Predicting adolescent suicidal behavior following inpatient discharge using structured and unstructured data.

BACKGROUND: The objective was to develop and assess performance of an algorithm predicting suicide-related ICD codes within three months of psychiatric discharge. METHODS: This prognostic study used a retrospective cohort of EHR data from 2789 youth (12 to 20 years old) hospitalized in a safety net institution in the Northeastern United States. The dataset combined structured data with unstructured data obtained through natural language processing of clinical notes. Machine learning approaches compared gradient boosting to random forest analyses. RESULTS: Area under the ROC and precision-recall curve were 0.88 and 0.17, respectively, for the final Gradient Boosting model. The cutoff point of the model-generated predicted probabilities of suicide that optimally classified the individual as high risk or not was 0.009. When applying the chosen cutoff (0.009) to the hold-out testing set, the model correctly identified 8 positive cases out of 10, and 418 negative cases out 548. The corresponding performance metrics showed 80 % sensitivity, 76 % specificity, 6 % PPV, 99 % NPV, F-1 score of 0.11, and an accuracy of 76 %. LIMITATIONS: The data in this study comes from a single health system, possibly introducing bias in the model's algorithm. Thus, the model may have underestimated the incidence of suicidal behavior in the study population. Further research should include multiple system EHRs. CONCLUSIONS: These performance metrics suggest a benefit to including both unstructured and structured data in design of predictive algorithms for suicidal behavior, which can be integrated into psychiatric services to help assess risk.

Estimates of Major Depressive Disorder and Treatment Among Adolescents by Race and Ethnicity.

Importance: The COVID-19 pandemic has contributed to poorer mental health and a greater need for treatment. Nationally representative estimates of major depressive disorder (MDD) and mental health treatment among US adolescents during the pandemic are needed. Objective: To estimate MDD prevalence among adolescents, evaluate mental health treatment use among adolescents with MDD, and assess differences by race and ethnicity. Design, Setting, and Participants: This cross-sectional analysis of the nationally representative 2021 National Survey on Drug Use and Health included noninstitutionalized US adolescents between the ages of 12 and 17 years (n = 10 743). Analytic weights were applied to all rates and model estimates to be nationally representative and account for sample design and survey nonresponse. Data were collected from January 14 to December 20, 2021, and analyzed from February 11 to April 3, 2023. Exposures: Self-reported race and ethnicity. Main Outcomes and Measures: Dichotomous outcomes of MDD as defined by the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition), MDD-specific mental health treatment, any type of mental health treatment, telehealth visits, and delays in mental health treatment. Results: The sample included 10 743 adolescents (51.1% male). Self-reported race and ethnicity included 5.1% Asian, 14.1% Black, 23.3% Latinx, 51.2% White, and 6.3% more than 1 race. Ages were evenly distributed: 34.0% aged 12 to 13 years; 33.3% aged 14 to 15 years; and 32.7% aged 16 to 17 years. Adolescents of more than 1 race or ethnicity had the highest MDD rate (26.5%). Compared with White adolescents, the lowest rates of any MDD treatment overall were found among Latinx adolescents (29.2% [95% CI, 22.2%-36.2%]) and those of more than 1 race or ethnicity (21.1% [95% CI, 11.6%-30.7%]). Similar results were found for treatment by any clinician (Latinx, 25.6% [95% CI, 18.8%-32.4%]; >1 race or ethnicity, 19.1% [95% CI, 9.7%-28.6%]), treatment by a mental health specialist (Latinx, 22.9% [95% CI, 16.9%-28.9%]; >1 race or ethnicity, 16.7% [95% CI, 7.1%-26.3%]), treatment by a nonspecialist clinician (Latinx, 7.3% [95% CI, 3.3%-11.3%]; >1 race or ethnicity, 4.8% [95% CI, 1.9%-7.7%]), and use of any psychotropic medication prescription (Latinx, 11.6% [95% CI, 7.3%-15.9%]; >1 race or ethnicity, 8.3% [95% CI, 2.8%-13.7]). Compared with White adolescents, Black adolescents had lower rates of MDD treatment by any clinician (31.7% [95% CI, 23.7%-39.8%]) and by nonspecialist clinicians (8.4% [95% CI, 3.8%-13.2%]) and experienced lower prescription rates for any psychotropic medication (12.6 [95% CI, 4.6%-20.6%]). Asian (16.0% [95% CI, 5.0%-27.2%]) and Latinx (17.8% [95% CI, 12.6%-23.0%]) adolescents had lower rates of virtual mental health treatment compared with White adolescents. Black (19.1% [95% CI, 14.1%-24.2%]) and Latinx (17.9% [95% CI, 15.0%-21.1%]) adolescents had lower rates of appointments transition to telehealth, while Black adolescents (14.1% [95% CI, 10.7%-17.4%]) experienced delays getting their prescriptions. Conclusions and Relevance: During the first full calendar year of the pandemic, approximately 1 in 5 adolescents had MDD, and less than half of adolescents who needed treatment had any mental health treatment. Adolescents in racial and ethnic minority groups, particularly Latinx, experienced the lowest treatment rates. Federal policy should target adolescents as a whole, and minority populations in particular, to ensure equitable treatment access. Efforts should consider the social, racial, ethnic, and cultural determinants of health.

