan, Tetrault, Desai, & Fiellin, 2008; Compton, Jones, & Baldwin, 2016; Fogger & McGuinness, 2015; Jones, 2013; SAMHSA, 2011). This is of particular concern given that, in the U.S., the number of individuals aged 18–25 with past-year heroin dependence has almost doubled between 2002–2005 and 2009–2011 (SAMHSA, 2012a). Also, the number of adolescents that are dependent on heroin increased significantly by more than 50% (from 8,000 to 13,000) (SAMHSA, 2012a). Previous research has also found an increased use of heroin among youth that have initiated using prescription opioids nonmedically early in their adolescence, with a peak period of heroin initiation at age 17–18 (Cerdá, Santaella, Marshall, Kim, & Martins, 2015).

Using U.S. nationally representative population-based data (2002 to 2014) on adolescents (12–17 yrs.), emerging adults (18–25 yrs.) and young adults (26–34 yrs.), we sought to answer the following research questions: 1) Were there significant changes between 2002 and 2014 in past-year prescription opioid use disorder secondary to NMPO use among those who were nonmedical PO users? 2) Were there significant changes between 2002 and 2014 in past-year heroin use among individuals who were NMPO users? Examining changes in prescription opioid use disorder secondary to prescription opioid use over time and heroin use among NMPO users is important for informing policies related to prescription opioid use as well as evidence-based prevention and treatment strategies (NSDUH, 2016). A closer look at earlier critical developmental periods—in particular adolescence and young adulthood—is warranted if we want to curb the increasing morbidity and mortality associated with NMPO use.

2. Materials and Methods

2.1. Sample

Data were derived from the 2002 to 2014 National Survey on Drug Use and Health (NSDUH) specifically focusing on youth who were NMPO users: 12–17 years old (N=15,308), 18–25 years old (N=25,751), and 26–34 years old (N=5,121). The NSDUH is sponsored by the Substance Abuse and Mental Health administration (SAMHSA) and is designed to provide annual prevalence estimates of nonmedical use of legal and illegal drugs in the household population 12 years of age and older in the United States (SAMHSA, 2012a). The survey employs a 50 state design with an independent multistage area probability sample for each state and the District of Columbia and oversamples younger age groups (aged 12–25) as well as African-Americans and Hispanics. Response rates varied between 81.94–91.00% for weighted screening response rate, and between 71.2–79.00%, for weighted interview response rate. Interviews were administered by a trained interviewer using computer-assisted personal interviewing (CAPI). Drug sections were administered more privately using audio computer-assisted self-interviewing (ACASI) to increase the level of honest reporting of illegal drug use and other sensitive behaviors (Morral, McCaffrey, & Chien, 2003). Participants were offered a $30 incentive. Detailed information about the sampling and survey methodology of NSDUH can be found elsewhere (SAMHSA, 2012a).

2.2. Measures

2.2.1. Past-year nonmedical use of prescription opioids

The survey includes a stem question that first determines if NMPO use occurred: “These questions are about prescription pain reliever use. We are not interested in your use of over-the-counter pain relievers that can be bought in stores without a doctor’s prescription.” Participants endorsed if they had used any NMPO in the past-year by answering: “how long has it been since you last used any prescription pain reliever that was not prescribed for you or that you took only for the experience or feeling it caused” (SAMHSA, 2012a). To improve the quality of reporting, participants were given a card with names of prescription opioids (non-opioid medications are not included). Respondents were asked a series of follow-ups question on specific drugs included in this class.

Past-year heroin use

Participants were asked if they had used heroin during the past 12 months. Individuals were classified as past-year heroin users if they endorsed using heroin at least once during the previous 12 months.

2.2.2. Prescription opioid use disorder

Information on past-year prescription opioid abuse and dependence was obtained from a set of structured questions based on criteria for substance disorders from the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) (American Psychiatric Association, 2000). The NSDUH provides a summary variable for prescription opioid use disorder based on whether the respondent endorsed 1 of the 4 abuse questions and/or 3 of the 7 dependence questions. Probable disorder diagnosis based on these questions has been found to have good agreement with clinical judgement (Jordan, Karg, Batts, Epstein, & Wiesen, 2008).

2.2.3. Covariates

The covariates considered for adjustment were the respondents’ sex, race/ethnicity (Whites, Blacks, Hispanics, Asians, and Other race/ethnicity), and calendar year of interview (2002–2014).

2.3. Data Analyses

Data were analyzed using STATA 13.0 (STATA, 2013). Weights were included to reflect the complex design of the NSDUH/NHSDA sample. We used Taylor series linearization estimation methods (Stata ‘svy’ commands) to obtain standard errors for the cross-tabulations Past-year PO use disorder and past-year heroin use were our two main outcomes. First, we estimated the yearly increase in the odds ratio of past-year PO use disorder and heroin use among NMPO users, over time (2002 to 2014), using weighted logistic regression analyses adjusted for demographics (sex, race/ethnicity). Then, separately, we estimated the yearly prevalence of PO use disorder and heroin use by adjusting weighted linear regression models. We calculated the yearly trend (p-value for trend) by including year as a continuous variable in separate linear regression models.

3. Results

Among past-year NMPO users (aged 12–34 years), the majority of the respondents were Whites (70.80% vs. Blacks=9.61%, Hispanics=14.65%, Asians=2.05% and other race/ethnic group=2.89%). There were slightly more males than females (55.05% vs. 44.95). Overall, the past-year prevalence of NMPO use significantly decreased from 2002 to 2014 among adolescents (7.51% to 4.82%, p-value for trend <0.05), among emerging adults ages 18–25 (11.43% to 7.59%, p-value for trend <0.05), and among young adults ages 26–34 (6.18% to 6.08%, p-value for trend <0.05). Compared to 2002, the yearly prevalence of NMPO use in 2014 decreased 37% in adolescents (aOR=0.63; 95%CI=0.56–0.71), 34% in emerging adults (aOR=0.66; 95%CI=0.60–0.73), and remained unchanged in young adults (aOR=1.00; 95%CI=0.81–1.23).

3.1. Prescription opioid use disorder among NMPO users: changes in past-year prevalence

Figure 1 illustrates the prevalence of prescription opioid use disorder among NMPO users from 2002 to 2014. The prevalence of prescription opioid use disorder significantly increased among emerging adults aged 18–25 (11.98% to 15.11%, p-value for trend <0.05, aOR=1.37; 95%CI=1.03–1.81), and likewise from 2002 to 2014 among young adults aged 26–34 (11.27% to 23.52%, p-value for trend <0.05, aOR=2.43; 95%CI=1.56–3.78). Overall, during the study period, the difference in prescription opioid use disorder prevalence among NMPO users from 2002 to 2014 was 1.41% in adolescents, 3.13% in emerging adults and 12.25% in young adults (Figure 2). Among adolescents (12–17 years), the prevalence of prescription opioid use disorder remained relatively stable during the same period (Appendix A: Supplemental table 1). From 2002 to 2010 no significant trends were observed; from 2011 until 2014, emerging and young adults had a significantly higher prevalence of prescription opioid use disorder compared to adolescents (17.65%, aOR=1.62, 95%CI=1.29–2.05; 17.32%, aOR=1.66, 95%CI=1.01–2.72; 16.36%, aOR=1.41, 95%CI=1.05–1.90; respectively) (Appendix A: Supplemental Table 1).

Figure 1.

Figure 1

Open in a new tab

Adjusted prevalence of prescription opioid use disorder among past-year nonmedically prescription opioids users, stratified by age, in the U.S. household population

*Yearly adjusted prevalence compared to 2002, p < 0.05. Model adjusted for sex & ethnicity.

Figure 2.

Figure 2

Open in a new tab

Average change in the prevalence of prescription opioid use disorder, from 2002–2014, among NMPO users by age groups.

Y axis value of 0 represents the mean prevalence of prescription opioid use disorder in 2002 among NMPO users, which was 8.81% for adolescents, 9.37% for emerging adults, and 12.95% for young adults.

3.2. Heroin use among NMPO users: changes in past-year prevalence over time

Figure 3 shows past-year heroin use among past-year NMPO users, and we can see an increasing trend from 2002 to 2014 among emerging adults (2.11% to 7.35%, p-trend <0.05) and young adults (1.62% to 12.29%, p-trend <0.05). There is only a slight and non-significant increase in past-year heroin use among adolescents who were also NMPO users (1.80% to 2.30%, p-trend = 0.17, see Appendix A: Supplemental table 2). The difference in the prevalence of heroin use among NMPO users from 2002 to 2014 was 0.5%, 5.24% and 10.67% among adolescents, emerging adults and young adults, respectively (Figure 4). Overall, the prevalence of past-year heroin use among NMPO users increased four-fold in emerging adults (aOR=4.18; 95%CI=2.59–6.73) and nine-fold in young adults (aOR=9.09; 95%CI=2.96–27.95). Across the study period, the increment in past-year heroin use is more dramatically observed from 2012 onwards among emerging and young adults (see Appendix A: Supplemental Table 2; aOR=3.57; 95%CI=2.24–5.70, and aOR=3.61; 95%CI=1.05–12.42, respectively).

