This cohort study of data over a 9-year period evaluates whether diagnosis of attention-deficit/hyperactivity disorder, symptom severity, and pharmacotherapy are associated with incident e-cigarette and tobacco use.
Key Points
Question
Do youths with asymptomatic attention-deficit/hyperactivity disorder (ADHD) differ from youths with symptomatic ADHD and population controls without ADHD in their risk of incident e-cigarette and tobacco use?
Findings
In this cohort study of 13 572 US youths, odds of e-cigarette use, cigarette smoking, other tobacco use, and dual use did not significantly differ between those with asymptomatic ADHD (with or without pharmacotherapy) and population controls. In contrast, all youths who had 3 or more ADHD symptoms (with or without pharmacotherapy) had significantly higher adjusted odds of using nicotine and tobacco products.
Meaning
These findings highlight the importance of early diagnosis and effective treatment of ADHD to mitigate symptoms and reduce the risk of later nicotine and tobacco use.
Abstract
Importance
Information about longitudinal associations of attention-deficit/hyperactivity disorder (ADHD) diagnosis, symptom severity, pharmacotherapy, and incident nicotine and tobacco use, including e-cigarettes, among US youths is limited.
Objective
To evaluate whether ADHD diagnosis, symptom severity, and pharmacotherapy are associated with incident e-cigarette and tobacco use over a 9-year period.
Design, Setting, and Participants
This longitudinal cohort study followed up a nationally representative sample of US youths and their parents in the Population Assessment of Tobacco and Study via questionnaires from wave 1 (September 2013 to December 2014) to waves 2 to 7 (October 2014 to April 2023). Participants were representative of the US civilian noninstitutionalized population. Youths aged 12 to 17 years at wave 1 (N = 13 572) and their parents were interviewed.
Exposures
Time in years and history of ADHD diagnosis, symptom severity, and pharmacotherapy at wave 1 were used to construct 9 mutually exclusive subgroups of US youths, including those with ADHD diagnosis and pharmacotherapy, ADHD diagnosis without pharmacotherapy, and population controls without ADHD diagnosis; within each of these 3 subgroups, ADHD symptom severity was categorized as none, 1 to 2, or 3 to 4 symptoms.
Main Outcomes and Measures
Incident e-cigarette use, cigarette smoking, other tobacco use, and dual use (e-cigarette and cigarette and/or other tobacco use) in weighted percentages with 95% CIs.
Results
Of the 13 572 youths included in the analysis, 6967 (51.3%; 95% CI, 51.2%-51.5%) were male. An estimated 1881 participants (14.1%; 95% CI, 13.2%-15.0%) were diagnosed with ADHD. Multivariable logistic regression analyses indicated that the adjusted odds of incident e-cigarette use, cigarette smoking, other tobacco use, and dual use did not significantly differ between those with asymptomatic ADHD (with or without pharmacotherapy) compared with population controls. In contrast, all subgroups who had 3 or more ADHD symptoms (with or without pharmacotherapy) had significantly higher adjusted odds of e-cigarette use (adjusted odds ratio [AOR], 1.60; 95% CI, 1.34-2.04), cigarette smoking (AOR, 1.52; 95% CI, 1.22-1.89), other tobacco use (AOR, 1.61; 95% CI, 1.27-2.02), and dual use (AOR, 1.72; 95% CI, 1.38-2.14) compared with youths with asymptomatic ADHD or population controls. Among youths with ADHD, those with highly symptomatic ADHD were significantly more likely to initiate e-cigarette (AOR, 1.68; 95% CI, 1.16-2.44) and dual use (AOR, 1.82; 95% CI, 1.17-2.83) than youths without symptoms.
Conclusions and Relevance
In this cohort study of US youths, ADHD symptoms were associated with the onset of nicotine and tobacco use. Findings highlight the importance of early diagnosis and effective treatment of ADHD to alleviate symptoms and reduce the risk of later nicotine and tobacco use.
Introduction
Tobacco use remains the leading cause of preventable death in the US and worldwide.1,2,3 While associations between attention-deficit/hyperactivity disorder (ADHD) and tobacco use are well-established,4,5,6,7,8,9,10,11 the landscape of ADHD, nicotine, and tobacco use among US youths has changed over the past decade.12,13,14 For instance, the prevalence of electronic nicotine delivery systems (e-cigarettes) surpassed cigarette smoking among US youths in 2018, and e-cigarette use is now the second most prevalent substance use behavior.14,15 The prevalence of ADHD diagnoses and the prescribing of stimulant and nonstimulant pharmacotherapy for ADHD have also increased over the past decade.12,14
ADHD is characterized by functional impairment, inattention, and/or hyperactivity and is one of the most common psychiatric disorders among US children and adolescents, with the prevalence increasing over the past 2 decades.16,17,18 In 2022, approximately 1 in 9 US youths (11.4%) had received an ADHD diagnosis in their lifetime, and approximately 1 in 10 (10.5%) had a current ADHD diagnosis.13 Among US youths with current ADHD, 53.6% used ADHD pharmacotherapy and 44.4% received psychosocial treatment to manage their ADHD symptoms.10
A large body of research has established an association between ADHD and tobacco use.4,5,6,7,8,9,10,11 For example, a meta-analytic review4 concluded that youths with ADHD had more than double the odds of nicotine use by middle adolescence relative to their peers without ADHD. Moreover, a population-based prospective Swedish twin study5 followed up nearly 1500 pairs of twins from childhood to adolescence and found that hyperactive and/or impulsive symptoms of ADHD were associated with early onset-tobacco use. Early onset of tobacco use can serve as an important antecedent to substance use disorder in US youths with ADHD and can offer a useful signal to intervene before substance use disorder develops.19,20,21
Some experts have asserted that alleviating ADHD symptoms may reduce impulsivity and engagement in substance use and other risky behaviors.22,23 However, there are no known national prospective probability-based US studies examining the association between childhood ADHD and later nicotine or tobacco use that have parsed out the nuances of ADHD treatment and ADHD symptom severity. Within this context, prospective research examining the longitudinal associations among ADHD diagnosis, pharmacotherapy, inattentive symptoms, hyperactive and/or impulsive symptoms, and later nicotine e-cigarette and tobacco use among US youths is warranted.
This cohort study aims to extend the literature regarding associations between ADHD and tobacco use by using current (to 2023) nationally representative longitudinal data over a 9-year period that accounts for ADHD symptom severity and assesses longitudinal associations with multiple forms of nicotine and tobacco use, including more contemporary smokeless and electronic products. The following research questions were examined in this study: (1) Do youths with asymptomatic ADHD (with or without pharmacotherapy) differ from youths without ADHD or ADHD symptoms in their risk of incident e-cigarette and tobacco use? (2) Are there differences between youths with ADHD symptoms, with or without an ADHD diagnosis, compared with youths without ADHD or ADHD symptoms in their risk of incident e-cigarette and tobacco use? and (3) Do youths with symptomatic ADHD have an increased risk of incident e-cigarette and tobacco use compared with youths with asymptomatic ADHD?
