Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2025 Nov 1.
Published in final edited form as: J Consult Clin Psychol. 2024 Nov;92(11):769–778. doi: 10.1037/ccp0000919

Examining Racial and Ethnic Differences in Youth Psychotherapy Treatment Engagement and Outcomes

Kara Johansen 1, Indrani Saran 1, Evelyn Cho 2, John R Weisz 2, Maggi A Price 1,2
PMCID: PMC12060078  NIHMSID: NIHMS2056928  PMID: 39621369

Abstract

Objective:

Research has identified racial/ethnic disparities in mental health treatment engagement and there have been recent calls to examine effects of mental health treatment engagement on clinical outcomes among youth of Color. This study aimed to examine racial/ethnic differences in (1) behavioral and attitudinal engagement, (2) treatment effectiveness, and (3) the associations between engagement and treatment effectiveness.

Methods:

N=200 youth (ages 7–15; 33% White, 28% Black, 25% Hispanic/Latinx, and 14% Multiracial; 52% male) and their N=200 parents participated in a randomized controlled trial testing the effectiveness of a transdiagnostic psychotherapy for common youth emotional and behavioral problems. Youth and parents reported internalizing and externalizing symptoms and treatment engagement (e.g., behavioral and attitudinal). Multilevel regression models examined variations in youth symptom trajectories by racial/ethnic group.

Results:

While all racial/ethnic groups showed comparable attitudinal engagement scores, Black and Latinx youth attended significantly fewer sessions than White and Multiracial youth (8–9 versus 13). However, youth in all racial/ethnic groups showed significant, and similar, improvements in treatment outcomes.

Conclusions:

Black and Latinx youth attended fewer sessions than White youth, but their clinical outcomes were similar to those of White youth. Future research should examine the meaning and implications of session attendance in relation to outcomes in youth of Color.

Keywords: racial/ethnic disparities, treatment engagement, behavioral engagement, transdiagnostic therapy

Public Health Significance:

This study showed that Black and Latinx youth derive comparable benefits from transdiagnostic treatment despite attending fewer sessions than their White counterparts. The findings emphasize the need for a shift toward personalized and efficient mental health interventions for youth of Color.

Research suggests that racial/ethnic inequities in mental health care for youth may be wide ranging and may include differences in access (Lu et al., 2021; Miranda et al., 2015), diagnosis (Chen et al., 2019; Lu, 2019), engagement (Flicker et al., 2008; Kivlighan et al., 2019) and effectiveness (Huey et al., 2023). These inequities appear to have worsened amidst the COVID-19 pandemic (Friis-Healy et al., 2021; Shim & Starks, 2021), which disproportionately burdened racially/ethnically minoritized youth (i.e., “youth of Color” herein, for brevity), including worsening mental health (Rothman et al., 2020; Smith et al., 2020). Accordingly, there have been calls for increased research on effective mental health treatments for youth of Color (Becker & Chorpita, 2023; Lakind et al., 2022; Office of the Surgeon General, 2021).

Research on psychotherapy effectiveness for youth of Color is mixed. Multiple studies have found racial/ethnic differences in clinical outcomes, with youth of Color experiencing less improvement than White youth (Lang et al., 2021; Pina et al., 2019; Price et al., 2022). However, some meta-analyses suggest that the effectiveness of psychotherapy does not vary by race or ethnicity (Carpenter et al., 2018; Huey et al., 2023; Huey & Polo, 2010; Pina et al., 2019). Some research suggests that these conflicting findings may be attributable in part to differences across studies in youth treatment engagement (Huey et al., 2023; Pina et al., 2019).

Treatment engagement in psychotherapy is a multi-faceted construct capturing how a client participates in and relates to therapy. Measures of engagement have been regarded by some researchers as indicators of the quality of care (Acevedo et al., 2016; Dixon et al., 2016; Staudt, 2007). Treatment engagement can be divided into two categories: behavioral and attitudinal (Lewis et al., 2020; Staudt, 2007). Behavioral engagement measures how a client actively participates in and adheres to treatment, such as session attendance, attrition, and treatment duration (Ewell Foster et al., 2022; Hock et al., 2015; Karver et al., 2005; Staudt, 2007). Attitudinal engagement refers to how a client thinks about treatment (e.g., treatment satisfaction), including their attitudes towards the provider (e.g., therapeutic alliance; Dowell & Nielsen, 2021; Ewell Foster et al., 2022; Staudt, 2007). Greater treatment engagement (both behavioral and attitudinal) has been found to be associated with better mental health outcomes in both adults and youth (de Jong et al., 2021; Duppong Hurley et al., 2015; Irvine et al., 2010; Karver et al., 2019; Meyers et al., 2012).

Psychotherapy research on behavioral engagement suggests that clients of Color are more likely to discontinue treatment prematurely compared to White clients (Becker & Chorpita, 2023; Hack et al., 2020; Marotta et al., 2022; Pinedo, 2019). Clients of Color have also been found to attend fewer sessions than their White counterparts (Kivlighan et al., 2019; Marrast et al., 2016). Regarding attitudinal engagement, research finds that clients of Color (vs. White clients) report weaker therapeutic alliance and satisfaction (Chu et al., 2022; Flicker et al., 2008). Treatment engagement inequities may be attributable to a variety of factors, such as the dearth of therapists of Color (Chu et al., 2022) and provider discrimination (Brener et al., 2010; Miranda et al., 2015).It is possible that racial/ethnic patterns in treatment effectiveness are at least partially attributable to differential associations between engagement and effectiveness across racial/ethnic groups (Huey et al., 2014, 2023; Pina et al., 2019).

Despite these conceptual and empirical links, little is known about whether and how treatment engagement impacts clinical outcomes across racial/ethnic groups. A better understanding of this could inform the development and use of strategies to reduce mental health inequities and optimize care for youth of Color (Jensen et al., 2001). Accordingly, the present study analyzed treatment engagement and effectiveness data from a racially/ethnically diverse sample of youth who received evidence-based transdiagnostic psychotherapy. The goal was to examine racial/ethnic differences in (1) behavioral (i.e., treatment termination and session attendance) and attitudinal (i.e., therapy satisfaction and therapeutic alliance) engagement, (2) treatment effectiveness, as well as (3) the associations between engagement and treatment effectiveness. Based on extant studies, we hypothesized that compared to White youth, youth of Color would (h1) demonstrate lower behavioral and attitudinal engagement (Flicker et al., 2008), and (h2) worse clinical outcomes (i.e., lower treatment effectiveness). Finally, we expected that (h3) race/ethnicity would moderate the association between treatment engagement and treatment outcomes (de Jong et al., 2021; Karver et al., 2019).

Methods

Participants

Participants were N=200 youth (ages 7–15; 54% male) and their N=200 parents (including legal guardians) who participated in a randomized controlled trial (RCT) from 2014 to 2018 implementing an evidence-based, transdiagnostic psychotherapy for common youth emotional and behavioral problems (40% (n=78) depression, 38% (n=75) conduct, 19% (n=38) anxiety, and 3% (n=5) trauma) called Modular Approach to Therapy for Children (MATCH; Chorpita & Weisz, 2009). Participants were recruited among families seeking outpatient youth psychotherapy at four community mental health clinics in Connecticut funded by the state’s Department of Children and Families (see inclusion criteria in the Supplemental Materials). The RCT examined whether MATCH outcomes differed when delivered with low-cost support (e.g., video recordings, handouts) versus low-cost support plus expert consultation. There were no significant outcome differences between the two groups (Chorpita & Weisz, 2009), so the present study combined the groups. See Chorpita & Weisz, 2009 for detailed procedures. There were four broad races/ethnicities in this sample that inform all our analyses examining racial/ethnic differences: White (33%), Black (28%), Hispanic/Latinx (25%), and Multiracial (14%; Table 1). Asian (n=2) and Native American (n=2) participants were excluded from analyses due to small subsample sizes. See Table 1 for parents’ socioeconomic characteristics.

