Maternal Role & High-Risk Pregnancy Experience with Antepartum Hospitalization

Purpose. The focus of maternal role development, historically, has been on the tasks and processes during pregnancy as they relate to postpartum role transition. The purpose of this study was to investigate how women hospitalized with high-risk pregnancy cognitively construct pregnancy and impending motherhood. ^ Design. The study employed a triangulation design using a convergence model with a dominant focused ethnographic approach. ^ Setting. The antepartum units of two tertiary care centers in a large metropolitan city in southeast Texas. ^ Sample. Data saturation was determined with thirteen (13) primigravid women who had been hospitalized more than 72 hours with preterm labor (PTL) or preterm premature rupture of membranes (PPROM) who subsequently delivered seventeen (17) infants which included 4 sets of twins. ^ Methods. Open-ended, semi-structured interviews and field work were used to explore the development of maternal role in this population. After collecting descriptive data, long individual interviews were conducted and the Prenatal Self Evaluation Questionnaire (PSEQ), an instrument to measure prenatal adaptation to pregnancy, was administered. The interview focused on exploring the woman's experiences of pregnancy and impending motherhood while hospitalized. Interview data and field notes were coded and analyzed using qualitative thematic analytic techniques. The PSEQ was scored and the findings of the qualitative data and PSEQ data were compared. ^ Findings. Thematic analysis of the qualitative data provided an understanding of the cognitive process that occurs as the pregnant woman builds a relationship with the fetus. Thematic analysis resulted in a conceptual model with two complementary components that occur throughout the pregnancy: Establishing a Relationship and Dynamic Equilibrium. Establishing a Relationship includes subthemes of: Courting, Building a Connection, and Engagement. Dynamic equilibrium is the balance between expectations and reality and exists regardless of pregnancy complications. The negotiation of this potential imbalance is triggered by uncertainty, loss of autonomy and control, and isolation and is exacerbated by the high-risk pregnancy and subsequent hospitalization. These triggers can serve as obstacles to maternal role development, but may be mediated by external support from friends and family or health care providers. Support from others may come in the form of anticipatory guidance, presence, or activities that promote self-agency. PSEQ scores were similar to previous reports, but due to the small sample, scores were used primarily for comparison to qualitative data. The qualitative findings were congruent with the PSEQ findings in all of the subscales except in the concern for the well-being of the baby. Interview reports included comments demonstrating significant concern for the well-being of the infant, yet the related subscale did not demonstrate such concern. ^ Conclusions. An understanding of the cognitive process involved in establishing a relationship with the developing fetus related to impending motherhood and the importance of dynamic equilibrium can allow healthcare providers and those who interact with pregnant women to support development of the maternal role and anticipate those barriers that may impede that process. Findings from this study identify those triggers and mediators that influence development of the maternal role and suggest potential intervening strategies for those involved in the care of childbearing families. ^

A model of the roles of essential kinases in the induction and expression of late long-term potentiation.

The induction of late long-term potentiation (L-LTP) involves complex interactions among second-messenger cascades. To gain insights into these interactions, a mathematical model was developed for L-LTP induction in the CA1 region of the hippocampus. The differential equation-based model represents actions of protein kinase A (PKA), MAP kinase (MAPK), and CaM kinase II (CAMKII) in the vicinity of the synapse, and activation of transcription by CaM kinase IV (CAMKIV) and MAPK. L-LTP is represented by increases in a synaptic weight. Simulations suggest that steep, supralinear stimulus-response relationships between stimuli (e.g., elevations in [Ca(2+)]) and kinase activation are essential for translating brief stimuli into long-lasting gene activation and synaptic weight increases. Convergence of multiple kinase activities to induce L-LTP helps to generate a threshold whereby the amount of L-LTP varies steeply with the number of brief (tetanic) electrical stimuli. The model simulates tetanic, -burst, pairing-induced, and chemical L-LTP, as well as L-LTP due to synaptic tagging. The model also simulates inhibition of L-LTP by inhibition of MAPK, CAMKII, PKA, or CAMKIV. The model predicts results of experiments to delineate mechanisms underlying L-LTP induction and expression. For example, the cAMP antagonist RpcAMPs, which inhibits L-LTP induction, is predicted to inhibit ERK activation. The model also appears useful to clarify similarities and differences between hippocampal L-LTP and long-term synaptic strengthening in other systems.

Simulation study of joint transition and Weibull survival model with shared parameters

This study investigates a theoretical model where a longitudinal process, that is a stationary Markov-Chain, and a Weibull survival process share a bivariate random effect. Furthermore, a Quality-of-Life adjusted survival is calculated as the weighted sum of survival time. Theoretical values of population mean adjusted survival of the described model are computed numerically. The parameters of the bivariate random effect do significantly affect theoretical values of population mean. Maximum-Likelihood and Bayesian methods are applied on simulated data to estimate the model parameters. Based on the parameter estimates, predicated population mean adjusted survival can then be calculated numerically and compared with the theoretical values. Bayesian method and Maximum-Likelihood method provide parameter estimations and population mean prediction with comparable accuracy; however Bayesian method suffers from poor convergence due to autocorrelation and inter-variable correlation. ^