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. Author manuscript; available in PMC: 2022 Mar 30.
Published in final edited form as: Evid Based Pract Child Adolesc Ment Health. 2018 Aug 24;4(2):113–121. doi: 10.1080/23794925.2018.1501328

Factors Influencing Emerging Adults’ Use of Outpatient Mental Health Services

Sarah R Black a, Mary A Fristad a,b, L Eugene Arnold a, Boris Birmaher c, Robert L Findling d, Eric A Youngstrom e, Sarah M Horwitz f
PMCID: PMC8966385  NIHMSID: NIHMS1788265  PMID: 35360447

Abstract

Rates of treatment utilization decline as adolescents make the transition to adulthood even though young adults are particularly vulnerable to the negative outcomes of untreated mental illness. Although a variety of factors have been explored to explain decreased treatment utilization in this age group, previous research has almost exclusively employed cross-sectional methods rather than following a group of youth as they enter adulthood. The current study aims to address this methodological limitation by assessing treatment utilization in emerging adults who began participating in a longitudinal study during childhood. One hundred and thirty seven youth who turned 18 during the 96-month follow-up period were included in the current analyses. Demographic and socioeconomic variables such as sex, race, and insurance status and clinical variables such as psychiatric diagnoses and perceptions of treatment effectiveness were investigated as factors potentially associated with outpatient treatment use before and after age 18. Prior to age 18, youth reported using outpatient services at 75% of their visits, but after age 18, outpatient treatment utilization dropped to around 50%. White race, increased parental stress, and increased parental perception of treatment usefulness were associated with greater treatment use prior to age 18, whereas only increased youth perception of symptom-related dysfunction were associated with increased treatment use after age 18. Findings point to the importance of including youth preferences and perceptions of dysfunction in treatment decisions across adolescence in order to optimize treatment use following the transition to adulthood.

Youth with psychiatric disorders are at risk for a variety of negative outcomes, including academic, social, and occupational difficulties. Although services are in place to assist youth and their families to obtain mental health treatment (e.g., subsidized mental health services for youth through the federal Children’s Health Insurance Program), many youths tend to drop out of treatment during the transition from child- to adult-based services (Singh et al., 2010). In addition, emerging adults often leave their homes for the first time for work or study, and consequently may have less structure and fewer emotional and financial resources (Shaver, Furman, & Buhrmester, 1985). Simultaneously, rates of many psychiatric disorders increase during this period (especially substance and mood disorders; Kessler et al., 2005), and psychosocial problems associated with preexisting mental illness may peak and present additional challenges to youth (Davis & Vander Stoep, 1997; Stoep et al., 2000). This creates a precarious situation wherein youth become increasingly vulnerable to mental illness and its consequences at the same time that they are decreasing the use of services that could prevent or lessen these negative consequences.

Among youth younger than age 18, service use has been associated with demographic factors such as racial/ethnic minority status (Broman, 2012) and the availability of health insurance (Angold et al., 2002; Mojtabai, 2005). Furthermore, youth with anxiety and depression are more likely to continue in treatment, whereas youth with disruptive behavior disorders and externalizing problems are more likely to discontinue (Baruch, Gerber, & Fearon, 1998; Baruch, Vrouva, & Fearon, 2009; de Haan, Boon, de Jong, Hoeve, & Vermeiren, 2013). Important to note, however, treatment decisions for children and adolescents are often made by their parents or guardians, which may explain why so many youth drop out of treatment upon reaching the age of 18. Investigations of treatment discontinuation in the adult population, for example, have found younger age to be a robust predictor of dropout (Edlund et al., 2002; Henzen, Moeglin, Giannakopoulos, & Sentissi, 2016), especially in early phases of treatment (Olfson et al., 2009). Other investigations with a general adult population have found that the risk of dropout is highest among individuals receiving pharmacotherapy only versus those receiving psychotherapy or a combination treatment (Edlund et al., 2002), and among individuals being treated by general physicians rather than mental health specialists (Olfson et al., 2009). Anxiety, substance use, and personality disorders have also been shown to be associated with treatment discontinuation in adults, as well as psychiatric comorbidities (diagnosis of two or more classes of psychiatric disorders; Henzen et al., 2016; Olfson et al., 2009). Similar to findings in youth, treatment dropout in adults has also been associated with ethnic minority status, low income, lack of health insurance, lower educational attainment, and unemployment (Olfson et al., 2009), as well as experiences of stigma (Sirey et al., 2001).

Previous research has documented a clear decline in mental health treatment use during young adulthood (Pottick, Bilder, Stoep, Warner, & Alvarez, 2008; Wang et al., 2005). These studies, however, have typically compared age groups cross-sectionally, rather than longitudinally (Baruch et al., 2009; Pottick et al., 2008). Pottick et al. (2008), for example, investigated differences in outpatient treatment use between participants a transition-aged group (ages 16–25), as well as comparing the transition age group to pretransition (ages 6–15) and posttransition (ages 26–35) participants. Baruch and colleagues (2009) followed participants ages 12–21 as they entered an outpatient treatment protocol and categorized those individuals who discontinued before completing 20 weeks of treatment as “prematurely terminated,” whereas those who completed more than 21 weeks were considered to have “continued.” In both cases, study participants could necessarily only be counted in one category, which limited the investigators’ abilities to assess changes in treatment use within individuals during the transition to adulthood. This introduces the possibility that a factor or factors other than age may have influenced treatment utilization patterns in these samples. Alternate explanations could include cohort effects in attitudes toward treatment, or shifts in cohort rates of mental health challenges (Twenge, 2000, 2011; Twenge & Nolen-Hoeksema, 2002). Studies assessing changes in treatment use longitudinally have focused on children in the foster care system (Courtney, Piliavin, Grogan-Kaylor, & Nesmith, 2001; McMillen & Raghavan, 2009), findings that may not be applicable to the general population of emerging adults.

The current study, therefore, looked at changes in treatment utilization in a longitudinal sample of youth first assessed in childhood and followed into early adulthood. We explored the following hypotheses:

H1: Outpatient treatment use (both pharmacotherapy and psychotherapy) will decline after age 18.

H2: Demographic variables including race and insurance status will influence treatment use both prior to and after age 18.

H3: Greater treatment use prior to the age of 18 will be a robust predictor of greater treatment use after age 18.

H4: Greater number of diagnoses and more severe diagnoses (including affective and substance use disorders) after age 18 will be associated with less decline in treatment use.

H5: Young adult perception of treatment helpfulness will be associated with less decline in treatment use across the transition to adulthood.

Method

Participants

The original sample included 685 youth between the ages of 6 and 12 at their initial screening visit to one of nine general outpatient psychiatric clinics (Findling et al., 2013; Findling et al., 2010; Horwitz et al., 2010). Families visiting these clinics and seeking services unrelated to research protocols were approached by study staff during a mental health visit and invited to participate in a longitudinal, nonintervention follow-up study. Participation in the current research study did not impact their outpatient treatment, and vice versa.

The current sample (n = 137) consists of participants who turned 18 by their 96-month visit (8 years after baseline) and had completed at least one annual study visit after the age of 18. Participants were primarily male (n = 84, 61%) and White (n = 99, 72%), with an average age of 11.5 years (SD = 0.9) at baseline. By design, a majority (n = 115, 84%) of youth were classified as having elevated symptoms of mania (ESM+; scoring ≥ 12 on the parent version of the General Behavior Inventory 10-Item Mania Form; Youngstrom, Frazier, Demeter, Calabrese, & Findling, 2008), with 22 ESM-group matched comparisons. Participants in the current sample completed an average of six (SD = 1.4) study visits prior to the age of 18, and two (SD = 0.75) visits after turning 18. Youth who turned 18 during the course of the study but did not complete assessments after the age of 18 (n = 131) did not differ from youth included in the current analyses with regard to sex, race, ESM status, insurance status, or clinical factors (including specific diagnoses and overall number of diagnoses).

Measures

Demographics

Guardians provided information regarding age, sex, race, and insurance status at the baseline assessment, updating as relevant at later interviews.

Diagnoses

Youth and their guardians participated in a semistructured diagnostic interview (the Schedule for Affective Disorders and Schizophrenia for School-Age Children Present and Lifetime Episode [K-SADS-PL; Kaufman et al., 1997] with additional mood symptoms derived from the Washington University in St. Louis K-SADS [Geller et al., 2001]) to diagnose mood and comorbid disorders. Mood disorders and symptoms were assessed every 6 months, whereas other disorders (including anxiety, disruptive behavior, eating, psychotic, and substance use disorders) were assessed every 12 months. For the purposes of the current study, diagnoses were collapsed across assessments and designated as occurring before or after turning 18, or both.

Treatment utilization

Prior to age 18, parents or guardians of enrolled youth completed the parent version of the Service Assessment for Children and Adolescents (Hoagwood et al., 2000; Horwitz et al., 2001; Stiffman et al., 2000), which measures a child’s interaction with various mental health services including inpatient, outpatient, and school based. Parents or guardians also reported on their perceptions of how helpful treatment services were for their children, and any barriers to initiating or continuing mental health treatment. Once participants turned 18, they completed the self-report version of the Service Assessment for Children and Adolescents.

Treatment utilization was defined as the percentage of study visits at which participants reported engaging in outpatient mental health services, including psychotherapeutic or pharmacological interventions; study-related clinic visits were not included in this calculation. School-based interventions and inpatient services were also not included in this calculation, as these services are often recommended and/or mandated by individuals outside of the child’s family. Youth were coded as having used outpatient mental health services at a given study visit or not (yes/no), regardless of the number of outpatient visits or professionals seen. The number of study visits at which treatment utilization was reported was then divided by the total number of study visits attended to calculate a percentage of treatment utilization. Percentage of treatment utilization was calculated separately for all visits prior to age 18 and visits including and after age 18. Post-18 visits were those at which the participant was 18 years or older on the day of the study visit.

For the current study, information on perceived treatment helpfulness was collected from parents at each annual assessment prior to their child’s 18th birthday; these measures of helpfulness were then averaged over assessments to create a “helpfulness” composite. Young adults’ reports of treatment benefit were similarly collected and averaged over assessments completed after they turned 18.

Psychosocial functioning

Young adults completed the Adult Self-Report Inventory (ASRI-4; Gadow, Sprafkin, & Weiss, 2004) at annual assessments following their 18th birthday. The ASRI-4 includes questions about behavioral symptoms of many psychiatric disorders and asks the participant to rate the extent to which these symptoms have interfered with their functioning. For the current study, functional impairment ratings were collapsed across diagnostic categories to produce both a maximum and a mean dysfunction score for each time point; time point scores were then averaged for an overall dysfunction score.

Procedure

Procedures for recruiting the sample and enrolling them in comprehensive baseline and ongoing assessments have been described previously (Findling et al., 2013; Findling et al., 2010; Horwitz et al., 2010). The university Institutional Review Boards at all study research sites reviewed and approved all procedures. Written informed consent and assent were obtained from all youth and their guardians prior to any study procedures.

Missing data

Notably, data about perception of treatment helpfulness were not available for all individuals after age 18 (n = 54), as some individuals did not utilize treatment after age 18 and therefore were not asked about its benefit (whereas all individuals utilized some treatment prior to age 18 due to the recruitment strategies of the original study). Similarly, youth who denied any difficulty with psychiatric symptoms on the ASRI-4 did not report functional impairment or symptom-related dysfunction (n = 55).

Statistical analyses

Statistical analyses used SPSS version 22; the PROCESS macro (Hayes, 2018) tested for moderation hypotheses. Data were screened prior to analysis and found to meet all assumptions of normality (Curran, West, & Finch, 1996). Significance of the difference in treatment utilization prior to and after turning 18 was measured by a paired t test, whereas independent t tests and bivariate correlations assessed the relationships between percentage of treatment utilization and demographic factors (sex, race, ESM status, and insurance status) as well as clinical factors (youth diagnoses, parental stress, perceptions of treatment helpfulness, and levels of dysfunction). Finally, simultaneous linear regression determined variables that influenced change in treatment utilization during the transition to adulthood. PROCESS version 3 (Hayes, 2018) was used to consider insurance status as a potential moderating variable in regression analyses. Missing data were handled with listwise deletion.

Results

Demographic and clinical characteristics both up to and after age 18 are reported in Table 1.

Table 1.

Youth demographic and clinical characteristics.