Table 1:

Demographic Characteristics and Pre-treatment Symptoms by Youth Race (N=196)

N (%) or Mean (SD)
White (n=65) Black (n=55) Latinx (n=48) Mixed Race (n=28) F-stat/ χ2 (df)
Child Characteristics
Male sex 36 (55.4%) 31 (56.4%) 25 (52.1%) 14 (50.0%) χ2 (3)=.42
Age 10.89 (2.46) 10.75 (2.44) 10.54 (2.29) 10.79 (2.63) F(3,192)=.19
Parent Characteristics
Income (% of federal poverty threshold)
0–99% 12 (20.7%) 23 (44.2%) 21 (51.2%) 10 (38.5%)
100–199% 19 (32.8%) 19 (36.5%) 15 (36.6%) 11 (42.3%) χ2 (9)=29.7***
200–299% 9 (15.5%) 4 (7.7%) 4 (9.8%) 5 (19.2%)
300%+ 18 (31.0%) 6 (11.5%) 1 (2.4%) 0 (0.0%)
Education
7th-11th grade 2 (3.1%) 3 (5.5%) 14 (29.2%) 5 (17.9%)
HS/GED 22 (33.8%) 23 (41.8%) 18 (37.5%) 10 (35.7%) χ2 (9)=31.6***
Some College 27 (41.5%) 20 (36.4%) 14 (29.2%) 13 (46.4%)
College Degree 14 (21.5%) 9 (16.4%) 2 (4.2%) 0 (0.0%)
Treatment-Related Variables
Protocol
Anxiety 22 (33.8%) 5 (9.1%) 4 (8.3%) 7 (25.0%)
Depression 23 (35.4%) 18 (32.7%) 27 (56.2%) 10 (35.7%) χ2 (9)=26.7**
Trauma 2 (3.1%) 3 (5.5%) 0 (0.0%) 0 (0.0%)
Conduct 18 (27.7%) 29 (52.7%) 17 (35.4%) 11 (39.3%)
CBCL (Baseline)
Internalizing 66.14 (7.70) 61.73 (9.75) 65.12 (9.78) 66.93 (7.44) F(3,192)=3.29*
Externalizing 62.69 (8.95) 65.16 (9.83) 64.23 (9.34) 64.82 (10.48) F(3,192)=.76
Total 65.72 (6.46) 66.05 (7.20) 66.40 (7.56) 67.21 (7.61) F(3,192)=.31
YSR (Baseline)
Internalizing 56.94 (11.85) 55.20 (12.88) 58.52 (10.81) 61.41 (7.12) F(3,190)=1.98
Externalizing 52.43 (10.40) 56.72 (11.16) 54.42 (10.06) 52.33 (10.30) F(3,190)=1.93
Total 56.06 (11.10) 57.87 (12.05) 58.71 (10.31) 59.26 (8.11) F(3,190)=.83
Open in a new tab

Notes: The F-stat is from an ANOVA. Baseine YSR values are missing for 2 youth, and income was missing for 3 youth.

*

P<.05

**

P<.01

***

P<.001

Measures

Assessments were conducted at baseline, post-treatment, and quarterly (i.e., 3, 6, 9, 12, 18 months after baseline). Internalizing and externalizing symptoms were assessed at each time point, and post-treatment assessments also measured attitudinal treatment engagement. See psychometric and missingness details for respective measures in the Supplemental Materials.

Child Race and Ethnicity

Parents reported their child’s race/ethnicity. They were asked to check one of the following “ethnicities”: Caucasian, Black, Latino/Hispanic, Asian, Multiracial or Other. If the respondent checked Multiracial or Other, they were asked to write in additional information. Three participants endorsed “Other,” including 2 Native American youth excluded from analyses, and 1 Puerto Rican and St. Lucian youth who was re-coded as Multiracial.

Clinical Outcomes: Internalizing and Externalizing Symptoms

Internalizing symptoms (e.g., anxiety) and externalizing symptoms (e.g., misconduct) were measured based on parent-report using the Child Behavior Checklist (CBCL; Achenbach et al., 2002) and by youth-report via the Youth Self-Report (YSR; Achenbach et al., 2002).

Treatment Engagement

Behavioral Treatment Engagement

Behavioral treatment engagement was measured in two ways based on previous studies (Ewell Foster et al., 2022; Hock et al., 2015; Staudt, 2007): treatment termination and attendance. Treatment termination was categorized as either routine (i.e., therapy ended following a full course of treatment) or premature (i.e., therapy ended prior to completing the full treatment). Stated reasons for premature termination included scheduling conflicts, the family not returning to the clinic, the family withdrawing from therapy or the study, therapist turnover, or clients needing a higher level of care. The 15 youth who were still in treatment when the study ended were excluded from all analyses assessing termination. Attendance reflected the number of sessions attended rather than percent of sessions attended because MATCH does have a prescribed number of sessions.

Attitudinal Treatment Engagement

Attitudinal treatment engagement included measures of parent- and youth-reported satisfaction and therapeutic alliance based on previous studies (Becker et al., 2014; de Jong et al., 2021; Hock et al., 2015). Parent treatment satisfaction was measured using the total score from the 21-item Youth Services Survey for Families (YSS-F; Riley et al., 2005). Youth treatment satisfaction was measured using the composite score from the three-item Child Satisfaction Survey (CSS; Hawley & Weisz, 2005). Therapeutic alliance was measured using the total scores from an adapted 9-item version of the Therapeutic Alliance Scales for Children (TASC; Shirk & Saiz, 1992) and a parallel parent-report form (Hawley & Weisz, 2005).

Analyses

Demographics and Pretreatment Symptom Severity

Differences in demographic characteristics and pre-treatment symptom severity by youth race/ethnicity were assessed using Chi-square tests (for categorical variables) and ANOVA (for continuous variables).

Treatment Effectiveness

Treatment effectiveness (assessed quarterly by CBCL/YSR) was examined using multilevel modeling with repeated observations (level 1) nested within each individual (level 2), and each individual nested within therapist (level 3). Consistent with prior MATCH studies (Hollinsaid et al., 2020; Chorpita & Weisz, 2009, 2020), time was modeled as the number of days since baseline, with days transformed into log-days (natural logarithm of days since baseline + 1) for analyses. The model included an interaction between time and youth race/ethnicity to assess differences in trajectories across racial/ethnic groups.

All models controlled for clinic, MATCH protocol, and primary parent education. Parent education and MATCH protocol were controlled for because they were associated with youth race/ethnicity and with some of the outcomes. Moreover, treatment effectiveness generally differs based on treatment target (Weisz et al., 2017).

Two questions were of interest in these models: (1) do youth in each racial/ethnic group improve over time (i.e., is each group’s slope negative, and significantly so?) and (2) do youth in one or more racial/ethnic groups improve faster than those in other racial/ethnic groups (i.e., are the groups’ slopes significantly different)? Effect sizes were calculated using the difference in slopes divided by the square root of the overall time slope variance. Youth trajectory models were estimated using mixed effects models with restricted maximum likelihood (REML). All analyses were conducted in STATA 15 (StataCorp, 2017). Supplementary analyses were conducted to examine differences in the proportion of youth in each racial/ethnic group who had symptoms above the clinical threshold (YSR/CBCL internalizing, externalizing or total T-scores >= 60) at post-treatment.

Post-Treatment Differences in Behavioral and Attitudinal Engagement

Differences in measures of behavioral and attitudinal engagement were assessed across race/ethnicity at post-treatment. Bivariate associations between racial/ethnic groups and post-treatment engagement were tested using ANOVA and chi-square.

