Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2024 May 8.
Published in final edited form as: Adm Policy Ment Health. 2024 Feb 13;51(3):384–392. doi: 10.1007/s10488-024-01342-w

Pediatric Mental Health Care and Scope-of-Practice Expansions

Phillip M Hughes 1,2,3, Genevieve Graaf 4, Kristin H Gigli 5, Neal A deJong 6, Robert E McGrath 7, Kathleen C Thomas 1,3
PMCID: PMC11076160  NIHMSID: NIHMS1971343  PMID: 38349470

Abstract

To examine the association between psychologist and nurse practitioner scope-of-practice (SoP) regulations and pediatric mental health service access. A nationally representative sample of children with mental health needs was identified using 5 years of National Survey of Children’s Health (2016–2020). Utilization was measured in two ways: (1) unmet mental health care needs and (2) receipt of mental health medication. Expanded SoP for psychologists and nurse practitioners was measured based on the child’s state of residence and the year of the survey. The associations between both SoP expansion and both outcomes were assessed using logistic regression models adjusted for multiple covariates. The probability of having unmet mental health needs was 5.4 percentage points lower (95% CI − 0.102, − 0.006) for children living in a state with psychologist SoP expansion; however, there was no significant difference in unmet mental health needs between states with and without NP SoP expansion. The probability of receiving a mental health medication was 2.0 percentage points higher (95% CI 0.007, 0.034) for children living in a state with psychologist SoP expansion. Conversely, the probability of receiving a mental health medication was 1.5 percentage points lower (95% CI − 0.023, − 0.007) for children living in a state with NP SoP expansion. Expanded SoP for psychologists is associated with improved access to pediatric mental health care in terms of both unmet need and receiving medication. Expanded SoP for NPs, however, was not associated with unmet need and lower receipt of medication.

Keywords: Mental health, Scope of practice, Medication, Nurse practitioners, Psychologists

Mental health problems among children are a significant and growing public health concern. Approximately 20% of children ages 12–17 have experienced depression, and nearly 10% of all children have been diagnosed with attention deficit/hyperactivity disorder or anxiety (Bitsko et al., 2022). Prevalence of depression and anxiety among children additionally grew during the COVID-19 pandemic, including a nearly 2.5-fold increase in suicidal ideation (38% of children during the pandemic vs 17% in 2017) (Murata et al., 2021; Samji et al., 2022). Unfortunately, nearly half (49.4%) of all children with a mental health condition in the US receive no treatment (Pasli & Tumin, 2022; Whitney & Peterson, 2019). In light of this, the US Department of Health and Human Services adopted several objectives for Healthy People 2030 regarding the proportion of children receiving mental health treatment (National Academies of Sciences, Engineering, and Medicine (U.S.) & Committee on Informing the Selection of Leading Health Indicators for HealthyPeople 2030, 2020). One systemic barrier to achieving this goal, however, is the ongoing shortage of mental health providers (Andrilla et al., 2020a; Thomas et al., 2009).

Expanding scope-of-practice (SOP) is one policy lever that may improve access to treatment. In particular, expanded prescriptive authority could increase access to mental health medications, particularly when implemented among nurse practitioners (NPs) and psychologists. Currently, 27 states and Washington, D.C. allow NP full practice authority (FPA), eliminating supervision or collaboration requirements related to prescribing (American Association of Nurse Practitioners, 2022). Additionally, 6 states have adopted prescriptive authority for psychologist (RxP) policies, in which psychologists meeting specific educational requirements can apply for a prescribing license (Curtis et al., 2022). There is notable variation in RxP laws from state to state in terms of the breadth of patients treated; for example, Illinois explicitly prohibits psychologists from prescribing for pediatric and geriatric populations (Curtis et al., 2022). Idaho, Iowa, and New Mexico currently have both RxP and NP policies in place.

To date, FPA for NPs has been associated with reductions in poor mental health days and mental health-related mortality among adults in underserved counties (Alexander & Schnell, 2019). Similarly, there is some evidence that RxP policies reduce mental health-related mortality and may be a cost-effective approach to reducing suicides (Choudhury & Plemmons, 2023; Hughes et al., 2023b, 2023c). However, research on the mental health impacts of SOP expansion for NPs and psychologists has not focused on pediatrics. Given that children make up 12.9% and 14.4% of patients seen by NPs (Kleinpell et al., 2018) and prescribing psychologists (Peck et al., 2021), respectively, it seems plausible that SOP policies may contribute to improved access to mental health care for children.

Given the demand for pediatric mental health care and the ongoing mental health workforce shortage, it is important to understand if SOP expansion improves access to care. To address this important knowledge gap, this study examines the relationship between state SOP policies and mental health care access in children using the Andersen Behavioral Model of Healthcare Utilization (ABM) as a theoretical framework (Aday & Andersen, 1974; Andersen, 1995). The ABM posits that healthcare utilization is determined by the combination of predisposing factors (e.g., biological sex), enabling factors (e.g., insurance), need factors (e.g., having a mental health problem) and context (such as state policy). Under the ABM, expanded SOP would constitute a state-level contextual factor, which we hypothesize will be associated with relatively lower unmet need for mental health care and relatively higher receipt of mental health medications.

