Bridging Alone: Religious Conservatism, Marital Homogamy, and Voluntary Association Membership

This study characterizes social insularity of religiously conservative American married couples by examining patterns of voluntary associationmembership. Constructing a dataset of 3938 marital dyads from the second wave of the National Survey of Families and Households, the author investigates whether conservative religious homogamy encourages membership in religious voluntary groups and discourages membership in secular voluntary groups. Results indicate that couples’ shared affiliation with conservative denominations, paired with beliefs in biblical authority and inerrancy, increases the likelihood of religious group membership for husbands and wives and reduces the likelihood of secular group membership for wives, but not for husbands. The social insularity of conservative religious groups appears to be reinforced by homogamy—particularly by wives who share faith with husbands

Training Models in Counseling Psychology: Scientist-Practitioner Versus Practitioner-Scholar

Considerable discussion has occurred through the years regarding models of training. With the recent accreditation of counseling psychology programs espousing the practitioner-scholar model, the importance of reexamining the merits of this as well as the traditional scientist-practitioner is now very important for the future of the field. This article consists of two positions: One pro practitioner-scholar and the other pro scientist-practitioner and con practitioner-scholar. The first position (first part of the article) by Biever, Patterson, and Welch argues for inclusion of the practitioner-scholar model as an alternative for training in counseling psychology. The second position (in the second part of the article) by Stoltenberg, Pace, and Kashubeck reviews concerns with two competing models. These authors conclude that the scientist-practitioner model is a better fit for training in counseling psychology. Recommendations for training within models are presented.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Early Detection of Ovarian Cancer using the Risk of Ovarian Cancer Algorithm with Frequent CA125 Testing in Women at Increased Familial Risk – Combined Results from Two Screening Trials

Purpose: Women at familial/genetic ovarian cancer risk often undergo screening despite unproven efficacy. Research suggests each woman has her own CA125 baseline; significant increases above this level may identify cancers earlier than standard 6- to 12-monthly CA125 > 35 U/mL. Experimental Design: Data from prospective Cancer Genetics Network and Gynecologic Oncology Group trials, which screened 3,692 women (13,080 woman-screening years) with a strong breast/ovarian cancer family history or BRCA1/2 mutations, were combined to assess a novel screening strategy. Specifically, serum CA125 q3 months, evaluated using a risk of ovarian cancer algorithm (ROCA), detected significant increases above each subject's baseline, which triggered transvaginal ultrasound. Specificity and positive predictive value (PPV) were compared with levels derived from general population screening (specificity 90%, PPV 10%), and stage-at-detection was compared with historical high-risk controls. Results: Specificity for ultrasound referral was 92% versus 90% ( P = 0.0001), and PPV was 4.6% versus 10% ( P > 0.10). Eighteen of 19 malignant ovarian neoplasms [prevalent = 4, incident = 6, risk-reducing salpingo-oophorectomy (RRSO) = 9] were detected via screening or RRSO. Among incident cases (which best reflect long-term screening performance), three of six invasive cancers were early-stage (I/II; 50% vs. 10% historical BRCA1 controls; P = 0.016). Six of nine RRSO-related cases were stage I. ROCA flagged three of six (50%) incident cases before CA125 exceeded 35 U/mL. Eight of nine patients with stages 0/I/II ovarian cancer were alive at last follow-up (median 6 years). Conclusions: For screened women at familial/genetic ovarian cancer risk, ROCA q3 months had better early-stage sensitivity at high specificity, and low yet possibly acceptable PPV compared with CA125 > 35 U/mL q6/q12 months, warranting further larger cohort evaluation. Clin Cancer Res; 23(14); 3628-37. ©2017 AACR

Inferring causal molecular networks: empirical assessment through a community-based effort

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense