Adolescent Use, Diversion Sources, and Perceived Procurement Difficulty of Prescription Medications

Sean Esteban McCabe; Emily Pasman; Tim Wilens; Ty S Schepis; Vita McCabe; Jason Ford; Phil Veliz

doi:10.1001/jama.2024.12030

. 2024 Jul 24;332(7):587–589. doi: 10.1001/jama.2024.12030

Adolescent Use, Diversion Sources, and Perceived Procurement Difficulty of Prescription Medications

Sean Esteban McCabe ¹, Emily Pasman ¹, Tim Wilens ^2,³, Ty S Schepis ^1,⁴, Vita McCabe ^1,⁵, Jason Ford ^1,⁶, Phil Veliz ^1,^✉

¹Center for the Study of Drugs, Alcohol, Smoking and Health, University of Michigan School of Nursing, Ann Arbor

²Massachusetts General Hospital, Boston

³Harvard Medical School, Cambridge, Massachusetts

⁴Department of Psychology, Texas State University, San Marcos

⁵Department of Psychiatry, University of Michigan, Ann Arbor

⁶Department of Sociology, University of Central Florida, Orlando

Accepted for Publication: June 4, 2024.

Published Online: July 24, 2024. doi:10.1001/jama.2024.12030

^✉

Corresponding Author: Phil Veliz, PhD, School of Nursing, Center for the Study of Drugs, Alcohol, Smoking and Health, University of Michigan, Ann Arbor, MI 48109 (ptveliz@umich.edu).

Author Contributions: Drs Veliz and S. E. McCabe had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: S. E. McCabe, Wilens, Schepis, V. McCabe, Ford, Veliz.

Acquisition, analysis, or interpretation of data: S. McCabe, Pasman, Ford, Veliz.

Drafting of the manuscript: S. E. McCabe, Pasman, Veliz.

Critical review of the manuscript for important intellectual content: All authors.

Statistical analysis: S. E. McCabe, Wilens, Veliz.

Obtained funding: S. E. McCabe, Schepis.

Administrative, technical, or material support: S. E. McCabe, V. McCabe, Ford, Veliz.

Supervision: S. E. McCabe.

Clinical expertise: V. McCabe.

Conflict of Interest Disclosures: Dr S. E. McCabe reported grants from the National Institutes of Health (NIH) during the conduct of the study. Dr Wilens reported grants from the NIH National Institute on Drug Abuse (NIDA) during the conduct of the study; consulting fees from the Gavin Foundation, Bay Cove Human Services, National Football League (ERM Associates), Minor and Major League Baseball, White Rhino, and 3D Therapy; serving as coeditor for Psychiatric Clinics of North America; employment with Massachusetts General Hospital outside the submitted work; a patent for Ironshore with royalties; co-owning the Before School Functioning Questionnaire; and a patent for Guilford Press and Cambridge University Press, both with royalties. Dr V. McCabe reported grants from NIH during the conduct of the study. Dr Ford reported grants from NIDA during the conduct of the study. No other disclosures were reported.

Funding/Support: This study was supported by research awards from NIDA (R01DA031160, UH3DA050252, and R01DA043691).

Role of the Funder/Sponsor: NIDA had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 2.

Additional Contributions: The authors acknowledge data management and statistical assistance from John Jardine, MA (School of Nursing, University of Michigan). Mr Jardine did not receive any compensation for his contributions.

^✉

Corresponding author.

PMCID: PMC11270238 PMID: 39046750

Abstract

This study examines trends in medical use, nonmedical use, diversion sources, and perceived procurement difficulty of prescription medications for nonmedical use among US adolescents.

Prescription stimulants, opioids, and benzodiazepines are 3 of the most commonly prescribed and nonmedically used controlled substances among US adolescents.^1,2 Trends in prescribing have occurred and adolescent overdose deaths have increased, partially due to proliferation of counterfeit pills.^2,3,4,5,6 This study examined trends in medical use, nonmedical use (NMU), diversion sources, and perceived procurement difficulty of prescription medications for NMU among US adolescents.

Methods

Monitoring the Future is an annual self-administered survey conducted with nationally representative samples of high school students. This study used data collected in 2009 through 2022 from 12th-grade students²; mean response rate was 80.20%. The University of Michigan’s institutional review board approved this study. Parents could opt their child out of the study (eAppendix in Supplement 1), and informed consent was written.