Methods

Data and Participants

We conducted a pooled cross-sectional analysis using 5 years of data (2016–2020) from the National Survey of Children’s Health (NSCH), resulting in a sample of 174,551 children. The NSCH is a publicly available, nationally-representative telephone survey conducted by the US Census Bureau on behalf of the Maternal and Child Health Bureau of the Health Resources and Services Administration (Ghandour et al., 2018). Broadly, the NSCH includes questions regarding the physical health, mental health, healthcare service utilization, socioeconomic status, and demographics of non-institutionalized children under age 18 across the country. Additional details regarding the survey are available elsewhere (Ghandour et al., 2018). Given our focus on mental health services, we limited our analyses to children with mental health problems (n = 33,790) defined as either the presence of a mental health diagnosis or caregiver-reported emotional, behavioral, or developmental problems (Bethell et al., 2022). As a secondary analysis of publicly available de-identified data, this study does not constitute human-subjects research.

Measures

Primary Outcomes

We had two distinct outcomes of interest: unmet need for mental health care and the receipt of mental health medication. Consistent with recent studies (Lebrun-Harris et al., 2019; Pasli & Tumin, 2022), unmet need for mental health care was defined using the question “During the past 12 months, has this child received any treatment or counseling from a mental health professional? Mental health professionals include psychiatrists, psychologists, psychiatric nurse practitioners, and clinical social workers.” Those who responded “Yes” were coded as having no unmet need, while those who responded “No, but this child needed to see a mental health professional” were coded as having an unmet need. Those who responded “No, this child did not need to see a mental health professional” were excluded from this outcome, as they identified no need for mental health care, resulting in a smaller sample for this outcome (n = 17,574). The assessment of unmet needs included a need for any mental health treatment, including psychotherapy. The second outcome, receipt of a mental health medication, was a binary variable measured using the question “During the past 12 months, has this child taken any medication because of difficulties with his or her emotions, concentration, or behavior?”.

SOP Expansion

Our two primary policies of interest were for NPs and RxP. Binary indicator variables for both SOP expansions were created to designate children from states with the corresponding policy. For RxP, this indicator denoted the five states (New Mexico, Louisiana, Illinois, Iowa, and Idaho) that allowed psychologists to become licensed prescribers during the study period. While prescribing psychologists in Illinois are not allowed to treat children, they were included as a treated state given that the policy may impact unmet need in other ways, such as reducing wait times for children to see a psychiatrist by increasing access to care for the adult population. The sixth state where psychologists can prescribe, Colorado (2023), passed RxP after the study period and was therefore coded as a non-RxP state.

For NP FPA, we categorized states as either having FPA or reduced/restricted SOP consistent with prior approaches to classifying NP regulations (American Association of Nurse Practitioners, 2022; Traczynski & Udalova, 2018). A total of 25 states and Washington, D.C. were coded as FPA (Table 1). Three additional states, Massachusetts (2021), Kansas (2022), and New York (2022), passed FPA laws in the years following the study period and were therefore coded as not having FPA. Additionally, both Idaho (RxP) and South Dakota (FPA) passed their laws during the study period (both 2017); respondents from these states during the 2016 NSCH were coded as not having the respective expanded SOP.

Table 1.

State’s SOP status for nurse practitioners and psychologists

Nurse practitioners Full practice authority AK (1987), AZ (2000), CO (2010), CT (2014), DC (1995), DE (2015), HI (2011), IA (1995), ID (2004), MD (2010), ME (1996), MN (2015), MT (1984), ND (2011), NE (2015), NH (1991), NM (1993), NV (2013), OR (1979), RI (2013), SD (2017)a, UT (1998), VT (2011), WA (2001), WY (1993)
Reduced/restricted SOP AL, AR, CA, FL, GA, IL, IN, KSb, KY, LA, MAb, MI, MO, MS, NC, NJ, NYb, OH, OK, PA, SC, TN, TX, VA, WI, WV
Psychologists Prescriptive authority IA (2016), ID (2017a), ILc (2014), LA (2004), NM (2002)
No prescriptive authority AK, AL, AR, AZ, CA, COd, CT, DC, DE, FL, GA, HIe, IN, KS, KY, MA, MD, ME, MI, MN, MO, MS, MT, NC, ND, NE, NH, NV, NY, OH, OK, ORe, PA, RI, SC, SD, TN, TX, UT, VA, VT, WA, WI, WV, WY
Open in a new tab

Nurse practitioner scope of practice classifications based on Traczysnki and Udalova (2014) and the American Association of Nurse Practitioner Practice Environment Map