Figure 3.

Figure 3

Open in a new tab

Adjusted prevalence of heroin use among NMPO users in the U.S. household population (2002–14).

*Yearly adjusted prevalence compared to 2002, p < 0.05. Model adjusted for sex & ethnicity.

Figure 4.

Figure 4

Open in a new tab

Total percentage change from 2002 to 2014 in heroin use prevalence among NMPO users, in the U.S. household population, by age groups.

Y axis value of 0 represents the mean prevalence of heroin use in 2002 among NMPO users, which was 1.6% for adolescents, 2.89 for emerging adults, and 3.56 for young adults.

4. Discussion

The main findings of this study can be described as follows: 1) there was an increase in the probability of having a prescription opioid use disorder in the past year among past-year 18–34 year old NMPO users (compared to 2002, in 2014 there was a 37% increase in the odds of having a disorder for emerging adults and a doubling of the odds among young adults); 2) there was a four-fold and nine-fold increase over time in the odds of heroin use among emerging adults and young adults who were NMPO users, respectively; and 3) there were no significant changes prescription opioid use disorder secondary to NMPO use or heroin use among adolescent users.

Our study’s findings parallel the public health concern on the rise of prescription opioid and heroin overdoses and mortality (Ballantyne & Kolodny, 2015; CDC, 2012). To our knowledge, this is the first national study to analyze the time trends of prescription opioid use disorder and heroin use among NMPO users on a yearly basis among adolescents and emerging and young adults over a twelve-year time period. NMPO use is a common growing public health problem that is not limited to the United States; prescription opioid consumption doubled from 2004–2006 to 2010–2011 in the general population in Ontario, Canada (Fischer et al., 2014). Similarly, Australia’s general population experienced a 15-fold increase in NMPO, from 1992 to 2012 (Blanch, Pearson, & Haber, 2014). Research from different countries push forward a similar conclusion: there are important gaps in knowledge in prescription opioid use and, more specifically, in NMPO use to compute the health impact and inform interventions.

Moreover, our results show that trends of NMPO use in recent years, after 2008, among the U.S. general population are declining. This finding is in contrast with increases seen in the general U.S. population before 2007 according to national representative data (SAMHSA, 2008), and data from the Research Abuse, Diversion and Addiction-Related Surveillance (RADARS) System Poison Centers Program in the US that showed a linear increase in NMPO in adults aged 20 to 59 years between 2006–2013 (West, Severtson, Green, & Dart, 2015). Declines in NMPO use in the same period (2003–2014) have been seen among adolescents in the NSDUH after the year 2008 (Vaughn, Nelson, Salas-Wright, Qian, & Schootman, 2016), and in other datasets such as the Monitoring the Future (MTF), where declines after the same year (2008) in prescription opioid use (like Vicodin® and Oxycontin®) among 12th graders, college students and young adults were reported (Johnston, O’Malley, Bachman, Schulenberg, & Miech, 2016; Miech, Johnston, O’Malley, Bachman, & Schulenberg, 2016). Similarly, McCabe et al. reported declines in NMPO use among U.S. college students in the Midwest from 2003–2013 (McCabe, West, Teter, & Boyd, 2014). Our study not only expands the analyses of this trend by investigating prescription opioid use disorder secondary to use in across a 13-year span, but adds two important findings: 1) an increasing trend of this disorder found among young adult users aged 18–35; and 2) a parallel increasing trend in heroin use among NMPO users in the same age range.

Previous research in U.S. population 12 years and older, using NSDUH data, supports the relationship between prescription opioid and heroin use; an increase in heroin use was found among those reporting NMPO use between 2002–2005 and 2008–2011 (Martins, Santaella-Tenorio, Marshall, Maldonado, & Cerda, 2015). However, a separate analysis showed that 3.6% of NMPO users initiate heroin within five years of NMPO initiation and 4.2% of NMPO users also used heroin in the past-year (Compton et al., 2016). Our study is in accordance with past research (Blanco et al., 2007), as we found a worrisome increasing trend in heroin use among NMPO users, in particular in 18–34 year olds.