Methods
In this cohort study, a nationally representative sample of US youths (N = 13 651) aged 12 to 17 years old and their parents (N = 13 588) from the Population Assessment of Tobacco and Health (PATH) Study were surveyed via questionnaires at wave 1 (September 2013 to December 2014) and followed up over 6 additional waves in subsequent years (October 2014 to April 2023). Beginning in wave 2, youths who turned 18 years of age continued to be followed up via the PATH adult survey. At wave 1, household screenings were conducted with computer-assisted personal interviewing to determine eligibility. All surveys were conducted using audio computer-assisted self-interviews in English or Spanish.24 The weighted response rate at wave 1 for youths was 78.4%. Weighted response rates at follow-up ranged from 87.3% (wave 2) to 54.3% (wave 7). Additional details regarding interviewing procedures, sampling, and weighting are available elsewhere.25 The present study excluded 2.3% of the sample due to missingness on variables at wave 1, resulting in a final analytic sample of 13 572 youths. The study was approved by the Westat Institutional Review Board, and this secondary data analysis study with restricted data was determined exempt from informed consent by the University of Michigan Institutional Review Board because the data were deidentified. We followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.
Measures
Key Outcome Variables
At each wave, youths reported on lifetime and past-year use of 9 different nicotine or tobacco products: (1) electronic nicotine products such as e-cigarettes, vape pens, personal vaporizers and mods, e-cigars, e-pipes, e-hookahs, or hookah pens (collectively termed e-cigarettes for this study); (2) cigarettes; (3) cigars; (4) little cigars, cigarillos, or filtered cigars; (5) pipes; (6) hookahs; (7) smokeless tobacco; (8) snus; or (9) dissolvable tobacco. As the primary outcomes, we examined the incidence (new onset of use over the follow-up period 2015-2023 or waves 2-7) of 4 nicotine or tobacco outcomes among youths who reported no lifetime use at wave 1: e-cigarette use, cigarette smoking, other tobacco use (cigars, little cigars, cigarillos, or filtered cigars; pipes, hookahs, smokeless tobacco, snus, or dissolvable tobacco), and dual use (both e-cigarettes and cigarettes or tobacco products). Wave 1 prevalence of these 4 outcomes was also examined.
Key Exposure Variables
At wave 1, parents self-reported whether their child had a history of an ADHD diagnosis (“Has [Child’s first name] ever been told by a doctor, nurse, or other health professional that [he or she] has ADHD or ADD?” [yes or no]) and whether their child regularly took medication for ADHD (“In the past 12 months, has [Child’s first name] taken medications regularly for ADHD or ADD?” [yes or no]). From these 2 questions, we created 3 mutually exclusive groups: ADHD diagnosis with pharmacotherapy, ADHD diagnosis without pharmacotherapy, and population controls without an ADHD diagnosis or pharmacotherapy.
Youths completed items from the Global Appraisal of Individual Needs (GAIN) assessment,24,26,27 which included a list of ADHD symptoms from validated and reliable screeners recommended in the PhenX Toolkit.28 The following 4 items from the GAIN externalizing scale assessed DSM-based ADHD inattentive and hyperactive and/or impulsive symptoms:
“Had a hard time paying attention at school, work, or home?”
“Had a hard time listening to instructions at school, work, or home?”
“Felt restless or the need to run around or climb on things?”
“Gave answers before the other person finished asking the question?”
For each item, respondents indicated whether they had experienced the symptom multiple times in the past month, 2 to 12 months ago, over 1 year ago, or never. The Cronbach α for the 4 ADHD symptoms was 0.73. Based on recommended cut points, we summed the number of past-year symptoms at wave 1 (range, 0-4) and categorized participants into tertiles consisting of no symptoms, 1 to 2 symptoms, and 3 to 4 symptoms.26
Covariate Variables
Covariates at wave 1 included age (12-14 vs 15-17 years), sex, US region (Northeast, Midwest, South, or West), internalizing symptoms (feeling very trapped, sad, or depressed; trouble sleeping; feeling nervous, anxious, tense, or scared; and being distressed or upset about the past [scored as 0-4]), other externalizing symptoms (lied or conned to get something; bullied or threatened people; or started a physical fight [scored as 0-3]), lifetime nonmedical use of prescription stimulants (methylphenidate and amphetamine products without a prescription or other than prescribed), Hispanic ethnicity, and race. Participants self-reported their race by answering the question “What is your race? Choose all that apply.” The options included American Indian or Alaska Native, Asian Indian, Black or African American, Chinese, Filipino, Guamanian or Chamorro, Japanese, Korean, Native Hawaiian, Other Asian, Other Pacific Islander, Samoan, Vietnamese, White, do not know, or declined to answer. The PATH team combines many of these categories into Asian and Pacific Islander when they make the data available. Race and other covariates were included because they have been shown to be associated with ADHD diagnosis, symptoms, pharmacotherapy, and e-cigarette or tobacco use.13,14,15,16,17,29,30,31,32,33
Statistical Analysis
We first calculated weighted descriptive statistics for the overall sample and by ADHD diagnosis and use of pharmacotherapy at wave 1. We then estimated the prevalence of each of the 4 nicotine or tobacco use outcomes at wave 1 (2013-2014) and the incidence at follow-up waves 2 through 7 (2015-2023). For each incidence outcome, analyses were restricted to the subpopulation of individuals who were at risk for new use at wave 1. For example, analyses examining incidence of e-cigarette use included only those who had not yet used e-cigarettes by wave 1 and analyses examining incidence of cigarette smoking included only those who had not yet smoked cigarettes by wave 1. A sensitivity analysis was conducted by excluding youths who reported any nicotine or tobacco use at wave 1. Finally, discrete time hazard models were fitted to the PATH data to examine the associations of ADHD diagnosis, pharmacotherapy, and symptoms at wave 1 with subsequent incidence of e-cigarette use, cigarette smoking, other tobacco use, and dual use. To do this we created a long-format data file with a row for each person-wave of data contributed. By using a person-wave data format, we were able to use standard multivariable logistic regression models to estimate the discrete time hazard function.34,35 All analyses accounted for the complex sample design of the PATH and used the Stata suite of svy commands, version 18 (StataCorp LLC) and balanced repeated replication weights with a 0.3 Fay adjustment. Two-sided P < .05 indicated statistical significance.