Behavioral and Attitudinal Engagement as Moderators of Treatment Effectiveness

The relationship between behavioral and attitudinal engagement indicators on treatment effectiveness was examined in both the full sample and separately by youth race/ethnicity. Like the main models, these were estimated using mixed effects models with REML, with repeated observations (level 1), nested within individuals (level 2), nested within therapists (level 3).

The association between number of sessions attended and pre-post symptom change was assessed both in the full sample and by youth race/ethnicity, the latter using an interaction term. This model only included random effects for the therapist. The association between premature termination and symptom change was assessed by including an interaction between time and premature termination (for the full sample) and an interaction between time, premature termination, and youth race/ethnicity (to test for differences by youth race/ethnicity).

Lastly, the potential moderating effect of attitudinal engagement on symptom change in the full sample was assessed via regressions with an interaction between time and satisfaction, as well as interactions between time and therapeutic alliance. Similar regressions were conducted in each of the youth race/ethnicity subsamples. See Supplemental Materials for information on multiple comparisons and missing data.

Transparency, openness, and ethical compliance

Requests for data and analytic code can be sent to the last author. The trial was pre-registered but this secondary analysis was not. The Harvard IRB approved the trial and the Boston College IRB approved this secondary analysis. This manuscript complies with Journal Article Reporting Standards.

Results

Racial Differences in Baseline Characteristics

Significant racial/ethnic differences in parent education and income were found, with more education and higher income among White parents (Table 1). Two significant differences in assigned protocol were identified: compared to other racial/ethnic groups, Latinx youth were most likely to be assigned to the depression protocol, and Black youth most likely to be assigned to the conduct protocol. Internalizing and externalizing symptoms were similar across all racial/ethnic groups at baseline, except for parent-reported internalizing symptoms which were lower for Black youth compared to the other racial/ethnic groups.

Racial/ethnic Differences in Behavioral and Attitudinal Engagement

Significant racial/ethnic differences in treatment session attendance were identified (F(3, 192) =5.00, p=.002). Black and Latinx youth attended significantly fewer sessions (Ms=8 and 9, respectively) compared to White (M=13) and Multiracial youth (M=13). No statistically significant differences in termination basis (routine vs. premature) by race/ethnicity were found, though White youth had slightly lower rates of premature termination. Among premature terminaters, White youth attended 4 additional sessions on average compared to other racial/ethnic groups. Among routine terminators, no group differences in session attendance were identified (Table S1). All racial/ethnic groups evidenced comparable attitudinal engagement scores (Table 2).

Table 2:

Behavioral and Attitudinal Engagement Outcomes and Symptoms at Post by Youth Race (N=196)

N (%) or Mean (SD)
White (n=65) Black (n=55) Latinx (n=48) Mixed Race (n=28) F-stat (df)
Attitudinal Engagement
Parent Satisfaction 84.13 (2.90) 83.23 (3.03) 87.42 (2.93) 87.88 (4.50) F(3,84)=.5
Parent Therapeutic Alliance 31.57 (0.82) 32.14 (0.72) 32.94 (0.96) 32.94 (1.49) F(3,60)=.5
Child Satisfaction 6.41 (0.41) 6.36 (0.46) 7.24 (0.51) 7.50 (1.01) F(3,55)=.84
Child Therapeutic Alliance 29.94 (1.05) 28.98 (1.16) 31.13 (1.46) 31.90 (1.79) F(3,59)=.89
Behavioral Engagement
Number of Sessions Attended 13.26 (9.67) 7.93 (6.19) 8.81 (8.31) 13.11 (11.94) F(3,192)=5**
Premature Termination 34 (59.6%) 36 (67.9%) 32 (66.7%) 15 (65.2%) F(3,177)=.81
Post-treatment symptoms
CBCL symptoms above clinical threshold
Internalizing 29.25 (45%) 16.5 (30%) 20.64 (43%) 10.92 (39%) F(3,745)=.83
Externalizing 31.2 (48%) 30.25 (55%) 20.16 (42%) 13.16 (47%) F(3,816)=.48
Total 35.1 (54%) 25.3 (46%) 22.56 (47%) 12.88 (46%) F(3, 456)=.22
YSR symptoms above clinical threshold
Internalizing 13 (20%) 7.15 (13%) 10.56 (22%) 5.88 (21%) F(3,338)=.38
Externalizing 7.15 (11%) 9.35 (17%) 6.24 (13%) 8.4 (30%) F(3,779)=1.54
Total 9.1 (14%) 8.25 (15%) 11.04 (23%) 6.44 (23%) F(3,383)=.59
Open in a new tab

Notes: The F-stat is from a linear/logistic regression (as appropriate) with no controls. Premature Termination excludes the 15 youth who were forced to stop treatment due to the end of the study. Missing values for attitudinal engagement/symptoms at post were imputed using multiple imputation.

*

P<.05

**

P<.01

***

P<.001

Racial/ethnic Differences in Treatment Outcomes

Youth in all racial/ethnic groups demonstrated significant improvements across all youth- and parent-reported outcomes (internalizing, externalizing, and total problems; Table S2). The proportion of youth reporting symptoms at levels above the clinical threshold were similar across all races/ethnicities at post-treatment (Table 2). However, significantly steeper declines in youth-reported externalizing problems were found for White (vs. Multiracial) youth (difference=−.72, p=.02). Similarly, Black youth had significant steeper declines in youth-reported externalizing problems relative to Latinx (difference=−.57, p=.03) and Multiracial youth (difference=−.79, p=.01). White youth’s symptoms declined less steeply compared to Latinx youth in parent-reported externalizing problems (difference=.49, p=.02). No other differences in treatment outcomes across racial/ethnic groups were found (Table 3).

Table 3:

Estimated Differences in Treatment Effects by Youth Race

CBCL- Parent Report
Internalizing Externalizing Total
Estimate p-value ES 95% CI Estimate p-value ES 95% CI Estimate p-value ES 95% CI
White vs Black −0.03 0.88 −0.03 [−.49, .42] 0.19 0.33 0.20 [−.2, .58] 0.20 0.31 0.17 [−.19, .60]
White vs Latino/Hispanic 0.21 0.40 0.18 [−.28, .69] 0.49 0.02 0.50 [.08, .91] 0.53 0.01 0.44 [.11, .95]
White vs Mixed Race 0.17 0.58 0.14 [−.42, .75] 0.19 0.46 0.20 [−.31, .69] 0.06 0.83 0.05 [−.45, .57]
Black vs Latino/Hispanic 0.24 0.34 0.20 [−.26, .74] 0.30 0.16 0.31 [−.12, .72] 0.33 0.13 0.27 [−.1, .76]
Black vs Mixed Race 0.20 0.51 0.17 [−.4, .80] −0.01 0.98 −0.01 [−.52, .51] −0.15 0.58 −0.12 [−.67, .37]
Latino/Hispanic vs Mixed Race −0.04 0.90 −0.03 [−.66, .58] −0.31 0.26 −0.32 [−.83, .22] −0.48 0.08 −0.40 [−1.01, .06]
YSR- Youth Self-Report
Internalizing Externalizing Total
Estimate p-value ES 95% CI Estimate p-value ES 95% CI Estimate p-value ES 95% CI
White vs Black −0.17 0.56 −0.15 [−.73, .40] 0.07 0.77 0.07 [−.41, .55] −0.02 0.94 −0.02 [−.54, .5]
White vs Latino/Hispanic −0.12 0.70 −0.10 [−.7, .47] −0.49 0.05 −0.50 [−.99, .01] −0.25 0.38 −0.22 [−.79, .3]
White vs Mixed Race 0.10 0.80 0.09 [−.64, .83] −0.72 0.02 −0.73 [−1.35, -.09] −0.06 0.87 −0.05 [−.74, .62]
Black vs Latino/Hispanic 0.05 0.87 0.04 [−.55, .66] −0.57 0.03 −0.58 [−1.08, -.05] −0.23 0.43 −0.20 [−.79, .33]
Black vs Mixed Race 0.26 0.49 0.22 [−.48, 1.01] −0.79 0.01 −0.81 [−1.43, -.16] −0.04 0.91 −0.03 [−.73, .65]
Latino/Hispanic vs Mixed Race 0.21 0.59 0.18 [−.55, .98] −0.23 0.50 −0.23 [−.88, .43] 0.19 0.61 0.16 [−.53, .9]
Open in a new tab

Note: Results are from a mixed-effects regression with random effects for therapist and client and controls for agency, parent education, and protocol. Estimates are differences in coefficients on log days since baseline. Effect sizes are calculated using the difference in slopes divided by the square root of the overall time slope variance.