Variable N/M %/SD
Age at Baseline (Years) 11.50 0.95
Sex (% Male) 84 61
Racea
 White 99 73
 Black 44 32
 Asian 2 2
 Native American 7 5
 Native Hawaiian or Pacific Islander 2 2
 ESM Status (% ESM+) 115 84
 Percentage Treatment Use Through Age 18 74.09 28.02
 Percentage Treatment Use After Age 18 50.73 47.52
Psychopathology Through Age 18
 Depressive Disorders 52 38
 Bipolar Disorders 46 34
 Anxiety Disorders 60 44
 Attention-Deficit Hyperactivity Disorders 97 71
 Disruptive Behavior Disorders 67 49
 Substance Use Disorders 13 10
Psychopathology After Age 18
 Depressive Disorders 25 18
 Bipolar Disorders 46 34
 Anxiety Disorders 37 27
 Attention-Deficit Hyperactivity Disorders 59 43
 Disruptive Behavior Disorders 19 14
 Substance Use Disorders 29 21
Insurance Status Through Age 18
 Private Insurance or Private Pay 66 48
 Medicaid 71 52
Insurance Status After Age 18
 Private Insurance 65 50
 Medicaid or Self Pay 65 50
 Parent Perception of Treatment Helpfulness Through Age 18 1.33 0.53
 Emerging Adult Perception of Treatment Helpfulness After Age 18 1.35 0.59
 Emerging Adult Perception of Dysfunction After Age 18 1.22 1.04
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Note. ESM = elevated symptoms of mania.

a

The N/% for race is greater than 100 due to participants selecting more than one racial category

Treatment utilization before and after age 18

Participants endorsed utilizing outpatient services at an average of 4.37 visits (SD = 1.98), or approximately 74% of their study interview visits before age 18. After age 18, outpatient treatment utilization was endorsed at 0.89 visits (SD = 0.92), or 51% of study visits. A paired samples t test indicated that this decline in treatment utilization, as hypothesized, was statistically significant, t(136) = 6.59, p < .001, d = .60.

Predictors of treatment utilization

Use until age 18

Next, we examined variables that were hypothesized to influence treatment utilization until age 18 (Table 2). The results of independent t tests indicated that non-White race (t = −4.21, p < .001, d = 0.72) was associated with decreased use of outpatient treatments before age of 18, whereas bivariate correlations indicated that parents’ perceptions of increased treatment helpfulness until age 18 (r = .29, p < .001) and greater parental stress at baseline (r = .17, p = .05) were positively associated with treatment use. Child psychopathology prior to the age of 18 did not significantly influence treatment utilization in the same period. Furthermore, simultaneous linear regression models including interactions with insurance status did not yield significant results.

Table 2.

Bivariate correlations and independent t tests measuring associations with treatment utilization.

% Treatment Utilization Prior to Age 18 % Treatment Utilization After Age 18
Age at Baseline r = −.03 r = −.06
Sex t = 1.32 t = 0.57
Race t = −4.21*** t = −1.83†
ESM Status t = −0.32 t = 0.65
Baseline Parental Stress Scale r = .17† r = .08
Pre-18 Insurance t = 1.02 t = 1.03
Post-18 Insurance t = −0.34 t = 0.28
Pre-18 Treatment Helpfulness r = .29** r = .16†
Post-18 Treatment Helpfulness r = .46** r = .39***
Post-18 Dysfunction r = .16 r = .35***
Pre-18 Depression t = −0.55 t = −0.48
Pre-18 Bipolar Disorder t = −0.13 t = −0.06
Pre-18 Anxiety t = −1.59 t = −1.48
Pre-18 Disruptive Behavior Disorder t = 0.44 t = 1.32
Pre-18 Substance Use Disorder t = 1.38 t = 2.04†
Post-18 Depression t = −0.69 t = 0.09
Post-18 Bipolar Disorder t = −0.13 t = −0.06
Post-18 Anxiety t = 0.14 t = −2.01*
Post-18 Disruptive Behavior Disorder t = −0.57 t = 0.94
Post-18 Substance Use Disorder t = 1.55 t = 0.17
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Note. ESM = elevated symptoms of mania.

*

p < .05.

**

p < .01.

***

p < .001.

†

p < .10.

