Mental health worsened in adolescents and young adults after the coronavirus disease 2019 (COVID-19) outbreak in March 2020, but whether antidepressant dispensing to this population changed is unknown.
We identified antidepressant prescriptions dispensed to US individuals aged 12 to 25 years from 2016 to 2022 using the IQVIA Longitudinal Prescription Database, an all-payer national database. The outcome was the monthly antidepressant dispensing rate, defined as the monthly number of individuals with ≥1 dispensed antidepressant prescription per 100 000 people. We fitted linear segmented regression models assessing for level or slope changes during March 2020 and conducted subgroup analyses by sex and age group.
Between January 2016 and December 2022, the monthly antidepressant dispensing rate increased 66.3%, from 2575.9 to 4284.8. Before March 2020, this rate increased by 17.0 per month (95% confidence interval: 15.2 to 18.8). The COVID-19 outbreak was not associated with a level change but was associated with a slope increase of 10.8 per month (95% confidence interval: 4.9 to 16.7). The monthly antidepressant dispensing rate increased 63.5% faster from March 2020 onwards compared with beforehand. In subgroup analyses, this rate increased 129.6% and 56.5% faster from March 2020 onwards compared with beforehand among females aged 12 to 17 years and 18 to 25 years, respectively. In contrast, the outbreak was associated with a level decrease among males aged 12 to 17 years and was not associated with a level or slope change among males aged 18 to 25 years.
Antidepressant dispensing to adolescents and young adults was rising before the COVID-19 outbreak and rose 63.5% faster afterward. This change was driven by increased antidepressant dispensing to females and occurred despite decreased dispensing to male adolescents.
The authors of a handful of studies have assessed changes in US antidepressant dispensing after the COVID-19 outbreak in March 2020, but none of these studies were specific to adolescents and young adults nor analyzed data beyond 2020.
Using 2016 to 2022 data from a national prescription dispensing database, we found that antidepressant dispensing to adolescents and young adults rose 63.5% faster after the COVID-19 outbreak. This change was driven by increased antidepressant dispensing to female patients.
Before the COVID-19 outbreak in March 2020, the prevalence of depression and anxiety was rising among adolescents aged 12 to 17 years and young adults aged 18 to 25 years.1,–10 Several studies suggest the prevalence of these disorders may have continued to rise after the outbreak, especially among females.11,–14 According to the nationally representative Youth Behavior Risk Survey, the proportion of high school students reporting persistent feelings of sadness or hopelessness increased from 21% to 29% among males between 2011 and 2021, compared with 36% to 57% in females.4 From February 20, 2021 to March 20, 2021, the mean weekly number of US emergency department visits for suspected suicide attempts was 50.6% higher among female adolescents compared with the same period in 2019, 5.8% higher in female young adults, 3.7% higher in male adolescents, and 4.2% lower in male young adults.15
Antidepressants can be an important tool in the management of depression and anxiety in adolescents and young adults.16,–19 Antidepressant dispensing is a function of the prevalence of mental health conditions, as well as the receipt of care for these conditions. Consequently, evaluating changes in antidepressant dispensing to adolescents and young adults after the COVID-19 outbreak could inform ongoing debates regarding the degree to which the mental health of this population worsened during the COVID-19 pandemic,20 and could also illustrate the degree to which the receipt of mental health care in this population may have changed during the pandemic.
To date, the authors of a handful of studies have used national data to assess changes in antidepressant dispensing after the COVID-19 outbreak,21,–23 but none of these studies were specific to adolescents and young adults nor analyzed data beyond 2020. Using 2016 to 2022 data from a national prescription dispensing database, we evaluated the association between the COVID-19 outbreak and antidepressant dispensing to adolescents and young adults.
Methods
Data Source
We analyzed the IQVIA Longitudinal Prescription Database, a prescription-level, all-payer database that reports dispensing from most retail, mail-order, and long-term care pharmacies in the United States. The database does not capture prescription drug dispensing from pharmacies only open to patients of specific health systems, such as the Veterans Administration or Kaiser Permanente. From 2016 through 2022, the database included 92.5% to 94.4% of antidepressant prescriptions dispensed in US retail pharmacies, suggesting that coverage of this drug class was both comprehensive and stable during the study period (personal communication with Allen Campbell, IQVIA Institute, November 3, 2022). Data elements include encrypted patient identifiers, demographic characteristics (age, sex, state), days supplied, and prescription method of payment (commercial, Medicaid, Medicare, cash). Data on race and ethnicity, income, and prescription indication are not reported. As IQVIA data are deidentified, this analysis was not regulated as human subjects research by the Institutional Review Board of the University of Michigan Medical School.
Sample
Following previous studies,24 we defined adolescents as ages 12 to 17 years and young adults as ages 18 to 25 years. The sample included antidepressant prescriptions dispensed to adolescents and young adults residing in 1 of the 50 US states or the District of Columbia between January 2016 and December 2022.15 We used IQVIA’s market definition to identify antidepressant prescriptions (Supplemental Table 3). This definition includes selective serotonin reuptake inhibitors, selective norepinephrine reuptake inhibitors, tricyclic antidepressants, and other antidepressants (eg, bupropion).
Outcomes
The outcome was the monthly antidepressant dispensing rate, defined as the monthly number of adolescents and young adults with ≥1 dispensed antidepressant prescription per 100 000 people aged 12 to 25 years. We obtained population denominators from the Census Bureau (Supplemental Table 4).
Statistical Analysis
Using an interrupted time series design, we fitted linear segmented regression models assessing for abrupt level and slope changes in outcomes during March 2020.25 We assessed for autocorrelation with the Cumby-Huizinga test and accounted for any autocorrelation using robust Newey-West standard errors with the appropriate number of lags.26 To facilitate interpretation, we calculated the difference between the observed antidepressant dispensing rate in December 2022 and the rate predicted by the counterfactual trend (ie, the rate if pre-March 2020 trends had continued).