Engagement and Treatment Outcomes

Full Sample

In the full sample, more sessions attended were significantly associated with greater symptom reduction in youth-reported internalizing problems (β=−.26, p=.02; Table S3) and not in any other outcomes. While those who had routine terminations had steeper declines for all outcomes, statistically significant differences were only present in the full sample on parent-reported externalizing (difference=−.37, p=.03) and total problems (difference=−.38, p=.03; Table S5). There were no statistically significant associations (at p=.0065) between attitudinal engagement measures and treatment outcomes in the full sample (Table S6).

Racial/Ethnic Differences in Behavioral Engagement and Treatment Outcomes

Analyses of separate racial/ethnic groups indicated that the number of sessions attended was not significantly associated with pre-post differences in any of the outcomes (Table S3). Analyses examining the potential influence of termination basis on outcomes indicated that all youth, regardless of termination basis (i.e., routine vs. premature), demonstrated significant improvements in all outcomes (Table S5). Youth who terminated routinely (vs. prematurely) generally showed steeper declines, though these differences were statistically significant only for parent-reported internalizing symptoms in Multiracial youth (difference=−1.24, p=.03; Table S5).

Racial/Ethnic Differences in Attitudinal Engagement and Treatment Outcomes

There were no statistically significant associations (at p=.0016) between attitudinal engagement measures and outcomes in any of the race/ethnicity subsamples (Table S7a–b).

Discussion

In response to increasing demand for research on race-related treatment inequities (Becker & Chorpita, 2023; Lakind et al., 2022; Office of the Surgeon General, 2021), this study explored racial/ethnic differences in treatment engagement and clinical outcomes in a racially/ethnically diverse sample of youth who received transdiagnostic psychotherapy. Our hypotheses were partially supported. Specifically, Black and Latinx youth demonstrated lower treatment engagement in the form of number of sessions attended, relative to White youth (partially supporting h1). Our hypotheses that there would be racial/ethnic differences in clinical outcomes favoring White youth (h2) and that race would moderate the association between treatment engagement and treatment outcomes (h3) were largely unsupported. Instead, results suggested that despite attending only 8–9 sessions on average, Black and Latinx youth (respectively) benefited from treatment just as much as White and Multiracial youth, who attended more sessions (mean of 13 sessions for both groups). These findings have several research and clinical implications.

Previous studies find that, compared to White youth, youth of Color attend fewer sessions (Kivlighan et al., 2019; Marrast et al., 2016), which is consistent with our findings for Black and Latinx youth. Previous studies also suggest that youth of Color are less likely to complete treatment (Becker & Chorpita, 2023; Hack et al., 2020; Marotta et al., 2022; Pinedo, 2019), and report lower attitudinal engagement (Chu et al., 2022; Flicker et al., 2008) compared to White youth. In contrast, we did not find significant racial/ethnic group differences in attitudinal engagement or termination basis.

Importantly, youth in all racial/ethnic groups demonstrated significant improvements in treatment outcomes. Though significant differences in symptom-reduction trajectories were identified across some racial/ethnic groups (i.e., some youth improved more quickly and robustly than others), they did not demonstrate a reliable pattern. Additionally, there were a few significant differences in treatment outcomes between youth of Color subgroups. White youth did exhibit significantly better treatment outcomes compared to mixed-race youth (Table 3), suggesting the potential for additional benefits experienced by White youth relative to this group. Taken together, these findings mirror the widespread inconsistencies in extant literature, with some studies failing to find differences in clinical outcomes (Kaminski & Claussen, 2017; McCart & Sheidow, 2016), others finding robust differences (Cave et al., 2020, p. 202; Mpofu, 2022; Priest et al., 2013), and others finding mixed results (Huey et al., 2014, 2023; Pina et al., 2019). There was no evidence that the association between engagement and clinical outcomes varied by racial/ethnic groups.

There are several possible explanations for why Black and Latinx youth may have experienced similar clinical benefits to White youth despite attending fewer sessions. The flexible nature of the MATCH treatment, which does not prescribe a specific duration or session sequence may have been particularly beneficial for Black and Latinx youth. The widespread benefits of MATCH found in this study are consistent with other studies of MATCH conducted with diverse youths and families (Chorpita et al., 2013; Chorpita & Weisz, 2009). It is possible that youth of Color benefit from treatment approaches that are especially scalable and efficient (e.g., requiring one or a few sessions; Alvarez, 2022; Castro-Ramirez et al., 2021; Okonofua et al., 2022). Accordingly, efforts to increase youth of Color’s access to evidence-based care may aid in achieving equitable mental health outcomes.

A growing research base highlights the resilience (i.e., protective factors enabling people to thrive despite adversity) of communities of Color (Boyd et al., 2022; Chesmore et al., 2016; Neblett & Neal, 2022). For example, religiosity, extended family support, and high coping strategy utilization have been identified as key resilience-promoting factors (Chesmore et al., 2016; S. C. T. Jones & Neblett, 2017; Kawakami et al., 2020). Indeed, studies find that resilience is strongly related to mental health among people of Color (Catabay et al., 2019; Simmons et al., 2023). Scholars suggest that resilience factors may buffer the impact of stress on mental health for people of Color (e.g., racial stress; S. C. T. Jones & Neblett, 2017; Neblett & Neal, 2022), which is partially supported by recent studies with adults of Color (e.g., Catabay et al., 2019; Kawakami et al., 2020). Efficient mental health treatment may expand upon youth of Color’s existing resilience factors, enabling them to benefit from relatively short treatment durations. Multiracial youth, who experienced both similar treatment engagement and outcomes to White youth, may have also benefited from their own specific resilience factors (e.g., racial identity flexibility; Gaither, 2015; Shih et al., 2019).

Research Implications

These results highlight the importance of understanding how various racial/ethnic groups respond to treatment. Historically, clinical research trials have primarily involved White participants, with recent efforts to include more diverse samples (NIH, 2019; NIMH, 2023). Accordingly, secondary analyses of clinical trial data of the relatively few trials of racially diverse samples are needed to further explicate potential differences (or lack thereof), and to clarify the contexts in and treatments for which racial/ethnic differences do emerge. Increased funding is also needed to support research focused on therapy with youth of Color (NIMH, 2021; Santoro, 2023), including qualitative research of treatment barriers to understand youth of Color’s experience in treatment.