SOP scope of practice

a

Idaho (psychologists) and South Dakota (NPs) expanded SOP during the study period (both 2017)

b

Massachusetts (2021), Kansas (2022), and New York (2022) have expanded nurse practitioner scope of practice in the years following the study period

c

Psychologists in Illinois (2014) may only prescribe to adults aged 18–64

d

Colorado (2023) has passed a prescriptive authority law in the years following the study period

e

Hawaii (2007) and Oregon (2010) both passed a bill authorizing prescribing psychologists, but both were ultimately vetoed by their respective governors

Covariates

We selected covariates based on their theoretical role in the ABM as related to mental health services. The selected predisposing factors included age group (0–5, 6–11, 12–17 years), binary biological sex, language spoken in the home (English, language other than English), and combined race/ethnicity (Hispanic, Non-Hispanic White, Non-Hispanic Black, and Non-Hispanic Other/Multiracial). Race/ethnicity and household language were included to account for the role of structural barriers and cultural preferences rather than biological differences. To account for enabling factors, we included insurance status (public only, private only, public and private, none), an indicator of income less than 200% of the federal poverty limit, caregiver’s education level (less than high school, high school graduate, more than high school), and having a single-parent household. To account for enabling factors, we included an indicator for rurality (rural or urban), defined as residing outside of a metropolitan statistical area using the approach described in the NSCH documentation (U.S Census Bureau, 2021). Given that our sample only included children with a mental health problem, we included measures of physical health and mental health problem severity to account for variation in need for services. These included special health care need status (as identified by the children with special health care needs screening included in the NSCH) and any limitation on daily activities caused by a health condition. Additionally, caregivers who reported that their child had a diagnosis of anxiety, depression, attention-deficit hyperactivity disorder, other behavioral problems, or other mental health conditions were asked to rate the severity of the condition as mild, moderate, or severe. We created a binary mental health severity indicator in which children who had any conditions rated as moderate or severe were denoted as having a severe condition.

Analysis

Analyses were conducted using STATA v.16.1 (StataCorp, College Station, TX). We accounted for the complex survey methodology of the NSCH via the use of the survey commands available in STATA, which account for weighting, stratification, and clustering to generate nationally representative results. Prior to public release, missing race/ethnicity, income, and ages in the NSCH are multiply imputed using hotdeck methods (Langkamp et al., 2010). As missingness was generally low in our study (unmet need: 2.1%; medications: 4.2%), we used a complete-case approach for each analysis; prior work suggests this approach is generally unbiased in secondary data analyses when missingness is below 10% (Langkamp et al., 2010). Additionally, we used the ‘subpop’ commands in STATA to define the analytic sample for each model, which allows STATA to use the appropriate design-corrected degrees of freedom in calculating standard errors by accounting for all strata and clusters within the full survey sample while limiting the model estimation to the subpopulation of interest (West et al., 2008). This approach resulted in analytic samples of 13,872 (unmet need) and 26,223 (medications).

We used logistic regression models with average marginal effects (AMEs) and 95% confidence intervals (CIs) to examine the impact of FPA and RxP on both measures of mental health care utilization. All models included year fixed effects to account for annual variation. In addition to our main analyses, we conducted several sensitivity analyses. First, we examined an alternative measure of unmet need (“During the past 12 months, was there any time when this child needed mental health care but it was not received?”) to examine sensitivity to the measure used. Second, we estimated the effect of FPA and RxP separately to examine sensitivity to states with both or neither policy. Finally, we excluded children five and under to limit the sample to children ages 6–17 who are more likely to use mental health services such as medication.

Results

After survey weighting, our sample of 33,790 children represented 12,217,989 children. In total, 8.1% of children were in a state with an RxP policy and 20.4% were in a state with FPA. A summary of the predisposing, enabling, need, and context factors stratified by policy adoption can be seen in Table 2. The sample was primarily ages 12–17 (50.3%), male (59.8%), and White (54.7%) and the majority were privately insured (48.7%), had a family income over 200% of the federal poverty limit (54.6%), and had a caregiver with more than a high school education (69.6%). Additionally, over a quarter (27.0%) of children were from rural areas and a third were from a single-parent household (36.4%). Over 70% of the sample were children with special healthcare needs, 50.0% had mental health problems that were considered severe, and 55.9% experienced impairments in daily living. There were no significant differences between children who lived in states with an RxP policy and those who did not with the exception of RxP states having fewer children in rural areas (27.6% vs 19.5%, p < 0.0001); however, children in states with NP full practice authority differed in several ways (Table 2). Compared to children in other states, those in states with NP FPA were older (Ages 12–17: 52.0% vs 49.9%; p = 0.014), more likely to be White (60.2% vs 53.3%; p < 0.001), and less likely to speak a language other than English (6.2% vs 8.6%; p = 0.001). They were predominantly from rural areas (59.8% vs 18.6%; p < 0.001), had parents with greater than a high school education (75.2% vs 68.1%; p < 0.001), and were less likely to be from single-parent households (31.6% vs 37.6%; p < 0.001).