For prescription stimulants, opioids, and benzodiazepines, respondents were asked about lifetime medical use (any vs none), past-year NMU (use without a prescription or other than prescribed, categorized as any vs none), past-year diversion sources (where medications were obtained for NMU; 10 options, including bought on the internet, obtained or bought from a friend or relative, and used from one’s own prescription), and perceived difficulty of obtaining prescription medications for NMU (probably impossible vs other) (eAppendix in Supplement 1).

Descriptive statistics estimated prevalence rates and 95% CIs. Multivariable binary logistic regression models estimated linear trends for medical use, NMU, diversion sources, and perceived difficulty of obtaining prescription medications, overall and by each prescription medication class. Models controlled for sex, race and ethnicity, parental education, urbanicity, and US region. Weighted analyses reported adjusted odds ratios (aORs) and 95% CIs for the linear trends. Missing data were handled using listwise deletion. Linear trends were considered statistically significant if the CIs did not contain 1. Analyses were conducted in Stata 18.0 (StataCorp).

Results

Of the 29 220 adolescents included, 51.84% were female. Between 2009 and 2022, reported lifetime medical use significantly decreased (23.66% to 16.00%; linear trend, aOR = 0.93 [95% CI, 0.91-0.95]), as did past-year NMU (11.49% to 2.38%; linear trend, aOR = 0.82 [95% CI, 0.80-0.85]) (Table 1). Trends in 2 diversion sources significantly declined. In 2009-2010, 57.96% reported being given prescription medications by a friend, which decreased to 26.87% in 2021-2022 (linear trend, aOR = 0.87 [95% CI, 0.81-0.93]); and 44.35% reported buying medications from a friend in 2009-2010, decreasing to 19.42% in 2021-2022 (linear trend, aOR = 0.91 [95% CI, 0.85-0.98]). Among adolescents reporting past-year NMU, the most prevalent diversion source in 2021-2022 was one’s own prescription (37.37%). The prevalence of adolescents reporting multiple diversion sources decreased from 56.27% in 2009-2010 to 29.33% in 2021-2022 (linear trend, aOR = 0.88 [95% CI, 0.82-0.94]). Prevalence of adolescents who reported it would be probably impossible for them to obtain prescription medications for NMU increased from 35.56% in 2009-2010 to 48.96% in 2021-2022 (linear trend, aOR = 1.08 [95% CI, 1.06-1.10]).

Table 1. Trends in Medical Use, Nonmedical Use, Diversion Sources, and Perceived Procurement Difficulty of Prescription Medications Among US Adolescents, 2009-2022^a.