In subgroup analyses, we repeated analyses among populations defined by sex and age group (12–17 vs 18–25 years) and populations defined by sex and Census region. As in the overall analysis, we derived subgroup-specific population denominators from the Census Bureau. A small number of individuals with unknown sex were excluded from the subgroup analyses.
For the analyses, we used R version 4.2.1 and 2-sided hypothesis tests with α = .05. Additional details on the statistical analysis are included in the Supplemental Information.
Sensitivity Analyses
We repeated analyses when modeling the monthly number of individuals with ≥1 dispensed antidepressant prescription, an outcome that avoids any uncertainty in the estimation of population denominators, and when modeling the monthly number of days supplied of antidepressants dispensed per 100 000 individuals, an outcome that accounts for any shifts in the mean duration of antidepressant prescriptions. To account for seasonality, we repeated analyses of the primary outcome when controlling for quarter (1 = January-March, 2 = April-June, 3 = July-September, 4 = October-December). Finally, we limited the definition of antidepressants to selective serotonin reuptake inhibitors.
Results
Sample
From 2016 to 2022, the database included 221 268 402 antidepressant prescriptions dispensed to 18 395 915 individuals, of whom 11 836 944 (64.4%) were female, 6 508 947 (35.8%) were male, and 50 025 (0.3%) were of unknown sex. At the time of sample entry, mean (SD) age was 19.2 (3.9) years, 11 908 010 (64.7%) individuals were aged 18 to 25 years, and 7 100 766 (38.6%) individuals resided in the South, compared with 2 961 720 (16.1%) in the Northeast, 4 719 080 (25.7%) in the Midwest, and 3 614 349 (19.6%) in the West. Among the 221 268 402 dispensed antidepressant prescriptions, 148 977 404 (67.3%) were for selective serotonin reuptake inhibitors. The 3 most common medications were sertraline (53 225 721; 24.1%), fluoxetine (40 815 093; 18.5%), and escitalopram (36 169 696; 16.3%).
Table 1 reveals the annual characteristics of adolescents and young adults with ≥1 dispensed antidepressant prescription during the year, as well as the characteristics of these prescriptions. Between 2016 and 2022, the number of adolescents and young adults with ≥1 dispensed antidepressant prescription increased by 46.1%, from 4 633 433 to 6 768 106. The number of adolescents and young adults initiating antidepressant therapy (defined as having a lack of antidepressant dispensing in the previous 180 days) increased by 31.0%, from 2 750 774 to 3 603 045. In 2016, advanced practice providers, defined as nurse practitioners and physician assistants, accounted for 6 081 971 of the 25 472 600 dispensed antidepressant prescriptions (23.9%). By 2022, these providers accounted for 15 787 158 of the 38 678 393 dispensed antidepressant prescriptions (40.8%).
Characteristic . | 2016 . | 2017 . | 2018 . | 2019 . | 2020 . | 2021 . | 2022 . | % Change, 2016–2022 . |
---|---|---|---|---|---|---|---|---|
Patient characteristics | ||||||||
No. with ≥1 dispensed antidepressant prescription | 4 633 433 | 4 932 222 | 5 229 206 | 5 474 554 | 5 763 236 | 6 462 760 | 6 768 106 | 46.1 |
Mean (SD) age in years | 19.6 (3.7) | 19.6 (3.7) | 19.6 (3.7) | 19.6 (3.7) | 19.7 (3.7) | 19.6 (3.7) | 19.6 (3.7) | 0.0 |
Age 12–17 y, n (%) | 1 429 035 (30.8) | 1 518 604 (30.8) | 1 599 787 (30.6) | 1 670 163 (30.5) | 1 727 042 (30.0) | 1 970 457 (30.5) | 2 043 476 (30.2) | 43.0 |
Age 18–25 y, n (%) | 3 204 398 (69.2) | 3 413 618 (69.2) | 3 629 418 (69.4) | 3 804 391 (69.5) | 4 036 194 (70.0) | 4 492 303 (69.5) | 4 724 630 (69.8) | 47.4 |