Table 2.

Descriptive statistics (sample N = 33,790, weighted N = 12,217,989)

RxP implemented
 p value NP full practice authority
 p value Total (%)
No (%) Yes (%) No (%) Yes (%)
Age 0.8174 0.0138
 0–5 10.7 11.3 11.1 9.3 10.7
 6–11 39.0 38.1 39.0 38.7 39.0
 12–17 50.3 50.6 49.9 52.0 50.3
Female 40.3 39.4 0.6120 40.1 40.8 0.5004 40.2
Race 0.0633 < .0001
 White, NH 54.7 54.8 53.3 60.2 54.7
 Black, NH 14.9 18.1 17.1 7.7 15.2
 Other, NH 8.5 7.1 7.8 10.4 8.3
 Hispanic 22.0 20.0 21.9 21.7 21.8
Language other than English 8.2 7.2 0.5075 8.6 6.2 0.0012 8.1
Insurance 0.8335 < .0001
 Public only 38.1 38.2 39.2 33.8 38.1
 Private only 48.8 48.1 47.5 53.4 48.7
 Private and public 7.9 7.8 7.8 8.3 7.9
 Not insured 5.2 6.0 5.5 4.4 5.3
Income < 200% FPL 54.8 53.0 0.3486 56.2 48.3 < .0001 45.4
Caregiver’s education 0.1216 < .0001
 Less than high school 8.9 7.9 9.5 6.2 8.9
 High school 21.8 18.6 22.4 18.5 21.6
 More than high school 69.2 73.5 68.1 75.2 69.6
Single-parent household 36.5 35.2 0.4855 37.6 31.6 < .0001 36.4
CSHCN 70.6 72.6 0.2241 70.9 70.0 0.3711 70.7
Severe mental health problem 50.0 49.4 0.7143 49.7 51.0 0.2558 50.0
Impairments in daily living 55.8 56.0 0.9344 55.7 56.4 0.4989
Rural 27.6 19.5 < .0001 18.6 59.8 < .0001 27.0%
Year 0.1343 0.1547
 2016 19.9 19.4 20.0 19.4 19.9
 2017 19.4 20.7 19.2 20.8 19.5
 2018 19.6 21.6 19.9 19.2 19.8
 2019 19.6 20.4 19.5 20.4 19.7
 2020 21.4 18.0 21.4 20.1 21.2
Open in a new tab

P values are from chi-square tests comparing children in states with and without scope-of-practice expansion

RxP prescriptive authority for psychologists, NP nurse practitioner, CSHCN children with special health care needs

The results of the logistic regression models for unmet need and receiving medications can be found in Table 3. In the model for unmet need for mental health care, RxP policies were associated with a 5.4 percentage point lower probability of a child having unmet need (AME [95% CI] = − 0.054 [− 0.102, − 0.006]). FPA for NPs, however, was not significantly associated with unmet need for mental health care (− 0.016 [− 0.047, 0.015]). In the model for receipt of medication for mental health conditions, RxP policies were associated with a 2 percentage point higher probability of a child receiving a medication (0.020 [0.007, 0.034]). FPA for NPs was associated with a 1.5 percentage point lower probability of a child receiving a medication (− 0.015 [− 0.023, − 0.007]). The results of both models were consistent across all three sensitivity analyses, as well (see Online Appendix).

Table 3.

Average marginal effects and 95% confidence intervals from logistic regression models

Unmet need
 Medication received
AME 95% CI
 AME 95% CI
Lower Upper Lower Upper
RxP implemented − 0.054 − 0.102 − 0.006 0.020 0.007 0.034
NP full practice authority − 0.016 − 0.047 0.015 − 0.015 − 0.023 − 0.007
Age
 0–5 0.119 0.045 0.194 − 0.139 − 0.155 − 0.122
 6–11 0.064 0.027 0.100 − 0.058 − 0.071 − 0.045
 12–17 Ref Ref Ref Ref Ref Ref
Female 0.022 − 0.015 0.059 − 0.018 − 0.027 − 0.009
Race
 White, NH Ref Ref Ref Ref Ref Ref
 Black, NH 0.099 0.037 0.162 − 0.020 − 0.035 − 0.005
 Other, NH 0.044 − 0.017 0.105 − 0.031 − 0.043 − 0.018
 Hispanic 0.007 − 0.047 0.062 − 0.026 − 0.041 − 0.011
Language other than English − 0.005 − 0.092 0.082 − 0.034 − 0.061 − 0.007
Insurance
 Public only 0.003 − 0.046 0.052 − 0.001 − 0.016 0.014
 Private only Ref Ref Ref Ref Ref Ref
 Private and public − 0.014 − 0.087 0.058 0.003 − 0.017 0.022
 Not insured 0.102 0.003 0.201 − 0.012 − 0.038 0.015
Income < 200% FPL 0.080 0.034 0.125 − 0.015 − 0.027 − 0.004
Caregiver’s education
 Less than high school − 0.061 − 0.142 0.020 0.008 − 0.024 0.040
 High school Ref Ref Ref Ref Ref Ref
 More than high school − 0.027 − 0.079 0.024 − 0.010 − 0.024 0.004
Single-parent household 0.019 − 0.020 0.058 0.001 − 0.010 0.012
CSHCN − 0.083 − 0.131 − 0.035 0.205 0.185 0.225
Severe mental health problem − 0.023 − 0.068 0.023 0.122 0.105 0.139
Impairments in daily living 0.030 − 0.017 0.076 0.008 − 0.003 0.019
Rural 0.002 − 0.031 0.036 0.017 0.007 0.026
Year
 2016 Ref Ref Ref Ref Ref Ref
 2017 0.054 − 0.007 0.115 0.007 − 0.009 0.022
 2018 − 0.004 − 0.053 0.045 0.008 − 0.006 0.022
 2019 − 0.021 − 0.070 0.028 0.005 − 0.007 0.018
 2020 0.018 − 0.032 0.068 − 0.007 − 0.018 0.005
Subpopulation sample N (weighted) 170,849 167,248
Weighted subpopulation N 13,872 26,223
Model F 4,738,424 9,257,837
Model p value 3.92 51.24
Open in a new tab

