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Open Access

To What Extent Are Trends in Teen Mental Health Driven by Changes in Reporting?

The Example of Suicide-Related Hospital Visits

Adriana Corredor-Waldron and View ORCID ProfileJanet Currie
Journal of Human Resources, April 2024, 59 (S) S14-S40; DOI: https://doi.org/10.3368/jhr.0423-12854R1
Adriana Corredor-Waldron
Adriana Corredor-Waldron is an Assistant Professor of Economics at the Poole College of Management, North Carolina State University.
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Janet Currie
Janet Currie is a Professor of Economics and Public Affairs at Princeton University .
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  • For correspondence: jcurrie{at}princeton.edu
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Article Figures & Data

Figures

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  • Trends in Suicide-Related Visits and Suicides in New Jersey, 2008–2019 Notes: These figures plot trends in suicide-related hospital visits, suicide deaths, and suicidal ideation hospital visits in New Jersey. The vertical lines at 2011 and 2016 help to visualize the changes related to the implementation of the Women’s Preventive Services Guidelines in 2012, as well the difference between 2015 and 2016 (implementation of ICD-10) and between 2016 and 2017 (implementation of the “include SI” guidance). a Includes ICD-9 codes for self-injury and ICD-10 codes for intentional self-harm and suicide attempts.
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    Figure 1

    Trends in Suicide-Related Visits and Suicides in New Jersey, 2008–2019

    Notes: These figures plot trends in suicide-related hospital visits, suicide deaths, and suicidal ideation hospital visits in New Jersey. The vertical lines at 2011 and 2016 help to visualize the changes related to the implementation of the Women’s Preventive Services Guidelines in 2012, as well the difference between 2015 and 2016 (implementation of ICD-10) and between 2016 and 2017 (implementation of the “include SI” guidance).

    a Includes ICD-9 codes for self-injury and ICD-10 codes for intentional self-harm and suicide attempts.

  • Teens with Primary Diagnoses of Mental Health Disorders and Secondary Diagnosis of Suicidal Ideation by Gender, Race, Insurance Status, and Hospital Type Notes: These figures show mood-disorder visits with a suicidal ideation diagnosis by gender, race, insurance status, and hospital type in New Jersey. The vertical lines at 2011 and 2016 help to visualize the changes related to the implementation of the Women’s Preventive Services Guidelines in 2012, as well as the difference between 2015 and 2016 (implementation of ICD-10) and between 2016 and 2017 (implementation of the “include SI” guidance).
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    Figure 2

    Teens with Primary Diagnoses of Mental Health Disorders and Secondary Diagnosis of Suicidal Ideation by Gender, Race, Insurance Status, and Hospital Type

    Notes: These figures show mood-disorder visits with a suicidal ideation diagnosis by gender, race, insurance status, and hospital type in New Jersey. The vertical lines at 2011 and 2016 help to visualize the changes related to the implementation of the Women’s Preventive Services Guidelines in 2012, as well as the difference between 2015 and 2016 (implementation of ICD-10) and between 2016 and 2017 (implementation of the “include SI” guidance).

  • Trends in Teen’s Mental Health Visits by Sex Notes: These figures plot trends in mental-health-related visits in New Jersey by sex at birth. The vertical lines at 2011 and 2016 help to visualize the changes related to the implementation of the Women’s Preventive Services Guidelines in 2012, as well as the difference between 2015 and 2016 (implementation of ICD-10) and between 2016 and 2017 (implementation of the “include SI” guidance).
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    Figure 3

    Trends in Teen’s Mental Health Visits by Sex

    Notes: These figures plot trends in mental-health-related visits in New Jersey by sex at birth. The vertical lines at 2011 and 2016 help to visualize the changes related to the implementation of the Women’s Preventive Services Guidelines in 2012, as well as the difference between 2015 and 2016 (implementation of ICD-10) and between 2016 and 2017 (implementation of the “include SI” guidance).

Tables

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    • View popup
    Table 1

    Teens’ Suicide-Related and Total Hospital Visits by Reported Primary Diagnosis

    Any Suicide-Related CodeSuicide-Related Code Is Suicidal IdeationSuicidal Ideation Is Secondary DiagnosisAll Visits
    2009–20102014–20152018–20192009–20102014–20152018–20192009–20102014–20152018–20192009–20102014–20152018–2019
    Panel A: Reported Primary Diagnosis
    All visits36.450.375.623.237.061.920.629.948.43,068.52903.82632.9
    Mood disorder is primary17.024.535.413.020.431.913.020.431.976.998.999.0
    Other mental health is primary7.17.414.45.35.812.55.35.812.5139.7140.4151.7
    Suicidal ideation is primary2.67.113.52.67.113.52.67.113.5
    Non-mental health is primary9.611.312.22.33.73.92.33.73.92,849.32,657.42,368.7
    Panel B: Corrected Primary Diagnosisa
    All visits36.450.375.623.237.061.922.335.157.83,068.52,903.82,632.9
    Mood disorder is primary18.027.540.514.023.437.014.023.437.077.9101.9104.0
    Other mental health is primary7.58.516.75.76.914.85.76.914.8140.1141.5154.0
    Suicidal ideation is primarya0.92.04.10.92.04.10.92.04.1
    Non-mental health is primary9.912.214.22.64.76.02.64.76.02,849.62,658.42,370.8
    • Notes: The table reports the rates per 10,000 teens.