Results
The sample of 13 572 US youths with weighted percentages (6967 male [51.3%; 95% CI, 51.2%-51.5%] and 6605 [48.7%; 95% CI, 48.5%-48.8%] female) comprised 6972 (50.4%; 95% CI, 50.3%-50.6%) aged 12 to 14 years and 6600 (49.6%; 95% CI, 49.4%-49.7%) aged 15 to 17 years old. In terms of race and ethnicity, 1665 (9.3%; 95% CI, 8.9%-9.7%) were American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, or multiracial; 412 (4.7% 95% CI, 4.6%-4.9%), Asian; 2073 (15.3% 95% CI, 15.0%-15.5%), Black or African American; 3897 (22.2% 95% CI, 22.0%-22.3%), Hispanic; and 9422 (70.8% 95% CI, 70.2%-71.4%), White. A total of 1881 US youths (14.1%; 95% CI, 13.2%-15.0%) were diagnosed with ADHD, with 1074 (57.9%; 95% CI, 55.2%-60.5%) having received pharmacotherapy for ADHD at wave 1 (Table 1). The distribution of ADHD inattentive and hyperactive and/or impulsive symptoms was as follows (percentages are weighted): 3527 youths (25.3%; 95% CI, 24.3%-26.3%) reported no ADHD symptoms, 5186 (38.4%; 95% CI, 37.5%-39.3%) reported 1 to 2 ADHD symptoms, and 4840 (36.3%; 95% CI, 35.3%-37.4%) reported 3 or more ADHD symptoms.
Table 1. Sample Characteristics of 13 572 US Youths Aged 12 to 17 Years at Wave 1a.
| Wave 1 characteristics | Diagnosis group, unweighted No. (weighted %) [95% CI] | P valueb | |||
|---|---|---|---|---|---|
| Overall | ADHD with pharmacotherapy | ADHD without pharmacotherapy | No ADHD (population controls) | ||
| ADHD diagnosis | |||||
| Yes | 1881 (14.1) [13.2-15.0] | 1074 (100) | 807 (100) | 0 | <.001 |
| No | 11 691 (85.9) [85.0-86.8] | 0 | 0 | 11 691 (100) | |
| ADHD pharmacotherapy | |||||
| Yes | 1074 (57.9) [55.2-60.5] | 1074 (100) | 0 | 0 | <.001 |
| No | 807 (42.1) [39.5-44.8] | 0 | 807 (100) | 11 691 (100) | |
| ADHD symptoms | |||||
| 3-4 | 4840 (36.3) [35.3-37.4] | 519 (48.9) [45.5-52.3] | 351 (44.4) [40.6-48.4] | 3970 (34.4) [33.3-35.6] | <.001 |
| 1-2 | 5186 (38.4) [37.5-39.3] | 334 (31.7) [29.0-34.6] | 270 (33.5) [30.3-36.8] | 4582 (39.3) [38.3-40.2] | |
| None | 3527 (25.3) [24.3-26.3] | 220 (19.4) [16.9-22.1] | 184 (22.1) [19.3-25.2] | 3123 (26.3) [25.2-27.5] | |
| Sex | |||||
| Female | 6605 (48.7) [48.5-48.8] | 320 (30.1) [27.1-33.2] | 259 (32.2) [29.1-35.4] | 6026 (51.5) [51.0-51.9] | <.001 |
| Male | 6967 (51.3) [51.2-51.5] | 754 (69.9) [66.8-72.9] | 548 (67.8) [64.6-70.9] | 5665 (48.5) [48.1-49.0] | |
| Race | |||||
| American Indian or Alaska Native, Native Hawaiian or Other Pacific Islander, or multiracial | 1665 (9.3) [8.9-9.7] | 129 (8.6) [7.1-10.4] | 116 (11.0) [9.0-13.4] | 1420 (9.2) [8.7-9.8] | <.001 |
| Asian | 412 (4.7) [4.6-4.9] | 16 (2.6) [1.3-3.6] | 12 (1.9) [1.2-3.2] | 384 (5.2) [5.0-5.4] | |
| Black or African American | 2073 (15.3) [15.0-15.5] | 147 (12.8) [10.3-15.8] | 136 (16.0) [13.4-19.0] | 1790 (15.4) [15.0-15.8] | |
| White | 9422 (70.8) [70.2-71.4] | 782 (76.5) [73.3-79.3] | 543 (71.0) [67.3-74.5] | 8097 (70.2) [69.5-70.9] | |
| Hispanic ethnicity | 3897 (22.2) [22.0-22.3] | 188 (13.2) [11.3-15.3] | 176 (17.7) [14.9-20.9] | 3533 (23.4) [23.1-23.8] | <.001 |
| US Census region | |||||
| Northeast | 2037 (16.9) [16.8-17.0] | 165 (16.6) [13.5-20.2] | 126 (16.1) [13.2-19.5] | 1746 (17.0) [16.5-17.4] | <.001 |
| Midwest | 2937 (21.6) [21.5-21.7] | 266 (23.6) [20.0-27.7] | 188 (23.0) [19.2-27.4] | 2483 (21.3) [20.8-21.8] | |
| South | 5136 (37.5) [37.4-37.7] | 466 (44.5) [40.4-48.6] | 308 (38.7) [34.6-42.9] | 4362 (36.8) [36.3-37.3] | |
| West | 3462 (24.0) [23.9-24.1] | 177 (15.3) [12.5-18.6] | 185 (22.2) [19.3-25.3] | 3100 (24.9) [24.5-25.4] | |
| Age, y | |||||
| 12-14 | 6972 (50.4) [50.3-50.6] | 630 (57.3) [54.1-60.4] | 352 (43.3) [39.9-46.9] | 5990 (50.4) [50.1-50.8] | <.001 |
| 15-17 | 6600 (49.6) [49.4-49.7] | 444 (42.7) [39.6-45.9] | 455 (56.7) [53.1-60.1] | 5701 (49.6) [49.2-49.9] | |
| No. of internalizing symptoms, mean (SD)c | 1.80 (1.55) | 1.95 (1.50) | 1.79 (1.61) | 1.78 (1.55) | .04 |
| No. of non-ADHD externalizing symptoms, mean (SD)d | 0.60 (0.76) | 0.82 (0.85) | 0.74 (0.85) | 0.62 (0.73) | <.001 |
| Lifetime nonmedical use of prescription stimulants | 332 (2.5) [2.2-2.8] | 91 (8.6) [6.9-10.6] | 40 (4.7) [3.5-6.5] | 201 (1.8) [1.6-2.0] | <.001 |
| Past-year e-cigarette use | 1184 (8.9) [8.3-9.5] | 131 (12.7) [10.3-15.5] | 106 (13.2) [10.5-16.5] | 947 (8.2) [7.7-8.9] | <.001 |
| Past-year cigarette smoking | 1159 (8.6) [8.0-9.2] | 162 (15.3) [13.1-17.7] | 122 (14.6) [12.1-17.5] | 875 (7.6) [7.0-8.2] | <.001 |
| Past-year other tobacco use | 1840 (11.4) [10.6-12.2] | 201 (15.1) [12.9-17.7] | 177 (17.2) [14.4-20.4] | 1462 (10.6) [9.8-11.4] | <.001 |
Abbreviation: ADHD, attention-deficit/hyperactivity disorder.