Measures	No. (%) [95% CI]							Linear trend, aOR (95% CI)^b
Measures	2009-2010	2011-2012	2013-2014	2015-2016	2017-2018	2019-2020	2021-2022	Linear trend, aOR (95% CI)^b
Lifetime medical use	n = 4631	n = 4604	n = 4140	n = 4100	n = 4392	n = 2768	n = 2776	n = 24 099
No. (%) [95% CI]	1073 (23.66) [22.24-25.14]	1141 (25.82) [24.35-27.35]	1001 (24.55) [23.06-26.10]	910 (23.31) [21.80-24.89]	858 (19.03) [17.70-20.43]	583 (20.53) [18.78-22.40]	442 (16.00) [14.27-17.89]	0.93 (0.91-0.95)
Past-year nonmedical use	n = 4609	n = 4578	n = 4104	n = 4079	n = 4365	n = 2749	n = 2767	n = 24 018
No. (%) [95% CI]	523 (11.49) [10.45-12.63]	535 (12.12) [11.03-13.30]	454 (11.04) [9.98-12.20]	385 (9.36) [8.36-10.47]	344 (7.62) [6.77-8.56]	163 (5.75) [4.75-6.93]	72 (2.38) [1.82-3.11]	0.82 (0.80-0.85)
Diversion sources	n = 475	n = 477	n = 397	n = 340	n = 290	n = 141	n = 75	n = 1822
Bought on internet	21 (4.19) [2.55-6.82]	23 (5.85) [3.64-9.29]	15 (4.25) [2.29-7.73]	11 (4.14) [1.98-8.45]	18 (6.89) [4.12-11.31]	12 (10.29) [5.09-19.68]	4 (6.47) [2.21-17.48]	1.02 (0.86-1.21)
Took from friend	36 (6.67) [4.60-9.57]	26 (4.20) [2.78-6.32]	20 (4.11) [2.55-6.55]	19 (6.40) [3.91-10.32]	8 (2.54) [1.24-5.14]	10 (7.42) [3.87-13.75]	8 (8.48) [3.95-17.26]	0.99 (0.84-1.16)
Took from relative	82 (16.69) [13.12-21.00]	85 (17.00) [13.48-21.22]	63 (16.69) [12.77-21.52]	45 (14.66) [10.67-19.81]	33 (10.22) [7.12-14.46]	19 (15.21) [8.95-24.66]	7 (8.81) [3.65-19.79]	0.92 (0.83-1.02)
Given by friend	277 (57.96) [52.66-63.08]	247 (54.61) [49.32-59.81]	200 (51.06) [45.43-56.67]	161 (45.69) [39.58-51.93]	125 (41.75) [35.36-48.43]	62 (42.34) [32.53-52.80]	23 (26.87) [17.36-39.12]	0.87 (0.81-0.93)
Given by relative	75 (14.81) [11.60-18.72]	97 (21.25) [17.16-26.01]	66 (16.69) [12.99-21.18]	50 (14.39) [10.66-19.14]	47 (16.47) [12.23-21.81]	31 (23.29) [15.34-33.72]	15 (13.63) [7.84-22.63]	1.00 (0.92-1.10)
Bought from friend	203 (44.35) [39.13-49.69]	174 (36.25) [31.36-41.45]	140 (33.15) [28.23-38.48]	116 (35.21) [29.48-41.41]	105 (38.21) [31.88-44.97]	49 (31.11) [22.77-40.88]	15 (19.42) [11.10-31.74]	0.91 (0.85-0.98)
Bought from relative	12 (2.82) [1.49-5.30]	23 (5.64) [3.48-9.00]	12 (2.71) [1.45-5.01]	15 (4.50) [2.54-7.84]	10 (3.56) [1.84-6.79]	8 (7.27) [2.86-17.27]	3 (2.90) [0.91-8.84]	0.92 (0.77-1.09)
From a prescription I had	140 (28.99) [24.44-34.02]	149 (31.53) [26.79-36.69]	102 (25.39) [20.86-30.52]	98 (29.46) [24.08-35.49]	62 (21.74) [16.71-27.79]	50 (30.36) [22.09-40.12]	32 (37.37) [25.65-50.79]	1.01 (0.94-1.08)
Bought from drug dealer or stranger	102 (22.25) [18.06-27.08]	90 (18.74) [14.88-23.32]	63 (17.94) [13.88-22.87]	52 (16.72) [12.49-22.02]	54 (18.47) [13.99-23.97]	34 (21.65) [14.52-31.01]	7 (9.03) [3.95-19.30]	0.94 (0.86-1.02)
Other	68 (14.79) [11.41-18.97]	59 (11.87) [8.89-15.68]	51 (12.38) [9.29-16.31]	39 (11.80) [8.19-16.71]	42 (16.16) [11.68-21.92]	39 (26.57) [18.63-36.37]	8 (11.53) [4.71-25.60]	0.99 (0.89-1.10)
No. of diversion sources	n = 475	n = 477	n = 397	n = 340	n = 290	n = 141	n = 66	n = 1822
Multiple	260 (56.27) [50.99-61.40]	242 (51.48) [46.17-56.75]	176 (44.23) [38.74-49.87]	141 (41.26) [35.30-47.48]	122 (42.65) [36.23-49.33]	76 (52.27) [41.85-62.51]	23 (29.33) [18.92-42.47]	0.88 (0.82-0.94)
Perceived difficulty of obtaining^c	n = 4726	n = 4690	n = 4208	n = 4181	n = 4428	n = 2806	n = 2008	n = 24 249
Probably impossible	1734 (35.56) [33.97-37.19]	1770 (38.24) [36.60-39.92]	1728 (41.57) [39.84-43.31]	1791 (42.98) [41.24-44.74]	1965 (45.34) [43.59-47.12]	1215 (43.41) [41.14-45.71]	1007 (48.96) [46.15-51.77]	1.08 (1.06-1.10)

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Abbreviation: aOR, adjusted odds ratio.