RxP prescriptive authority for psychologists, NP nurse practitioner, CSHCN children with special health care needs

Discussion

Expanding SOP for providers has been shown to improve population mental health, but research to date has not specifically examined the effect in pediatrics. We found that unmet need for mental health care is lower and receipt of medications for mental health is higher among children in states that have adopted an RxP policy; however, the influence of FPA for NPs appears to be uncertain. These findings have policy implications for improving pediatric mental health care.

Lower unmet need for pediatric mental health care in states with RxP policies is consistent with prior findings that mortality due to mental health declined when psychologists became eligible to prescribe medications (Choudhury & Plemmons, 2023; Hughes et al., 2023b). Given that RxP does not directly increase the number of available mental health professionals, it seems plausible that this reduction in unmet need may be attributable to a reduction in the number of referrals and separate visits needed for an individual patient to have their needs met. In non-RxP states, people in the care of a psychologist who might benefit from medication must meet with an additional provider authorized to prescribe—posing additional barriers to access, including finding a prescribing child provider and additional time initiating and attending appointments. Future research describing differences in the process and experience of finding pediatric mental health care from the parents’ perspective in states with and without RxP policies is needed to identify the mechanism by which unmet need is being addressed in those states.

Our finding that unmet need for pediatric mental health care was not lower in states with FPA is inconsistent with the substantial evidence of improved adult mental health in those states (Alexander & Schnell, 2019). Given the ample evidence that NPs can provide quality adult mental health care (Alexander & Schnell, 2019; Chapman et al., 2018), our findings may reflect the small number of NPs who provide pediatric mental health care (Delaney & Vanderhoef, 2019; Gigli et al., 2023). Future studies evaluating the distribution and practice patterns of the pediatric mental health NP workforce may elucidate opportunities to target expansion of this workforce in areas with greatest need. Additionally, strategies that leverage the adult mental health NP workforce and increase their capacity to care for children, through additional education or training or increased management of adolescent patients by NPs who traditionally care for adults, might increase the impact of FPA on pediatric mental health to the same extent seen in adult mental health care.

Regarding the receipt of medications, as anticipated, RxP policies were associated with higher rates of receiving medication. This suggests that these policies succeed in addressing mental health prescriber shortages to a degree, though it is important to note that this study was not designed to assert causality. Future studies are needed to examine how access to medications changed over time. Additionally, there remains a paucity of evidence regarding the safety and efficacy of psychologists’ prescribing practices. Future research is needed to understand whether the increase in medications resulted from psychologists meeting patient needs or from potentially unnecessary prescribing. Finally, medications are only one component of mental health care, as reflected by the policy having different effect sizes for unmet mental health needs (5.4 percentage points) versus medication (2.0 percentage points). While it could be inferred that the difference between these two estimates is the impact of RxP on psychotherapy access, future studies should examine this directly given that RxP is a policy specifically focused on prescribing.

The lower rates of receiving medication in states with FPA for NPs was unexpected given that FPA confers independent prescriptive authority for NPs. Our finding directly contradicts a prior study examining population-level prescribing of antidepressants and antipsychotics, in which FPA was associated with no change in prescribing for the general population, but increases for those in underserved counties and people insured through Medicaid (Alexander & Schnell, 2019). The reason for this discrepancy in the association for children versus the full population is not readily apparent. It is possible that NPs are prescribing less because they refer their pediatric mental health patients to other providers for prescribing, leading to drop-out, co-manage more complex patients with a physician, which might affect no change, or manage these patients themselves but with a preferent for nonmedication treatment (Hawkins-Walsh & Van Cleve, 2019; Hughes et al., 2023a). Future research is needed to understand NP mental health practices, if they vary by FPA, and why children in states with FPA are less likely to receive mental health medications. Finally, it is possible that this reduction in mental health medications may be beneficial. Currently, psychotropic medications are the most common form of mental health treatment for children (Ali et al., 2019), and the majority of those prescriptions come from primary care physicians (Mark et al., 2009). There is concern about the high rate of psychotropic prescribing in primary care (Barnett et al., 2020), and it seems plausible that this reduction in medications received may reflect increased discretion in prescribing. Future research is needed to examine this possibility further.