Rates of missing items range from 0.01% (past-year other tobacco use) to 0.55% (ADHD diagnosis).
Continuous variables are compared using analysis of variance at the 95% level. Categorical variables are compared using Pearson χ2 test at the 95% level.
Ranges from 0 to 4.
Ranges from 0 to 3.
As shown in Table 2, the prevalence and incidence of all 4 nicotine and tobacco outcomes were highest among US youths who reported more ADHD symptoms. Across all 3 ADHD diagnosis and pharmacotherapy groups, most youths with highly symptomatic (3 or 4 symptoms) ADHD (range: 52.0% [95% CI, 49.9%-54.0%] to 58.6% [95% CI, 53.0%-64.0%]) reported incident e-cigarette use in the subsequent 9-year period. This compared with approximately one-third of youths with no symptoms in each of the 3 groups (range 31.4% [95% CI, 29.3%-33.5%] to 35.6% [95% CI, 27.3%-44.8%]). The prevalence and incidence of e-cigarette use, cigarette smoking, other tobacco use, or dual use among US youths with 1 or 2 ADHD symptoms consistently fell between the subgroup without symptoms and the subgroup with 3 or 4 ADHD symptoms for all nicotine and tobacco outcomes over a 9-year period. For instance, one-half of youths with highly symptomatic ADHD receiving pharmacotherapy reported incident dual use (50.8%; 95% CI, 45.3%-56.3%) in the subsequent 9-year period compared with a lower incidence of dual use among youths with an ADHD diagnosis taking pharmacotherapy with 1 or 2 ADHD symptoms (40.8%; 95% CI, 34.3%-47.8%) or no ADHD symptoms (24.2%; 95% CI, 18.6%-30.9%).
Table 2. ADHD Diagnosis, Number of Symptoms, Use of Pharmacotherapy, and Later Nicotine and Tobacco Use in US Youthsa.
| Subgroup by symptoms at wave 1 | Weighted % (95% CI) | |||||||
|---|---|---|---|---|---|---|---|---|
| E-cigarette use | Cigarette smoking | Other tobacco use | Dual use | |||||
| Wave 1 prevalence (n = 13 336) | Waves 2-7 incidence (n = 12 091)b | Wave 1 prevalence (n = 13 336) | Waves 2-7 incidence (n = 11 722)b | Wave 1 prevalence (n = 13 336) | Waves 2-7 incidence (n = 11 700)b | Wave 1 prevalence (n = 13 336) | Waves 2-7 incidence (n = 12 417)b | |
| No ADHD diagnosis | ||||||||
| No symptoms (n = 3123) | 4.7 (4.0-5.5) | 31.4 (29.3-33.5) | 4.9 (4.1-5.8) | 18.8 (17.3-20.3) | 6.4 (5.5-7.5) | 24.1 (22.2-26.1) | 3.5 (2.9-4.3) | 23.5 (21.8-25.3) |
| 1 or 2 Symptoms (n = 4582) | 7.1 (6.3-7.9) | 41.6 (40.1-43.1) | 6.1 (5.2-7.1) | 23.5 (22.0-25.0) | 9.1 (8.1-10.2) | 31.7 (30.1-33.3) | 5.0 (4.3-5.7) | 31.0 (29.6-32.5) |
| 3-4 Symptoms (n = 3970) | 12.3 (11.3-13.4) | 52.0 (49.9-54.0) | 11.3 (10.3-12.4) | 31.6 (29.6-33.7) | 15.4 (10.5-22.3) | 39.8 (37.8-41.8) | 8.8 (7.9-9.8) | 42.3 (40.2-44.5) |
| ADHD diagnosis and no ADHD pharmacotherapy | ||||||||
| No symptoms (n = 184) | 9.8 (5.7-16.6) | 35.6 (27.3-44.8) | 11.9 (7.6-18.1) | 27.6 (20.4-36.2) | 15.5 (10.5-22.3) | 33.0 (24.9-42.2) | 8.5 (4.7-14.9) | 29.6 (21.9-38.7) |
| 1 or 2 Symptoms (n = 270) | 11.8 (7.6-17.8) | 42.3 (36.3-48.4) | 12.6 (8.7-17.7) | 31.1 (25.0-37.9) | 17.0 (12.8-22.3) | 38.5 (32.1-45.3) | 9.1 (6.0-13.8) | 36.7 (31.0-42.8) |
| 3 or 4 Symptoms (n = 351) | 16.0 (12.3-20.7) | 56.8 (50.0-63.3) | 17.6 (13.9-22.1) | 35.7 (29.3-42.8) | 18.3 (14.3-23.1) | 48.7 (42.7-54.7) | 13.0 (9.7-17.1) | 49.5 (42.3-56.8) |
| ADHD diagnosis and ADHD pharmacotherapy | ||||||||
| No symptoms (n = 220) | 7.6 (4.4-12.7) | 31.8 (25.7-38.7) | 8.3 (5.0-13.4) | 21.8 (16.7-27.9) | 9.5 (5.8-15.0) | 30.2 (24.3-36.9) | 6.2 (3.6-10.5) | 24.2 (18.6-30.9) |
| 1 or 2 Symptoms (n = 334) | 11.9 (8.4-16.7) | 49.5 (43.5-55.5) | 12.7 (8.9-17.8) | 35.1 (28.2-42.6) | 12.1 (8.6-16.7) | 40.8 (33.5-48.6) | 9.4 (6.5-13.6) | 40.8 (34.3-47.8) |
| 3 or 4 Symptoms (n = 519) | 15.1 (11.9-19.0) | 58.6 (53.0-64.0) | 19.8 (16.7-23.3) | 39.3 (34.5-44.3) | 19.4 (16.1-23.2) | 46.6 (40.4-52.9) | 12.3 (9.5-15.9) | 50.8 (45.3-56.3) |
Abbreviation: ADHD, attention-deficit/hyperactivity disorder.
Includes 13 572 participants. Wave 1 measured past 12-month prevalence during 2013 to 2014; waves 2 to 7 follow-up occurred from 2015 to 2023.
Incidence estimates exclude individuals who reported the particular outcome at wave 1 to establish new onset.
