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A CBT intervention for low-income, high-risk Latinas reduced depressive symptoms during pregnancy but not during the postpartum period. Low levels of depressive symptoms and lower than expected rates of clinical depression in both groups may partially be due to methodological issues. As perinatal depression is a significant public health problem, more work is needed to prevent perinatal depression in low-income, ethnically diverse women.

Background The purpose of the current study was to determine the sensitivity, specificity, and positive predictive value of three depression screening tools among a low-income African American population of pregnant and recently delivered women enrolled in home visitation programs in a low-income urban community. Methods Ninety-five women enrolled in home visitation programs—32 who were pregnant and 63 with a child <6 months comprise the study sample. Each woman completed a structured clinical interview and three depression screening tools—the Edinburgh Postnatal Depression Scale (EPDS), Center for Epidemiologic Studies Depression Scale (CES-D), and Beck Depression Inventory II (BDI-II). Results Over a quarter of women (28.4%) were experiencing major depression. Each screening tool was highly accurate in detecting major depression and major or minor depression among prenatal and postpartum women, with areas under the curve (AUCs) >0.90. Sensitivities of all screening tools were improved when using cutoffs lower than those considered standard by instrument developers. Limitations Participants were recruited from home visitation programs in an urban context which may limit generalizability to other populations of low-income African American women. Given that no women during pregnancy met criteria for minor depression, it was not possible to determine optimal prenatal cutoff scores. Conclusions Three depression screening tools—the EPDS, CES-D, and BDI-II—appear to be reliable and brief assessments of major and minor depression among low-income African American perinatal women. Providers using these tools should consider using lower cutoff scores to most effectively identify women in need of depression treatment.

Individuals not fully complying with their assigned treatments is a common problem encountered in randomized evaluations of behavioral interventions. Treatment group members rarely attend all sessions or do all "required" activities; control group members sometimes find ways to participate in aspects of the intervention. As a result, there is often interest in estimating both the effect of being assigned to participate in the intervention, as well as the impact of actually participating and doing all of the required activities. Methods known broadly as "complier average causal effects" (CACE) or "instrumental variables" (IV) methods have been developed to estimate this latter effect, but they are more commonly applied in medical and treatment research. Since the use of these statistical techniques in prevention trials has been less widespread, many prevention scientists may not be familiar with the underlying assumptions and limitations of CACE and IV approaches. This paper provides an introduction to these methods, described in the context of randomized controlled trials of two preventive interventions: one for perinatal depression among at-risk women and the other for aggressive disruptive behavior in children. Through these case studies, the underlying assumptions and limitations of these methods are highlighted.

Perinatal depression is a prevalent and detrimental condition. Determining modifiable factors associated with it would identify opportunities for prevention. This paper: 1) identifies depressive symptom trajectories and heterogeneity in those trajectories during pregnancy through the first year postpartum, and 2) examines the association between unintended pregnancy and depressive symptoms. Depressive symptoms (BDI-II) were collected from low-income Hispanic immigrants (n= 215) 5 times from early pregnancy to 12 months postpartum. The sample was at high-risk for perinatal depression and recruited from two prenatal care settings. Growth mixture modeling (GMM) was used to identify distinct trajectories of depressive symptoms over the perinatal period. Multinomial logistic regression was then conducted to examine the association between unintended pregnancy (reported at baseline) and the depression trajectory patterns. Three distinct trajectory patterns of depressive symptoms were identified: high during pregnancy, but low postpartum (“Pregnancy High”: 9.8%); borderline during pregnancy, with a postpartum increase (“Postpartum High”: 10.2%); and low throughout pregnancy and postpartum (“Perinatal Low”: 80.0%). Unintended pregnancy was not associated with the “Pregnancy High” pattern, but was associated with a marginally significant nearly 4-fold increase in risk of the “Postpartum High” pattern in depressive symptoms (RRR= 3.95, p<0.10). Family planning is a potential strategy for the prevention of postpartum depression. Women who report unintended pregnancies during prenatal care must be educated of their increased risk, even if they do not exhibit antenatal depressive symptoms. Routine depression screening should occur postpartum and referral to culturally appropriate treatment should follow positive screening results.