Objective-This study measured rates of and determined factors associated with mental health service use among a cohort of 465 pregnant and postpartum women receiving care at publicly funded obstetrical clinics.Methods-Women underwent a diagnostic evaluation, were provided with at least one mental health referral, and were encouraged to seek treatment; follow-up with provision of additional referrals occurred at 1, 3, and 6 months after the initial assessment. Logistic regression was used to estimate the relationship between clinical and psychosocial factors and self-reported mental health service use.Results-38.1% of referred women attended at least one mental health visit while only 6% of women remained in treatment during the entire 6-month follow-up interval. Postpartum women were more likely than pregnant women to attend a mental health treatment visit (O.R. = 4.17). Being born in the United States (O.R = 2.06), exposed to interpersonal violence (O.R. = 2.52), and unemployed (O.R. = 2.69) were associated with attending at least one mental health care visit. Women who received a behavioral health referral to the same site as their prenatal or postpartum care were more likely than those women referred offsite to attend a mental health treatment visit (O.R. = 3.23).Conclusions-Despite active follow-up, rates of accessing and particularly continuing in mental health treatment were low. More work is needed to support the integration of specialty behavioral health services in primary care settings accessed by perinatal women.

Given the risk of adverse perinatal outcomes associated with a depressive disorder, the Health Resources and Services Administration’s (HRSA) Maternal and Child Health Bureau (MCHB) from 2001–2005 devoted resources through the Federal Healthy Start Initiative to screen pregnant women for depression and link them with services. In this report, we present the evaluation of a program that screened for depression and provided services for women with depressive symptoms or psychiatric distress in pregnancy to assess whether the program was associated with a reduction in babies born low birth weight, small for gestational age, or preterm. The program impact was examined among 1,100 women in three cohorts enrolled from 2001–2005 that included: (1) subjects recruited prior to the inception of the Healthy Start Initiative; (2) subjects enrolled in the Healthy Start Initiative; and (3) a comparison group recruited during the project period but not enrolled in the Healthy Start Initiative. After adjustment for covariates, women with probable depression were over one and a half times more likely to give birth to a preterm baby than non depressed women. Neither adjusted nor unadjusted risks for delivery of preterm, low birth weight or small for gestational age infants were significantly lower for women enrolled in Healthy Start as compared to women not enrolled in Healthy Start. However, regardless of enrollment in Healthy Start, women who delivered babies after the Healthy Start program began were 85% less likely to deliver preterm babies than women giving birth before the program began. Depression status conferred increased risk of adverse birth outcomes, results that were not altered by participation in the Healthy Start program. We cannot exclude the possibility that the community activities of the Healthy Start program promoted increased attention to health issues among depressed women and hence enhance birth outcomes.

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Objective: To address problems with low rates of detection and treatment of depression of pregnant and postpartum women, many advocate depression screening in obstetrical settings. This study evaluated the Healthy Start depression initiative to assess whether it resulted in diminished rates of depressive symptoms and increased rates of detection, referral, and treatment among pregnant and postpartum women. Methods: Three cohorts were used to examine the program impact: a pre–Healthy Start depression initiative cohort, a post–Healthy Start depression initiative cohort that was enrolled in New Haven Healthy Start, and a post–Healthy Start depression initiative cohort not enrolled in the New Haven program. Participants included 1,336 pregnant and postpartum women receiving obstetrical care at publicly funded health care clinics. Measures included the Primary Care Evaluation of Mental Disorders Brief Patient Health Questionnaire; the PTSD Symptom Scale; a five-item modification of the Conflict Tactics Scale; and questions regarding alcohol, illicit substances, and general medical and obstetrical history. Results: The Healthy Start depression initiative changed neither levels of depressive symptoms nor use of depression treatment in unselected populations. The initiative may have decreased the rate of referral for depression in the cohort under study. Conclusions: Universal screening and support for treatment referral by paraprofessionals did not reduce the overall rates of depressive symptoms of perinatal women who received care at publicly funded obstetrical clinics. Future work on depression screening should consider strategies to engage women who are more severely affected by a depressive disorder in behavioral health treatment.

To achieve a successful grasp, gripper attributes including geometry and kinematics play a role equally important to the target object geometry. The majority of previous work has focused on developing grasp methods that generalize over novel object geometry but are specific to a certain robot hand. We propose UniGrasp, an efficient data-driven grasp synthesis method that considers both the object geometry and gripper attributes as inputs. UniGrasp is based on a novel deep neural network architecture that selects sets of contact points from the input point cloud of the object. The proposed model is trained on a large dataset to produce contact points that are in force closure and reachable by the robot hand. By using contact points as output, we can transfer between a diverse set of Nfingered robotic hands. Our model produces over 90% valid contact points in Top10 predictions in simulation and more than 90% successful grasps in the real world experiments for various known two-fingered and three-fingered grippers. Our model also achieves 93% and 83% successful grasps in the real world experiments for a novel two-fingered and five-fingered anthropomorphic robotic hand, respectively.