Female, n (%)a | 2 964 917 (64.0) | 3 176 815 (64.4) | 3 382 211 (64.7) | 3 554 744 (64.9) | 3 819 110 (66.3) | 4 360 570 (67.5) | 4 566 611 (67.5) | 54..0 |
Male, n (%)a | 1 650 153 (35.6) | 1 741 301 (35.3) | 1 833 606 (35.1) | 1 905 747 (34.8) | 1 942 119 (33.7) | 2 096 478 (32.4) | 2 199 404 (32.5) | 33.2 |
No. initiating antidepressant therapyb | 2 750 774 | 2 861 920 | 2 994 042 | 3 086 140 | 3 187 685 | 3 623 477 | 3 603 045 | 31.0 |
Prescription characteristics | ||||||||
No. dispensed antidepressant prescriptions | 25 472 660 | 27 709 372 | 29 745 517 | 30 525 809 | 32 673 893 | 36 462 758 | 38 678 393 | 51.8 |
Medication, n (%) | ||||||||
Sertraline | 5 860 088 (23.0) | 6 504 616 (23.5) | 7 120 308 (23.9) | 7 408 480 (24.3) | 7 953 885 (24.3) | 8 920 814 (24.5) | 9 457 530 (24.5) | 61.4 |
Fluoxetine | 4 493 446 (17.6) | 4 976 214 (18.0) | 5 400 012 (18.2) | 5 596 933 (18.3) | 6 023 857 (18.4) | 6 900 150 (18.9) | 7 424 481 (19.2) | 65.2 |
Escitalopram | 3 600 851 (14.1) | 4 092 031 (14.8) | 4 618 640 (15.5) | 4 951 096 (16.2) | 5 523 026 (16.9) | 6 420 344 (17.6) | 6 963 708 (18.0) | 93.4 |
Bupropion | 2 342 230 (9.2) | 2 569 609 (9.3) | 2 754 348 (9.3) | 2 821 150 (9.2) | 3 042 178 (9.3) | 3 548 112 (9.7) | 3 879 150 (10.0) | 65.6 |
Trazodone | 1 876 689 (7.4) | 2 017 907 (7.3) | 2 133 433 (7.2) | 2 149 802 (7.0) | 2 379 424 (7.3) | 2 539 291 (7.0) | 2 626 692 (6.8) | 40.0 |
Venlafaxine | 1 169 361 (4.6) | 1 308 650 (4.7) | 1 400 172 (4.7) | 1 437 051 (4.7) | 1 504 497 (4.6) | 1 632 843 (4.5) | 1 716 677 (4.4) | 46.8 |
Citalopram | 2 263 405 (8.9) | 2 137 183 (7.7) | 1 970 109 (6.6) | 1 740 555 (5.7) | 1 618 189 (5.0) | 1 542 763 (4.2) | 1 401 936 (3.6) | −38.1 |
Duloxetine | 712 903 (2.8) | 815 902 (2.9) | 902 802 (3.0) | 968 781 (3.2) | 1 058 000 (3.2) | 1 181 165 (3.2) | 1 260 601 (3.3) | 76.8 |
Amitriptyline | 872 571 (3.4) | 886 829 (3.2) | 900 613 (3.0) | 863 519 (2.8) | 857 626 (2.6) | 874 789 (2.4) | 880 236 (2.3) | 0.9 |
Mirtazapine | 534 527 (2.1) | 578 875 (2.1) | 630 245 (2.1) | 652 445 (2.1) | 723 444 (2.2) | 804 920 (2.2) | 856 283 (2.2) | 60.2 |
All other antidepressants | 1 746 589 (6.9) | 1 821 556 (6.6) | 1 914 835 (6.4) | 1 935 997 (6.3) | 1 989 767 (6.1) | 2 097 567 (5.8) | 2 211 099 (5.7) | 26.6 |
Payment method, n (%) | ||||||||
Commercial | 17 534 278 (68.8) | 19 078 749 (68.9) | 20 452 743 (68.8) | 21 022 646 (68.9) | 22 365 906 (68.5) | 24 862 923 (68.2) | 26 130 146 (67.6) | 49.0 |
Medicaid/other public | 6 381 366 (25.1) | 7 095 792 (25.6) | 7 781 756 (26.2) | 8 076 761 (26.5) | 8 853 671 (27.1) | 10 053 303 (27.6) | 11 010 199 (28.5) | 72.5 |
Medicare | 508 977 (2.0) | 508 086 (1.8) | 432 990 (1.5) | 438 507 (1.4) | 476 964 (1.5) | 517 897 (1.4) | 569 639 (1.5) | 11.9 |
Cash | 1 045 016 (4.1) | 1 025 515 (3.7) | 1 077 191 (3.6) | 986 989 (3.2) | 976 385 (3.0) | 1 023 489 (2.8) | 966 792 (2.5) | −7.5 |
Prescriber specialty | ||||||||
Nurse practitioner | 4 669 242 (18.3) | 5 655 448 (20.4) | 6 755 117 (22.7) | 7 753 607 (25.4) | 9 027 705 (27.6) | 11 012 398 (30.2) | 12 812 656 (33.1) | 174.4 |
Psychiatry | 9 150 273 (35.9) | 9 613 750 (34.7) | 9 965 499 (33.5) | 9 778 086 (32.0) | 9 819 062 (30.1) | 10 274 940 (28.2) | 10 070 718 (26.0) | 10.1 |
Family medicine | 4 725 491 (18.6) | 4 951 654 (17.9) | 5 057 894 (17.0) | 4 950 447 (16.2) | 5 094 997 (15.6) | 5 329 577 (14.6) | 5 357 312 (13.9) | 13.4 |
Pediatrics | 2 408 648 (9.5) | 2 683 278 (9.7) | 2 977 501 (10.0) | 3 164 604 (10.4) | 3 406 720 (10.4) | 4 052 478 (11.1) | 4 390 079 (11.4) | 82.3 |
Physician assistant | 1 412 729 (5.5) | 1 650 435 (6.0) | 1 886 088 (6.3) | 2 056 688 (6.7) | 2 302 113 (7.0) | 2 697 273 (7.4) | 2 974 502 (7.7) | 110.6 |
