Within- and between individual variability of personality characteristics and physical exercise

Four types of change and self-other agreement on change in personality traits during college years: A multi-informant longitudinal study

Research in personality trait change has largely relied on mean-level and rank-order change across the lifespan. The current research expanded the literature in several ways: analyzing four types of change and correlated change patterns, obtaining multi-informant reports, including lower-order personality traits, and collecting multiple assessments during a short yet important time for college-attending emerging adults (baseline N = 259, M_age  = 18.79). There was little evidence for mean-level change, yet participants showed significant individual differences such that rank-ordering and ipsative profiles were much more dynamic than mean score patterns. Informant-reports from close others demonstrated largely similar patterns: little to no mean-level change, significant increase in rank-ordering, and about half of participants reporting configural change mostly in elevation and scatter rather than in profile shapes. Interestingly, there was no correlated change between self and other-reports. This indicated that close others do not share individuals' perception of their own personality trait change, at least not in the demographic group studied. By examining individual-level, sample-level, and multi-informant perspectives, our thorough investigation provided useful benchmarks for future research to examine the source of variability in change trajectories.

The relationship between Big Five Personality Traits, eating habits, physical activity, and obesity in Indonesia based on analysis of the 5th wave Indonesia Family Life Survey (2014)

This study investigated the association between Big Five Personality Traits (Openness to new experience, Conscientiousness, Extraversion, Agreeableness, Neuroticism) and nutrition-related variables (eating habits, physical activity, and obesity using Body Mass Index). We used secondary data from the Indonesia Family Life Survey (IFLS) wave 5 involving a total of 14,473 men and 16,467 women aged 15-101 years (mean = 37.34; SD = 14.916) in Indonesia that was selected by stratified random sampling conducted in the period 2014 to 2015. Data were collected through interviews with the Big Five Index 15 and a questionnaire similar to the Global Physical Activity Questionnaire which was translated into the Indonesian language, and based on measurements of height and weight. Analyses used binary logistic regression test controlled by socio-demographic factors (age, gender, education, occupation, and marital status) to determine the association between Big Five Personality Traits and eating habits (recommended and non-recommended foods), physical activity, and obesity. Results showed that openness and extraversion were positively associated with recommended and non-recommended foods, conscientiousness was positively associated with only recommended foods, agreeableness was positively associated with recommended foods, and negatively associated with only one non-recommended food. Whereas, neuroticism was positively associated with non-recommended foods and negatively associated with recommended foods. Openness (p = 0.010; OR = 1.015; 95% CI = 1.004-1.027) and conscientiousness (p < 0.001; OR = 1.045; 95% CI = 1.030-1.059) were associated with physical activity. Conscientiousness (p = 0.002; OR = 1.025; 95% CI = 1.009-1.041), extraversion (p < 0.001; OR = 1.079; 95% CI = 1.065-1.092), and neuroticism (p < 0.001; OR = 0.966; 95% CI = 0.953-0.978) were associated with obesity. Although some results were different from previous studies, these associations can be used as strategies of behavioral change due to the adaptation of personality characteristics, which can be modified even though the personality tends to be persistent. Further studies are needed to understand other mechanisms that might underlie this association.

Temporal associations between objectively measured physical activity and depressive symptoms: An experience sampling study

Background

This study aimed to examine the relationship between the timing of physical activity and within-individual differences in depressive symptoms, positive affect, and negative affect in individuals with different baseline levels of depressive symptoms.

Methods

Experience sampling methodology (ESM) was used to measure real-time depressive symptoms, positive affect, and negative affect in a convenience sample of 78 healthy adults (aged M = 25.46 years, SD = 6.18; 57 females) five times per day for 14 days. We measured physical activity throughout the 14 days by using activity sensors. Baseline levels of depressive symptoms were assessed with the PHQ-9 to build subgroups with low vs. mild-moderate depressive symptoms.

