This multi-wave longitudinal study investigated potential transactional and accumulating influences among co-rumination, interpersonal stressors, and internalizing symptoms among a sample of early and middle adolescents (N=350; 6th–10th graders). Youth completed self-report measures of co-rumination at Times 1, 2, and 4, and negative life events, internalizing symptoms (general depressive, specific anhedonic depressive, anxious arousal, general internalizing) and externalizing problems at all four time points (5 weeks between each assessment across 4 months). Results supported hypotheses. First, baseline co-rumination predicted prospective trajectories of all forms of internalizing symptoms but not externalizing problems. Second, baseline co-rumination predicted generation of interpersonal dependent, but not interpersonal independent or non-interpersonal stressors. Third, interpersonal dependent events partially mediated the longitudinal association between baseline co-rumination and prospective internalizing symptoms. Fourth, a transactional, bi-directional set of associations was supported in that initial internalizing symptoms and stressors predicted later elevations in co-rumination, and in turn, co-rumination predicted later symptoms through the mediating role of interpersonal stressors to complete both streams in the transactional chain of influence. Finally, girls and older adolescents exhibited higher co-rumination, but neither age nor sex moderated any associations. These findings are discussed within a transactional, developmental cascade model.

This study examines the effects of perceived housing environment on selected well-being outcomes of a seriously mentally ill population in supported housing programs. Individuals live independently in their own apartments and use supportive mental health services as needed. The study conceptualizes one's housing environment as existing at the apartment, neighborhood and the surrounding community levels of analysis that, taken together, form a multi-dimensional construct of housing environment. Self-report data from interviews with a sample of seriously mentally ill adults is paired with (a) observer ratings of housing environments, (b) census profiles of the surrounding community and (c) case manager ratings of clients' functioning in order to explore the effects of supported housing environments on well-being outcomes. Well-being is operationalized here as levels of psychiatric distress, recovery orientation, residential satisfaction, and adaptive functioning. Hierarchical regression models posit that apartment, neighborhood and census tract level variables are unique predictors of these domains of well-being. Results show that neighborhood level variables, especially those relating to the social environment, are the most influential predictors for understanding variance in well-being, with apartment level variables also contributing to understanding of housing environment effects. The census tract level predictors did not contribute a significant amount of explanation of the variance in well-being outcomes. Implications for supported housing programs and the role of ecological levels of analysis in conceptualizing and measuring housing environment influence are discussed.

Prediction of tandem mass spectrometric (MS/MS) fragmentation for non-peptidic molecules based on structure is of immense interest to the mass spectrometrist. If a reliable approach to MS/MS prediction could be achieved its impact within the pharmaceutical industry could be immense. Many publications have stressed that the fragmentation of a molecular ion or protonated molecule is a complex process that depends on many parameters, making prediction difficult. Commercial prediction software relies on a collection of general heuristic rules of fragmentation, which involve cleaving every bond in the structure to produce a list of 'expected' masses which can be compared with the experimental data. These approaches do not take into account the thermodynamic or molecular orbital effects that impact on the molecule at the point of protonation which could influence the potential sites of bond cleavage based on the structural motif. A series of compounds have been studied by examining the experimentally derived high-resolution MS/MS data and comparing it with the in silico modelling of the neutral and protonated structures. The effect that protonation at specific sites can have on the bond lengths has also been determined. We have calculated the thermodynamically most stable protonated species and have observed how that information can help predict the cleavage site for that ion. The data have shown that this use of in silico techniques could be a possible way to predict MS/MS spectra.

Community integration research explores community contexts and factors that encourage or hinder individuals with serious mental illness (SMI) from actively participating in community life. This research agenda can be advanced by using mixed-methods that better document the relationships between contextual factors and individual experience. Two such methods were applied to a mixedmethods study of 40 adults with SMI living in independent housing in the Southeastern United States. Their contextualized experiences of community integration were measured by applying innovative participatory mapping and Geographic Information Systems (GIS) mapping techniques. Use of these methods in conjunction with one another facilitated the creation of activity spaces, which can measure geographic accessibility and help to represent an individual's experience of place and degree of mobility. The utility of these newly applied methods for better understanding community integration for persons with SMI is explored and implications for using these measures in research and practice are discussed. KeywordsPsychiatric disabilities; Community integration; Geographic Information Systems; Participatory Mapping; Activity Space All too often, individuals with serious mental illness experience isolation and lack opportunities to fulfill meaningful roles and activities in their communities. This is unfortunate because there is abundant evidence that participation in community life positively affects health (Antze, 1979;Barrera, 2000;Strauss & Carpenter, 1977). While most research on the experience of serious mental illness (SMI) has focused on individual's functioning, we argue that it is important to understand the role of place in participation in community life, particularly as it relates to health. The emerging body of community integration research has been devoted to studying the community contexts and factors that encourage or hinder individuals with serious mental illness from actively participating in community life (e.g., Aubry & Myner, 1996;Gulcer, Tsemberis, Stefancic, & Greenwood, 2007;Prince & Gerber, 2005;Wong & Solomon, 2002). This research agenda can be advanced by using methods that better document the relationships of contextual factors to individual experience. The overwhelming majority of community integration studies have used survey and self-report data to understand the experience of community life for persons with SMI. Further, few studies have directly assessed the impact of place on community integration, despite suggestions that it may be a critical component in the integration process (Carling, 1995;Yanos, 2007). The authors of this paper aim to contribute to the literature by presenting the methods and findings from a pair of innovative approaches to conceptualizing and measuring community integration. We argue NIH Public Access NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscriptthat an expansion of the methods used for community integration research can better ground investigation in...

Ion mobility mass spectrometry is used to measure the drift-time of an ion. The drift-time of an ion can be used to calculate the collision cross-section (CCS) in travelling wave ion mobility (e.g. Waters Synapt and Vion instruments) or directly determine the experimental CCS (e.g. Agilent 6560 instrument and many drift-tube instruments). A comparison of the experimental CCS and theoretical CCS values obtained from trajectory method He(g) parameterised MOBCAL and N2(g) parameterised MOBCAL software, for a range of 20 'small molecules' is presented. This study utilises density functional theory B3LYP methods and the 6-31G+(d,p) basis set to calculate theoretical CCS values. This study seeks to assess the accuracy of a common procedure using CCS calibration with poly-(d/l)-alanine derived from drift-cell measurements and the original release of MOBCAL software and compare it with recent improvements with a drug-like molecule calibration set and a revision of MOBCAL parameterised for N2(g) drift gas. This study represents one of the first quantitative evaluations of the agreement between theoretical CCS and experimental CCS values for a range of small pharmaceutically relevant molecules using travelling wave ion mobility mass spectrometry. Accurate theoretical CCS may allow optimisation of ion mobility separations in silico, provide CCS databases that can confirm structures without the need for alternative analytical tools such as nuclear magnetic resonance spectroscopy (NMR) and assignment of unknowns and positional isomers without requiring reference materials.