A Primer on Meta-Analytic Structural Equation Modeling: the Case of Depression.

In this paper, we show how the methods of systematic reviewing and meta-analysis can be used in conjunction with structural equation modeling to summarize the results of studies in a way that will facilitate the theory development and testing needed to advance prevention science. We begin with a high-level overview of the considerations that researchers need to address when using meta-analytic structural equation modeling (MASEM) and then discuss a research project that brings together theoretically important cognitive constructs related to depression to (a) show how these constructs are related, (b) test the direct and indirect effects of dysfunctional attitudes on depression, and (c) test the effects of study-level moderating variables. Our results suggest that the indirect effect of dysfunctional attitudes (via negative automatic thinking) on depression is two and a half times larger than the direct effect of dysfunctional attitudes on depression. Of the three study-level moderators tested, only sample recruitment method (clinical vs general vs mixed) yielded different patterns of results. The primary difference observed was that the dysfunctional attitudes → automatic thoughts path was less strong for clinical samples than it was for general and mixed samples. These results illustrate how MASEM can be used to compare theoretically derived models and predictions resulting in a richer understanding of both the empirical results and the theories underlying them.

Genetic Mapping of a new Hippo allele, HpoN.1.2, in Drosophila melanogaster.

Genetic screens provide a mechanism to identify genes involved with different cellular and organismal processes. Using a Flp/FRT screen in the Drosophila eye we identified mutations that result in alterations and de-regulation of cell growth and division. From this screen a group of undergraduate researchers part of the Fly-CURE consortium mapped and characterized a new allele of the gene Hippo, HpoN.1.2.

Impacts of the San Francisco Bay Area shelter-in-place during the COVID-19 pandemic on urban heat fluxes.

The purpose of this study was to make quantitative connections between changes in social and economic activities in northern California urban areas and related Earth system environmental responses to the COVID-19 pandemic in 2020. We tested the hypothesis that the absence of worker activities during Shelter-in-Place in the San Francisco Bay Area detectably altered the infrared heat flux from parking lots, highways, and large building rooftops, caused primarily by quantitative changes in the reflective properties in these different classes of urban surfaces. The Landsat satellite's thermal infrared (TIR) sensor imagery for surface temperature (ST) was quantified for all the large urban features in the Bay Area that have flat (impervious) surfaces, such parking lots, wide roadways, and rooftops. These large impervious surface features in the five-county Bay Area were first delineated and classified using sub-meter aerial imagery from the National Agriculture Imagery Program (NAIP). We then compared Landsat ST data acquired on (or near) the same dates from the three previous years (2017-2019) for all these contiguous impervious surfaces. Results showed that all the large parking lots, roadway corridors, and industrial/commercial rooftops across the entire Bay Area urban landscape were detected by Landsat ST time series as significantly cooler (by 5o C to 8o C) during the unprecedented Shelter-in-Place period of mid-March to late-May of 2020, compared to same months of the three previous years. The explanation for this region-wide cooling pattern in 2020 that was best supported by both remote sensing and ground-based data sets was that relatively low atmospheric aerosol lower (PM2.5) concentrations from mid-March to late May of 2020 resulted in weaker temperature inversions over the Bay Area, higher diurnal surface mixing, and lowered urban surface temperatures, compared to the three previous years.

LARS&LISA: a universal school-based cognitive-behavioral program to prevent adolescent depression.

Adolescent depression is a prevailing international mental health concern as up to 27% of adolescents experience either subsyndromal depression or a major depressive episode by the age of 18. Depression in adolescence has been found to negatively impact current and future academic achievement, functioning, mental health, and quality of life. Accordingly, the authors emphasize the importance of proactively preventing depression (and its negative outcomes) instead of waiting and having to "fix" the problems after they have already developed. The current article begins with a discussion of the various types of prevention, including their respective advantages and disadvantages. Further and more importantly, the article's primary focus is to provide a summary of the theoretical basis, development of, empirical support for, and content of a universal school-based cognitive-behavioral program to prevent adolescent depression entitled LARS&LISA (Lust An Realistischer Sicht & Leichtigkeit Im Sozialen Alltag). As the program exists within the overlapping realms of universal prevention, school-based programs, and cognitive-behavioral interventions, the content of this article is relevant to all three areas and offers insight into the development of depression prevention in general. Finally, empirical support for the positive effects of the program is presented and some ideas for further research are discussed.

LARS&LISA: a universal school-based cognitive-behavioral program to prevent adolescent depression

Abstract Adolescent depression is a prevailing international mental health concern as up to 27% of adolescents experience either subsyndromal depression or a major depressive episode by the age of 18. Depression in adolescence has been found to negatively impact current and future academic achievement, functioning, mental health, and quality of life. Accordingly, the authors emphasize the importance of proactively preventing depression (and its negative outcomes) instead of waiting and having to "fix" the problems after they have already developed. The current article begins with a discussion of the various types of prevention, including their respective advantages and disadvantages. Further and more importantly, the article's primary focus is to provide a summary of the theoretical basis, development of, empirical support for, and content of a universal school-based cognitive-behavioral program to prevent adolescent depression entitled LARS&LISA (Lust An Realistischer Sicht & Leichtigkeit Im Sozialen Alltag). As the program exists within the overlapping realms of universal prevention, school-based programs, and cognitive-behavioral interventions, the content of this article is relevant to all three areas and offers insight into the development of depression prevention in general. Finally, empirical support for the positive effects of the program is presented and some ideas for further research are discussed.