Although our study does not assess underlying causes, the increasing trend in prescription opioid use disorder observed in young adults might be at least partially explained by historical factors described elsewhere in the literature, such as: a shift in medical practice of prescribing opioids from end-of-life pain and cancer to chronic non-cancer pain, particularly in young adults (Franklin et al., 2015); an increased rate of opioid prescription by physicians due to a higher sensitivity to patient’s pain (CDC, 2012); the endorsement of pain as a “fifth vital sign” by the Joint Commission with a controverted pain metric (Franklin et al., 2015); an increased distribution of opioids by the pharmaceutical industry and creation of an opioid rich environment (Rintoul & Dobbin, 2014); state lobbying by pain advocates for prescription opioids use; physician sensitivity to pain exploitation by opioid users; as well as “doctor shopping” by patients (Ballantyne & Kolodny, 2015; CDC, 2012; Shepherd, 2014) and overprescribing (Compton et al., 2016), which leaves excess medications available for misuse or redistribution via nonmedical sanctioned venues. In addition, Friedman suggests that positive media attention, which fosters an image that prescription drug use is a routine aspect of everyday life, together with an increase in the pharmaceutical industry expenditures in direct-to-consumer advertising, has led to growing confidence in the safety of using prescription drugs nonmedically (i.e., ‘normalization” of nonmedical use of these drugs) (Friedman, 2006). This could be worrisome given normalization of attitudes and behaviors upon exposure to mass media, especially among impressionable youths (Montgomery, 2011).

Our study is not void of limitations including the fact that weights from the 2002–2010 NSDUH were calculated using the 2000 U.S. census data, while the 2011–2014 weights were based on 2010 census data. Although this might have slightly affected the comparability of estimates across years, evidence shows that the impact of this change on estimates are not substantial (SAMHSA, 2012a). Moreover, as in most large-scale epidemiologic surveys, information is based on self-report, and there might be recall bias in reporting both drug use and other sensitive behaviors (Morral et al., 2003), keeping in mind that our study was limited to use, and use disorder in the preceding year at each year. Still, respondents might under-report prescription opioid use disorder symptoms and their use of heroin which is a drug that has more stigma associated with it. Also, data to distinguish whether these NMPO users first started using these drugs when legitimately prescribed (e.g., pain relief) or when obtained illegally (i.e., to get high) are still unavailable in the NSDUH. Similarly, with the data used in this paper we cannot make real inferences on whether NMPO use preceded heroin use onset due to the cross-sectional nature of the annual NSDUH and the limited availability on data on age of onset (available only for respondents up to age 21). However, data on age of first use for heroin and NMPO is available in the NSDUH data sets. We ran post-hoc analyses among those that endorsed using NMPO and found that, among the three age groups, the vast majority had started using heroin after starting NMPO use. Specifically, 52.98% of those 12–17 years old, 78.51% of those 18–24 years old, and 69.16% of those 25–34 years old had higher age of onset for heroin use than for NMPO use (see Supplemental Table 3).

5. Conclusion

In conclusion, between 2002 and 2014, prescription opioid-related use disorders secondary to nonmedical use and heroin use among NMPO users increased among emerging and young adults. Although our descriptive analyses do not address the potential causes in the rise of these trends, it seeks to present the evidence in order to raise awareness and urgency to address these rising and problematic trends among youth. There is some evidence that increases in prescription opioid use disorder secondary to NMPO use might be rooted in health policy, medical practice, pharmaceutical industry interests and patient behavior (Belcher et al., 2014). While pain management is an important feature in the medical conversation and practice when patients are prescribed prescription opioids (Dowell, Haegerich, & Chou, 2016), it is imperative that the general public, particularly youth, are informed about the related harms and disorders that can occur when prescription opioids are used without regular medical supervision.

Supplementary Material

supplement
NIHMS816880-supplement.docx (100.6KB, docx)

Highlights.

  • Trends analyses were done in U.S. nonmedical prescription opioid users.

  • From 2002–14, opioid disorder increased in NMPO users ages 18–34.

  • Trends in heroin use increased significantly in 18–34 NMPO users.

  • There was no change in opioid disorder or heroin use among NMPO users ages 12–17.

  • Results call to action to stop these rising trends among NMPO youth.

Acknowledgments

Role of Funding Sources

NIDA DA031099 (Hasin); 1R01 HD060072 (Martins, Canino and Duarte), 1R01 DA037866-01 (Martins); K01 AA021511 (Keyes), New York State Psychiatric Institute (Hasin). Data come from the National Survey of Drug Use and Health (NSDUH) public use files made publicly available by the Substance Abuse and Mental Health Services.

