Rating scales are often used to measure behavioral constructs. Yet, different informants’ ratings may not necessarily agree. The situational specificity (SS) perspective postulates that discrepancies between ratings by different informants are primarily attributable to contextual behavior of the people being rated. The multitrait-multimethod (MTMM) perspective, however, attributes discrepancies between informants to rater bias, i.e., each informant provides a systematically distorted picture of the person being rated. Similarly, the Attribution-Bias-Context (ABC) perspective also attributes informant discrepancies to systematic biases. Within the context of measuring hierarchical constructs, we proposed a hybrid perspective that takes account of variance attributable to the behavior of the person being rated in a particular context from the perspective of a specific informant. We then provided a parametric representation of this perspective and analyses of mother, teacher, and self-ratings of Rule-Breaking and Aggressive Behavior to illustrate features of the model. Strengths and limitations of the SS, MTMM, and hybrid perspectives are discussed.
The prevalence of obesity in the United States continues to rise, increasing individual vulnerability to an array of adverse health outcomes. One factor that has been implicated causally in the increased accumulation of fat and excess food intake is the activity of the limbic-hypothalamic-pituitary-adrenal (LHPA) axis in the face of relentless stressor exposure. However, translational and clinical research continues to understudy the effects sex and gonadal hormones and LHPA axis dysfunction in the etiology of obesity even though women continue to be at greater risk than men for stress-induced disorders, including depression, emotional feeding and obesity. The current review will emphasize the need for sex-specific evaluation of the relationship between stress exposure and LHPA axis activity on individual risk for obesity by summarizing data generated by animal models currently being leveraged to determine the etiology of stress-induced alterations in feeding behavior and metabolism. There exists a clear lack of translational models that have been used to study female-specific risk. One translational model of psychosocial stress exposure that has proven fruitful in elucidating potential mechanisms by which females are at increased risk for stress-induced adverse health outcomes is that of social subordination in socially housed female macaque monkeys. Data from subordinate female monkeys suggest that increased risk for emotional eating and the development of obesity in females may be due to LHPA axis-induced changes in the behavioral and physiological sensitivity of estradiol. The lack in understanding of the mechanisms underlying these alterations necessitate the need to account for the effects of sex and gonadal hormones in the rationale, design, implementation, analysis and interpretation of results in our studies of stress axis function in obesity. Doing so may lead to the identification of novel therapeutic targets with which to combat stress-induced obesity exclusively in females.
Background:
Despite tremendous potential for public health impact and continued investments in development and evaluation, it is rare for eHealth behavioral interventions to be implemented broadly in practice. Intervention developers may not be planning for implementation when designing technology-enabled interventions, thus creating greater challenges for real-world deployment following a research trial. To facilitate faster translation to practice, we aimed to provide researchers and developers with an implementation-focused approach and set of design considerations as they develop new eHealth programs.
Methods:
Using the Accelerated Creation-to-Sustainment model as a lens, we examined challenges and successes experienced during the development and evaluation of four diverse eHealth HIV prevention programs for young men who have sex with men: Keep It Up!, Harnessing Online Peer Education, Guy2Guy, and HealthMindr. HIV is useful for studying eHealth implementation because of the substantial proliferation of diverse eHealth interventions with strong evidence of reach and efficacy and the responsiveness to rapid and radical disruptions in the field.
Results:
Rather than locked-down products to be disseminated, eHealth interventions are complex sociotechnical systems that require continual optimization, vigilance to monitor and troubleshoot technological issues, and decision rules to refresh content and functionality while maintaining fidelity to core intervention principles. Platform choice and sociotechnical relationships (among end users, implementers, and the technology) heavily influence implementation needs and challenges. We present a checklist of critical implementation questions to address during intervention development.
Conclusion:
In the absence of a clear path forward for eHealth implementation, deliberate design of an eHealth intervention’s service and technological components in tandem with their implementation plans is critical to mitigating barriers to widespread use. The design considerations presented can be used by developers, evaluators, reviewers, and funders to prioritize the pragmatic scalability of eHealth interventions in research.
Building on interpersonal theories of depression, the current study sought to explore whether early childhood social withdrawal serves as a risk factor for depressive symptoms and diagnoses in young adulthood. The researchers hypothesized that social impairment at age 15 would mediate the association between social withdrawal at age 5 and depression by age 20. This mediational model was tested in a community sample of 702 Australian youth followed from mother's pregnancy to youth age 20. Structural equation modeling analyses found support for a model in which childhood social withdrawal predicted adolescent social impairment, which, in turn, predicted depression in young adulthood. Additionally, gender was found to moderate the relationship between adolescent social impairment and depression in early adulthood, with females exhibiting a stronger association between social functioning and depression at the symptom and diagnostic level. This study illuminates one potential pathway from early developing social difficulties to later depressive symptoms and disorders.
Affective spectrum and anxiety disorders have come to be recognized as the most prevalently diagnosed psychiatric disorders. Among a suite of potential causes, changes in mitochondrial energy metabolism and function have been associated with such disorders. Thus, proteins that specifically change mitochondrial functionality could be identified as molecular targets for drugs related to treatment for affective spectrum disorders. Here, we report generation of transgenic mice overexpressing the scaffolding and mitophagy related protein Sequestosome1 (SQSTM1/p62) or a single point mutant (P392L) in the UBA domain of SQSTM1/p62. We show that overexpression of SQSTM1/p62 increases mitochondrial energy output and improves transcription factor import into the mitochondrial matrix. These elevated levels of mitochondrial functionality correlate directly with discernible improvements in mouse behaviors related to affective spectrum and anxiety disorders. We also describe how overexpression of SQSTM1/p62 improves spatial learning and long term memory formation in these transgenic mice. These results suggest that SQSTM1/p62 provides an attractive target for therapeutic agents potentially suitable for the treatment of anxiety and affective spectrum disorders.