Internal medicine | 1 428 422 (5.6) | 1 478 237 (5.3) | 1 473 654 (5.0) | 1 405 961 (4.6) | 1 434 880 (4.4) | 1 482 575 (4.1) | 1 482 738 (3.8) | 3.8 |
Other specialty | 1 401 231 (5.5) | 1 413 272 (5.1) | 1 389 765 (4.7) | 1 299 217 (4.3) | 1 318 591 (4.0) | 1 324 301 (3.6) | 1 297 023 (3.4) | −79.1 |
Unknown specialty | 276 624 (1.1) | 263 298 (1.0) | 239 999 (0.8) | 117 199 (0.4) | 269 825 (0.8) | 289 216 (0.8) | 293 365 (0.8) | 6.1 |
Characteristic . | 2016 . | 2017 . | 2018 . | 2019 . | 2020 . | 2021 . | 2022 . | % Change, 2016–2022 . |
---|---|---|---|---|---|---|---|---|
Patient characteristics | ||||||||
No. with ≥1 dispensed antidepressant prescription | 4 633 433 | 4 932 222 | 5 229 206 | 5 474 554 | 5 763 236 | 6 462 760 | 6 768 106 | 46.1 |
Mean (SD) age in years | 19.6 (3.7) | 19.6 (3.7) | 19.6 (3.7) | 19.6 (3.7) | 19.7 (3.7) | 19.6 (3.7) | 19.6 (3.7) | 0.0 |
Age 12–17 y, n (%) | 1 429 035 (30.8) | 1 518 604 (30.8) | 1 599 787 (30.6) | 1 670 163 (30.5) | 1 727 042 (30.0) | 1 970 457 (30.5) | 2 043 476 (30.2) | 43.0 |
Age 18–25 y, n (%) | 3 204 398 (69.2) | 3 413 618 (69.2) | 3 629 418 (69.4) | 3 804 391 (69.5) | 4 036 194 (70.0) | 4 492 303 (69.5) | 4 724 630 (69.8) | 47.4 |
Female, n (%)a | 2 964 917 (64.0) | 3 176 815 (64.4) | 3 382 211 (64.7) | 3 554 744 (64.9) | 3 819 110 (66.3) | 4 360 570 (67.5) | 4 566 611 (67.5) | 54..0 |
Male, n (%)a | 1 650 153 (35.6) | 1 741 301 (35.3) | 1 833 606 (35.1) | 1 905 747 (34.8) | 1 942 119 (33.7) | 2 096 478 (32.4) | 2 199 404 (32.5) | 33.2 |
No. initiating antidepressant therapyb | 2 750 774 | 2 861 920 | 2 994 042 | 3 086 140 | 3 187 685 | 3 623 477 | 3 603 045 | 31.0 |
Prescription characteristics | ||||||||
No. dispensed antidepressant prescriptions | 25 472 660 | 27 709 372 | 29 745 517 | 30 525 809 | 32 673 893 | 36 462 758 | 38 678 393 | 51.8 |
Medication, n (%) | ||||||||
Sertraline | 5 860 088 (23.0) | 6 504 616 (23.5) | 7 120 308 (23.9) | 7 408 480 (24.3) | 7 953 885 (24.3) | 8 920 814 (24.5) | 9 457 530 (24.5) | 61.4 |
Fluoxetine | 4 493 446 (17.6) | 4 976 214 (18.0) | 5 400 012 (18.2) | 5 596 933 (18.3) | 6 023 857 (18.4) | 6 900 150 (18.9) | 7 424 481 (19.2) | 65.2 |
Escitalopram | 3 600 851 (14.1) | 4 092 031 (14.8) | 4 618 640 (15.5) | 4 951 096 (16.2) | 5 523 026 (16.9) | 6 420 344 (17.6) | 6 963 708 (18.0) | 93.4 |
Bupropion | 2 342 230 (9.2) | 2 569 609 (9.3) | 2 754 348 (9.3) | 2 821 150 (9.2) | 3 042 178 (9.3) | 3 548 112 (9.7) | 3 879 150 (10.0) | 65.6 |
Trazodone | 1 876 689 (7.4) | 2 017 907 (7.3) | 2 133 433 (7.2) | 2 149 802 (7.0) | 2 379 424 (7.3) | 2 539 291 (7.0) | 2 626 692 (6.8) | 40.0 |
Venlafaxine | 1 169 361 (4.6) | 1 308 650 (4.7) | 1 400 172 (4.7) | 1 437 051 (4.7) | 1 504 497 (4.6) | 1 632 843 (4.5) | 1 716 677 (4.4) | 46.8 |
Citalopram | 2 263 405 (8.9) | 2 137 183 (7.7) | 1 970 109 (6.6) | 1 740 555 (5.7) | 1 618 189 (5.0) | 1 542 763 (4.2) | 1 401 936 (3.6) | −38.1 |
Duloxetine | 712 903 (2.8) | 815 902 (2.9) | 902 802 (3.0) | 968 781 (3.2) | 1 058 000 (3.2) | 1 181 165 (3.2) | 1 260 601 (3.3) | 76.8 |
Amitriptyline | 872 571 (3.4) | 886 829 (3.2) | 900 613 (3.0) | 863 519 (2.8) | 857 626 (2.6) | 874 789 (2.4) | 880 236 (2.3) | 0.9 |
Mirtazapine | 534 527 (2.1) | 578 875 (2.1) | 630 245 (2.1) | 652 445 (2.1) | 723 444 (2.2) | 804 920 (2.2) | 856 283 (2.2) | 60.2 |
All other antidepressants | 1 746 589 (6.9) | 1 821 556 (6.6) | 1 914 835 (6.4) | 1 935 997 (6.3) | 1 989 767 (6.1) | 2 097 567 (5.8) | 2 211 099 (5.7) | 26.6 |
Payment method, n (%) | ||||||||
Commercial | 17 534 278 (68.8) | 19 078 749 (68.9) | 20 452 743 (68.8) | 21 022 646 (68.9) | 22 365 906 (68.5) | 24 862 923 (68.2) | 26 130 146 (67.6) | 49.0 |