Footnotes

Contributors

All authors have contributed significantly to the work and agree with the submission. Dr. Martins designed the study, directed Dr. Luis Segura and Dr. Santaella-Tenorio on the data analyses, and wrote the first full draft of the manuscript with their assistance. Drs. Segura and Mr. Alexander Perlmutter conducted the literature review, Dr. Santaella-Tenorio prepared the Methods sections of the text and Dr. Segura drafted the final version of the Results section. Dr. Miriam C. Fenton, Dr. Magdalena Cerdá, Dr. Katherine M. Keyes, Dr. Lilian A. Ghandour, Dr. Carla L. Storr, and Dr. Deborah S. Hasin critically reviewed and edited all sections of the manuscript.

Conflict of Interest

Dr. Hasin is Principal Investigator of a study on a measure of addiction to prescription opioids funded by InVentive Health Consulting, which combines support from nine pharmaceutical companies. All other authors have no conflict of interest to declare.

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Contributor Information

Silvia S. Martins, Email: ssm2183@columbia.edu.

Luis E. Segura, Email: les2196@cumc.columbia.edu.

Julian Santaella-Tenorio, Email: js4222@cumc.columbia.edu.

Alexander Perlmutter, Email: asp2183@cumc.columbia.edu.

Miriam C. Fenton, Email: miriamfenton@gmail.com.

Magdalena Cerdá, Email: cerda@ucdavis.edu.

Katherine M. Keyes, Email: kmk2104@cumc.columbia.edu.

Lilian A. Ghandour, Email: lg01@aub.edu.lb.

Carla L. Storr, Email: storr@son.umaryland.edu.

Deborah S. Hasin, Email: deborah.hasin@gmail.com.