Limitations

This study had several important limitations. First, the NSCH does not include institutionalized children, such as those in juvenile detention, and those children are more likely to have mental health problems (Beaudry et al., 2021). Second, while state effects were incorporated in survey weighting, we were unable to account for substate differences, such as provider distributions, provider employment patterns, and provider-to-population ratios. Our inclusion of rurality captures some of this indirectly, as the distribution of psychologists and NPs vary by rurality (Andrilla et al., 2018; Zhang et al., 2020); however, this does not encompass all sub-state regional variation. Future studies should seek to examine how these policies impact access to mental health care within states. Similarly, this study did not account for workforce issues that could limit the impact of these policies, such as difficulty finding clinical training experiences and disparities in insurance reimbursement rates across payors. Furthermore, state agency-level (e.g., Medicaid) and individual practice-level policies that were unaccounted for may have limited the impact of these policies. For example, practice-level policies have been cited as a limiting factor for nurse practitioners seeking to prescribe in other clinical populations (Andrilla et al., 2020b). Future studies are needed to explore the barriers faced by psychologists and NPs seeking to prescribe for the pediatric mental health population. Third, a few states passed SoP expansions immediately preceding or during the study period; however, there may be delays in the uptake of SoP expansion among providers for various reasons resulting in policy effect estimates that may be biased towards the null hypothesis of no effect. A quasi-experimental study should explore this possibility once more years of NSCH data are available. Finally, the NSCH is a parent-report survey and therefore does not necessarily reflect objective measures of access. While the family-reported experience provides important information about the impact of these policies, future studies are needed to examine their impact on provider distributions, available patient contact hours, and other measures of provider availability and reach.

Conclusion

Pediatric mental health care from 2016 to 2020 appears to be more accessible in states that have expanded SoP for psychologists but not NPs. Unmet need for mental health care was lower by approximately 5.5% in states with RxP policies. Receiving medications for mental health conditions was higher in states with RxP policies but lower in those with NP FPA. These may both be positive outcomes. Future research is needed on the mechanisms behind these changes in order to understand benefits and best strategies for delivering the most valuable care to children who need it.

Supplementary Material

supplemental files

Funding

Phillip Hughes was partially supported by a National Research Service Award Pre-Doctoral/Post-Doctoral Traineeship from the Agency for Healthcare Research and Quality sponsored by The Cecil G. Sheps Center for Health Services Research, The University of North Carolina at Chapel Hill, Grant No. T32-HS000032. Dr. Graaf was supported in part by the National Institute of Mental Health of the National Institutes of Health under Award Number 1K01MH129991. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

Declarations

Conflict of interest Phillip Hughes was awarded the 2023 Patrick H. DeLeon Prize for Outstanding Student Contribution to the Advancement of Pharmacotherapy from APA Division 55 (Society for Prescribing Psychology). The other authors have no relevant conflicts to disclose.

Research Involving Human Participants This study does not constitute human subjects research.

Reporting Guidelines This study was reported in accordance with the STROBE guidelines.

Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s10488-024-01342-w.