As shown in Table 3, the resulting sample sizes of the applicable subpopulations were 11 722 for cigarettes, 12 091 for e-cigarette, 11 700 for other tobacco products, and 12 417 for dual use. Discrete time survival models indicated that the adjusted odds of incident e-cigarette use, cigarette smoking, other tobacco use, and dual use did not significantly differ between youths with asymptomatic ADHD (whether they were receiving pharmacotherapy for ADHD or not) compared with population controls. In contrast, all 3 subgroups of youths with 3 or more ADHD symptoms had significantly greater adjusted odds of most incident outcomes compared with population controls. For instance, youths with ADHD receiving pharmacotherapy and reporting 3 or more past-year ADHD symptoms at wave 1 had greater odds of incident e-cigarette use (adjusted odds ratio [AOR], 1.60; 95% CI, 1.34-2.04), cigarette smoking (AOR, 1.52; 95% CI, 1.22-1.89), other tobacco use (AOR, 1.61; 95% CI, 1.27-2.02), and dual use (AOR, 1.72; 95% CI, 1.38-2.14) than population controls reporting no symptoms. Consistent with the bivariate results, the adjusted odds for US youths with 1 or 2 ADHD symptoms consistently fell between the subgroups without symptoms and 3 or more ADHD symptoms for all the nicotine and tobacco outcomes consistent with a dose-response association.
Table 3. ADHD Diagnosis, Use of Pharmacotherapy, and Number of Symptoms at Wave 1 and Odds of Later Nicotine and Tobacco Use at Waves 2 to 7 in US Youths.
| Subgroup by symptoms at wave 1 | Incidence, AOR (95% CI)a | |||
|---|---|---|---|---|
| E-cigarette use (n = 12 091) | Cigarette smoking (n = 11 722) | Other tobacco use (n = 11 700) | Dual use (n = 12 417) | |
| No ADHD diagnosis | ||||
| No symptoms | 1 [Reference] | 1 [Reference] | 1 [Reference] | 1 [Reference] |
| 1-2 Symptoms | 1.15 (1.05-1.27)b | 1.03 (0.90-1.19) | 1.16 (1.03-1.32)b | 1.08 (0.97-1.19) |
| 3-4 Symptoms | 1.36 (1.20-1.54)b,c | 1.21 (1.04-1.41)b | 1.36 (1.17-1.59)b | 1.32 (1.15-1.52)b,c |
| ADHD diagnosis and no ADHD pharmacotherapy | ||||
| No symptoms | 1.12 (0.78-1.60) | 1.39 (0.92-2.12) | 1.17 (0.81-1.70) | 1.14 (0.76-1.70) |
| 1-2 Symptoms | 1.13 (0.88-1.44) | 1.35 (0.97-1.87) | 1.35 (1.00-1.82)b | 1.23 (0.94-1.61) |
| 3-4 Symptoms | 1.53 (1.18-1.99)b,c | 1.32 (0.94-1.86) | 1.68 (1.30-2.18)b | 1.53 (1.17-2.01)b,c |
| ADHD diagnosis and ADHD pharmacotherapy | ||||
| No symptoms | 0.98 (0.74-1.30) | 1.01 (0.71-1.46) | 1.25 (0.88-1.77) | 0.92 (0.65-1.30) |
| 1-2 Symptoms | 1.42 (1.11-1.81)b,c | 1.43 (1.05-1.95)b | 1.45 (1.09-1.92)b | 1.40 (1.05-1.86)b,c |
| 3-4 Symptoms | 1.60 (1.34-2.04)b,c,d | 1.52 (1.22-1.89)b | 1.61 (1.27-2.02)b | 1.72 (1.38-2.14)b,c |
Abbreviations: ADHD, attention-deficit/hyperactivity disorder; AOR, adjusted odds ratio.
Incidence estimates exclude individuals who reported the specified outcome at wave 1 (2013-2014) to establish new onset during the follow-up period of waves 2 to 7 (2015-2023). All models control for the age, sex, race, Hispanic ethnicity, region, other externalizing symptoms, internalizing symptoms, and nonmedical use of prescription stimulants.
Significantly different from the subgroup with no ADHD diagnosis and no ADHD symptoms.
Significantly different from the subgroup with ADHD diagnosis, ADHD pharmacotherapy, and no ADHD symptoms.
Significantly different from the subgroup with ADHD diagnosis, no ADHD pharmacotherapy, and no ADHD symptoms.
Youths with no ADHD diagnosis and 3 or more ADHD symptoms had greater odds of incident e-cigarette use (AOR, 1.36; 95% CI, 1.20-1.54), cigarette smoking (AOR, 1.21; 95% CI, 1.04-1.41), other tobacco use (AOR, 1.36; 95% CI, 1.17-1.59), and dual use (AOR, 1.32; 95% CI, 1.15-1.52) compared with population controls (Table 3). A sensitivity analysis was conducted by excluding youths who reported any nicotine or tobacco use at wave 1 and the substantive results in Table 3 did not change. Youths with ADHD experiencing 3 or more ADHD symptoms and receiving pharmacotherapy were significantly more likely to initiate e-cigarette (AOR, 1.68; 95% CI, 1.16-2.44) and dual use (AOR, 1.82; 95% CI, 1.17-2.83) than youths with asymptomatic ADHD receiving pharmacotherapy (Figure 1 and Figure 2). In addition, youths with no ADHD diagnosis and 3 or more ADHD symptoms had significantly greater adjusted odds of incident e-cigarette use (AOR, 1.39; 95% CI, 1.02-1.89) and incident dual use (AOR, 1.44; 95% CI, 1.01-2.06) compared with youths with asymptomatic ADHD receiving pharmacotherapy (Figures 1 and 2).
Figure 1. Association of E-Cigarette Use With Attention-Deficit/Hyperactivity Disorder (ADHD) Diagnosis, Number of Symptoms, and Use of Pharmacotherapy in US Youths (2015-2023).
Low symptoms are defined as 1 or 2 symptoms; high, 3 or 4 symptoms. The reference was the subgroup with ADHD diagnosis with ADHD medications and no ADHD symptoms. AOR indicates adjusted odds ratio.
Figure 2. Association of Dual E-Cigarette and Tobacco Use With Attention-Deficit/Hyperactivity Disorder (ADHD) Diagnosis, Number of Symptoms, and Use of Pharmacotherapy in US Youths (2015-2023).
Low symptoms are defined as 1 or 2 symptoms; high, 3 or 4 symptoms. The reference was the subgroup with ADHD diagnosis with ADHD medications and no ADHD symptoms. AOR indicates adjusted odds ratio.
Discussion
The present cohort study found that US youths with asymptomatic ADHD—with or without ADHD pharmacotherapy—did not differ from population controls in their odds of initiating e-cigarette use, cigarette smoking, other tobacco use, or dual use over the subsequent 9 years. In contrast, US youths who reported higher levels of ADHD symptoms—regardless of lifetime ADHD diagnosis or pharmacotherapy—had significantly greater odds of initiating e-cigarette use, cigarette smoking, other tobacco use, or dual use in the subsequent 9 years.