References

  1. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition: DSM-IV-TR®. American Psychiatric Association; 2000. [Google Scholar]
  2. Ballantyne JC, Kolodny A. Preventing prescription opioid abuse. JAMA. 2015;313(10):1059. doi: 10.1001/jama.2015.0521. [DOI] [PubMed] [Google Scholar]
  3. Becker WC, Sullivan LE, Tetrault JM, Desai RA, Fiellin DA. Non-medical use, abuse and dependence on prescription opioids among U.S. adults: psychiatric, medical and substance use correlates. Drug and Alcohol Dependence. 2008;94(1–3):38–47. doi: 10.1016/j.drugalcdep.2007.09.018. [DOI] [PubMed] [Google Scholar]
  4. Belcher J, Nielsen S, Campbell G, Bruno R, Hoban B, Larance B, … Degenhardt L. Diversion of prescribed opioids by people living with chronic pain: results from an Australian community sample. Drug and Alcohol Review. 2014;33(1):27–32. doi: 10.1111/dar.12084. [DOI] [PubMed] [Google Scholar]
  5. Blanch B, Pearson S, Haber P. An overview of the patterns of prescription opioid use, costs and related harms in Australia. British Journal of Clinical Pharmacology. 2014;78(5):1159–66. doi: 10.1111/bcp.12446. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Blanco C, Alderson D, Ogburn E, Grant BF, Nunes EV, Hatzenbuehler ML, Hasin DS. Changes in the prevalence of non-medical prescription drug use and drug use disorders in the United States: 1991–1992 and 2001–2002. Drug and Alcohol Dependence. 2007;90(2–3):252–260. doi: 10.1016/j.drugalcdep.2007.04.005. [DOI] [PubMed] [Google Scholar]
  7. Boyd CJ, McCabe S, Teter CJ. Medical and nonmedical use of prescription pain medication by youth in a Detroit-area public school district. Drug and Alcohol Dependence. 2006;81(1):37–45. doi: 10.1016/j.drugalcdep.2005.05.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Boyd CJ, McCabe SE, Cranford JA, Young A. Adolescents’ motivations to abuse prescription medications. Pediatrics. 2006;118(6):2472–2480. doi: 10.1542/peds.2006-1644. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. CDC. Morbidity and Mortality Weekly Report: CDC Grand Rounds: Prescription Drug Overdoses—a U.S. Epidemic. 2012. [PubMed] [Google Scholar]
  10. Cerda M, Santaella J, Marshall BD, Kim JH, Martins SS. Nonmedical Prescription Opioid Use in Childhood and Early Adolescence Predicts Transitions to Heroin Use in Young Adulthood: A National Study. Journal of Pediatrics. 2015;167(3):605–612. doi: 10.1016/j.jpeds.2015.04.071. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Chambers RA, Taylor JR, Potenza MN. Developmental neurocircuitry of motivation in adolescence: a critical period of addiction vulnerability. American Journal of Psychiatry. 2003;160(6):1041–1052. doi: 10.1176/appi.ajp.160.6.1041. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Compton W, Dawson D, Goldstein R, Grant B. Crosswalk between DSM-IV dependence and DSM-5 substance use disorders for opioids, cannabis, cocaine and alcohol. Drug and Alcohol Dependence. 2013;132(1–2):387–90. doi: 10.1016/j.drugalcdep.2013.02.036. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Compton W, Jones C, Baldwin G. Relationship between Nonmedical Prescription-Opioid Use and Heroin Use. New England Journal of Medicine. 2016;374(2):154–163. doi: 10.1056/NEJMra1508490. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Degenhardt L, Black E, Breen C, Bruno R, Kinner S, Roxburgh A, … Fischer J. Trends in morphine prescriptions, illicit morphine use and associated harms among regular injecting drug users in Australia. Drug and Alcohol Review. 2006;25(5):403–12. doi: 10.1080/09595230600868504. [DOI] [PubMed] [Google Scholar]
  15. Dowell D, Haegerich TM, Chou R. CDC guideline for prescribing opioids for chronic pain—United States, 2016. JAMA. 2016;315(15):1624–1645. doi: 10.1001/jama.2016.1464. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Edlund MJ, Martin BC, Russo JE, DeVries A, Braden JB, Sullivan MD. The role of opioid prescription in incident opioid abuse and dependence among individuals with chronic noncancer pain: the role of opioid prescription. Clinical Journal of Pain. 2014;30(7):557–564. doi: 10.1097/AJP.0000000000000021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Fischer B, Gooch J, Goldman B, Kurdyak P, Rehm J. Non-medical prescription opioid use, prescription opioid-related harms and public health in Canada: an update 5 years later. Canadian Journal of Public Health. 2014;105(2):e146–9. doi: 10.17269/cjph.105.4143. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Fischer B, Ialomiteanu A, Kurdyak P, Mann RE, Rehm J. Reductions in non-medical prescription opioid use among adults in Ontario, Canada: are recent policy interventions working? Substance Abuse Treatment, Prevention, and Policy. 2013;8(1):1. doi: 10.1186/1747-597X-8-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Fitzcharles MA, Shir Y. Pain Management: Opioid guidelines: helpful for the rheumatologist? Nature Reviews Rheumatology. 2009;5(5):242–244. doi: 10.1038/nrrheum.2009.63. [DOI] [PubMed] [Google Scholar]