    • ↵a Suicidal ideation is a symptom and is not supposed to be coded as primary if there is another confirmed diagnosis.

    • In Panel B, we reassign visits with a primary diagnosis of suicidal ideation and a secondary diagnosis code to make the non-SI code primary. For example, if SI is primary, but the secondary diagnosis is a mood disorder, then we count the visit in the “Mood disorder is primary” row in Panel B.

    • View popup
    Table 2

    Impact of the Women’s Preventive Screening Guidelines for Depression on Mental Health Hospital Visits for Teens

    Visits with:
    Mental Health DiagnosisMood Disorders DiagnosisAnxiety Disorders DiagnosisSuicidal Ideation Diagnosis
    (1)(2)(3)(4)
    2015 × Female0.00530.01300.00830.0046
    (0.0035)(0.0035)(0.0015)(0.0012)
    2014 × Female0.00680.01250.00710.0047
    (0.0038)(0.0037)(0.0014)(0.0011)
    2013 × Female0.00930.01250.00660.0047
    (0.0036)(0.0036)(0.0014)(0.0011)
    2012 × Female0.00150.00580.00160.0029
    (0.0036)(0.0029)(0.0011)(0.0009)
    Female−0.00940.01480.00670.0022
    (0.0016)(0.0010)(0.0004)(0.0003)
    Baseline meana0.0680.0200.0050.006
    Sample2008–20152008–20152008–20152008–2015
    Observations2,647,0432,647,0432,647,0432,647,043
    R-squared0.08750.07580.01360.0158
    • Notes: The table reports coefficients from linear regression models. The dependent variable for each column is one if the hospital record for a visit includes the condition and zero otherwise. All regressions include fixed effects for hospital, year, month, single year of child’s age, race (Black, white, other race), gender, and insurance (Medicaid, private, self-pay). In addition, the models include zip code characteristics, such as median income and the shares of poor, renters, college educated, non-Hispanic Black, non-Hispanic white, Hispanics, Asians, and age bins. Standard errors are clustered by hospital–year. The sample includes all teen visits to hospitals from 2008 to 2015.

    • ↵a Baseline mean corresponds to the boys’ mean before 2012.

    • View popup
    Table 3

    Impact of the Women’s Preventive Screening Guidelines for Depression on Mental Health Hospital Visits for Teens, Including First Visit in the Year Only

    Visits with:
    Mental Health DiagnosisMood Disorders DiagnosisAnxiety Disorders DiagnosisSuicidal Ideation Diagnosis
    (1)(2)(3)(4)
    2015 × Female0.00480.00980.00600.0034
    (0.0026)(0.0023)(0.0010)(0.0007)
    2014 × Female0.00690.00940.00590.0039
    (0.0029)(0.0023)(0.0010)(0.0008)
    2013 × Female0.00670.00790.00540.0030
    (0.0028)(0.0022)(0.0011)(0.0007)
    2012 × Female0.00030.00460.00130.0022
    (0.0028)(0.0019)(0.0008)(0.0007)
    Female−0.00960.01000.00560.0019
    (0.0012)(0.0007)(0.0003)(0.0002)
    Baseline meana0.0950.0230.0100.005
    Sample2008–20152008–20152008–20152008–2015
    Observations1,792,5591,792,5591,792,5591,792,559
    R-squared0.06790.05350.00960.0103
    • Notes: The table reports coefficients from linear regression models. The dependent variable for each column is one if the hospital record for a visit includes the condition and zero otherwise. All regressions include fixed effects for hospital, year, month, single year of child’s age, race (Black, white, other race), gender, and insurance (Medicaid, private, self-pay). In addition, we include zip code characteristics, such as median income and the shares of poor, renters, college educated, non-Hispanic Black, non-Hispanic white, Hispanics, Asians, and age bins. Standard errors are clustered by hospital–year. The sample includes teen visits to hospital from 2008 to 2015.

    • ↵a Baseline mean corresponds to the boys’ mean before 2012.