Despite decades of research demonstrating worse mental health outcomes for people of Color exposed to structural racism, little attention has been given to the location of clinical treatment. Structural racism (i.e., the systemic and institutional assertion of racist policies and practices that reinforce racial inequality by creating differential access to resources and opportunities) varies by location (e.g., state, city, neighborhood; Dean & Thorpe, 2022; Jones, 2000; Peguero & Williams, 2013). Racial/ethnic inequities in treatment engagement and outcomes may be influenced by contextual factors like structural racism, consistent with behavioral health intervention studies (Pearce et al., 2012; Price et al., 2022; Reid et al., 2014). In fact, a recent meta-analysis found that psychotherapy is less effective for Black youth living in states with high (vs. low) levels of state-level attitudinal racism (Price et al., 2022). The current study, conducted in Connecticut with relatively low levels of structural racism toward Black and Latinx people, may explain the lack of racial/ethnic differences in outcomes (Hatzenbuehler et al., 2022; Price et al., 2022; Reid et al., 2014). Accordingly, it is possible that the lack of racial/ethnic differences in outcomes is attributable to the context of the study being conducted in a state with relatively low levels of structural racism. Structural interventions (i.e., an intervention aimed at reducing stigma in an environment such as schools or communities) may be needed to achieve the same clinical outcomes in higher-racism states and communities (Chaudoir et al., 2017; Cook et al., 2014; Price & Hollinsaid, 2022).

Clinical Implications

Generally, our findings indicated that youth of Color engaged in and benefited from a modular transdiagnostic psychotherapy. Additionally, these findings suggest that MATCH may be a promising approach for youth of Color, even when treatment is relatively brief. Moving forward, further research on how MATCH is personalized for youth of Color, and whether and how this personalization is linked to clinical outcomes may help advance the development and adaptation of effective mental health treatments for communities of Color.

In this study, significant racial/ethnic differences in parent education and income were found, with more education and higher income among White parents (Table 1). Therefore, the families of Color in this study may be facing resource limitations and barriers to treatment, such as insurance status or parental job pressures (Fante-Coleman & Jackson-Best, 2020; Ofonedu et al., 2017) and subsequently benefitting from short-term treatment duration. It may be beneficial to develop other short-term, scalable (e.g., single-session treatments; Loades & Schleider, 2023; Schleider et al., 2022) treatments for families with resource limitations. Youth with resource limitations may also benefit from lower cost of care (e.g., sliding scales) and increased telehealth options (Bailey et al., 2021; Castro-Ramirez et al., 2021; Lichstein et al., 2013).

Strengths and Limitations

Our study had noteworthy strengths and responded to numerous calls for research on race and ethnicity in relation to treatment process and outcome (Becker & Chorpita, 2023; Lakind et al., 2022; Office of the Surgeon General, 2021). Strengths included examining a racially/ethnically diverse sample of youth, assessing their clinical outcomes at multiple time points, and including measures of both behavioral and attitudinal treatment engagement. The study also had several limitations that should be considered alongside these strengths. First, this project was a secondary analysis; the original study (Chorpita & Weisz, 2009) focused on the effectiveness of different therapist supports for clinicians implementing a transdiagnostic psychotherapy and did not collect data on factors that may have contributed to racial/ethnic treatment differences (e.g., interpersonal discrimination, neighborhood-level structural racism). Second, measures of attitudinal engagement were missing for a large proportion of participants. Although these were imputed using multiple imputation, it is possible that this missingness was associated with unobservable factors that may have biased the results. Third, while this sample of youth was diverse, it was relatively small, which may have resulted in low power to detect an effect. However, we cannot confirm this, as post-hoc power analyses can be highly misleading (Dziak et al., 2020). Instead, we calculated confidence intervals for all analyses, many of which were quite wide, suggesting uncertainty in our estimates (See Table S3, S5, and S7a–b). Coupled with generally small effect sizes, our results point to the importance of replicating this study with larger samples, ideally with prospective power analyses. Generalizability was further limited by the fact that this study was conducted in a low-racism state, and the findings therefore may not be generalizable to other states with different levels of racism (Price et al., 2022). Fourth, Asian (n=2) and Native American (n=2) participants were excluded from the study due to their small subsample size. Future research should examine treatment engagement and outcomes in Asian and Native American youth. Finally, none of the authors identify as Black or Latinx, which were two primary populations of interest in this paper, and only one identifies as Multiracial (three identify as partially or fully Asian and two as fully White). These limitations influence the depth of our understanding of racial/ethnic treatment inequities, and may potentially bias the results.

Summary and Conclusions

This study was a secondary analysis of RCT data from a trial of a modular transdiagnostic treatment with racially diverse youth. Results indicated that, despite attending relatively few treatment sessions, Black and Latinx youth experienced similar clinical outcomes compared to White youth. Results underscore the need for research and practice focused on enhancing access to effective interventions for youth of Color.

Supplementary Material

supplement

Acknowledgments

This paper is a secondary analysis of data collected in a randomized control trial (RCT; ClinicalTrials ID NCT03153904) funded by the MacArthur Foundation, the Norlien Foundation, and the National Institute of Mental Health.

Appendix 1: Data Transparency (Masked)

Findings from the data collection have been reported in the five previous manuscripts listed above. Manuscript 1 (published) focuses treatment outcomes for youth varying irritability and dysregulation. Manuscript 2 (published) focuses on treatment outcomes for youth of varying gender identities. Manuscript 3 (under review) focuses on outcomes for youth with vagal tone and vagal regulation. Manuscript 4 (published) focuses on provider competence with low cost and consultation plus high cost supports. Manuscript 5 (published) was the RCT focusing on intervention effectiveness on the full sample. In contrast, the current manuscript focuses on treatment engagement and outcomes for youth of varying ethnic/racial identities.

Footnotes

Dr. John R. Weisz is a co-developer of the MATCH treatment manual used in the original RCT study and receives royalties for its sale.

This manuscript and accompanied analysis code are available at https://osf.io/v9cdb.