Piloting Smartphone Digital Phenotyping to Understand Problematic Internet Use in an Adolescent and Young Adult Sample.

Problematic Internet use (PIU) preferentially affects youth development, particularly youth with psychiatric conditions. Studies attempting to understand PIU and its impact on adolescent mental health have been limited by cross-sectional design and self-report data. Even with a small sample size, digital phenotyping (DP) methodology can address these limitations through repeated sampling and collection of survey and sensor data through personal smartphones. This study pilots a 6-week DP protocol in 28 youth in mental health treatment in order to assess relationships between PIU, mood symptoms, and daily behaviors like smartphone engagement and daily travel in this high-risk population. Our results found shared associations between depression and PIU, where symptom severity of both worsened in the setting of decreased smartphone engagement. These clinically relevant findings indicate that, rather than uniformly worsening mental health, increased digital engagement may actually provide short-term relief from negative affect in youth with psychiatric comorbidities.

Racial and Ethnic Disparities in Childhood ADHD Treatment Access and Utilization: Results From a National Study.

OBJECTIVE: The study examined racial-ethnic disparities in access to and utilization of treatment for attention-deficit hyperactivity disorder (ADHD) and other psychiatric diagnoses among children with ADHD. METHODS: Nationally representative, cross-sectional data from the Household Component of the Medical Expenditure Panel Survey 2011-2019 were used to examine racial-ethnic disparities in access to and utilization of treatment by children ages 5-17 with ADHD (N=5,838). Logistic regression models were estimated for access outcomes, and generalized linear models were estimated for utilization outcomes. Multivariable regression models adjusted for race-ethnicity, age, sex, and treatment need in accordance with the Institute of Medicine definition of health care disparities. RESULTS: In adjusted analyses, compared with White children with ADHD, Black, Hispanic, and Asian children with ADHD had significantly lower rates of any past-year treatment visit for ADHD or for other psychiatric diagnoses. They also had lower rates of having accessed ADHD medication. Compared with White children, Black and Asian children with ADHD used fewer ADHD medications, and Black and Hispanic children with ADHD had lower overall mental health treatment expenditures. CONCLUSIONS: Disparities in ADHD treatment among children from racial-ethnic minority populations may be driven primarily by disparities in access rather than in utilization. Once treatment had been accessed, disparities in utilization were largely accounted for by differences in socioeconomic status. These findings suggest that interventions targeting access to treatment among children from racial-ethnic minority populations may help close existing care gaps.

Problematic Internet Use Before and During the COVID-19 Pandemic in Youth in Outpatient Mental Health Treatment: App-Based Ecological Momentary Assessment Study.