Use after turning 18

Race did not continue to predict treatment utilization after turning 18, but youth psychopathology (specifically, anxiety disorders diagnosed after age 18) was significantly related to increased treatment use (t = −2.01, p < .05, d = 0.35; Table 2). Furthermore, youth perception of treatment helpfulness (r = .39, p < .001) and youth self-report of symptom-related dysfunction (r = .35, p < .001) were also positively associated with treatment use after turning 18. No significant interactions between insurance status and the variables just noted were detected.

Predictors of changes in treatment utilization

Next, variables of interest (including demographic factors, youth psychopathology, youth perception of treatment helpfulness, and symptom-related dysfunction) were explored as variables predicting treatment use after the age of 18, controlling for treatment use prior to age 18 to ascertain the impact of each variable on change in treatment use across time.

When entered as independent variables into simultaneous linear regression models predicting treatment utilization after turning 18, controlling for treatment use prior to age 18, demographic factors (sex, race, insurance status both before and after age 18) were not associated with changes in treatment utilization, nor was psychopathology diagnosed before age 18. Anxiety diagnosed after age 18, however, was positively associated with treatment utilization after age 18 after controlling for pre-18 utilization (β = .22, r2 change = .03, p < .01; Table 3), and disruptive behavior disorders were significantly associated with a decrease in treatment use (β = −.17, r2 change = .02, p < .05). Participants’ report of symptom-related dysfunction was also positively associated post-18 treatment utilization when controlling for pre-18 treatment use (β = .30, r2 change = .05, p < .05), and participants’ perception of treatment helpfulness after age 18 was associated at a trend level (β = .25, r2 change = .04, p = .06; Table 4).

Table 3.

Simultaneous linear regression model predicting change in outpatient treatment utilization from diagnoses after age 18.

Variable   β B SE
Post-18 Depressive Disorder −.13 −15.59 10.31
Post-18 Bipolar Disorder −.01 −.94 7.87
Post-18 Anxiety Disorder   .22** 23.01 8.31
Post-18 Disruptive Behavior Disorder −.17* −22.85 11.47
Post-18 Substance Use Disorder   .14 15.79 9.81
Percentage Treatment Utilization Prior to Age 18   .53*** .90 .13
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*

p < .05.

**

p < .01.

***

p < .001.

Table 4.

Simultaneous linear regression model predicting change in outpatient treatment utilization from emerging adult report of treatment helpfulness and symptom-related dysfunction.

Variable β B SE
Post-18 Treatment Helpfulness .25† 14.44 7.57
Post-18 Dysfunction .30* 9.20 3.79
Percentage Treatment Utilization Prior to Age 18 .26†   .38   .19
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†

p < .10.

*

p < .05.

Discussion

The current study investigated patterns of outpatient treatment utilization in a high-risk clinical sample, focusing on participants who turned 18 during the course of a 96-month follow-up period. We explored several hypotheses regarding treatment use before and after age 18, as well as predictors of change in treatment utilization.

As expected, percentage of outpatient treatment utilization declined as participants in this sample turned 18, a finding consistent with previous research in this area. Through age 18, demographic and family factors (such as race, parental stress, and parental perceptions of treatment helpfulness) were the most influential in predicting treatment use. With regard to demographic factors, previous research has demonstrated that non-White families engage in outpatient treatment less frequently (Broman, 2012), possibly due to limited financial resources or inadequate access to care (Mojtabai, 2005; Sareen et al., 2007) or perceived self- and family-stigma (Clement et al., 2015; Franz et al., 2010; Rehman & Owen, 2013). Although we do not have information regarding stigma surrounding mental health treatment, non-White families in our sample were significantly more likely to report being on Medicaid than White families, suggesting limited financial resources. Following age 18, however, participant level of dysfunction was the best predictor of treatment utilization, as participants who experienced higher levels of distress reported greater utilization of outpatient treatment. Perceptions of treatment usefulness also provided helpful information about treatment utilization, albeit to a smaller effect.

