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Objective: To investigate racial/ethnic differences in teachers' and other adults' identification and/or encouragement of parents to seek treatment for psychiatric problems in their children and to evaluate if and whether identification/encouragement is associated with service use. Method: Data on identification/encouragement to seek treatment for externalizing disorders (i.e., attention-deficit/hyperactivity disorder, oppositional-defiant disorder, and/or conduct disorder) and internalizing disorders (i.e., major depressive episode/dysthymia and/or separation anxiety disorder) and services used were obtained for 6,112 adolescents (13-17 years of age) in the National Comorbidity Survey Adolescent Supplement. Racial/ethnic differences were examined for Latinos, non-Latino blacks, and non-Latino whites. Results: There were few racial/ethnic differences in rates of youth identification/encouragement and how identification/encouragement related to service use. Only non-Latino black youth with low severity internalizing disorders were less likely to be identified/encouraged to seek services compared with non-Latino white youth with the same characteristics (odds ratio [OR] = 0.4, 95% confidence interval [CI] = [0.2-0.7]). Identification/encouragement increased the likelihood of seeking services for externalizing and internalizing disorders for all youth. However, compared with their non-Latino white counterparts, non-Latino black youth who met criteria for internalizing disorders appeared less likely to have used any services (OR = 0.4, 95%, CI = 0.2-0.7), after adjusting for identification/encouragement, clinical, and sociodemographic characteristics. Non-Latino black youth with internalizing disorders and without identification/encouragement were less likely to use the specialty care sector than their non-Latino white counterparts. Conclusions: In this study of a nationally representative sample of adolescents, almost no ethnic/racial differences in identification/encouragement were found. However, identification/encouragement may increase service use for all youth. (Contains 6 tables.)

Objectives. We examined potential pathways by which time in the United States may relate to differences in the predicted probability of past-year psychiatric disorder among Latino immigrants as compared with US-born Latinos. Methods. We estimated predicted probabilities of psychiatric disorder for US-born and immigrant groups with varying time in the United States, adjusting for different combinations of covariates. We examined 6 pathways by which time in the United States could be associated with psychiatric disorders. Results. Increased time in the United States is associated with higher risk of psychiatric disorders among Latino immigrants. After adjustment for covariates, differences in psychiatric disorder rates between US-born and immigrant Latinos disappear. Discrimination and family cultural conflict appear to play a significant role in the association between time in the United States and the likelihood of developing psychiatric disorders. Conclusions. Increased perceived discrimination and family cultural conflict are pathways by which acculturation might relate to deterioration of mental health for immigrants. Future studies assessing how these implicit pathways evolve as contact with US culture increases may help to identify strategies for ensuring maintenance of mental health for Latino immigrants. (Am J Public Health. 2009;99:2247-2254. doi: 10.2105/AJPH.2008.137091)

This article presents analyses of a representative sample of U.S. Latinos (N = 2,540) to investigate whether family cohesion moderates the effects of cultural conflict on psychological distress. The results for the aggregated Latino group suggest a significant association between family cohesion and lower psychological distress, and the combination of strong family cohesion with presence of family cultural conflict is associated with higher psychological distress. However, this association differs by Latino groups. In this study, no association for Puerto Ricans is seen; Cuban results are similar to the aggregate group, family cultural conflict in Mexicans is associated with higher psychological distress whereas family cohesion in other Latinos is associated with higher psychological distress. Implications of these findings are discussed to unravel the differences in family dynamics across Latino subethnic groups. Keywords: family cohesion; family conflict; psychological distress; Latino ethnic groups