BACKGROUND: Youth with existing psychiatric illness are more apt to use the internet as a coping skill. Because many "in-person" coping skills were not easily accessible during the COVID-19 pandemic, youth in outpatient mental health treatment may have been particularly vulnerable to the development of problematic internet use (PIU). The identification of a pandemic-associated worsening of PIU in this population is critical in order to guide clinical care; if these youth have become dependent upon the internet to regulate their negative emotions, PIU must be addressed as part of mental health treatment. However, many existing studies of youth digital media use in the pandemic do not include youth in psychiatric treatment or are reliant upon cross-sectional methodology and self-report measures of digital media use. OBJECTIVE: This is a retrospective cohort study that used data collected from an app-based ecological momentary assessment protocol to examine potential pandemic-associated changes in digital media youth in outpatient mental health treatment. Secondary analyses assessed for differences in digital media use dependent upon personal and familial COVID-19 exposure and familial hospitalization, as well as factors associated with PIU in this population. METHODS: The participants were aged 12-23 years and were receiving mental health treatment in an outpatient community hospital setting. All participants completed a 6-week daily ecological momentary assessment protocol on their personal smartphones. Questions were asked about depression (PHQ-8 [8-item Patient Health Questionnaire]), anxiety (GAD-7 [7-item General Anxiety Disorder]), PIU (PIU-SF-6 [Problematic Internet Use Short Form 6]), digital media use based on Apple's daily screen time reports, and personal and familial COVID-19 exposure. The analyses compared screen time, psychiatric symptoms, and PIU between cohorts, as well as between youth with personal or familial COVID-19 exposures and those without. The analyses also assessed for demographic and psychiatric factors associated with clinically significant PIU-SF-6 scores. RESULTS: A total of 69 participants completed the study. The participants recruited during the pandemic were significantly more likely to meet the criteria for PIU based on their average PIU-SF-6 score (P=.02) and to spend more time using social media each day (P=.049). The overall amount of daily screen time did not differ between cohorts. Secondary analyses revealed a significant increase in average daily screen time among subjects who were exposed to COVID-19 (P=.01). Youth with clinically significant PIU-SF-6 scores were younger and more likely to have higher PHQ-8 (P=.003) and GAD-7 (P=.003) scores. No differences in scale scores or media use were found between subjects based on familial COVID-19 exposure or hospitalization. CONCLUSIONS: Our findings support our hypothesis that PIU may have worsened for youth in mental health treatment during the pandemic, particularly the problematic use of social media. Mental health clinicians should incorporate screening for PIU into routine clinical care in order to prevent potential familial conflict and subsequent psychiatric crises that might stem from unrecognized PIU.

Promoting Population Behavioral Health in a Safety-Net Health System During the COVID-19 Pandemic.

The COVID-19 pandemic has been expected to lead to substantial increases in need for behavioral health care. A population health framework can facilitate the development of interventions and policies to promote the equitable distribution of care across the population. This column describes the application of population behavioral health principles in a safety-net health system during the pandemic. The approach includes stepped models of care, interventions to target individuals at high behavioral health risk, and measurement-based care. Early data suggest that these strategies have resulted in expanded behavioral health care capacity.

A pilot study using ecological momentary assessment via smartphone application to identify adolescent problematic internet use.

For some youth, pathologic Internet use can cause significant distress and dysfunction, a phenomenon known as Problematic Internet Use (PIU). PIU has been associated with poorer health outcomes in adolescents with existing psychiatric illness but understanding PIU has been challenging due to research methodologies using cross-sectional, self-report data. This study assessed the feasibility of using app-based ecological momentary assessment (EMA) to provide more ecologically-valid data to identify and characterize the relationship between mood symptoms and PIU in adolescents in active mental health treatment. 25 youth (aged 12-23) were recruited to use an EMA app for 6 weeks. 96% of participants completed the study and the majority of participants completed surveys at least once weekly. Youth with anxiety disorders endorsed significantly greater benefit from using the app to monitor PIU. While PIU severity was positively correlated with worsened anxiety and depression, analyses of the temporal relationships between PIU and mood symptoms showed that anxiety symptoms were significantly improved after episodes of PIU. Overall results suggest that app-based EMA may be both acceptable and feasible to understand PIU in this population. Follow-up studies should consider personalization of study protocols and use of digital phenotyping methodology to collect more objective measurements of behavior.