  20. Fogger S, McGuinness TM. Adolescents at risk: pain pills to heroin: part II. Journal of Psychosocial Nursing and Mental Health Services. 2015;53(2):27–30. doi: 10.3928/02793695-20150106-01. [DOI] [PubMed] [Google Scholar]
  21. Fortuna R, Robbins B, Caiola E, Joynt M, Halterman J. Prescribing of controlled medications to adolescents and young adults in the United States. Pediatrics. 2010;126(6):1108–16. doi: 10.1542/peds.2010-0791. [DOI] [PubMed] [Google Scholar]
  22. Franklin G, Sabel J, Jones C, Mai J, Baumgartner C, Banta-Green C, … Tauben D. A comprehensive approach to address the prescription opioid epidemic in Washington State: milestones and lessons learned. American Journal of Public Health. 2015;105(3):463–9. doi: 10.2105/AJPH.2014.302367. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Frenk SM, Porter KS, Paulozzi LJ. Prescription opioid analgesic use among adults: United States, 1999–2012. NCHS Data Brief. 2015;(189):1–8. [PubMed] [Google Scholar]
  24. Friedman RA. The changing face of teenage drug abuse-the trend toward prescription drugs. New England Journal of Medicine. 2006;354(14):1448. doi: 10.1056/NEJMp068010. [DOI] [PubMed] [Google Scholar]
  25. Gallagher RM, Rosenthal LJ. Chronic pain and opiates: balancing pain control and risks in long-term opioid treatment. Archives of Physical Medicine and Rehabilitation. 2008;89(3 Suppl 1):S77–82. doi: 10.1016/j.apmr.2007.12.003. [DOI] [PubMed] [Google Scholar]
  26. Han B, Compton WM, Jones CM, Cai R. Nonmedical prescription opioid use and use disorders among adults aged 18 through 64 years in the United States, 2003–2013. JAMA. 2015;314(14):1468–1478. doi: 10.1001/jama.2015.11859. [DOI] [PubMed] [Google Scholar]
  27. Huang B, Dawson DA, Stinson FS, Hasin DS, Ruan WJ, Saha TD, … Grant BF. Prevalence, correlates, and comorbidity of nonmedical prescription drug use and drug use disorders in the United States: Results of the National Epidemiologic Survey on Alcohol and Related Conditions. Journal of Clinical Psychiatry. 2006;67(7):1062–1073. doi: 10.4088/jcp.v67n0708. [DOI] [PubMed] [Google Scholar]
  28. Hwang J, Kim JE, Kaufman MJ, Renshaw PF, Yoon S, Yurgelun-Todd DA, … Lyoo IK. Enlarged cavum septum pellucidum as a neurodevelopmental marker in adolescent-onset opiate dependence. PLoS One. 2013;8(10):e78590. doi: 10.1371/journal.pone.0078590. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Jones CM. Heroin use and heroin use risk behaviors among nonmedical users of prescription opioid pain relievers - United States, 2002–2004 and 2008–2010. Drug and Alcohol Dependence. 2013;132(1–2):95–100. doi: 10.1016/j.drugalcdep.2013.01.007. [DOI] [PubMed] [Google Scholar]
  30. Jordan BK, Karg RS, Batts KR, Epstein JF, Wiesen C. A clinical validation of the National Survey on Drug Use and Health assessment of substance use disorders. Addictive Behaviors. 2008;33:782–798. doi: 10.1016/j.addbeh.2007.12.007. [DOI] [PubMed] [Google Scholar]
  31. Martins SS, Santaella-Tenorio J, Marshall BD, Maldonado A, Cerda M. Racial/ethnic differences in trends in heroin use and heroin-related risk behaviors among nonmedical prescription opioid users. Drug and Alcohol Dependence. 2015;151:278–83. doi: 10.1016/j.drugalcdep.2015.03.020. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Meyer R, Patel A, Rattana S, Quock T, Mody S. Prescription opioid abuse: a literature review of the clinical and economic burden in the United States. Population Health Management. 2014;17(6):372–87. doi: 10.1089/pop.2013.0098. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Minozzi S, Amato L, Davoli M. Development of dependence following treatment with opioid analgesics for pain relief: a systematic review. Addiction. 2013;108(4):688–698. doi: 10.1111/j.1360-0443.2012.04005.x. [DOI] [PubMed] [Google Scholar]
  34. Montgomery K. Youth and digital media: A policy research agenda. Journal of Adolescent Health. 2000;27(2):61–68. doi: 10.1016/s1054-139x(00)00130-0. [DOI] [PubMed] [Google Scholar]
  35. Morral AR, McCaffrey DF, Chien S. Measurement of adolescent drug use. Journal of Psychoactive Drugs. 2003;35(3):301–309. doi: 10.1080/02791072.2003.10400013. [DOI] [PubMed] [Google Scholar]
  36. NSDUH. [Accessed 05.23.16];Who Uses NSDUH Data? 2016 https://nsduhweb.rti.org/respweb/project_description.html/