References

  1. Acevedo A, Garnick D, Ritter G, Lundgren L, & Horgan C (2016). Admissions to detoxification after treatment: Does engagement make a difference? Substance Abuse, 37(2), 364–371. 10.1080/08897077.2015.1080784 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Achenbach TM, Dumenci L, & Rescorla LA (2002). Ten-year comparisons of problems and competencies for national samples of youth: Self, parent, and teacher reports. Journal of Emotional and Behavioral Disorders, 10(4), 194–203. 10.1177/10634266020100040101 [DOI] [Google Scholar]
  3. Alvarez CH (2022). Structural racism as an environmental justice issue: A multilevel analysis of the state racism index and environmental health risk from air toxins. Journal of Racial and Ethnic Health Disparities. 10.1007/s40615-021-01215-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Bailey JE, Gurgol C, Pan E, Njie S, Emmett S, Gatwood J, Gauthier L, Rosas LG, Kearney SM, Robler SK, Lawrence RH, Margolis KL, Osunkwo I, Wilfley D, & Shah VO (2021). Early patient-centered outcomes research experience with the use of telehealth to address disparities: Scoping review. Journal of Medical Internet Research, 23(12), e28503. 10.2196/28503 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Becker KD, & Chorpita BF (2023). Future Directions in Youth and Family Treatment Engagement: Finishing the Bridge Between Science and Service. Journal of Clinical Child & Adolescent Psychology, 52(2), 284–309. 10.1080/15374416.2023.2169926 [DOI] [PubMed] [Google Scholar]
  6. Becker KD, Kiser LJ, Herr SR, Stapleton LM, Barksdale CL, & Buckingham S (2014). Changes in treatment engagement of youths and families with complex needs. Children and Youth Services Review, 46, 276–284. 10.1016/j.childyouth.2014.09.005 [DOI] [Google Scholar]
  7. Brener L, von Hippel W, von Hippel C, Resnick I, & Treloar C (2010). Perceptions of discriminatory treatment by staff as predictors of drug treatment completion: Utility of a mixed methods approach. Drug and Alcohol Review, 29(5), 491–497. 10.1111/j.1465-3362.2010.00173.x [DOI] [PubMed] [Google Scholar]
  8. Carpenter JK, Andrews LA, Witcraft SM, Powers MB, Smits JAJ, & Hofmann SG (2018). Cognitive behavioral therapy for anxiety and related disorders: A meta-analysis of randomized placebo-controlled trials. Depression and Anxiety, 35(6), 502–514. 10.1002/da.22728 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Castro-Ramirez F, Al-Suwaidi M, Garcia P, Rankin O, Ricard JR, & Nock MK (2021). Racism and poverty are barriers to the treatment of youth mental health concerns. Journal of Clinical Child & Adolescent Psychology, 50(4), 534–546. 10.1080/15374416.2021.1941058 [DOI] [PubMed] [Google Scholar]
  10. Cave L, Cooper MN, Zubrick SR, & Shepherd CCJ (2020). Racial discrimination and child and adolescent health in longitudinal studies: A systematic review. Social Science & Medicine, 250, 112864. 10.1016/j.socscimed.2020.112864 [DOI] [PubMed] [Google Scholar]
  11. Chaudoir SR, Wang K, & Pachankis JE (2017). What reduces sexual minority stress? A review of the intervention “toolkit.” The Journal of Social Issues, 73(3), 586–617. 10.1111/josi.12233 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Chen D, Kolbuck VD, Sutter ME, Tishelman AC, Quinn GP, & Nahata L (2019). Knowledge, practice behaviors, and perceived barriers to fertility care among providers of transgender healthcare. Journal of Adolescent Health, 64(2), 226–234. 10.1016/j.jadohealth.2018.08.025 [DOI] [PubMed] [Google Scholar]
  13. Chorpita BF, Weisz J, Daleiden EL, Schoenwald SK, Palinkas LA, Miranda J, Higa-McMillan CK, Nakamura BJ, Austin AA, Borntrager CF, Ward A, Wells KC, Gibbons RD, & Research Network on Youth Mental Health. (2013). Long-term outcomes for the Child STEPs randomized effectiveness trial: A comparison of modular and standard treatment designs with usual care. Journal of Consulting and Clinical Psychology, 81(6), 999–1009. 10.1037/a0034200 [DOI] [PubMed] [Google Scholar]
  14. Chu W, Chorpita BF, & Becker KD (2022). Race, racial matching, and cultural understanding as predictors of treatment engagement in youth mental health services. Psychotherapy Research, 1–14. 10.1080/10503307.2022.2150582 [DOI] [PubMed] [Google Scholar]
  15. Cook JE, Purdie-Vaughns V, Meyer IH, & Busch JTA (2014). Intervening within and across levels: A multilevel approach to stigma and public health. Social Science & Medicine (1982), 103, 101–109. 10.1016/j.socscimed.2013.09.023 [DOI] [PubMed] [Google Scholar]
  16. de Jong K, Conijn JM, Gallagher RAV, Reshetnikova AS, Heij M, & Lutz MC (2021). Using progress feedback to improve outcomes and reduce drop-out, treatment duration, and deterioration: A multilevel meta-analysis. Clinical Psychology Review, 85, 102002. 10.1016/j.cpr.2021.102002 [DOI] [PubMed] [Google Scholar]
  17. Dean LT, & Thorpe RJ Jr. (2022). What structural racism is (or is not) and how to measure it: Clarity for public health and medical researchers. American Journal of Epidemiology, 191(9), 1521–1526. 10.1093/aje/kwac112 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Dixon LB, Holoshitz Y, & Nossel I (2016). Treatment engagement of individuals experiencing mental illness: Review and update: •••. World Psychiatry, 15(1), 13–20. 10.1002/wps.20306 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Dowell KA, & Nielsen SJ (2021). Caregiver engagement in youth partial hospitalization treatment. Clinical Child Psychology and Psychiatry, 26(2), 355–366. 10.1177/1359104520978448 [DOI] [PubMed] [Google Scholar]
  20. Duppong Hurley K, Van Ryzin MJ, Lambert M, & Stevens AL (2015). Examining change in therapeutic alliance to predict youth mental health outcomes. Journal of Emotional and Behavioral Disorders, 23(2), 90–100. 10.1177/1063426614541700 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Dziak JJ, Dierker LC, & Abar B (2020). The Interpretation of Statistical Power after the Data have been Gathered. Current Psychology (New Brunswick, N.J.), 39(3), 870–877. 10.1007/s12144-018-0018-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Ewell Foster C, Magness C, Czyz E, Kahsay E, Martindale J, Hong V, Baker E, Cavataio I, Colombini G, Kettley J, Smith PK, & King C (2022). Predictors of Parent Behavioral Engagement in Youth Suicide Discharge Recommendations: Implications for Family-Centered Crisis Interventions. Child Psychiatry & Human Development, 53(6), 1240–1251. 10.1007/s10578-021-01176-9 [DOI] [PubMed] [Google Scholar]
  23. Fante-Coleman T, & Jackson-Best F (2020). Barriers and facilitators to accessing mental healthcare in Canada for Black youth: A scoping review. Adolescent Research Review, 5(2), 115–136. 10.1007/s40894-020-00133-2 [DOI] [Google Scholar]
  24. Flicker SM, Turner CW, Waldron HB, Brody JL, & Ozechowski TJ (2008). Ethnic background, therapeutic alliance, and treatment retention in functional family therapy with adolescents who abuse substances. Journal of Family Psychology, 22(1), 167–170. 10.1037/0893-3200.22.1.167 [DOI] [PubMed] [Google Scholar]
  25. Friis-Healy EA, Nagy GA, & Kollins SH (2021). It is time to REACT: Opportunities for digital mental health apps to reduce mental health disparities in racially and ethnically minoritized groups. JMIR Mental Health, 8(1), e25456. 10.2196/25456 [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Gaither SE (2015). “Mixed” Results: Multiracial Research and Identity Explorations. Current Directions in Psychological Science, 24(2), 114–119. 10.1177/0963721414558115 [DOI] [Google Scholar]
  27. Hack SM, Muralidharan A, Brown CH, Drapalski AL, & Lucksted AA (2020). Stigma and discrimination as correlates of mental health treatment engagement among adults with serious mental illness. Psychiatric Rehabilitation Journal, 43(2), 106–110. 10.1037/prj0000385 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Hatzenbuehler ML, McKetta S, Kim R, Leung S, Prins SJ, & Russell ST (2022). Evaluating litigation as a structural strategy for addressing bias-based bullying among youth. JAMA Pediatrics, 176(1), 52. 10.1001/jamapediatrics.2021.3660 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Hawley KM, & Weisz J (2005). Youth versus parent working alliance in usual clinical care: Distinctive associations with retention, satisfaction, and treatment outcome. Journal of Clinical Child & Adolescent Psychology, 34(1), 117–128. 10.1207/s15374424jccp3401_11 [DOI] [PubMed] [Google Scholar]
