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Recent investigations highlighted the role of within-person pubertal changes for adolescents' behavior. Yet, little is known about effects on adolescents' daily affect, particularly regarding the hormonal changes underlying physical changes during puberty. In a study with 148 boys aged 10 to 20years, we tested whether within-person physical and hormonal changes over eight months predicted everyday affect fluctuations, measured with experience sampling. As expected, greater within-person changes in testosterone (but not in dehydroepiandrosterone) were associated with higher affect fluctuations in daily life. Additionally, greater physical changes predicted higher affect fluctuations for individuals in the beginning of puberty. The findings demonstrate the relevance of physical and hormonal changes in boys' affective (in)stability., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Positive (PA) and negative affect (NA) are important constructs in health and well-being research. Good longitudinal measurement is crucial to conducting meaningful research on relationships between affect, health, and well-being across the lifespan. One common affect measure, the PANAS, has been evaluated thoroughly with factor analysis, but not with Racsh-based latent trait models (RLTMs) such as the Partial Credit Model (PCM), and not longitudinally. Current longitudinal RLTMs can computationally handle few occasions of data. The present study compares four methods of anchoring PCMs across 56 occasions to longitudinally evaluate the psychometric properties of the PANAS plus additional items. Anchoring item parameters on mean parameter values across occasions produced more desirable results than using no anchor, using first occasion parameters as anchors, or allowing anchor values to vary across occasions. Results indicated problems with NA items, including poor category utilization, gaps in the item distribution, and a lack of easy-to-endorse items. PA items had much more desirable psychometric qualities.

Resilience is often considered both a trait and a process. The current study proposes a new way to conceptualize resilience-as-process based on dynamical systems modeling, which allows researchers to capture the process of stress management in real time. Coupled damped linear oscillator models succinctly describe daily stress and negative affect in terms of developmental forces (e.g., velocity, acceleration). Models were fit to 56-day daily response data from 42 aging adults (M(age) = 78.8 years; SD(age) = 6.6 years) to observe and understand linkages between daily stress and affect. It was speculated that individuals with greater resilience would experience stress as less coupled to changes in negative affect (less stress reactivity), and would recover their affective equilibrium more quickly following a given exogenous stressor (greater stress recovery). To identify resilience resources related to reliable interindividual differences in coupling and damping between stress and negative affect, we examined possible protective factors. Aspects of personality and social support predicted both the strength and nature of this coupling, such that higher levels of these resources resulted in greater protection from the cost to negative affect from stress, as observed in damping of negative affect and decreased coupling between systems., ((c) 2010 APA, all rights reserved.)

A dynamical systems approach was used to model the intraindividual variability in emotional well-being following conjugal loss. Well-being in a sample of 19 recently bereaved older adult widows was measured every day for 3 months. The pattern of variability of well-being was hypothesized to be an oscillating process that damps across time (i.e., large swings followed by a gradual damping). Results indicated that there was significant patterned variability in the emotional well-being adjustment that can be modeled by a linear oscillator model (R2=.77), in addition to an overall positive trend. Applying dynamical systems analyses to capture variability and subsequent well-being trajectories following spousal loss is an important step in delineating the complex adjustment to widowhood.