Specifying the effects of religion on medical helpseeking: The case of infertility

Several recent studies have examined the connection between religion and medical service utilization. This relationship is complicated because religiosity may be associated with beliefs that either promote or hinder medical helpseeking. The current study uses structural equation modeling to examine the relationship between religion and fertility-related helpseeking using a probability sample of 2183 infertile women in the United States. We found that, although religiosity is not directly associated with helpseeking for infertility, it is indirectly associated through mediating variables that operate in opposing directions. More specifically, religiosity is associated with greater belief in the importance of motherhood, which in turn is associated with increased likelihood of helpseeking. Religiosity is also associated with greater ethical concerns about infertility treatment, which are associated with decreased likelihood of helpseeking. Additionally, the relationships are not linear throughout the helpseeking process. Thus, the influence of religiosity on infertility helpseeking is indirect and complex. These findings support the growing consensus that religiously-based behaviors and beliefs are associated with levels of health service utilization.

Model complexity affects transient population dynamics following a dispersal event: A case study with pea aphids

Stage-structured population models predict transient population dynamics if the population deviates from the stable stage distribution. Ecologists’ interest in transient dynamics is growing because populations regularly deviate from the stable stage distribution, which can lead to transient dynamics that differ significantly from the stable stage dynamics. Because the structure of a population matrix (i.e., the number of life-history stages) can influence the predicted scale of the deviation, we explored the effect of matrix size on predicted transient dynamics and the resulting amplification of population size. First, we experimentally measured the transition rates between the different life-history stages and the adult fecundity and survival of the aphid, Acythosiphon pisum. Second, we used these data to parameterize models with different numbers of stages. Third, we compared model predictions with empirically measured transient population growth following the introduction of a single adult aphid. We find that the models with the largest number of life-history stages predicted the largest transient population growth rates, but in all models there was a considerable discrepancy between predicted and empirically measured transient peaks and a dramatic underestimation of final population sizes. For instance, the mean population size after 20 days was 2394 aphids compared to the highest predicted population size of 531 aphids; the predicted asymptotic growth rate (λmax) was consistent with the experiments. Possible explanations for this discrepancy are discussed. Includes 4 supplemental files.