Like prior studies of ADHD symptoms and cigarette smoking,7,8 the odds of initiating e-cigarette use, cigarette smoking, other tobacco use, or dual use, increased with ADHD symptom severity in a dose-response association, with the subgroups without symptoms demonstrating the lowest risk, those with lower ADHD symptom severity (1-2 symptoms) demonstrating intermediate risk, and those with higher ADHD symptom severity (3-4 symptoms) demonstrating the highest risk. Potential reasons for this increased risk are that youths with higher symptom severity may use nicotine to self-treat their ADHD symptoms. Nicotine has been shown to enhance cognition in general and reduce ADHD symptoms specifically.36 Moreover, it has been speculated that nicotine may increase the release of several neurotransmitters that via nicotinic receptors increase catechol, indolamines, β-endorphin, and γ-aminobutyric acid levels, potentially mediating the neurobiological deficits inherent in ADHD.37,38
The findings in the present study add to existing literature in compelling ways and have important clinical and policy implications. First, the results highlight the significant longitudinal association between ADHD symptom severity and future nicotine and tobacco use. Most US youths who reported 3 or more ADHD symptoms in the present study at wave 1 initiated e-cigarette use in the subsequent 9-year period, which was not observed among those with 0 to 2 symptoms. Second, the finding that US youths with asymptomatic ADHD—with or without pharmacotherapy—did not differ from their population control peers without ADHD diagnoses in their odds of initiating e-cigarette use, cigarette smoking, other tobacco use, or dual use over the subsequent 9-year period highlights the importance of monitoring and management of ADHD symptoms and the potential protective effect of treatment against nicotine and tobacco use.
A major clinical implication of these findings is that health care professionals need to closely monitor inattentive and hyperactive and/or impulsive symptoms and work to reduce them to the lowest levels. While more research is needed to determine the degree to which ADHD symptom reduction lowers risk behaviors, there is a growing body of literature showing that greater symptom reduction through treatment results in improved functional outcomes,39 while persistence of ADHD symptoms can result in adverse outcomes.40 The present findings support the assertion from prior clinical studies that alleviating core ADHD symptoms may lead to a reduction in risky behaviors among US youths with ADHD.22,41
Given the increased risk of nicotine and tobacco use in those with ADHD,1,2,3 the null findings between youths with asymptomatic ADHD and later nicotine and tobacco initiation could be interpreted as ADHD treatment being protective against subsequent nicotine and tobacco use. Indeed, those with no ADHD diagnosis and higher ADHD symptom severity were at greater risk for nicotine and tobacco onset than youths with asymptomatic ADHD. Taken together, these findings underscore the risk associated with higher levels of inattentive and hyperactive and/or impulsive symptoms and the need to identify such youths as early as possible so that they may access services to reduce symptoms. The group of adolescents with inattentive and hyperactive and/or impulsive symptoms and no ADHD diagnosis represents a high-risk subpopulation often missed in clinical research. Pediatric health care professionals should be knowledgeable about ADHD symptoms, screening and assessment tools, and treatment options, including stimulant and nonstimulant medications and psychosocial interventions that reduce inattentive and hyperactive and/or impulsive symptoms.42,43 In addition, parents and caregivers should be educated on ADHD symptoms, screening and assessment tools, and treatment options.
Strengths and Limitations
There are several notable strengths of the present study, including the use of a large nationally representative longitudinal sample of US youths whose ADHD diagnosis, symptoms, and pharmacotherapy were assessed using the same methodology over time. The study featured population controls without ADHD and assessed multiple forms of nicotine and tobacco use to better understand the current landscape of substance use among US youths, including newer e-products.
There were also some limitations that must be weighed when considering the implications of the findings. The list of ADHD symptoms that was assessed included several items from validated and reliable screeners recommended in the PhenX Toolkit28 but did not include an exhaustive list of all ADHD symptoms. Screening instruments based on self-reports are designed to quickly identify individuals who have a potential diagnosis and may need more comprehensive follow-up clinical assessment. Prior work has shown screening tools such as the GAIN Short Screener should not be used by clinicians to establish a specific diagnosis on its own due to low specificity and the risk of misclassifying individuals.26,44 The sample included individuals 12 years and older, and some had already initiated nicotine or tobacco use at wave 1. While examining incident use (ie, rather than overall prevalence) partially addressed this limitation, future longitudinal research should begin assessments for ADHD symptoms and nicotine and tobacco use at earlier ages. Finally, the COVID-19 pandemic had a major impact on ADHD diagnosis, treatment, and substance use among US youths.14,45,46,47,48,49 In recent years, there have been shortages of some ADHD medications that, along with disruptions caused by the COVID-19 pandemic, have impacted ADHD treatment for many US youths (S. He, S.E.M., R Conti, A. Volerman, K. P. Chua; unpublished data; completed September 23, 2024).49 While we examined nicotine and tobacco initiation after onset of the COVID-19 pandemic, future research is warranted to examine potential changes in ADHD diagnosis, treatment, and the associations between ADHD and substance use onset, specifically during and following the COVID-19 pandemic.
Conclusions
In this cohort study of US youths, the findings support prior research and provide more current information about the associations between ADHD symptoms and newer forms of nicotine and tobacco use. Findings highlight the importance of early diagnosis and effective treatment of ADHD—with or without pharmacotherapy—to alleviate ADHD symptoms and thus reduce the risk of later nicotine and tobacco use among US youths. Future research should consider similar methods to examine associations between ADHD treatment, symptoms, and other substance use and adverse health outcomes to better understand whether a threshold of inattentive and hyperactive and/or impulsive symptoms exists that can be clinically monitored to improve health outcomes. This line of research is needed to guide clinicians in treating ADHD and to prevent the onset and escalation of nicotine and tobacco use among this high-risk population.