Understanding the Role of Past Health Care Discrimination in Help-Seeking and Shared Decision-Making for Depression Treatment Preferences.

As a part of a larger, mixed-methods research study, we conducted semi-structured interviews with 21 adults with depressive symptoms to understand the role that past health care discrimination plays in shaping help-seeking for depression treatment and receiving preferred treatment modalities. We recruited to achieve heterogeneity of racial/ethnic backgrounds and history of health care discrimination in our participant sample. Participants were Hispanic/Latino (n = 4), non-Hispanic/Latino Black (n = 8), or non-Hispanic/Latino White (n = 9). Twelve reported health care discrimination due to race/ethnicity, language, perceived social class, and/or mental health diagnosis. Health care discrimination exacerbated barriers to initiating and continuing depression treatment among patients from diverse backgrounds or with stigmatized mental health conditions. Treatment preferences emerged as fluid and shaped by shared decisions made within a trustworthy patient-provider relationship. However, patients who had experienced health care discrimination faced greater challenges to forming trusting relationships with providers and thus engaging in shared decision-making processes.

Depression treatment preferences by race/ethnicity and gender and associations between past healthcare discrimination experiences and present preferences in a nationally representative sample.

BACKGROUND: Depression treatment disparities are well documented. Differing treatment preferences across social groups have been suggested as a cause of these disparities. However, existing studies of treatment preferences have been limited to individuals currently receiving clinical care, and existing measures of depression treatment preferences have not accounted for factors that may be disproportionately relevant to the preferences of disparities populations. This study therefore aimed to assess depression treatment preferences by race/ethnicity and gender in a representative community sample, while accounting for access to healthcare, provider characteristics, and past experiences of discrimination in healthcare settings. METHODS: We conducted a nationally representative study of individuals with depression in and out of clinical care. Treatment preferences (medication versus talk therapy) were elicited through a discrete choice experiment that accounted for tradeoffs with factors related to access and provider characteristics deemed relevant by community stakeholders. Past discrimination was assessed through questions about unfair treatment from medical providers and front desk staff due to personal characteristics (e.g., race, gender). We used conditional logit models to assess treatment preferences by race/ethnicity and gender and examined whether preferences were associated with past experiences of healthcare discrimination. RESULTS: Non-Hispanic white respondents (OR-here, the odds of a talk therapy preference over the odds of a medication preference: 0.80, 95% CI: 0.64, 0.99) and men (OR 0.76, 95% CI: 0.60, 0.96) preferred medication over talk therapy, while non-Hispanic black respondents, Hispanic respondents, and women did not prefer one over the other. Past discrimination in healthcare settings was associated with lower preferences for talk therapy and greater preferences for medication, particularly among non-Hispanic black respondents and women respondents. CONCLUSIONS: Addressing previous methodological limitations yielded estimates for depression treatment preferences by race/ethnicity and gender that differed from past studies. Also, past discrimination in healthcare settings was associated with current treatment preferences.

Problematic Internet Use and Associated High-Risk Behavior in an Adolescent Clinical Sample: Results from a Survey of Psychiatrically Hospitalized Youth.

Problematic Internet use (PIU) is a growing clinical concern to clinicians working in adolescent mental health, with significant potential comorbidities like depression and substance use. No prior study has examined associations between PIU, high-risk behavior, and psychiatric diagnoses specifically in psychiatrically hospitalized adolescents. Here, we analyzed how PIU severity correlated with preadmission Internet habits, psychiatric symptoms, and high-risk behavior in this unique population. We hypothesized that as the severity of PIU increased, so would endorsement of mood symptoms, engagement in risky behaviors, and chances of having comorbid mood and aggression-related diagnoses. We performed a cross-sectional survey on an adolescent psychiatric inpatient unit in an urban community hospital in Massachusetts. Participants were 12-20 years old (n = 205), 62.0 percent female, and of diverse racial/ethnic backgrounds. Relationships between PIU, high-risk symptoms, diagnoses, and behaviors were performed both using chi-square tests and determining Pearson correlation coefficients. Two hundred five adolescents participated in the study. PIU severity was associated with being female (p < 0.005), sexting (p < 0.05), cyberbullying (p < 0.005), and increased suicidality within the last year (p < 0.05). Adolescents with aggressive and developmental disorders, but not depressive disorders, also had significantly higher PIU scores (p ≤ 0.05). In our sample of psychiatrically hospitalized adolescents, PIU severity was significantly associated with both serious psychiatric symptoms and high-risk behaviors, including those related to suicide. Our findings may improve safety assessments in this vulnerable adolescent population by identifying comorbid risks associated with problematic digital media use.