Medicaid/other public | 6 381 366 (25.1) | 7 095 792 (25.6) | 7 781 756 (26.2) | 8 076 761 (26.5) | 8 853 671 (27.1) | 10 053 303 (27.6) | 11 010 199 (28.5) | 72.5 |
Medicare | 508 977 (2.0) | 508 086 (1.8) | 432 990 (1.5) | 438 507 (1.4) | 476 964 (1.5) | 517 897 (1.4) | 569 639 (1.5) | 11.9 |
Cash | 1 045 016 (4.1) | 1 025 515 (3.7) | 1 077 191 (3.6) | 986 989 (3.2) | 976 385 (3.0) | 1 023 489 (2.8) | 966 792 (2.5) | −7.5 |
Prescriber specialty | ||||||||
Nurse practitioner | 4 669 242 (18.3) | 5 655 448 (20.4) | 6 755 117 (22.7) | 7 753 607 (25.4) | 9 027 705 (27.6) | 11 012 398 (30.2) | 12 812 656 (33.1) | 174.4 |
Psychiatry | 9 150 273 (35.9) | 9 613 750 (34.7) | 9 965 499 (33.5) | 9 778 086 (32.0) | 9 819 062 (30.1) | 10 274 940 (28.2) | 10 070 718 (26.0) | 10.1 |
Family medicine | 4 725 491 (18.6) | 4 951 654 (17.9) | 5 057 894 (17.0) | 4 950 447 (16.2) | 5 094 997 (15.6) | 5 329 577 (14.6) | 5 357 312 (13.9) | 13.4 |
Pediatrics | 2 408 648 (9.5) | 2 683 278 (9.7) | 2 977 501 (10.0) | 3 164 604 (10.4) | 3 406 720 (10.4) | 4 052 478 (11.1) | 4 390 079 (11.4) | 82.3 |
Physician assistant | 1 412 729 (5.5) | 1 650 435 (6.0) | 1 886 088 (6.3) | 2 056 688 (6.7) | 2 302 113 (7.0) | 2 697 273 (7.4) | 2 974 502 (7.7) | 110.6 |
Internal medicine | 1 428 422 (5.6) | 1 478 237 (5.3) | 1 473 654 (5.0) | 1 405 961 (4.6) | 1 434 880 (4.4) | 1 482 575 (4.1) | 1 482 738 (3.8) | 3.8 |
Other specialty | 1 401 231 (5.5) | 1 413 272 (5.1) | 1 389 765 (4.7) | 1 299 217 (4.3) | 1 318 591 (4.0) | 1 324 301 (3.6) | 1 297 023 (3.4) | −79.1 |
Unknown specialty | 276 624 (1.1) | 263 298 (1.0) | 239 999 (0.8) | 117 199 (0.4) | 269 825 (0.8) | 289 216 (0.8) | 293 365 (0.8) | 6.1 |
A total of 50 024 (0.3%) individuals had unknown sex.
Defined as the number of individuals with ≥1 initial antidepressant prescription during the year. Initial prescriptions were those without antidepressant dispensing in the previous 180 days.
Monthly Antidepressant Dispensing Rate
Table 2 reveals coefficients from segmented regression models for the monthly antidepressant dispensing rate. Between January 2016 and December 2022, this rate increased by 66.3%, from 2575.9 to 4284.8 individuals per 100 000 (Fig 1). Before March 2020, this rate increased by 17.0 (95% confidence interval [CI]: 15.2 to 18.8) per month. The outbreak was not associated with a level change (−37.4, 95% CI: −153.4 to 78.7) but was associated with a slope increase (10.8 per month, 95% CI: 4.9 to 16.7). From March 2020 onwards, the monthly antidepressant dispensing rate increased by 27.8 per month (95% CI: 22.1 to 33.4), or 63.5% higher than the rate of change before March 2020. During December 2022, the antidepressant dispensing rate was 166.7 (4.0%) higher than predicted by the counterfactual trend.
Group . | Intercept [95% CI] . | Slope Before March 2020 [95% CI] . | Level Change in March 2020 [95% CI] . | Slope Change After March 2020 [95% CI] . | Slope After March 2020 [95% CI] . | Observed Minus Predicted Rate in December 2022 (% Difference)a . |
---|---|---|---|---|---|---|
Overall, 12–25 y | 2691.0 [2641.7, 2740.2] | 17.0 [15.2 to 18.8] | −37.4 [−153.4 to 78.7] | 10.8 [4.9 to 16.7] | 27.8 [22.1 to 33.4] | 166.7 (4.0%) |
Sex/age groupb | ||||||
Females aged 12–17 y | 2536.3 [2428.8, 2643.7] | 17.9 [13.7 to 22.2] | −188.8 [−413.6 to 36.0] | 23.1 [14.3 to 32.0] | 41.1 [32.9 to 49.2] | 514.6 (12.7%) |
Males aged 12–17 y | 1823.5 [1782.8, 1864.2] | 8.7 [7.1 to 10.4] | −224.3 [−328.2 to −120.4] | 1.1 [−2.3 to 4.4] | 9.8 [6.3 to 13.3] | −182.2 (-7.1%) |
Females aged 18–25 y | 4145.1 [4059.5, 4230.6] | 28.6 [25.3 to 31.9] | 227.3 [6.9 to 447.6] | 16.2 [4.6 to 27.8] | 44.8 [33.3 to 56.3] | 403.8 (6.2%) |
Males aged 18–25 y | 1980.3 [1949.7, 2011.0] | 11.7 [10.5 to 13.0] | 17.8 [−51.3 to 86.8] | 3.7 [−0.8 to 8.2] | 15.5 [11.2 to 19.7] | 0.1 (0.0%) |