^{^a}

The estimates assessing past-year nonmedical prescription drug use, lifetime medical prescription medication use, and sources for nonmedical use came from Form 1 of the Monitoring the Future (MTF) survey (2009-2022; n = 29 220); estimates assessing difficulty to get prescription drugs came from Form 2 of the MTF (2009-2022; n = 29 243). Analyses were weighted.

^{^b}

The adjusted logistic regression models controlled for sex, race and ethnicity, highest level of parental education, metropolitan status of residence, and US region of residence. Of the 29 220 adolescents included, 22.93% were American Indian, Asian, or multiracial, or had missing data; 10.94% were Black; 15.79% were Hispanic; and 50.34% were White. Race and ethnicity were self-reported according to a question provided in the survey instrument.

^{^c}

Response categories for perceived difficulty of obtaining prescription medications were collapsed to compare “probably impossible” with “very easy,” “fairly easy,” “fairly difficult,” and “very difficult.”

Prevalence of adolescents reporting multiple diversion sources significantly decreased for opioids (47.83% to 36.71%; linear trend, aOR = 0.90 [95% CI, 0.82-1.00]) and benzodiazepines (53.09% to 24.30%; linear trend, aOR = 0.86 [95% CI, 0.76-0.98]), but not stimulants (Table 2). Perceived difficulty of obtaining prescription medications for NMU significantly increased for each prescription medication class.

Table 2. Trends in Number of Diversion Sources and Perceived Difficulty in Obtaining Prescription Medications Among US Adolescents, 2009-2022^a.

Measures	No. (%) [95% CI]							Linear trend, aOR (95% CI)^b
Measures	2009-2010	2011-2012	2013-2014	2015-2016	2017-2018	2019-2020	2021-2022	Linear trend, aOR (95% CI)^b
Stimulants
No. of diversion sources	n = 234	n = 270	n = 230	n = 192	n = 179	n = 70	n = 39	n = 1001
Multiple sources	107 (46.48) [38.92-54.21]	110 (38.22) [31.73-45.16]	92 (39.06) [32.27-46.30]	69 (35.42) [27.95-43.68]	58 (32.41) [25.03-40.79]	42 (59.05) [46.11-70.85]	13 (26.07) [14.41-42.49]	0.94 (0.85-1.03)
Perceived difficulty of obtaining^c	n = 4688	n = 4661	n = 4185	n = 4155	n = 4401	n = 2791	n = 1999	n = 24 118
Probably impossible	918 (19.30) [18.00-20.68]	928 (20.86) [19.46-22.33]	939 (22.57) [21.11-24.09]	993 (23.84) [22.37-25.38]	1083 (26.34) [24.77-27.97]	660 (24.77) [22.80-26.85]	633 (31.65) [29.08-34.34]	1.08 (1.06-1.11)
Opioids
No. of diversion sources	n = 294	n = 265	n = 207	n = 163	n = 106	n = 52	n = 22	n = 948
Multiple sources	143 (47.83) [41.28-54.46]	119 (48.04) [41.05-55.10]	79 (38.68) [31.48-46.40]	67 (45.94) [37.13-55.00]	36 (35.56) [26.18-46.20]	20 (36.39) [23.57-51.48]	8 (36.71) [17.73-60.94]	0.90 (0.82-1.00)
Perceived difficulty of obtaining^c	n = 4700	n = 4664	n = 4177	n = 4152	n = 4399	n = 2791	n = 2000	n = 24 133
Probably impossible	1020 (21.37) [20.01-22.80]	922 (20.24) [18.88-21.68]	944 (22.72) [21.25-24.26]	1070 (25.97) [24.45-27.55]	1204 (28.78) [27.17-30.45]	788 (28.96) [26.90-31.11]	870 (41.84) [39.10-44.63]	1.15 (1.12-1.17)
Benzodiazepines
No. of diversion sources	n = 192	n = 177	n = 136	n = 130	n = 113	n = 68	n = 20	n = 671
Multiple sources	99 (53.09) [44.72 61.29]	71 (40.25) [32.04-49.06]	47 (31.62) [23.79-40.65]	29 (23.52) [15.87-33.39]	34 (30.37) [21.64-40.80]	38 (53.42) [37.76-68.44]	7 (24.30) [10.75-46.12]	0.86 (0.76-0.98)
Perceived difficulty of obtaining^c	n = 4668	n = 4643	n = 4166	n = 4137	n = 4374	n = 2186	n = 2000	n = 23 461
Probably impossible	1501 (31.22) [29.68-32.80]	1586 (34.74) [33.11-36.40]	1552 (38.00) [36.30-39.74]	1595 (38.96) [37.24-40.71]	1721 (40.22) [38.48-41.98]	897 (40.95) [38.50-43.45]	739 (37.00) [34.31-39.76]	1.06 (1.04-1.07)