In assessing the mechanism of treatment efficacy in randomized clinical trials, investigators often perform mediation analyses by analyzing if the significant intent-to-treat treatment effect on outcome occurs through or around a third intermediate or mediating variable: indirect and direct effects, respectively. Standard mediation analyses assume sequential ignorability, i.e. conditional on covariates the intermediate or mediating factor is randomly assigned, as is the treatment in a randomized clinical trial. This research focuses on the application of the principal stratification (PS) approach for estimating the direct effect of a randomized treatment but without the standard sequential ignorability assumption. This approach is used to estimate the direct effect of treatment as a difference between expectations of potential outcomes within latent subgroups of participants for whom the intermediate variable behavior would be constant, regardless of the randomized treatment assignment. Using a Bayesian estimation procedure, we also assess the sensitivity of results based on the PS approach to heterogeneity of the variances among these principal strata. We assess this approach with simulations and apply it to two psychiatric examples. Both examples and the simulations indicated robustness of our findings to the homogeneous variance assumption. However, simulations showed that the magnitude of treatment effects derived under the PS approach were sensitive to model mis-specification. Copyright © 2009 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Motivated by the need to meaningfully implement the Institute of Medicine's (IOM's) definition of health care disparity, this paper proposes statistical frameworks that lay out explicitly the needed causal assumptions for defining disparity measures. Our key emphasis is that a scientifically defensible disparity measure must take into account the direction of the causal relationship between allowable covariates that are not considered to be contributors to disparity and non-allowable covariates that are considered to be contributors to disparity, to avoid flawed disparity measures based on implausible populations that are not relevant for clinical or policy decisions. However, these causal relationships are usually unknown and undetectable from observed data. Consequently, we must make strong causal assumptions in order to proceed. Two frameworks are proposed in this paper, one is the conditional disparity framework under the assumption that allowable covariates impact non-allowable covariates but not vice versa. The other is the marginal disparity framework under the assumption that non-allowable covariates impact allowable ones but not vice versa. We establish theoretical conditions under which the two disparity measures are the same and present a theoretical example showing that the difference between the two disparity measures can be arbitrarily large. Using data from the Collaborative Psychiatric Epidemiology Survey, we also provide an example where the conditional disparity is misled by Simpson's paradox, whereas the marginal disparity approach handles it correctly. Copyright © 2008 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Lin et al. (http://www.biostatsresearch.com/upennbiostat/papers/, 2006) proposed a nested Markov compliance class model in the Imbens and Rubin compliance class model framework to account for time-varying subject noncompliance in longitudinal randomized intervention studies. We use superclasses, or latent compliance class principal strata, to describe longitudinal compliance patterns, and time-varying compliance classes are assumed to depend on the history of compliance. In this paper, we search for good subject-level baseline predictors of these superclasses and also examine the relationship between these superclasses and all-cause mortality. Since the superclasses are completely latent in all subjects, we utilize multiple imputation techniques to draw inferences. We apply this approach to a randomized intervention study for elderly primary care patients with depression. [ABSTRACT FROM AUTHOR]

Objective: Our purpose was to determine the personal characteristics associated with different patterns of adherence to the antidepressant citalopram in a primary care trial of depression management. Method: The study sample consisted of 228 adults aged 60 years and older recruited from primary care settings and who participated in a depression intervention. The intervention consisted of services of trained care managers, who offered recommendations to physicians following a clinical algorithm and helped patients with treatment adherence. Adherence to the antidepressant citalopram was measured using pill counts. We employed the latent class model to classify patients according to the pattern of adherence to citalopram over time. We examined the association of sociodemographic characteristics, depression status, cognitive status, and medical comorbidity with the resulting classes of adherence. Results: The latent class model generated three classes of adherence: known to be adherent, unknown adherence, and known to be nonadherent. Participants who were white were more likely to be in the known to be adherent class than in the known to be nonadherent class (odds ratio (OR) = 10.38, 95% confidence interval (CI) [3.47, 31.12]). Married participants were less likely to be in the unknown adherence class than the known to be nonadherent class (OR = 0.28, 95% CI [0.09, 0.85]). No associations between age, gender, education level, depression status, cognitive status, or medical comorbidity and classes of adherence were found. Conclusions: We found stronger relationships between ethnicity and marital status with patterns of adherence to citalopram than we did other personal characteristics. Identification of a subgroup of patients at particularly high risk of nonadherence is important for the development of adherence interventions. [ABSTRACT FROM AUTHOR]

A data monitoring committee (DMC) is a group of clinicians and biostatisticians appointed by study sponsors who provide independent assessment of the safety, scientific validity and integrity of clinical trials. In the United States, the Food and Drug Administration requires the formation of DMC in all trials that assess new interventions. DMC are also strongly recommended in other clinical studies that have substantial safety issues, that have double-blind treatment assignment or that are expected to have a major impact on clinical practice. They are important in clinical research in psychiatry because they provide an added layer of protection for the vulnerable populations that are often enrolled in such studies. This report describes the role, formation and operation of DMC. [ABSTRACT FROM AUTHOR]

Motivated by the need to meaningfully implement the Institute of Medicine's (IOM's) definition of health care disparity, this paper proposes statistical frameworks that lay out explicitly the needed causal assumptions for defining disparity measures. Our key emphasis is that a scientifically defensible disparity measure must take into account the direction of the causal relationship between allowable covariates that are not considered to be contributors to disparity and non-allowable covariates that are considered to be contributors to disparity, to avoid flawed disparity measures based on implausible populations that are not relevant for clinical or policy decisions. However, these causal relationships are usually unknown and undetectable from observed data. Consequently, we must make strong causal assumptions in order to proceed. Two frameworks are proposed in this paper, one is the conditional disparity framework under the assumption that allowable covariates impact non-allowable covariates but not vice versa. The other is the marginal disparity framework under the assumption that non-allowable covariates impact allowable ones but not vice versa. We establish theoretical conditions under which the two disparity measures are the same and present a theoretical example showing that the difference between the two disparity measures can be arbitrarily large. Using data from the Collaborative Psychiatric Epidemiology Survey, we also provide an example where the conditional disparity is misled by Simpson's paradox, whereas the marginal disparity approach handles it correctly., Statistics