  30. Hock R, Yingling ME, & Kinsman A (2015). A Parent-Informed Framework of Treatment Engagement in Group-Based Interventions. Journal of Child and Family Studies, 24(11), 3372–3382. 10.1007/s10826-015-0139-1 [DOI] [Google Scholar]
  31. Hollinsaid NL, Weisz J, Chorpita BF, Skov HE, & Price MA (2020). The effectiveness and acceptability of empirically supported treatments in gender minority youth across four randomized controlled trials. Journal of Consulting and Clinical Psychology, 88(12), 1053–1064. 10.1037/ccp0000597 [DOI] [PubMed] [Google Scholar]
  32. Huey SJ, Park AL, Galán CA, & Wang CX (2023). Culturally Responsive Cognitive Behavioral Therapy for Ethnically Diverse Populations. Annual Review of Clinical Psychology, 19, 51–78. 10.1146/annurev-clinpsy-080921-072750 [DOI] [PubMed] [Google Scholar]
  33. Huey SJ, & Polo AJ (2010). Assessing the Effects of Evidence-Based Psychotherapies with Ethnic Minority Youths. In Weisz J & Kazdin AE (Eds.), Evidence-Based Psychotherapies for Children and Adolescents (2nd ed., pp. 451–465). The Guilford Press. [Google Scholar]
  34. Huey SJ, Tilley JL, Jones EO, & Smith CA (2014). The contribution of cultural competence to evidence-based care for ethnically diverse populations. Annual Review of Clinical Psychology, 10(1), 305–338. 10.1146/annurev-clinpsy-032813-153729 [DOI] [PubMed] [Google Scholar]
  35. Irvine J, Stanley J, Ong L, Cribbie R, Ritvo P, Katz J, Dorian P, O’Donnell S, Harris L, Cameron D, Hill A, Newman D, Johnson SN, Bilanovic A, & Sears SF (2010). Acceptability of a Cognitive Behavior Therapy Intervention to Implantable Cardioverter Defibrillator Recipients. Journal of Cognitive Psychotherapy, 24(4), 246–264. 10.1891/0889-8391.24.4.246 [DOI] [Google Scholar]
  36. Jensen PS, Hinshaw SP, Swanson JM, Greenhill LL, Conners CK, Arnold LE, Abikoff HB, Elliott G, Hechtman L, Hoza B, March JS, Newcorn JH, Severe JB, Vitiello B, Wells K, & Wigal T (2001). Findings from the NIMH Multimodal Treatment Study of ADHD (MTA): Implications and Applications for Primary Care Providers: Journal of Developmental & Behavioral Pediatrics, 22(1), 60–73. 10.1097/00004703-200102000-00008 [DOI] [PubMed] [Google Scholar]
  37. Johansen K, Saran I, Cho E, Weisz J, Price M (2023, November 30). Examining Racial and Ethnic Differences in Youth Psychotherapy Treatment Engagement and Outcomes. 10.31219/osf.io/v9cdb [DOI] [PMC free article] [PubMed]
  38. Jones CP (2000). Levels of racism: A theoretic framework and a gardener’s tale. American Journal of Public Health, 90(8), 1212–1215. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Jones SCT, & Neblett EW (2017). Future directions in research on racism-related stress and racial-ethnic protective factors for Black youth. Journal of Clinical Child and Adolescent Psychology: The Official Journal for the Society of Clinical Child and Adolescent Psychology, American Psychological Association, Division 53, 46(5), 754–766. 10.1080/15374416.2016.1146991 [DOI] [PubMed] [Google Scholar]
  40. Kaminski JW, & Claussen AH (2017). Evidence Base Update for Psychosocial Treatments for Disruptive Behaviors in Children. Journal of Clinical Child and Adolescent Psychology, 46(4), 477–499. 10.1080/15374416.2017.1310044 [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Karver MS, De Nadai AS, Monahan M, & Shirk SR (2019). Alliance in child and adolescent psychotherapy. In Psychotherapy relationships that work: Evidence-based therapist contributions, Vol. 1, 3rd ed (pp. 79–116). Oxford University Press. 10.1093/med-psych/9780190843953.003.0003 [DOI] [Google Scholar]
  42. Karver MS, Handelsman JB, Fields S, & Bickman L (2005). A theoretical model of common process factors in youth and family therapy. Mental Health Services Research, 7(1), 35–51. 10.1007/s11020-005-1964-4 [DOI] [PubMed] [Google Scholar]
  43. Kivlighan DM, Jung A-K, Berkowitz AB, Hammer JH, & Collins NM (2019). ‘To show or No-show’? Therapist Racial-ethnic Disparities in Clients’ Nonattendance in Therapy. Journal of College Student Psychotherapy, 33(1), 1–13. 10.1080/87568225.2018.1424597 [DOI] [Google Scholar]
  44. Lakind D, Bradley WJ, Patel A, Chorpita BF, & Becker KD (2022). A Multidimensional Examination of the Measurement of Treatment Engagement: Implications for Children’s Mental Health Services and Research. Journal of Clinical Child & Adolescent Psychology, 51(4), 453–468. 10.1080/15374416.2021.1941057 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Lang JM, Lee P, Connell CM, Marshall T, & Vanderploeg JJ (2021). Outcomes, evidence-based treatments, and disparities in a statewide outpatient children’s behavioral health system. Children and Youth Services Review, 120, 105729. 10.1016/j.childyouth.2020.105729 [DOI] [Google Scholar]
  46. Lewis EM, Hooley C, Feely M, Lanier P, Korff SJ, & Kohl PL (2020). Engaging Child Welfare–Involved Families in Evidence-Based Interventions to Address Child Disruptive Behavior Disorders. Journal of Emotional and Behavioral Disorders, 28(1), 43–51. 10.1177/1063426618806253 [DOI] [Google Scholar]
  47. Lichstein KL, Scogin F, Thomas SJ, DiNapoli EA, Dillon HR, & McFadden A (2013). Telehealth Cognitive Behavior Therapy for Co-Occurring Insomnia and Depression Symptoms in Older Adults. Journal of Clinical Psychology, 69(10), 1056–1065. 10.1002/jclp.22030 [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Loades ME, & Schleider JL (2023). Technology Matters: Online, self-help single session interventions could expand current provision, improving early access to help for young people with depression symptoms, including minority groups. Child and Adolescent Mental Health, Advance online publication. 10.1111/camh.12659 [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Lu W (2019). Adolescent Depression: National Trends, Risk Factors, and Healthcare Disparities. American Journal of Health Behavior, 43(1), 181–194. 10.5993/AJHB.43.1.15 [DOI] [PubMed] [Google Scholar]
  50. Lu W, Todhunter-Reid A, Mitsdarffer ML, Muñoz-Laboy M, Yoon AS, & Xu L (2021). Barriers and Facilitators for Mental Health Service Use Among Racial/Ethnic Minority Adolescents: A Systematic Review of Literature. Frontiers in Public Health, 9. https://www.frontiersin.org/articles/10.3389/fpubh.2021.641605 [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Marotta PL, Tolou-Shams M, Cunningham-Williams RM, Washington DM, & Voisin D (2022). Racial and Ethnic Disparities, Referral Source and Attrition From Outpatient Substance Use Disorder Treatment Among Adolescents in the United States. Youth & Society, 54(1), 148–173. 10.1177/0044118X20960635 [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Marrast L, Himmelstein DU, & Woolhandler S (2016). Racial and Ethnic Disparities in Mental Health Care for Children and Young Adults: A National Study. International Journal of Health Services, 46(4), 810–824. 10.1177/0020731416662736 [DOI] [PubMed] [Google Scholar]
  53. McCart MR, & Sheidow AJ (2016). Evidence-Based Psychosocial Treatments for Adolescents With Disruptive Behavior. Journal of Clinical Child and Adolescent Psychology: The Official Journal for the Society of Clinical Child and Adolescent Psychology, American Psychological Association, Division 53, 45(5), 529–563. 10.1080/15374416.2016.1146990 [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Meyers DC, Durlak JA, & Wandersman A (2012). The quality implementation framework: A synthesis of critical steps in the implementation process. American Journal of Community Psychology, 50(3–4), 462–480. 10.1007/s10464-012-9522-x [DOI] [PubMed] [Google Scholar]