References

  1. Aday LA, & Andersen R (1974). A framework for the study of access to medical care. Health Services Research, 9(3), 208–220. [PMC free article] [PubMed] [Google Scholar]
  2. Alexander D, & Schnell M (2019). Just what the nurse practitioner ordered: Independent prescriptive authority and population mental health. Journal of Health Economics, 66, 145–162. 10.1016/j.jhealeco.2019.04.004 [DOI] [PubMed] [Google Scholar]
  3. Ali MM, Sherman LJ, Lynch S, Teich J, & Mutter R (2019). Differences in utilization of mental health treatment among children and adolescents with Medicaid or private insurance. Psychiatric Services, 70(4), 329–332. 10.1176/appi.ps.201800428 [DOI] [PubMed] [Google Scholar]
  4. American Association of Nurse Practitioners. (2022, October). 2023 Nurse practitioner state practice environment https://www.aanp.org/advocacy/state/state-practice-environment
  5. Andersen RM (1995). Revisiting the behavioral model and access to medical care: Does it matter? Journal of Health and Social Behavior, 36(1), 1. 10.2307/2137284 [DOI] [PubMed] [Google Scholar]
  6. Andrilla CHA, Garberson LA, Patterson DG, Quigley TF, & Larson EH (2020a). Comparing the health workforce provider mix and the distance travelled for mental health services by rural and urban Medicare beneficiaries. The Journal of Rural Health, 37(4), 692–699. 10.1111/jrh.12504 [DOI] [PubMed] [Google Scholar]
  7. Andrilla CHA, Jones KC, & Patterson DG (2020b). Prescribing practices of nurse practitioners and physician assistants waivered to prescribe buprenorphine and the barriers they experience prescribing buprenorphine. The Journal of Rural Health, 36(2), 187–195. [DOI] [PubMed] [Google Scholar]
  8. Andrilla CHA, Patterson DG, Garberson LA, Coulthard C, & Larson EH (2018). Geographic variation in the supply of selected behavioral health providers. American Journal of Preventive Medicine, 54(6), S199–S207. 10.1016/j.amepre.2018.01.004 [DOI] [PubMed] [Google Scholar]
  9. Barnett ER, Trepman AZ, Fuson HA, Acquilano SC, McLaren JL, Woloshin S, & Leyenaar JK (2020). Deprescribing psychotropic medications in children: Results of a national qualitative study. BMJ Quality & Safety, 29(8), 655–663. 10.1136/bmjqs-2019-010033 [DOI] [PubMed] [Google Scholar]
  10. Beaudry G, Yu R, Långström N, & Fazel S (2021). An updated systematic review and meta-regression analysis: Mental disorders among adolescents in juvenile detention and correctional facilities. Journal of the American Academy of Child & Adolescent Psychiatry, 60(1), 46–60. 10.1016/j.jaac.2020.01.015 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Bethell CD, Garner AS, Gombojav N, Blackwell C, Heller L, & Mendelson T (2022). Social and relational health risks and common mental health problems among us children. Child and Adolescent Psychiatric Clinics of North America, 31(1), 45–70. 10.1016/j.chc.2021.08.001 [DOI] [PubMed] [Google Scholar]
  12. Bitsko RH, Claussen AH, Lichstein J, Black LI, Jones SE, Danielson ML, Hoenig JM, Davis Jack SP, Brody DJ, Gyawali S, Maenner MJ, Warner M, Holland KM, Perou R, Crosby AE, Blumberg SJ, Avenevoli S, Kaminski JW, Ghandour RM, … Meyer LN (2022). Mental health surveillance among children—United States, 2013–2019. MMWR Supplements, 71(2), 1–42. 10.15585/mmwr.su7102a1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Chapman SA, Phoenix BJ, Hahn TE, & Strod DC (2018). Utilization and economic contribution of psychiatric mental health nurse practitioners in public behavioral health services. American Journal of Preventive Medicine, 54(6), S243–S249. 10.1016/j.amepre.2018.01.045 [DOI] [PubMed] [Google Scholar]
  14. Choudhury AR, & Plemmons A (2023). Effects of giving psychologists prescriptive authority: Evidence from a natural experiment in the United States. Health Policy, 134, 104–846. 10.1016/j.healthpol.2023.104846 [DOI] [PubMed] [Google Scholar]
  15. Curtis SE, Hoffmann S, & O’Leary Sloan M (2022). Prescriptive authority for psychologists: The next step. Psychological Services 10.1037/ser0000667 [DOI] [PubMed]
  16. Delaney KR, & Vanderhoef D (2019). The psychiatric mental health advanced practice registered nurse workforce: Charting the future. Journal of the American Psychiatric Nurses Association, 25(1), 11–18. 10.1177/1078390318806571 [DOI] [PubMed] [Google Scholar]
  17. Ghandour RM, Jones JR, Lebrun-Harris LA, Minnaert J, Blumberg SJ, Fields J, Bethell C, & Kogan MD (2018). The design and implementation of the 2016 National Survey of Children’s Health. Maternal and Child Health Journal, 22(8), 1093–1102. 10.1007/s10995-018-2526-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Gigli KH, Martsolf GR, Vinci RJ, & Buerhaus PI (2023). A cross-sectional examination of the nurse practitioner workforce caring for children in the United States. The Journal of Pediatrics 10.1016/j.jpeds.2023.02.020 [DOI] [PubMed]
  19. Hawkins-Walsh E, & Van Cleve SN (2019). A job task analysis of the expanding role of the pediatric mental health specialist and the nurse practitioner in pediatric mental health. Journal of Pediatric Health Care, 33(3), e9–e17. 10.1016/j.pedhc.2018.11.001 [DOI] [PubMed] [Google Scholar]