    • View popup
    Table 4

    ICD-10 Coding Changes and Suicide-Related Hospital Visits for Teens

    Visits with:
    Suicide-Related DiagnosisSuicide-Related DiagnosisSuicidal Ideation Is Secondary DiagnosisSelf Injuryb Is Diagnosis
    (1)(2)(3)(4)
    2019 × Mood primary0.10190.10150.1151−0.0101
    (0.0497)(0.0431)(0.0474)(0.0064)
    2018 × Mood primary0.10560.10630.1175−0.0074
    (0.0453)(0.0397)(0.0427)(0.0069)
    2017 × Mood primary0.06120.06340.0742−0.0057
    (0.0424)(0.0374)(0.0386)(0.0054)
    2016 × Mood primary0.02110.02430.0254−0.0003
    (0.0360)(0.0321)(0.0324)(0.0054)
    2019 × Other mental0.03810.03910.04160.0001
    (0.0162)(0.0138)(0.0142)(0.0019)
    2018 × Other mental0.04050.04190.04470.0009
    (0.0155)(0.0135)(0.0131)(0.0020)
    2017 × Other mental0.02310.02490.0286−0.0005
    (0.0121)(0.0108)(0.0103)(0.0017)
    2016 × Other mental−0.00040.00120.00180.0003
    (0.0075)(0.0073)(0.0069)(0.0017)
    mood primary0.24060.23360.20410.0476
    (0.0160)(0.0161)(0.0155)(0.0036)
    other mental0.04600.04610.04310.0086
    (0.0039)(0.0041)(0.0038)(0.0008)
    Baseline meana0.0060.0060.0010.003
    Hospital FENYYY
    Sample2013–20192013–20192013–20192013–2019
    Observations2,188,5652,188,5652,188,5652,188,565
    R-squared0.14200.15580.19520.0178
    • Notes: The table reports coefficients from linear regression models. The dependent variable for each column is one if the hospital record for a visit includes the condition and zero otherwise. All regressions include fixed effects for year, month, single year of child’s age, race (Black, white, other race), gender, and insurance (Medicaid, private, self-pay). In addition, the models include zip code characteristics, such as median income and the shares of poor, renters, college educated, non-Hispanic Black, non-Hispanic white, Hispanics, Asians, and age bins. Standard errors are clustered by hospital–year. The sample corresponds to all teen visits from 2013 to 2019 for any indication.

    • ↵a Baseline mean corresponds to the non-mental-health visits’ mean before 2016.

    • ↵b Includes ICD-9 codes for self-injury and ICD-10 codes for intentional self-harm and suicide attempts.

    • View popup
    Table 5

    ICD-10 Coding Changes and Suicidal Ideation Diagnosis, First Visits Only

    Sample: AllSample: First Visit in the YearSample: First Visit in Sample Period
    (1)(2)(3)
    2019 × Mood primary0.11510.08430.0821
    (0.0474)(0.0382)(0.0367)
    2018 × Mood primary0.11750.07670.0570
    (0.0427)(0.0337)(0.0356)
    2017 × Mood primary0.07420.03320.0272
    (0.0386)(0.0301)(0.0316)
    2016 × Mood primary0.0254−0.0037−0.0024
    (0.0324)(0.0288)(0.0312)
    2019 × Other mental0.04160.04140.0493
    (0.0142)(0.0135)(0.0158)
    2018 × Other mental0.04470.04680.0517
    (0.0131)(0.0129)(0.0165)
    2017 × Other mental0.02860.02290.0333
    (0.0103)(0.0079)(0.0102)
    2016 × Other mental0.0018−0.0028−0.0051
    (0.0069)(0.0056)(0.0063)
    Mood primary0.20410.21520.2229
    (0.0155)(0.0146)(0.0152)
    Other mental0.04310.03880.0409
    (0.0038)(0.0032)(0.0036)
    Baseline meana0.0010.0010.001
    Sample2013–20192013–20192013–2019
    Observations2,188,5651,460,977596,055
    R-squared0.19520.17190.1669
    • Notes: The table reports coefficients from linear regression models. The dependent variable for each column is one if the hospital record for a visit includes the condition and zero otherwise. All regressions include fixed effects for year, month, single year of child’s age, race (Black, white, other race), gender, and insurance (Medicaid, private, self-pay). In addition, we include zip code characteristics, such as median income and the shares of poor, renters, college educated, non-Hispanic Black, non-Hispanic white, Hispanics, Asians, and age bins. Standard errors are clustered by hospital–year. The sample includes teen visits from 2013 to 2019.

    • ↵a Baseline mean corresponds to the non-mental-health visits’ mean before 2016.

Additional Files

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  • Free alternate access to The Journal of Human Resources supplementary materials is available at https://uwpress.wisc.edu/journals/journals/jhr-supplementary.html

    • 0423-12854R1_repmat.do
    • 0423-12854R1_supp.pdf
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To What Extent Are Trends in Teen Mental Health Driven by Changes in Reporting?
Adriana Corredor-Waldron, Janet Currie
Journal of Human Resources Apr 2024, 59 (S) S14-S40; DOI: 10.3368/jhr.0423-12854R1

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To What Extent Are Trends in Teen Mental Health Driven by Changes in Reporting?
Adriana Corredor-Waldron, Janet Currie
Journal of Human Resources Apr 2024, 59 (S) S14-S40; DOI: 10.3368/jhr.0423-12854R1
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  • Article
    • Abstract
    • I. Introduction
    • II. Background: Factors Potentially Driving Increases in Reports of Suicidal Behaviors
    • III. Data
    • IV. Methods
    • V. Results
    • VI. Discussion
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