Sex/regionb | ||||||
Females, Northeast | 4068.8 [3970.5, 4167.1] | 22.8 [19.1 to 26.6] | −154.2 [−377.0 to 68.6] | 28.0 [16.7 to 39.2] | 50.8 [40.1 to 61.5] | 559.5 (9.3%) |
Females, Midwest | 4390.3 [4288.7, 4491.9] | 34.5 [30.6 to 38.4] | −7.9 [−300.9 to 245.0] | 17.5 [3.8 to 31.1] | 52.0 [38.8 to 65.2] | 238.7 (3.3%) |
Females, South | 3275.7 [3196.1, 3355.2] | 21.2 [18.7 to 23.7] | 69.7 [−76.5 to 215.9] | 19.8 [12.4 to 27.3] | 41.0 [33.8 to 48.2] | 511.3 (10.1%) |
Females, West | 2568.4 [2518.5, 2618.3] | 19.6 [17.7 to 21.5] | 131.4 [−14.5 to 277.2] | 14.1 [7.2 to 21.1] | 33.8 [26.9 to 40.7] | 397.0 (9.4%) |
Males, Northeast | 2280.1 [2240.7, 2319.5] | 11.3 [9.7 to 12.9] | −207.2 [−310.5 to −104.0] | 4.3 [0.4 to 8.1] | 15.6 [11.6 to 19.5] | −127.9 (-4.0%) |
Males, Midwest | 2354.2 [2310.2, 2398.2] | 14.9 [13.2 to 16.5] | −122.4 [−220.6 to −24.3] | 0.9 [−4.0 to 5.8] | 15.8 [11.1 to 20.4] | −217.4 (-6.0%) |
Males, South | 1790.9 [1758.8, 1823.0] | 8.9 [7.8 to 9.9] | −63.1 [−118.7 to −7.6] | 3.9 [1.1 to 6.7] | 12.8 [10.2 to 15.3] | −1.3 (-0.1%) |
Males, West | 1462.6 [1449.2, 1475.9] | 8.6 [8.0 to 9.1] | −35.5 [−75.1 to 4.1] | 0.6 [−1.6 to 2.7] | 9.1 [7.0 to 11.3] | −72.9 (-3.3%) |
Group . | Intercept [95% CI] . | Slope Before March 2020 [95% CI] . | Level Change in March 2020 [95% CI] . | Slope Change After March 2020 [95% CI] . | Slope After March 2020 [95% CI] . | Observed Minus Predicted Rate in December 2022 (% Difference)a . |
---|---|---|---|---|---|---|
Overall, 12–25 y | 2691.0 [2641.7, 2740.2] | 17.0 [15.2 to 18.8] | −37.4 [−153.4 to 78.7] | 10.8 [4.9 to 16.7] | 27.8 [22.1 to 33.4] | 166.7 (4.0%) |
Sex/age groupb | ||||||
Females aged 12–17 y | 2536.3 [2428.8, 2643.7] | 17.9 [13.7 to 22.2] | −188.8 [−413.6 to 36.0] | 23.1 [14.3 to 32.0] | 41.1 [32.9 to 49.2] | 514.6 (12.7%) |
Males aged 12–17 y | 1823.5 [1782.8, 1864.2] | 8.7 [7.1 to 10.4] | −224.3 [−328.2 to −120.4] | 1.1 [−2.3 to 4.4] | 9.8 [6.3 to 13.3] | −182.2 (-7.1%) |
Females aged 18–25 y | 4145.1 [4059.5, 4230.6] | 28.6 [25.3 to 31.9] | 227.3 [6.9 to 447.6] | 16.2 [4.6 to 27.8] | 44.8 [33.3 to 56.3] | 403.8 (6.2%) |
Males aged 18–25 y | 1980.3 [1949.7, 2011.0] | 11.7 [10.5 to 13.0] | 17.8 [−51.3 to 86.8] | 3.7 [−0.8 to 8.2] | 15.5 [11.2 to 19.7] | 0.1 (0.0%) |
Sex/regionb | ||||||
Females, Northeast | 4068.8 [3970.5, 4167.1] | 22.8 [19.1 to 26.6] | −154.2 [−377.0 to 68.6] | 28.0 [16.7 to 39.2] | 50.8 [40.1 to 61.5] | 559.5 (9.3%) |
Females, Midwest | 4390.3 [4288.7, 4491.9] | 34.5 [30.6 to 38.4] | −7.9 [−300.9 to 245.0] | 17.5 [3.8 to 31.1] | 52.0 [38.8 to 65.2] | 238.7 (3.3%) |
Females, South | 3275.7 [3196.1, 3355.2] | 21.2 [18.7 to 23.7] | 69.7 [−76.5 to 215.9] | 19.8 [12.4 to 27.3] | 41.0 [33.8 to 48.2] | 511.3 (10.1%) |
Females, West | 2568.4 [2518.5, 2618.3] | 19.6 [17.7 to 21.5] | 131.4 [−14.5 to 277.2] | 14.1 [7.2 to 21.1] | 33.8 [26.9 to 40.7] | 397.0 (9.4%) |
Males, Northeast | 2280.1 [2240.7, 2319.5] | 11.3 [9.7 to 12.9] | −207.2 [−310.5 to −104.0] | 4.3 [0.4 to 8.1] | 15.6 [11.6 to 19.5] | −127.9 (-4.0%) |
Males, Midwest | 2354.2 [2310.2, 2398.2] | 14.9 [13.2 to 16.5] | −122.4 [−220.6 to −24.3] | 0.9 [−4.0 to 5.8] | 15.8 [11.1 to 20.4] | −217.4 (-6.0%) |
Males, South | 1790.9 [1758.8, 1823.0] | 8.9 [7.8 to 9.9] | −63.1 [−118.7 to −7.6] | 3.9 [1.1 to 6.7] | 12.8 [10.2 to 15.3] | −1.3 (-0.1%) |
Males, West | 1462.6 [1449.2, 1475.9] | 8.6 [8.0 to 9.1] | −35.5 [−75.1 to 4.1] | 0.6 [−1.6 to 2.7] | 9.1 [7.0 to 11.3] | −72.9 (-3.3%) |
Difference between the antidepressant dispensing rate in December 2022 and the rate predicted by the counterfactual trend (ie, the trend had pre-March 2020 trends continued).