  55. Miranda R, Soffer A, Polanco-Roman L, Wheeler A, & Moore A (2015). Mental Health Treatment Barriers Among Racial/Ethnic Minority Versus White Young Adults 6 Months After Intake at a College Counseling Center. Journal of American College Health, 63(5), 291–298. 10.1080/07448481.2015.1015024 [DOI] [PubMed] [Google Scholar]
  56. Mpofu JJ (2022). Perceived racism and demographic, mental health, and behavioral characteristics among high school students during the COVID-19 pandemic—Adolescent Behaviors and Experiences Survey, United States, January–June 2021. MMWR Supplements, 71(3), 22–27. 10.15585/mmwr.su7103a4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Neblett EW, & Neal AJ (2022). Measuring institutional and structural racism in research on adolescence and developmental science. Journal of Research on Adolescence, 32(4), 1280–1284. 10.1111/jora.12810 [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. NIH. (2019). Notice of NIH’s Interest in Diversity. National Institute of Health. https://grants.nih.gov/grants/guide/notice-files/NOT-OD-20-031.html [Google Scholar]
  59. NIMH. (2021). Funding opportunity on impact of structural racism and discrimination on minority health and health disparities. https://www.nih.gov/ending-structural-racism/funding-opportunity-impact-structural-racism-discrimination-minority-health-health-disparities
  60. NIMH. (2023). Diversity and Inclusion in Clinical Trials. National Institute of Mental Health. https://nimhd.nih.gov/resources/understanding-health-disparities/diversity-and-inclusion-in-clinical-trials.html [Google Scholar]
  61. Office of the Surgeon General. (2021). Protecting Youth Mental Health: The U.S. Surgeon General’s Advisory. US Department of Health and Human Services. http://www.ncbi.nlm.nih.gov/books/NBK575984/ [PubMed] [Google Scholar]
  62. Ofonedu ME, Belcher HME, Budhathoki C, & Gross DA (2017). Understanding Barriers to Initial Treatment Engagement among Underserved Families Seeking Mental Health Services. Journal of Child and Family Studies, 26(3), 863–876. 10.1007/s10826-016-0603-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Okonofua JA, Goyer JP, Lindsay CA, Haugabrook J, & Walton GM (2022). A scalable empathic-mindset intervention reduces group disparities in school suspensions. Science Advances, 8(12), eabj0691. 10.1126/sciadv.abj0691 [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Pearce J, Mann MK, Jones C, van Buschbach S, Olff M, & Bisson JI (2012). The Most Effective Way of Delivering a Train-the-Trainers Program: A Systematic Review. Journal of Continuing Education in the Health Professions, 32(3), 215–226. 10.1002/chp.21148 [DOI] [PubMed] [Google Scholar]
  65. Peguero AA, & Williams LM (2013). Racial and Ethnic Stereotypes and Bullying Victimization. Youth & Society, 45(4), 545–564. 10.1177/0044118X11424757 [DOI] [Google Scholar]
  66. Pina AA, Polo AJ, & Huey SJ (2019). Evidence-based psychosocial interventions for ethnic minority youth: The 10-year update. Journal of Clinical Child and Adolescent Psychology, 48(2), 179–202. 10.1080/15374416.2019.1567350 [DOI] [PubMed] [Google Scholar]
  67. Pinedo M (2019). A current re-examination of racial/ethnic disparities in the use of substance abuse treatment: Do disparities persist? Drug and Alcohol Dependence, 202, 162–167. 10.1016/j.drugalcdep.2019.05.017 [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Price MA, & Hollinsaid NL (2022). Future directions in mental health treatment with stigmatized youth. Journal of Clinical Child & Adolescent Psychology, 51(5), 810–825. 10.1080/15374416.2022.2109652 [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Price MA, Weisz J, McKetta S, Hollinsaid NL, Lattanner MR, Reid AE, & Hatzenbuehler ML (2022). Meta-analysis: Are psychotherapies less effective for Black youth in communities with higher levels of anti-Black racism? Journal of the American Academy of Child and Adolescent Psychiatry, 61(6), 754–763. 10.1016/j.jaac.2021.07.808 [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Priest N, Paradies Y, Trenerry B, Truong M, Karlsen S, & Kelly Y (2013). A systematic review of studies examining the relationship between reported racism and health and wellbeing for children and young people. Social Science & Medicine, 95, 115–127. 10.1016/j.socscimed.2012.11.031 [DOI] [PubMed] [Google Scholar]
  71. Reid AE, Dovidio JF, Ballester E, & Johnson BT (2014). HIV prevention interventions to reduce sexual risk for African Americans. Social Science & Medicine, 103, 118–125. 10.1016/j.socscimed.2013.06.028 [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Riley SE, Stromberg AJ, & Clark J (2005). Assessing Parental Satisfaction with Children’s Mental Health Services with the Youth Services Survey for Families. Journal of Child and Family Studies, 14(1), 87–99. 10.1007/s10826-005-1124-x [DOI] [Google Scholar]
  73. Rothman S, Gunturu S, & Korenis P (2020). The mental health impact of the COVID-19 epidemic on immigrants and racial and ethnic minorities. QJM: An International Journal of Medicine, 113(11), 779–782. 10.1093/qjmed/hcaa203 [DOI] [PMC free article] [PubMed] [Google Scholar]
  74. Santoro H (2023). APA 2023 Trends Report: The push for more equitable research is changing the field.
  75. Schleider JL, Mullarkey MC, Fox KR, Dobias ML, Shroff A, Hart EA, & Roulston CA (2022). A randomized trial of online single-session interventions for adolescent depression during COVID-19. Nature Human Behaviour, 6(2), Article 2. 10.1038/s41562-021-01235-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  76. Shih M, Wilton LS, Does S, Goodale BM, & Sanchez DT (2019). Multiple racial identities as sources of psychological resilience. Social and Personality Psychology Compass, 13(6), e12469. 10.1111/spc3.12469 [DOI] [Google Scholar]
  77. Shim RS, & Starks SM (2021). COVID-19, Structural Racism, and Mental Health Inequities: Policy Implications for an Emerging Syndemic. Psychiatric Services, 72(10), 1193–1198. 10.1176/appi.ps.202000725 [DOI] [PubMed] [Google Scholar]
  78. Shirk SR, & Saiz CC (1992). Clinical, empirical, and developmental perspectives on the therapeutic relationship in child psychotherapy. Development and Psychopathology, 4(04), 713. 10.1017/S0954579400004946 [DOI] [Google Scholar]
  79. Smith TE, Holmes SR, Sheridan SM, Cooper JM, Bloomfield BS, & Preast JL (2020). Effects of Consultation-Based Family-School Engagement on Student and Parent Outcomes: A Meta-Analysis. In Grantee Submission. Grantee Submission; eric. http://ezp-prod1.hul.harvard.edu/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=eric&AN=ED611789&site=ehost-live&scope=site [Google Scholar]
  80. StataCorp. (2017). Stata Statistical Software: Release 15 [Computer software].
  81. Staudt M (2007). Treatment engagement with caregivers of at-risk children: Gaps in research and conceptualization. Journal of Child and Family Studies, 16(2), 183–196. 10.1007/s10826-006-9077-2 [DOI] [Google Scholar]
  82. Chorpita BF & Weisz JR (2009). Modular approach to therapy for children with anxiety, depression, trauma, or conduct problems. Satellite Beach, FL: PracticeWise. [Google Scholar]
  83. Weisz J, Kuppens S, Ng MY, Eckshtain D, Ugueto AM, Vaughn-Coaxum R, Jensen-Doss A, Hawley KM, Krumholz Marchette LS, Chu BC, Weersing VR, & Fordwood SR (2017). What five decades of research tells us about the effects of youth psychological therapy: A multilevel meta-analysis and implications for science and practice. American Psychologist, 72(2), 79–117. 10.1037/a0040360 [DOI] [PubMed] [Google Scholar]
  84. Weisz J, Thomassin K, Hersh J, Santucci LC, MacPherson HA, Rodriguez GM, Bearman SK, Lang JM, Vanderploeg JJ, Marshall TM, Lu JJ, Jensen-Doss A, & Evans SC (2020). Clinician training, then what? Randomized clinical trial of child STEPs psychotherapy using lower-cost implementation supports with versus without expert consultation. Journal of Consulting and Clinical Psychology, 88(12), 1065–1078. 10.1037/ccp0000536 [DOI] [PubMed] [Google Scholar]

Associated Data

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

Supplementary Materials

supplement
NIHMS2056928-supplement-supplement.pdf (244.1KB, pdf)

RESOURCES