Data Sharing Statement
References
- 1.The health consequences of smoking—50 years of progress: a report of the Surgeon General. US Dept of Health and Human Services . 2014. Accessed July 29, 2024. https://stacks.cdc.gov/view/cdc/21569
- 2.Smoking cessation: a report of the surgeon general. United States Public Health Service Office of the Surgeon General . 2020. Accessed October 9, 2024. https://pubmed.ncbi.nlm.nih.gov/32255575/ [PubMed]
- 3.Le TTT, Méndez D, Warner KE. New estimates of smoking-attributable mortality in the U.S. from 2020 through 2035. Am J Prev Med. 2024;66(5):877-882. doi: 10.1016/j.amepre.2023.12.017 [DOI] [PubMed] [Google Scholar]
- 4.Charach A, Yeung E, Climans T, Lillie E. Childhood attention-deficit/hyperactivity disorder and future substance use disorders: comparative meta-analyses. J Am Acad Child Adolesc Psychiatry. 2011;50(1):9-21. doi: 10.1016/j.jaac.2010.09.019 [DOI] [PubMed] [Google Scholar]
- 5.Chang Z, Lichtenstein P, Larsson H. The effects of childhood ADHD symptoms on early-onset substance use: a Swedish twin study. J Abnorm Child Psychol. 2012;40(3):425-435. doi: 10.1007/s10802-011-9575-6 [DOI] [PubMed] [Google Scholar]
- 6.Groenman AP, Oosterlaan J, Rommelse N, et al. Substance use disorders in adolescents with attention deficit hyperactivity disorder: a 4-year follow-up study. Addiction. 2013;108(8):1503-1511. doi: 10.1111/add.12188 [DOI] [PubMed] [Google Scholar]
- 7.Wilens TE, Vitulano M, Upadhyaya H, et al. Cigarette smoking associated with attention deficit hyperactivity disorder. J Pediatr. 2008;153(3):414-419. doi: 10.1016/j.jpeds.2008.04.030 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Kollins SH, McClernon FJ, Fuemmeler BF. Association between smoking and attention-deficit/hyperactivity disorder symptoms in a population-based sample of young adults. Arch Gen Psychiatry. 2005;62(10):1142-1147. doi: 10.1001/archpsyc.62.10.1142 [DOI] [PubMed] [Google Scholar]
- 9.Upadhyaya HP, Rose K, Wang W, et al. Attention-deficit/hyperactivity disorder, medication treatment, and substance use patterns among adolescents and young adults. J Child Adolesc Psychopharmacol. 2005;15(5):799-809. doi: 10.1089/cap.2005.15.799 [DOI] [PubMed] [Google Scholar]
- 10.Tercyak KP, Lerman C, Audrain J. Association of attention-deficit/hyperactivity disorder symptoms with levels of cigarette smoking in a community sample of adolescents. J Am Acad Child Adolesc Psychiatry. 2002;41(7):799-805. doi: 10.1097/00004583-200207000-00011 [DOI] [PubMed] [Google Scholar]
- 11.Galéra C, Fombonne E, Chastang JF, Bouvard M. Childhood hyperactivity-inattention symptoms and smoking in adolescence. Drug Alcohol Depend. 2005;78(1):101-108. doi: 10.1016/j.drugalcdep.2004.10.003 [DOI] [PubMed] [Google Scholar]
- 12.Brumbaugh S, Tuan WJ, Scott A, Latronica JR, Bone C. Trends in characteristics of the recipients of new prescription stimulants between years 2010 and 2020 in the United States: an observational cohort study. EClinicalMedicine. 2022;50:101524. doi: 10.1016/j.eclinm.2022.101524 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Danielson ML, Claussen AH, Bitsko RH, et al. ADHD prevalence among U.S. children and adolescents in 2022: diagnosis, severity, co-occurring disorders, and treatment. J Clin Child Adolesc Psychol. 2024;53(3):343-360. doi: 10.1080/15374416.2024.2335625 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.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. 2023. Accessed March 3, 2024. https://monitoringthefuture.org/wp-content/uploads/2022/12/mtf2022.pdf
- 15.Pierce JP, Luo M, McMenamin SB, et al. Declines in cigarette smoking among US adolescents and young adults: indications of independence from e-cigarette vaping surge. Tob Control. Published online November 8, 2023. doi: 10.1136/tc-2022-057907 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Davidovitch M, Koren G, Fund N, Shrem M, Porath A. Challenges in defining the rates of ADHD diagnosis and treatment: trends over the last decade. BMC Pediatr. 2017;17(1):218. doi: 10.1186/s12887-017-0971-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Chung W, Jiang SF, Paksarian D, et al. Trends in the prevalence and incidence of attention-deficit/hyperactivity disorder among adults and children of different racial and ethnic groups. JAMA Netw Open. 2019;2(11):e1914344. doi: 10.1001/jamanetworkopen.2019.14344 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Li Y, Yan X, Li Q, et al. Prevalence and trends in diagnosed adhd among US children and adolescents, 2017-2022. JAMA Netw Open. 2023;6(10):e2336872. doi: 10.1001/jamanetworkopen.2023.36872 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Biederman J, Monuteaux M. Is cigarette smoking a gateway drug to subsequent alcohol and illicit drug use disorders: a controlled study of youth with and without ADHD. Eur Neuropsychopharmacol. doi: 10.1016/j.biopsych.2005.07.009 [DOI] [PubMed] [Google Scholar]
- 20.Trauth JA, Seidler FJ, Slotkin TA. Persistent and delayed behavioral changes after nicotine treatment in adolescent rats. Brain Res. 2000;880(1-2):167-172. doi: 10.1016/S0006-8993(00)02823-7 [DOI] [PubMed] [Google Scholar]
- 21.Wilens TE, Martelon M, Fried R, Petty C, Bateman C, Biederman J. Do executive function deficits predict later substance use disorders among adolescents and young adults? J Am Acad Child Adolesc Psychiatry. 2011;50(2):141-149. doi: 10.1016/j.jaac.2010.11.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Barkley RA, Murphy KR, Dupaul GI, Bush T. Driving in young adults with attention deficit hyperactivity disorder: knowledge, performance, adverse outcomes, and the role of executive functioning. J Int Neuropsychol Soc. 2002;8(5):655-672. doi: 10.1017/S1355617702801345 [DOI] [PubMed] [Google Scholar]
- 23.Chang Z, Lichtenstein P, D’Onofrio BM, Sjölander A, Larsson H. Serious transport accidents in adults with attention-deficit/hyperactivity disorder and the effect of medication: a population-based study. JAMA Psychiatry. 2014;71(3):319-325. doi: 10.1001/jamapsychiatry.2013.4174 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Hyland A, Ambrose BK, Conway KP, et al. Design and methods of the Population Assessment of Tobacco and Health (PATH) Study. Tob Control. 2017;26(4):371-378. doi: 10.1136/tobaccocontrol-2016-052934 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Population Assessment of Tobacco and Health (PATH) Study [United States] restricted-use files (ICPSR 36231). National Addiction & HIV Data Archive Program . October 11, 2024. Accessed October 11, 2024. https://www.icpsr.umich.edu/web/NAHDAP/studies/36231