Identification of suicidal behavior among psychiatrically hospitalized adolescents using natural language processing and machine learning of electronic health records.

OBJECTIVE: The rapid proliferation of machine learning research using electronic health records to classify healthcare outcomes offers an opportunity to address the pressing public health problem of adolescent suicidal behavior. We describe the development and evaluation of a machine learning algorithm using natural language processing of electronic health records to identify suicidal behavior among psychiatrically hospitalized adolescents. METHODS: Adolescents hospitalized on a psychiatric inpatient unit in a community health system in the northeastern United States were surveyed for history of suicide attempt in the past 12 months. A total of 73 respondents had electronic health records available prior to the index psychiatric admission. Unstructured clinical notes were downloaded from the year preceding the index inpatient admission. Natural language processing identified phrases from the notes associated with the suicide attempt outcome. We enriched this group of phrases with a clinically focused list of terms representing known risk and protective factors for suicide attempt in adolescents. We then applied the random forest machine learning algorithm to develop a classification model. The model performance was evaluated using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy. RESULTS: The final model had a sensitivity of 0.83, specificity of 0.22, AUC of 0.68, a PPV of 0.42, NPV of 0.67, and an accuracy of 0.47. The terms mostly highly associated with suicide attempt clustered around terms related to suicide, family members, psychiatric disorders, and psychotropic medications. CONCLUSION: This analysis demonstrates modest success of a natural language processing and machine learning approach to identifying suicide attempt among a small sample of hospitalized adolescents in a psychiatric setting.

Assessing provider and racial/ethnic variation in response to the FDA antidepressant box warning.

INTRODUCTION: After the 2004 FDA box warning raised concerns about increased suicidal ideation among youth taking antidepressants, antidepressant use decreased for White youth but slightly increased for Black and Latino youth. Better understanding of patient and provider factors contributing to these differences is needed to improve future risk warning dissemination. METHODS: We analyzed antidepressant prescriptions for youth aged 5-17 in 2002-2006 Medicaid claims data from four states (CA, FL, NC, and NY). In multilevel models, we assessed provider- and patient-level contributions to changes in antidepressant use by race/ethnicity and compared responses to the box warning between providers with large (>2/3) and small (<1/3) proportions of minority patients. RESULTS: A significant amount of variance in overall prescribing patterns (calculated by the ICC) was explained at the provider level. Significant provider-level variation was also identified in the differential effect of the box warning by racial/ethnic group. In a test of the influence of provider panel mix, we found that providers with large proportions of minority patients reduced antidepressant prescribing more slowly after the box warning than other providers. DISCUSSION: This study is the first to assess provider- and patient-level variation in the impact of a health care policy change on treatment disparities. Black and Latino youth Medicaid beneficiaries were seen by largely different providers than their White counterparts, and these distinct providers were influential in driving antidepressant prescription patterns following the box warning. Concerted outreach to providers of minority beneficiaries is needed to ensure that risk warnings and clinical innovations diffuse swiftly across racial/ethnic minority groups.

Examining racial/ethnic differences in patterns of benzodiazepine prescription and misuse.

