Filtering by
- Member of: ASU Regents' Professors Open Access Works
Testing mediation models is critical for identifying potential variables that need to be targeted to effectively change one or more outcome variables. In addition, it is now common practice for clinicians to use multiple informant (MI) data in studies of statistical mediation. By coupling the use of MI data with statistical mediation analysis, clinical researchers can combine the benefits of both techniques. Integrating the information from MIs into a statistical mediation model creates various methodological and practical challenges. The authors review prior methodological approaches to MI mediation analysis in clinical research and propose a new latent variable approach that overcomes some limitations of prior approaches. An application of the new approach to mother, father, and child reports of impulsivity, frustration tolerance, and externalizing problems (N = 454) is presented. The results showed that frustration tolerance mediated the relationship between impulsivity and externalizing problems. The new approach allows for a more comprehensive and effective use of MI data when testing mediation models.
There is a substantial literature of correlational findings from studies in developed countries where abortion is legal that are riddled with methodological problems and selective biases that exaggerate post-pregnancy mental health risks of abortion while minimizing risks for unwanted childbearing. Health professionals need to be able to critically evaluate this literature and use caution when generalizing findings across contexts differing in legal grounds for abortion. The impact of diversity in women’s characteristics, circumstances, and reasons for avoiding childbirth has not been adequately incorporated in theory or research seeking to explain the variations that are found in women’s post-abortion mental health. Critical reviews have established that predictors of problems after abortion or childbirth are similar. Further, when a woman has an unwanted pregnancy, i.e., a pregnancy that she does not wish to end in a term birth, the likelihood that she will have post-pregnancy mental health problems is similar regardless of pregnancy outcome (abortion vs. delivery). Selective sampling bias that advantages the delivery group, common risk factors, and confounding of abortion with unintended pregnancy explain the correlation of legal abortion with negative outcomes observed in the literature from developed countries. Meanwhile, documented negative effects of unwanted pregnancy and childbearing are multiple, severe, and long-lasting for mother and child. Changing societal conditions, particularly in developing countries, provide an opportunity for correcting biases and limitations of current research. High quality studies aimed at understanding the varied relationships of unintended pregnancy to mental health outcomes –both positive and negative– in the context of the diverse circumstances of women’s lives are sorely needed. Such studies can inform the development of programs to re- duce unwanted childbearing and promote pre- and post-pregnancy mental health for all women, regardless of how they choose to end their pregnancy.
Cancer is sometimes depicted as a reversion to single cell behavior in cells adapted to live in a multicellular assembly. If this is the case, one would expect that mutation in cancer disrupts functional mechanisms that suppress cell-level traits detrimental to multicellularity. Such mechanisms should have evolved with or after the emergence of multicellularity. This leads to two related, but distinct hypotheses: 1) Somatic mutations in cancer will occur in genes that are younger than the emergence of multicellularity (1000 million years [MY]); and 2) genes that are frequently mutated in cancer and whose mutations are functionally important for the emergence of the cancer phenotype evolved within the past 1000 million years, and thus would exhibit an age distribution that is skewed to younger genes. In order to investigate these hypotheses we estimated the evolutionary ages of all human genes and then studied the probability of mutation and their biological function in relation to their age and genomic location for both normal germline and cancer contexts.
We observed that under a model of uniform random mutation across the genome, controlled for gene size, genes less than 500 MY were more frequently mutated in both cases. Paradoxically, causal genes, defined in the COSMIC Cancer Gene Census, were depleted in this age group. When we used functional enrichment analysis to explain this unexpected result we discovered that COSMIC genes with recessive disease phenotypes were enriched for DNA repair and cell cycle control. The non-mutated genes in these pathways are orthologous to those underlying stress-induced mutation in bacteria, which results in the clustering of single nucleotide variations. COSMIC genes were less common in regions where the probability of observing mutational clusters is high, although they are approximately 2-fold more likely to harbor mutational clusters compared to other human genes. Our results suggest this ancient mutational response to stress that evolved among prokaryotes was co-opted to maintain diversity in the germline and immune system, while the original phenotype is restored in cancer. Reversion to a stress-induced mutational response is a hallmark of cancer that allows for effectively searching “protected” genome space where genes causally implicated in cancer are located and underlies the high adaptive potential and concomitant therapeutic resistance that is characteristic of cancer.