A total of 50 024 (0.3%) individuals with unknown sex were excluded from these subgroup analyses.
Subgroup Analysis: Sex and Age Group
Among female adolescents, the monthly antidepressant dispensing rate increased by 17.9 per month (95% CI: 13.7 to 22.2) before March 2020. The outbreak was not associated with a level change (−188.8, 95% CI: −413.6 to 36.0) but was associated with a slope increase (23.1 per month, 95% CI: 14.3 to 32.0). From March 2020 onwards, the monthly antidepressant dispensing rate increased by 41.1 per month (95% CI: 32.9 to 49.2), or 129.6% higher than the rate of change before March 2020. Among male adolescents, the monthly antidepressant dispensing rate increased 8.7 per month (95% CI: 7.1 to 10.4) before March 2020. The outbreak was associated with a level decrease (−224.3, 95% CI: −328.2 to −120.4) but not with a slope change (1.1 per month, 95% CI: −2.3 to 4.4). In December 2022, the antidepressant dispensing rate among male adolescents was 182.2 (−7.1%) lower than predicted by the counterfactual trend, compared with 514.6 (12.7%) higher than predicted among female adolescents (Fig 2A).
Among female young adults, the monthly antidepressant dispensing rate increased by 28.6 per month (95% CI: 25.3 to 31.9) before March 2020. The outbreak was associated with a level increase (227.3, 95% CI: 6.9 to 447.6) and slope increase (16.2 per month, 95% CI: 4.6 to 27.8). From March 2020 onwards, the monthly antidepressant dispensing rate increased by 44.8 per month (95% CI: 33.3 to 56.3), or 56.6% higher than the rate of change before March 2020. Among male young adults, the monthly antidepressant dispensing rate increased 11.7 per month (95% CI: 10.5 to 13.0) before March 2020. The outbreak was not associated with a level change (17.8, 95% CI: −51.3 to 86.8) or slope change (3.7 per month, 95% CI: −0.8 to 8.2). In December 2022, the antidepressant dispensing rate among male young adults was 0.1 (0.0%) higher than predicted by the counterfactual trend, compared with 403.8 (6.2%) higher among female young adults (Fig 2B).
Subgroup Analysis: Sex and Census Region
Among female adolescents and young adults in each Census region, the outbreak was not associated with a level change in the monthly antidepressant dispensing rate but was associated with a slope increase. In December 2022, the antidepressant dispensing rate was 3.3% to 10.1% higher than predicted by the counterfactual trend depending on the region, with the smallest increase occurring in the Midwest and the largest increase occurring in the South.
Among male adolescents and young adults, the outbreak was associated with level decreases in the antidepressant dispensing rate in every region, except the West, but was only associated with slope increases in the Northeast and South. In December 2022, the antidepressant dispensing rate was −6.0% to −0.1% lower than predicted by the counterfactual trend depending on the region, with the greatest decrease occurring in the Midwest and the smallest decrease occurring in the South (Fig 3).
Sensitivity Analyses
In the main analysis, the COVID-19 outbreak was not associated with a slope change in the monthly antidepressant dispensing rate among male young adults. In contrast, the outbreak was associated with a slope increase in this population when modeling the monthly number of individuals with ≥1 antidepressant prescription, when modeling the monthly number of days supplied of antidepressants dispensed per 100 000 people, and when controlling for season. However, in all sensitivity analyses, the outcome decreased after the outbreak among male adolescents but increased among female adolescents and young adults (Supplemental Tables 5–9).
Discussion
In this analysis of data from an all-payer, national prescription dispensing database, the monthly antidepressant dispensing rate among US adolescents and young adults increased by 66.3% between January 2016 and December 2022. This rate was increasing before the COVID-19 outbreak in March 2020 but increased 63.5% faster after the outbreak. Subgroup analyses revealed that the increase in antidepressant dispensing after the outbreak was driven by females in all Census regions and occurred despite a decline in dispensing to male adolescents.
Our findings are consistent with a national study revealing an increase in antidepressant dispensing among US adolescents aged 12 to 17 years from March 2020 to September 2020 compared with the same period in 2019.22 Findings differ from a national study revealing minimal changes in the number of antidepressant prescriptions dispensed to US individuals aged 0 to 19 years from March 2020 to December 2020 compared with the same period in 2019 and with a national study revealing a decline in new starts of antidepressants among individuals aged 0 to 18 years from March 2020 to August 2020, perhaps owing to different age groups and time periods.21,23 Our analysis builds on these 3 studies by using data through 2022, thus allowing for the assessment of changes in antidepressant dispensing over a longer period after the COVID-19 outbreak. We also used several years of data before 2020, which facilitated the establishment of the counterfactual trend.