BACKGROUND: Benzodiazepines (BZDs) are widely prescribed during psychiatric treatment. Unfortunately, their misuse has led to recent surges in overdose emergency visits and drug-related deaths. METHODS: Electronic health record data from a large healthcare system were used to describe racial/ethnic, sex, and age differences in BZD use and dependence. Among patients with a BZD prescription, we assessed differences in the likelihood of subsequently receiving a BZD dependence diagnosis, number of BZD prescriptions, receiving only one BZD prescription, and receiving 18 or more BZD prescriptions. We also estimated multivariate hazard models and generalized linear models, assessing racial/ethnic differences after adjustment for covariates. RESULTS: In both unadjusted and adjusted analyses, Whites were more likely than Blacks, Hispanics, and Asians to have a BZD dependence diagnosis and to receive a BZD prescription. Racial/ethnic minority groups received fewer BZD prescriptions, were more likely to have only one BZD prescription, and were less likely to have 18 or more BZD prescriptions. We identified greater BZD misuse among older patients but no sex differences. CONCLUSIONS: Findings from this study add to the emerging evidence of high relative rates of prescription drug abuse among Whites. There is a concern, given their greater likelihood of having only one BZD prescription, that Blacks, Hispanics, and Asians may be discontinuing BZDs before their clinical need is resolved. Research is needed on provider readiness to offer racial/ethnic minorities BZDs when indicated, patient preferences for BZDs, and whether lower prescription rates among racial/ethnic minorities offer protection against the progression from prescription to addiction.

Assessment of Digital Media Use in the Adolescent Psychiatric Evaluation.

Digital media (also called "new media") have become an important ecosystem in which adolescents develop biologically, psychologically, and socially. When assessing adolescents in the psychiatric interview, a nuanced understanding of digital media use can inform a more accurate formulation. However, there are few published resources to help the psychiatrist assess the impact of digital media during the initial adolescent interview. The authors propose an innovation on the traditional psychiatric assessment that addresses teen Internet use and digital media habits. Through this enhanced assessment, mental health clinicians can improve upon current interviewing practices of twenty-first century adolescents.

Effectiveness of the DECIDE Interventions on Shared Decision Making and Perceived Quality of Care in Behavioral Health With Multicultural Patients: A Randomized Clinical Trial.

Importance: Few randomized clinical trials have been conducted with ethnic/racial minorities to improve shared decision making (SDM) and quality of care. Objective: To test the effectiveness of patient and clinician interventions to improve SDM and quality of care among an ethnically/racially diverse sample. Design, Setting, and Participants: This cross-level 2 × 2 randomized clinical trial included clinicians at level 2 and patients (nested within clinicians) at level 1 from 13 Massachusetts behavioral health clinics. Clinicians and patients were randomly selected at each site in a 1:1 ratio for each 2-person block. Clinicians were recruited starting September 1, 2013; patients, starting November 3, 2013. Final data were collected on September 30, 2016. Data were analyzed based on intention to treat. Interventions: The clinician intervention consisted of a workshop and as many as 6 coaching telephone calls to promote communication and therapeutic alliance to improve SDM. The 3-session patient intervention sought to improve SDM and quality of care. Main Outcomes and Measures: The SDM was assessed by a blinded coder based on clinical recordings, patient perception of SDM and quality of care, and clinician perception of SDM. Results: Of 312 randomized patients, 212 (67.9%) were female and 100 (32.1%) were male; mean (SD) age was 44.0 (15.0) years. Of 74 randomized clinicians, 56 (75.7%) were female and 18 (4.3%) were male; mean (SD) age was 39.8 (12.5) years. Patient-clinician pairs were assigned to 1 of the following 4 design arms: patient and clinician in the control condition (n = 72), patient in intervention and clinician in the control condition (n = 68), patient in the control condition and clinician in intervention (n = 83), or patient and clinician in intervention (n = 89). All pairs underwent analysis. The clinician intervention significantly increased SDM as rated by blinded coders using the 12-item Observing Patient Involvement in Shared Decision Making instrument (b = 4.52; SE = 2.17; P = .04; Cohen d = 0.29) but not as assessed by clinician or patient. More clinician coaching sessions (dosage) were significantly associated with increased SDM as rated by blinded coders (b = 12.01; SE = 3.72; P = .001; Cohen d = 0.78). The patient intervention significantly increased patient-perceived quality of care (b = 2.27; SE = 1.16; P = .05; Cohen d = 0.19). There was a significant interaction between patient and clinician dosage (b = 7.40; SE = 3.56; P = .04; Cohen d = 0.62), with the greatest benefit when both obtained the recommended dosage. Conclusions and Relevance: The clinician intervention could improve SDM with minority populations, and the patient intervention could augment patient-reported quality of care. Trial Registration: clinicaltrials.gov Identifier: NCT01947283.