Treatment use before age 18 was a robust predictor of treatment use after age 18; analyses investigating measures of change in treatment, therefore, necessarily included this variable. Even when considering previous treatment exposure, however, several factors influenced changes in treatment use during emerging adulthood. Demographic factors such as race, sex, and insurance status (both prior to and after age 18) did not predict changes in treatment use, nor did psychopathology prior to the age of 18. Anxiety diagnosed after age 18, however, was positively associated treatment utilization, as individuals with anxiety were less likely to discontinue treatment. This may be due to the fact that treatments for anxiety typically have a higher rate of initial success than treatments for mood disorders (Westen & Morrison, 2001), leading individuals to be more reluctant to discontinue such treatment because they perceive it as helpful. In addition, the median age of onset for anxiety disorders is younger than mood disorders (age 11 vs. age 30; Kessler et al., 2005), suggesting that many individuals with anxiety disorders may have presented for targeted outpatient treatment earlier than other groups. Finally, the delay between recognition of a problem and treatment-seeking tends to be shorter for individuals with anxiety disorders versus mood disorders (Thompson, Issakidis, & Hunt, 2008), so newly diagnosed individuals in this sample may have been more likely to reinitiate or continue existing treatment if they had a new diagnosis of anxiety. Motivation for treatment is higher for people with anxiety disorders than with hypomania, substance misuse, attention problems, or disruptive behaviors, which often are noticed first by others (Freeman, Youngstrom, Freeman, Youngstrom, & Findling, 2011) and may be more distressing to them (Carlson & Youngstrom, 2011). Indeed, in the current analyses, contrary to individuals with anxiety disorders, those participants with disruptive behavior disorder diagnoses were significantly more likely to discontinue treatment after age 18.

Contrary to our expectations, greater number of diagnoses and more severe diagnoses (including affective disorders or substance dependence) after age 18 were not associated with any significant changes in treatment use. This may be due to specific characteristics of these diagnoses, however. For example, youth with substance use disorders may be reluctant to engage in or continue treatment after they are no longer bound by their parents’ rules and may not perceive their substance use as problematic. More important were participant perceptions of treatment usefulness and subjective levels of dysfunction: Participants who perceived their treatment as more helpful, or perceived themselves as experiencing higher levels distress, were significantly less likely to discontinue treatment. This pattern of findings suggests that transdiagnostic factors (such as level of distress), as well as diagnoses, should be considered when predicting who will remain in treatment.

As with all data, these have limitations. The original sample was recruited from families whose children were visiting mental health outpatient clinics in four areas in the Midwest and enriched for children with elevated symptoms of mania. Therefore, results may not generalize to those outside that geographical region or those without manic symptoms. The current analyses relied on parent- and youth-report of treatment use over the reporting period, but adherence with said treatment (e.g., medication use, therapy attendance) was not measured. It is possible that although more individuals reported treatment use prior to age 18, those over 18 were more engaged in their treatment. We also did not distinguish between different types of outpatient mental health services (group vs. individual therapy, medication management, etc.), thus limiting our understanding of the factors related to use of specific treatment modalities. Finally, residential status was not considered in our over-18 sample, so we do not know how living with one’s family versus living independently impacted treatment use in emerging adulthood. The sample, however, also has considerable strengths. It is well characterized diagnostically; diverse; and, most important, longitudinal, allowing a rare assessment of within-person changes in utilization over time.

Recommendations for clinicians

Results of the current study suggest points for intervention in efforts to increase mental health treatment utilization. For youth under the age of 18, targeting socioeconomically disadvantaged and racially diverse communities may be the most effective strategy, especially with ongoing public health campaigns aimed at reducing stigma around mental health treatment and increasing awareness ofthe symptoms of mental illness. More broadly, increasing insurance coverage for mental health services would enable all youth in need to obtain necessary psychiatric services. As treatment use prior to age 18 was a robust predictor of treatment use prior to age 18, engaging children and adolescents in treatment as soon as necessary may be the best way of keeping needy individuals connected to mental health services throughout the life span. Emerging adults, however, may be additionally influenced by efforts aimed at increasing their experiences of efficacy in, and benefit from, outpatient mental health treatment. The fact that subjective factors were more associated with continued treatment use after age 18 than demographic factors suggests that the emerging adult’s perception of their own treatment and functioning are crucial variables to consider in efforts aimed at keeping them engaged with treatment. Clinicians working with this population should take care to monitor their clients’ levels of satisfaction with the treatment approach, as emerging adults may be more likely to abruptly discontinue treatment without attempting to resolve dissatisfaction with the treatment first. Future research should consider interventions aimed at treatment-engaged youth in late adolescence, with the goal of keeping emerging adults in need in treatment through the transition to adulthood.

Funding

This study was funded by a National Institute of Mental Health grant (R01 MH073801).

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