Virtual organisms animated by a computational theory of selection by consequences responded on symmetrical and asymmetrical concurrent schedules of reinforcement. The theory instantiated Darwinian principles of selection, reproduction, and mutation such that a population of potential behaviors evolved under the selection pressure exerted by reinforcement from the environment. The virtual organisms' steady-state behavior was well described by the power function matching equation, and the parameters of the equation behaved in ways that were consistent with findings from experiments with live organisms. Together with previous research on single-alternative schedules (McDowell, 2004; McDowell & Caron, 2007) these results indicate that the equations of matching theory are emergent properties of the evolutionary dynamics of selection by consequences.
by
Mónica López-Vicente;
Oktay Agcaoglu;
Laura Pérez-Crespo;
Fernando Estévez-López;
José María Heredia-Genestar;
Rosa H Mulder;
John C Flournoy;
Anna CK van Duijvenvoorde;
Berna Güroğlu;
Tonya White;
Viince D Calhoun;
Henning Tiemeier;
Ryan L Muetzel
The longitudinal study of typical neurodevelopment is key for understanding deviations due to specific factors, such as psychopathology. However, research utilizing repeated measurements remains scarce. Resting-state functional magnetic resonance imaging (MRI) studies have traditionally examined connectivity as ‘static’ during the measurement period. In contrast, dynamic approaches offer a more comprehensive representation of functional connectivity by allowing for different connectivity configurations (time varying connectivity) throughout the scanning session. Our objective was to characterize the longitudinal developmental changes in dynamic functional connectivity in a population-based pediatric sample. Resting-state MRI data were acquired at the ages of 10 (range 8-to-12, n = 3,327) and 14 (range 13-to-15, n = 2,404) years old using a single, study-dedicated 3 Tesla scanner. A fully-automated spatially constrained group-independent component analysis (ICA) was applied to decompose multi-subject resting-state data into functionally homogeneous regions. Dynamic functional network connectivity (FNC) between all ICA time courses were computed using a tapered sliding window approach. We used a k-means algorithm to cluster the resulting dynamic FNC windows from each scan session into five dynamic states. We examined age and sex associations using linear mixed-effects models. First, independent from the dynamic states, we found a general increase in the temporal variability of the connections between intrinsic connectivity networks with increasing age. Second, when examining the clusters of dynamic FNC windows, we observed that the time spent in less modularized states, with low intra- and inter-network connectivity, decreased with age. Third, the number of transitions between states also decreased with age. Finally, compared to boys, girls showed a more mature pattern of dynamic brain connectivity, indicated by more time spent in a highly modularized state, less time spent in specific states that are frequently observed at a younger age, and a lower number of transitions between states. This longitudinal population-based study demonstrates age-related maturation in dynamic intrinsic neural activity from childhood into adolescence and offers a meaningful baseline for comparison with deviations from typical development. Given that several behavioral and cognitive processes also show marked changes through childhood and adolescence, dynamic functional connectivity should also be explored as a potential neurobiological determinant of such changes.
The original version of this Article contained an error in the spelling of the author Srilatha Sakamuru, which was incorrectly given as Srilatha Salamuru. This has now been corrected in both the PDF and HTML versions of the Article.
Virtual organisms animated by a selectionist theory of behavior dynamics worked on concurrent random interval schedules where both the rate and magnitude of reinforcement were varied. The selectionist theory consists of a set of simple rules of selection, recombination, and mutation that act on a population of potential behaviors by means of a genetic algorithm. An extension of the power function matching equation, which expresses behavior allocation as a joint function of exponentiated reinforcement rate and reinforcer magnitude ratios, was fitted to the virtual organisms' data, and over a range of moderate mutation rates was found to provide an excellent description of their behavior without residual trends. The mean exponents in this range of mutation rates were 0.83 for the reinforcement rate ratio and 0.68 for the reinforcer magnitude ratio, which are values that are comparable to those obtained in experiments with live organisms. These findings add to the evidence supporting the selectionist theory, which asserts that the world of behavior we observe and measure is created by evolutionary dynamics.
Background: Crack cocaine use and associated negative social and health consequences remain a significant public health problem. Research that expands beyond the individual by considering the environmental context as a determinant of cocaine use is growing. The main objectives of this paper are to examine the effects of perceived neighbourhood disorder as an independent correlate of the frequency of recent crack cocaine use and whether its impact is mediated by use-related practices and social context of use among an African American adult sample in Atlanta (GA).
Methods: Cross-sectional data were collected from 461 respondents who were recruited through active and passive community outreach from 70 disadvantaged urban neighbourhoods across Atlanta. Multivariable negative binomial regression was performed to assess the independent association of perceived neighbourhood disorder with crack cocaine use frequency and to explore potential mediation by use-related practices and social context of use.
Results: Perceived neighbourhood disorder did not remain statistically significant after accounting for use-related practices and social context of use. Involvement in drug distribution and having traded sex were associated with increases in frequency of drug use, while using in safer places and using alone were associated with decreases in frequency of use.
Conclusion: The results show that perceived neighbourhood disorder is associated with frequency of crack cocaine use independently of socio-demographics. However, its significance was eliminated when controlling for use-related practices and the social context of use. Such practices and the social context of use may mediate the relationship between neighbourhood disorder and crack cocaine use. Future research is needed to more fully elucidate the links between individual and neighbourhood characteristics that are related to crack cocaine use and strategies to reduce use must consider the salience of use-related practices and the social context of use.