A decline in depression treatment following FDA antidepressant warnings largely explains racial/ethnic disparities in prescription fills.

BACKGROUND: The Food and Drug Administration's 2004 antidepressant warning was followed by decreases in antidepressant prescribing for youth. This was due to declines in all types of depression treatment, not just the intended changes in antidepressant prescribing patterns. Little is known about how these patterns varied by race/ethnicity. METHOD: Data are Medicaid claims from four U.S. states (2002-2009) for youth ages 5-17. Interrupted time series analyses measured changes due to the warning in levels and trends, by race/ethnicity, of three outcomes: antidepressant prescription fills, depression treatment visits, and incident fluoxetine prescription fills. RESULTS: Prewarning, antidepressant fills were increasing across all racial/ethnic groups, fastest for White youth. Postwarning, there was an immediate drop and continued decline in the rate of fills among White youth, more than double the decline in the rate among Black and Latino youth. Prewarning, depression treatment visits were increasing for White and Latino youth. Postwarning, depression treatment stabilized among Latinos, but declined among White youth. Prewarning, incident fluoxetine fills were increasing for all groups. Postwarning, immediate increases and increasing trends of fluoxetine fills were identified for all groups. CONCLUSIONS: Antidepressant prescription fills declined most postwarning for White youth, suggesting that risk information may have diffused less rapidly to prescribers or caregivers of minorities. Decreases in depression treatment visits help to explain the declines in antidepressant prescribing and were largest for White youth. An increase in incident fluoxetine fills, the only medication indicated for pediatric depression at the time, suggests that the warning may have shifted prescribing practices.

Examining psychotropic medication use among youth in the U.S. by race/ethnicity and psychological impairment.

OBJECTIVE: Clinical practice guidelines underscore the need for careful evaluation of the risk-benefit ratio of psychotropic medications treating mental health disorders among youth. While it is well known that racial/ethnic disparities exist in psychotropic medication use, little is known about whether these differences are driven by over-prescribing among white youth, under-prescribing among minority youth, or both. To build evidence in this area, this study examined racial/ethnic differences in the prescription of psychotropic medications among youth with and without psychological impairment. METHODS: Secondary data on two-year medication use from the 2004-2011 Medical Expenditure Panel Surveys were analyzed. We capitalized on two-year panel data, creating variables that allow for differential sequencing of psychological impairment and medication prescription (e.g., impairment in year 1 or year 2, and a psychotropic medication fill in year 2). Statistical differences were determined using unadjusted rate comparisons and logistic regression models, after adjustment for socio-contextual and health status characteristics. RESULTS: Compared to Black and Latino youth with psychological impairment, White youth were more likely to be prescribed psychotropic medications when impaired. Among youth never having psychological impairment, White youth were also more likely to be prescribed medications compared to their racial/ethnic minority counterparts. CONCLUSIONS: Differences in rates of medication use among youth with and without impairment suggest poor medication targeting across racial/ethnic groups. These results, combined with recent psychotropic medication risk warnings and concerns over increases in psychotropic medication use among youth, suggest that a continued emphasis on accurate targeting of prescribing patterns is needed across racial/ethnic groups.

Patient-Provider Therapeutic Alliance Contributes to Patient Activation in Community Mental Health Clinics.

Patient activation, often conceptualized as an individual trait, contributes to mental health outcomes. This study assessed the relational contributors to activation by estimating the longitudinal association of patient-provider communication and two factors of therapeutic alliance (agreement on tasks/goals and bond), with patient activation. Participants were patients (n = 264) from 13 community-based mental health clinics across the United States. In multivariate models, controlling for patients' individual and clinical characteristics, the task/goal factor of therapeutic alliance emerged as a significant and independent predictor of greater change in patient activation scores. Improving patient activation may require addressing patient-provider interactions such as coming to collaborative agreement on the tasks/goals of care.