Results

Physical activity predicted decreased depressive symptom levels, negative affect, and increased positive affect. Associations were stronger for individuals with higher baseline levels of depressive symptoms and for physical activity between 0 and 30 min compared to physical activity between 30 and 180 min before the mood rating. Conversely, levels of depressive symptoms, positive and negative affect did not predict physical activity.

Limitations

The convenience sample may not have been representative of the general population or people with depression. Accelerometers may not have detected some types of physical activities such as bicycling. Causality could not be inferred because of the observational study design.

Conclusion

Individuals with higher levels of depressive symptoms may benefit from physical activity. While the effects were strongest for physical activity immediately before the mood ratings, the effects were in the same direction for up to 3 h before the mood ratings.

A Practical Cross-Sectional Framework to Contextual Reactivity in Personality: Response Times as Indicators of Reactivity to Contextual Cues

Contextual reactivity refers to the degree in which personality states are affected by contextual cues. Research into contextual reactivity has mainly focused on repeated measurement designs. In this paper, we propose a cross-sectional approach to study contextual reactivity. We argue that contextual reactivity can be operationalized as different response processes which are characterized by different mean response times and different measurement properties. We propose a within-person mixture modeling approach that adopts this idea and which enables studying contextual reactivity in cross-sectional data. We applied the model to data from the Revised Temperament and Character Inventory. Results indicate that we can distinguish between two response specific latent states. We interpret these states as a high contextual reactive state and a low contextual reactive state. From the results it appears that the low contextual reactive state is generally associated with smaller response times and larger discrimination parameters, as compared to the high contextual reactivity state. The utility of this approach in personality research is discussed.

The Gaussian Graphical Model in Cross-Sectional and Time-Series Data

We discuss the Gaussian graphical model (GGM; an undirected network of partial correlation coefficients) and detail its utility as an exploratory data analysis tool. The GGM shows which variables predict one-another, allows for sparse modeling of covariance structures, and may highlight potential causal relationships between observed variables. We describe the utility in three kinds of psychological data sets: data sets in which consecutive cases are assumed independent (e.g., cross-sectional data), temporally ordered data sets (e.g., n = 1 time series), and a mixture of the 2 (e.g., n > 1 time series). In time-series analysis, the GGM can be used to model the residual structure of a vector-autoregression analysis (VAR), also termed graphical VAR. Two network models can then be obtained: a temporal network and a contemporaneous network. When analyzing data from multiple subjects, a GGM can also be formed on the covariance structure of stationary means-the between-subjects network. We discuss the interpretation of these models and propose estimation methods to obtain these networks, which we implement in the R packages graphicalVAR and mlVAR. The methods are showcased in two empirical examples, and simulation studies on these methods are included in the supplementary materials.

Health promotion in young people: Identifying the predisposing factors of self-care health habits

Unhealthy behaviors are strongly associated with chronic diseases, disabilities, or mortality. Identifying the predisposing factors that influence on self-care healthy habits will improve an early detection of high-risk groups. Four hundred and sixty-six Spanish young people aged 18-25 years were assessed. Global perceived health self-care was predicted by Value of health and Conscientiousness, both in females (R² = 0.185; F = 29.661; p < 0.001) and males (R² = 0.154; F = 17.849; p < 0.001). The results have shown gender differences in health self-care habits. Health promotion policies should include specific health consciousness-based strategies.

Causal Unity of Broader Traits is an Illusion

Mõttus alerts us to the widespread predictive heterogeneity of different indicators of the same trait. This heterogeneity violates the assumption that traits have causal unity in their developmental antecedents and effects on outcomes. I would go a step further: broader traits are useful units for description and prediction but not for explaining personality development and personality effects. In most cases, the measured trait indicators are closer to relevant causal mechanisms, and within a network perspective on personality, broader traits as entities with causal potential can be dismissed completely. Copyright © 2016 European Association of Personality Psychology