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Abbreviation: aOR, adjusted odds ratio.

^{^a}

The estimates assessing sources for nonmedical use came from Form 1 of the Monitoring the Future (MTF) survey (2009-2022; n = 29 220); estimates assessing difficulty to get prescription drugs came from Form 2 of the MTF (2009-2022; n = 29 243). Analyses were weighted.

^{^b}

^{^c}

Discussion

Between 2009 and 2022, US adolescents reported declines in medical use and NMU of prescription medications, concurring with other research.^2,3,4,5 This study expands these findings by showing declines in peer-to-peer and multiple sources of diversion and increased perceived difficulty of obtaining prescription medications for NMU. These changes may be partially attributed to prescribing guideline changes⁵ and COVID-related school closures, which limited social interaction with peers. Study limitations include the cross-sectional design, potential self-report bias, and missing subpopulations of adolescents with lower (eg, homeschooled) and higher (eg, truant) rates of NMU.² Data from 2020 should be interpreted cautiously due to COVID-related disruptions. Efforts to further reduce NMU and diversion are needed, particularly given the role of counterfeit pills in the adolescent overdose crisis.⁶ Furthermore, monitoring, storage, and disposal of prescription medications and education regarding them are important.

Section Editors: Kristin Walter, MD, and Jody W. Zylke, MD, Deputy Editors; Karen Lasser, MD, MPH, Senior Editor.

Supplement 1.

eAppendix. Methods

jama-e2412030-s001.pdf^{(202.3KB, pdf)}

Supplement 2.

Data Sharing Statement

jama-e2412030-s002.pdf^{(12.2KB, pdf)}

References

1.Center for Behavioral Health Statistics and Quality . Results from the 2022 National Survey on Drug Use and Health. Substance Abuse and Mental Health Services Administration. Accessed February 23, 2024. https://www.samhsa.gov/data/report/2022-nsduh-detailed-tables
2.Miech RA, Johnston LD, Patrick ME, O’Malley PM, Bachman JG, Schulenberg JE. Monitoring the Future National Survey Results on Drug Use, 1975-2022: Secondary School Students. Institute for Social Research, University of Michigan; 2023. Accessed January 15, 2024. https://monitoringthefuture.org/wp-content/uploads/2022/12/mtf2022.pdf [Google Scholar]
3.Danielson ML, Bohm MK, Newsome K, et al. Trends in stimulant prescription fills among commercially insured children and adults—United States, 2016-2021. MMWR Morb Mortal Wkly Rep. 2023;72(13):327-332. doi: 10.15585/mmwr.mm7213a1 [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Toce MS, Michelson KA, Hudgins JD, Olson KL, Bourgeois FT. Trends in benzodiazepine prescribing for US adolescents and young adults from 2008 to 2019. JAMA Pediatr. 2022;176(3):312-313. doi: 10.1001/jamapediatrics.2021.5122 [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Bohnert ASB, Guy GP Jr, Losby JL. Opioid prescribing in the United States before and after the Centers for Disease Control and Prevention’s 2016 opioid guideline. Ann Intern Med. 2018;169(6):367-375. doi: 10.7326/M18-1243 [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Tanz LJ, Dinwiddie AT, Mattson CL, O’Donnell J, Davis NL. Drug overdose deaths among persons aged 10-19 years—United States, July 2019–December 2021. MMWR Morb Mortal Wkly Rep. 2022;71(50):1576-1582. doi: 10.15585/mmwr.mm7150a2 [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 1.

eAppendix. Methods

jama-e2412030-s001.pdf^{(202.3KB, pdf)}

Supplement 2.