Although our study does not allow for the identification of the mechanism of the observed increase in antidepressant dispensing to adolescents and young adults, multiple factors are likely involved. The increase may partly reflect a greater need for antidepressants, given evidence that the prevalence of depression and anxiety increased among adolescents and young adults after the outbreak.11,–14 Changes in access and treatment patterns may also have played a role. For example, for patients facing long waitlists for psychotherapy after the outbreak, initiating or continuing antidepressant therapy may have been more practical than relying on a therapy-only approach. Additionally, the shift toward telehealth for mental health care delivery may have increased access to clinicians who could prescribe antidepressants, at least among individuals without barriers to telehealth use.27
Subgroup analyses revealed marked heterogeneity in changes in antidepressant dispensing after the outbreak by sex and age group. Among female adolescents, a population with one of the highest rates of depression and anxiety of any demographic subgroup even before the COVID-19 outbreak1,3, the monthly antidepressant dispensing rate increased 129.6% faster from March 2020 through December 2022 compared with January 2016 through February 2020. This finding aligns with studies revealing marked increases in mental health symptoms, emergency department visits for mental health conditions, and hospitalizations for these conditions among female adolescents after the outbreak.15,28,–31 Collectively, these studies, along with ours, are consistent with the notion that the COVID-19 pandemic exacerbated a preexisting mental health crisis among female adolescents.32
In sharp contrast to female adolescents, the monthly antidepressant dispensing rate among male adolescents declined abruptly during March 2020 and did not recover afterward. One potential explanation for this finding is that the mental health of male adolescents improved during the pandemic, thus decreasing their need for antidepressants. However, this explanation is not supported by data revealing that emergency department visits for suspected suicide attempts in male adolescents were higher in early 2021 compared with early 2019,15 or by data revealing that the proportion of male high school students reporting persistent feelings of sadness or hopelessness increased between 2019 and 2021.4 A more plausible explanation is that male adolescents received care for mental health symptoms less often after the outbreak despite a lack of a decrease in the frequency of these symptoms. In support of this possibility, an analysis of national commercial claims data from 2016 to 2021 revealed that dispensing of medications for attention-deficit hyperactivity disorder declined after the outbreak among males aged 15 to 24 years.33 Future research should investigate if the decrease in antidepressant dispensing among male adolescents after the outbreak reflects underuse of these medications relative to the level of need.
Our study provides important information on changes in mental health utilization patterns among young adults after the COVID-19 outbreak. As with adolescents, changes varied markedly by sex, with little change in antidepressant dispensing to males and an increase among females. Although this increase was smaller compared with the increase among female adolescents, findings suggest mental health may have similarly worsened among female young adults after the outbreak, highlighting the importance of implementing interventions to promote mental health and improve access to mental health care in this population. For example, expanding insurance coverage may be one particularly important such intervention, given that young adults have the highest rates of uninsurance of any age group.34
This study has several strengths, including the use of timely national data over a 7-year period and the use of patient demographic data to explore heterogeneity in changes by sex, age, and region. However, the study had limitations. First, as with most pharmacy dispensing databases, the IQVIA database does not include information on prescription indication. Consequently, we could not determine if antidepressants were written to treat depression, anxiety, or other conditions, nor whether their use was guideline-concordant.35,–37 Second, the IQVIA database does not include information on whether antidepressants were prescribed during in-person versus telehealth visits. Third, the IQVIA database only includes information on prescription method of payment, which does not always equate to insurance type (eg, privately insured patients who pay for prescriptions with cash). As such, we could not examine whether changes in the monthly antidepressant dispensing rate after March 2020 varied according to whether patients were privately or publicly insured. Fourth, it was beyond the study’s scope to examine changes in the concurrent use of multiple antidepressants after the COVID-19 outbreak, changes in the concurrent use of other psychotropic drugs, or changes in patterns of antidepressant initiation and retention in therapy.
Finally, it is unclear whether findings can be generalized beyond 2022. The number of mental health-related emergency department visits among US adolescents was lower in fall 2022 compared with fall 2021,38 and the end of the Medicaid continuous enrollment provision on March 31, 2023 has resulted in large-scale Medicaid disenrollment, potentially disrupting antidepressant therapy among Medicaid-insured adolescents and young adults.39,40 Thus, the increase in antidepressant dispensing to adolescents and young adults observed in this study could slow over time.
Conclusions
Antidepressant dispensing to adolescents and young adults was rising before the COVID-19 outbreak and rose even faster afterward. Future research should investigate the degree to which this increase was driven by changes in mental health, changes in access to mental health care, and changes in treatment patterns for mental health conditions. Future research should also investigate which interventions can best promote the mental health of adolescents and young adults, thus mitigating the deleterious implications of poor mental health both in the short term and long term.
Acknowledgments
The authors would like to acknowledge Dr Michael Tang, MD, MBA, for his feedback on this manuscript. He was not compensated for these contributions. This study was presented at the American Academy of Pediatrics Presidential Plenary during the 2023 Pediatric Academic Societies meeting in Washington, DC on May 1, 2023.
Dr Chua conceptualized and designed the study, analyzed and interpreted the data, drafted the initial manuscript, and reviewed and revised the manuscript; Mr Zhang conceptualized and designed the study, analyzed and interpreted the data, and reviewed and revised the manuscript; Drs Volerman and Conti and Ms Hua conceptualized and designed the study, analyzed and interpreted the data, and revised the manuscript; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.
COMPANION PAPER: A companion to this article can be found online at www.pediatrics.org/cgi/doi/10.1542/peds.2023-064677.
FUNDING: Funding for the IQVIA data was provided by the Susan B. Meister Child Health Evaluation and Research Center in the Department of Pediatrics at the University of Michigan Medical School. Dr Chua is supported by grants R01DA056438-01, R01DA057284-01, and K08DA048110-04 from the National Institute on Drug Abuse. Dr Volerman is funded by the National Heart, Lung, and Blood Institute (K23HL143128), National Institute of General Medical Sciences (R01 GM147154), and Illinois Department of Public Health. Dr Conti is supported by grants from the National Institute on Drug Abuse, the Veterans Administration, the Arnold Foundation, the National Science Foundation, the Leukemia and Lymphoma Society. The other authors received no additional funding. The funders played 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.
CONFLICT OF INTEREST DISCLOSURES: Dr Chua reports receiving an honorarium from the Benter Foundation and consulting fees from the US Department of Justice for unrelated work. The other authors have indicated they have no potential conflicts of interest relevant to this article to report.
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