  20. Hughes PM, Harless C, Ramage M, Fusco C, & Ostrach B (2023a). Opioid use disorder practice by licensure category in North Carolina. North Carolina Medical Journal 10.18043/001c.74508 [DOI] [PubMed]
  21. Hughes PM, McGrath RE, & Thomas KC (2023b). Evaluating the impact of prescriptive authority for psychologists on the rate of deaths attributed to mental illness. Research in Social and Administrative Pharmacy, 19(4), 667–672. 10.1016/j.sapharm.2022.12.006 [DOI] [PubMed] [Google Scholar]
  22. Hughes PM, Phillips DC, McGrath RE, & Thomas KC (2023c). Examining psychologist prescriptive authority as a cost-effective strategy for reducing suicide rates. Professional Psychology: Research and Practice, 54(4), 284–294. 10.1037/pro0000519 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Kleinpell R, Cook ML, & Padden DL (2018). American Association of Nurse Practitioners National Nurse Practitioner sample survey: Update on acute care nurse practitioner practice. Journal of the American Association of Nurse Practitioners, 30(3), 140–149. 10.1097/JXX.0000000000000030 [DOI] [PubMed] [Google Scholar]
  24. Langkamp DL, Lehman A, & Lemeshow S (2010). Techniques for handling missing data in secondary analyses of large surveys. Academic Pediatrics, 10(3), 205–210. 10.1016/j.acap.2010.01.005 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Lebrun-Harris LA, Sherman LJ, Limber SP, Miller BD, & Edgerton EA (2019). Bullying victimization and perpetration among U.S. children and adolescents: 2016 National Survey of Children’s Health. Journal of Child and Family Studies, 28(9), 2543–2557. 10.1007/s10826-018-1170-9 [DOI] [Google Scholar]
  26. Mark TL, Levit KR, & Buck JA (2009). Datapoints: Psychotropic drug prescriptions by medical specialty. Psychiatric Services, 60(9), 1167–1167. 10.1176/ps.2009.60.9.1167 [DOI] [PubMed] [Google Scholar]
  27. Murata S, Rezeppa T, Thoma B, Marengo L, Krancevich K, Chiyka E, Hayes B, Goodfriend E, Deal M, Zhong Y, Brummit B, Coury T, Riston S, Brent DA, & Melhem NM (2021). The psychiatric sequelae of the COVID-19 pandemic in adolescents, adults, and health care workers. Depression and Anxiety, 38(2), 233–246. 10.1002/da.23120 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. National Academies of Sciences, Engineering, and Medicine (U.S.) & Committee on Informing the Selection of Leading Health Indicators for HealthyPeople 2030. (2020). Leading health indicators 2030: Advancing health, equity, and well-being https://nap.nationalacademies.org/catalog/25682/leading-health-indicators-2030-advancing-health-equity-and-well-being [PubMed]
  29. Pasli M, & Tumin D (2022). Children’s unmet need for mental health care within and outside metropolitan areas. Pediatrics & Neonatology, 63(5), 512–519. 10.1016/j.pedneo.2022.03.018 [DOI] [PubMed] [Google Scholar]
  30. Peck KR, McGrath RE, & Holbrook BB (2021). Practices of prescribing psychologists: Replication and extension. Professional Psychology: Research and Practice, 52(3), 195–201. 10.1037/pro0000338 [DOI] [Google Scholar]
  31. Samji H, Wu J, Ladak A, Vossen C, Stewart E, Dove N, Long D, & Snell G (2022). Review: Mental health impacts of the COVID-19 pandemic on children and youth—A systematic review. Child and Adolescent Mental Health, 27(2), 173–189. 10.1111/camh.12501 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Thomas KC, Ellis AR, Konrad TR, Holzer CE, & Morrissey JP (2009). County-level estimates of mental health professional shortage in the United States. Psychiatric Services, 60(10), 1323–1328. 10.1176/ps.2009.60.10.1323 [DOI] [PubMed] [Google Scholar]
  33. Traczynski J, & Udalova V (2018). Nurse practitioner independence, health care utilization, and health outcomes. Journal of Health Economics, 58, 90–109. 10.1016/j.jhealeco.2018.01.001 [DOI] [PubMed] [Google Scholar]
  34. U.S Census Bureau. (2021). 2020 National Survey of Children’s Health Methodology Report https://www.census.gov/programs-surveys/nsch/technical-documentation/methodology.html
  35. West BT, Berglund P, & Heeringa SG (2008). A closer examination of subpopulation analysis of complex-sample survey data. The Stata Journal: Promoting Communications on Statistics and Stata, 8(4), 520–531. 10.1177/1536867X0800800404 [DOI] [Google Scholar]
  36. Whitney DG, & Peterson MD (2019). US national and state-level prevalence of mental health disorders and disparities of mental health care use in children. JAMA Pediatrics, 173(4), 389. 10.1001/jamapediatrics.2018.5399 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Zhang D, Son H, Shen Y, Chen Z, Rajbhandari-Thapa J, Li Y, Eom H, Bu D, Mu L, Li G, & Pagán JA (2020). Assessment of changes in rural and urban primary care workforce in the United States from 2009 to 2017. JAMA Network Open, 3(10), e2022914. 10.1001/jamanetworkopen.2020.22914 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

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

Supplementary Materials

supplemental files
NIHMS1971343-supplement-supplemental_files.docx (33KB, docx)

RESOURCES