  37. Peer K, Rennert L, Lynch K, Farrer L, Gelernter J, Kranzler H. Prevalence of DSM-IV and DSM-5 alcohol, cocaine, opioid, and cannabis use disorders in a largely substance dependent sample. Drug and Alcohol Dependence. 2013;127(1–3):215–9. doi: 10.1016/j.drugalcdep.2012.07.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Rintoul A, Dobbin M, Drummer O, Ozanne-Smith J. Increasing deaths involving oxycodone, Victoria, Australia, 2000–09. Injury Prevention. 2011;17(4):254–9. doi: 10.1136/ip.2010.029611. [DOI] [PubMed] [Google Scholar]
  39. Rintoul AC, Dobbin M. Prescription opioid deaths: we need to treat sick populations, not just sick individuals. Addiction. 2014;109(2):185–6. doi: 10.1111/add.12343. [DOI] [PubMed] [Google Scholar]
  40. Rudolph KD, Lambert SF, Clark AG, Kurlakowsky KD. Negotiating the transition to middle school: the role of self-regulatory processes. Child Development. 2001;72(3):929–946. doi: 10.1111/1467-8624.00325. [DOI] [PubMed] [Google Scholar]
  41. SAMHSA. Results from the 2007 National Survey on Drug Use and Health: National Findings. Office of Applied Studies; 2008. [Accessed 07.28.16]. NSDUH Series H-34, DHHS Publication No. SMA 08-4343. http://www.alcoholandcrime.org/images/uploads/pdf_research/nsduh_2007.pdf. [Google Scholar]
  42. SAMHSA. [Accessed 04.12.16];Results from the 2008 National Survey on Drug Use and Health: National Findings NHSDA Series H-36, DHHS Publication No. SMA 09-4443. 2009 http://www.dpft.org/resources/NSDUHresults2008.pdf/
  43. SAMHSA. [Accessed 04.13.16];Results from the 2010 National Survey on Drug Use and Health: Summary of National Findings. NSDUH Series H-41, HHS Publication No. SMA 11-4658. 2011 http://www.samhsa.gov/data/sites/default/files/NSDUHNationalFindingsResults2010-web/2k10ResultsRev/NSDUHresultsRev2010.pdf/
  44. SAMHSA. [Accessed 04.15.16];Results from the 2011 National Survey on Drug Use and Health: Summary of National Findings. NSDUH Series H-44, HHS Publication No. (SMA) 12-4713. 2012a http://www.samhsa.gov/data/sites/default/files/Revised2k11NSDUHSummNatFindings/Revised2k11NSDUHSummNatFindings/NSDUHresults2011.htm/
  45. SAMHSA. Results from the 2012 NSDUH: Summary of National Findings. SAMHSA, CBHSQ; 2012b. [Accessed 04.14.16]. http://archive.samhsa.gov/data/NSDUH/2012SummNatFindDetTables/NationalFindings/NSDUHresults2012.htm-ch2/ [Google Scholar]
  46. SAMHSA. [Accessed 04.17.16];Results from the 2013 National Survey on Drug Use and Health: Summary of National Findings. NSDUH Series H-48, HHS Publication No. (SMA) 14-4863. 2014 http://www.samhsa.gov/data/sites/default/files/NSDUHresultsPDFWHTML2013/Web/NSDUHresults2013.pdf/
  47. Shand F, Slade T, Degenhardt L, Baillie A, Nelson E. Opioid dependence latent structure: two classes with differing severity? Addiction. 2011;106(3):590–8. doi: 10.1111/j.1360-0443.2010.03217.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Shepherd J. Combating the prescription painkiller epidemic: a national prescription drug reporting program. American Journal of Law and Medicine. 2014;40(1):85–112. doi: 10.1177/009885881404000103. [DOI] [PubMed] [Google Scholar]
  49. STATA. Stata Statistical Software: Release 13. College Station, TX: StataCorp LP; 2013. StataCorp. [Google Scholar]
  50. Uebel H, Wright IM, Burns L, Hilder L, Bajuk B, Breen C, … Oei JL. Reasons for Rehospitalization in Children Who Had Neonatal Abstinence Syndrome. Pediatrics. 2015;136(4):e811–20. doi: 10.1542/peds.2014-2767. [DOI] [PubMed] [Google Scholar]
  51. Wang H, Deng J, Zhou X, Lu C, Huang J, Huang G, … He Y. The nonmedical use of prescription medicines among high school students: a cross-sectional study in Southern China. Drug and Alcohol Dependence. 141:9–15. doi: 10.1016/j.drugalcdep.2014.04.004. [DOI] [PubMed] [Google Scholar]
  52. West NA, Severtson SG, Green JL, Dart RC. Trends in abuse and misuse of prescription opioids among older adults. Drug and Alcohol Dependence. 2015;149:117–21. doi: 10.1016/j.drugalcdep.2015.01.027. [DOI] [PubMed] [Google Scholar]
  53. Wu LT, Blazer DG, Li TK, Woody GE. Treatment use and barriers among adolescents with prescription opioid use disorders. Addictive Behaviors. 2011;36(12):1233–1239. doi: 10.1016/j.addbeh.2011.07.033. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Wu LT, Ringwalt CL, Mannelli P, Patkar AA. Prescription pain reliever abuse and dependence among adolescents: a nationally representative study. Journal of the American Academy of Child and Adolescent Psychiatry. 2008;47(9):1020–1029. doi: 10.1097/CHI.0b013e31817eed4d. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

supplement
NIHMS816880-supplement.docx (100.6KB, docx)

RESOURCES