Data Sharing Statement

jama-e2412030-s002.pdf^{(12.2KB, pdf)}

[jld240044r1] 1.Center for Behavioral Health Statistics and Quality . Results from the 2022 National Survey on Drug Use and Health. Substance Abuse and Mental Health Services Administration. Accessed February 23, 2024. https://www.samhsa.gov/data/report/2022-nsduh-detailed-tables

[jld240044r2] 2.Miech RA, Johnston LD, Patrick ME, O’Malley PM, Bachman JG, Schulenberg JE. Monitoring the Future National Survey Results on Drug Use, 1975-2022: Secondary School Students. Institute for Social Research, University of Michigan; 2023. Accessed January 15, 2024. https://monitoringthefuture.org/wp-content/uploads/2022/12/mtf2022.pdf [Google Scholar]

[jld240044r3] 3.Danielson ML, Bohm MK, Newsome K, et al. Trends in stimulant prescription fills among commercially insured children and adults—United States, 2016-2021. MMWR Morb Mortal Wkly Rep. 2023;72(13):327-332. doi: 10.15585/mmwr.mm7213a1 [DOI] [PMC free article] [PubMed] [Google Scholar]

[jld240044r4] 4.Toce MS, Michelson KA, Hudgins JD, Olson KL, Bourgeois FT. Trends in benzodiazepine prescribing for US adolescents and young adults from 2008 to 2019. JAMA Pediatr. 2022;176(3):312-313. doi: 10.1001/jamapediatrics.2021.5122 [DOI] [PMC free article] [PubMed] [Google Scholar]

[jld240044r5] 5.Bohnert ASB, Guy GP Jr, Losby JL. Opioid prescribing in the United States before and after the Centers for Disease Control and Prevention’s 2016 opioid guideline. Ann Intern Med. 2018;169(6):367-375. doi: 10.7326/M18-1243 [DOI] [PMC free article] [PubMed] [Google Scholar]

[jld240044r6] 6.Tanz LJ, Dinwiddie AT, Mattson CL, O’Donnell J, Davis NL. Drug overdose deaths among persons aged 10-19 years—United States, July 2019–December 2021. MMWR Morb Mortal Wkly Rep. 2022;71(50):1576-1582. doi: 10.15585/mmwr.mm7150a2 [DOI] [PMC free article] [PubMed] [Google Scholar]

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Adolescent Use, Diversion Sources, and Perceived Procurement Difficulty of Prescription Medications

Sean Esteban McCabe, PhD

Emily Pasman, PhD

Tim Wilens, MD

Ty S Schepis, PhD

Vita McCabe, MD

Jason Ford, PhD

Phil Veliz, PhD

Abstract

Methods

Results

Table 1. Trends in Medical Use, Nonmedical Use, Diversion Sources, and Perceived Procurement Difficulty of Prescription Medications Among US Adolescents, 2009-2022^a.

Table 2. Trends in Number of Diversion Sources and Perceived Difficulty in Obtaining Prescription Medications Among US Adolescents, 2009-2022^a.

Discussion

References

Associated Data

Supplementary Materials

ACTIONS

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RESOURCES

Cite

Add to Collections

PERMALINK

Adolescent Use, Diversion Sources, and Perceived Procurement Difficulty of Prescription Medications

Sean Esteban McCabe, PhD

Emily Pasman, PhD

Tim Wilens, MD

Ty S Schepis, PhD

Vita McCabe, MD

Jason Ford, PhD

Phil Veliz, PhD

Abstract

Methods

Results

Table 1. Trends in Medical Use, Nonmedical Use, Diversion Sources, and Perceived Procurement Difficulty of Prescription Medications Among US Adolescents, 2009-2022a.

Table 2. Trends in Number of Diversion Sources and Perceived Difficulty in Obtaining Prescription Medications Among US Adolescents, 2009-2022a.

Discussion

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

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Table 1. Trends in Medical Use, Nonmedical Use, Diversion Sources, and Perceived Procurement Difficulty of Prescription Medications Among US Adolescents, 2009-2022^a.

Table 2. Trends in Number of Diversion Sources and Perceived Difficulty in Obtaining Prescription Medications Among US Adolescents, 2009-2022^a.