- 26.Dennis ML, Chan YF, Funk RR. Development and validation of the GAIN Short Screener (GSS) for internalizing, externalizing and substance use disorders and crime/violence problems among adolescents and adults. Am J Addict. 2006;15(suppl 1):80-91. doi: 10.1080/10550490601006055 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Evans-Polce RJ, Schuler MS, Kcomt L, McCabe VV, McCabe SE. Sexual identity differences in tobacco (re)uptake: testing mediation by internalizing and externalizing symptoms. Am J Prev Med. 2023;64(6):824-833. doi: 10.1016/j.amepre.2023.01.017 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Phen X Toolkit. Protocol: attention-deficit hyperactivity disorder symptoms—child. 2024. Accessed October 9, 2024. https://www.phenxtoolkit.org/protocols/view/121502
- 29.Coker TR, Elliott MN, Toomey SL, et al. Racial and ethnic disparities in ADHD diagnosis and treatment. Pediatrics. 2016;138(3):e20160407. doi: 10.1542/peds.2016-0407 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Lariscy JT, Hummer RA, Rath JM, Villanti AC, Hayward MD, Vallone DM. Race/ethnicity, nativity, and tobacco use among US young adults: results from a nationally representative survey. Nicotine Tob Res. 2013;15(8):1417-1426. doi: 10.1093/ntr/nts344 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Miech RA, Johnston LD, Patrick ME, O’Malley PM. Monitoring the Future national survey results on drug use, 1975-2023: overview and detailed results for secondary school students. Institute for Social Research, University of Michigan . 2024. Accessed October 9, 2024. https://monitoringthefuture.org/wp-content/uploads/2024/01/mtfoverview2024.pdf
- 32.Patrick ME, Miech RA, Johnston LD, O’Malley PM. Monitoring the Future Panel Study annual report: national data on substance use among adults ages 19 to 65, 1976–2023. Institute for Social Research, University of Michigan . 2024. Accessed October 9, 2024. https://monitoringthefuture.org/wp-content/uploads/2024/07/mtfpanel2024.pdf
- 33.Shi Y, Hunter Guevara LR, Dykhoff HJ, et al. Racial disparities in diagnosis of attention-deficit/hyperactivity disorder in a US national birth cohort. JAMA Netw Open. 2021;4(3):e210321. doi: 10.1001/jamanetworkopen.2021.0321 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Singer JD, Willett JB. It’s about time: using discrete-time survival analysis to study duration and the timing of events. J Educ Stat. 1993;18(2):155-195. [Google Scholar]
- 35.Suresh K, Severn C, Ghosh D. Survival prediction models: an introduction to discrete-time modeling. BMC Med Res Methodol. 2022;22(1):207. doi: 10.1186/s12874-022-01679-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Wilens TE, Decker MW. Neuronal nicotinic receptor agonists for the treatment of attention-deficit/hyperactivity disorder: focus on cognition. Biochem Pharmacol. 2007;74(8):1212-1223. doi: 10.1016/j.bcp.2007.07.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Gray KM, Upadhyaya HP. Tobacco smoking in individuals with attention-deficit hyperactivity disorder: epidemiology and pharmacological approaches to cessation. CNS Drugs. 2009;23(8):661-668. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Kalil KL, Bau CH, Grevet EH, et al. Smoking is associated with lower performance in WAIS-R Block Design scores in adults with ADHD. Nicotine Tob Res. 2008;10(4):683-688. doi: 10.1080/14622200801979019 [DOI] [PubMed] [Google Scholar]
- 39.Buitelaar JK, Wilens TE, Zhang S, Ning Y, Feldman PD. Comparison of symptomatic versus functional changes in children and adolescents with ADHD during randomized, double-blind treatment with psychostimulants, atomoxetine, or placebo. J Child Psychol Psychiatry. 2009;50(3):335-342. doi: 10.1111/j.1469-7610.2008.01960.x [DOI] [PubMed] [Google Scholar]
- 40.Cherkasova MV, Roy A, Molina BSG, et al. Review: adult outcome as seen through controlled prospective follow-up studies of children with attention-deficit/hyperactivity disorder followed into adulthood. J Am Acad Child Adolesc Psychiatry. 2022;61(3):378-391. doi: 10.1016/j.jaac.2021.05.019 [DOI] [PubMed] [Google Scholar]
- 41.Molina BSG, Hinshaw SP, Swanson JM, et al. ; MTA Cooperative Group . The MTA at 8 years: prospective follow-up of children treated for combined-type ADHD in a multisite study. J Am Acad Child Adolesc Psychiatry. 2009;48(5):484-500. doi: 10.1097/CHI.0b013e31819c23d0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Lv YB, Cheng W, Wang MH, Wang XM, Hu YL, Lv LQ. Multimodal integrated intervention for children with attention-deficit/hyperactivity disorder. World J Clin Cases. 2023;11(18):4267-4276. doi: 10.12998/wjcc.v11.i18.4267 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Hirvikoski T, Waaler E, Alfredsson J, et al. Reduced ADHD symptoms in adults with ADHD after structured skills training group: results from a randomized controlled trial. Behav Res Ther. 2011;49(3):175-185. doi: 10.1016/j.brat.2011.01.001 [DOI] [PubMed] [Google Scholar]
- 44.Khanano R, Barbic S, Henderson J, Mathias S, Richardson CG. Reliability and concurrent validity of the GAIN Short Screener among youth utilizing integrated health services. J Can Acad Child Adolesc Psychiatry. 2021;30(2):82-91. [PMC free article] [PubMed] [Google Scholar]
- 45.Compton WM, Flannagan KSJ, Silveira ML, et al. Tobacco, alcohol, cannabis, and other drug use in the US before and during the early phase of the COVID-19 pandemic. JAMA Netw Open. 2023;6(1):e2254566. doi: 10.1001/jamanetworkopen.2022.54566 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Cunniff PJ, Ahsan A, McCrary C, et al. ADHD prescription patterns and medication adherence in children and adolescents during the COVID-19 pandemic in an urban academic setting. BMC Psychiatry. 2024;24(1):188. doi: 10.1186/s12888-024-05623-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Freedman S, Marquardt K, Salcedo D, Simon K, Wing C. Societal disruptions and childhood ADHD diagnosis during the COVID-19 pandemic. J Hum Resour. 2024;59:S187-S226. doi: 10.3368/jhr.1222-12708R2 [DOI] [Google Scholar]
- 48.Santosh P, Cortese S, Hollis C, et al. Remote assessment of ADHD in children and adolescents: recommendations from the European ADHD Guidelines Group following the clinical experience during the COVID-19 pandemic. Eur Child Adolesc Psychiatry. 2023;32(6):921-935. doi: 10.1007/s00787-023-02148-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.FDA announces shortage of Adderall. US Food and Drug Administration . August 1, 2023. Accessed July 9, 2024. https://www.fda.gov/drugs/drug-safety-and-availability/fda-announces-shortage-adderall?os=rokuZoazxZMs&ref=app
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