Development of Adolescent Problem Behavior

The developmental model of adolescent antisocial behavior advanced by Patterson and colleagues (e.g., Patterson, Reid, & Dishion, 1992) appears to generalize the development of a diverse set of problem behaviors. Structural equation modeling methods were applied to 18-month longitudinal data from 523 adolescents. The problem behavior construct included substance use, antisocial behavior, academic failure, and risky sexual behavior. Families with high levels of conflict were less likely to have high levels of parent–child involvement. Such family conditions resulted in less adequate parental monitoring of adolescent behavior, making associations with deviant peers more likely. Poor parental monitoring and associations with deviant peers were strong predictors of engagement in problem behavior. These constructs accounted for 46% of the variance in problem behavior. Although association with deviant peers was the most proximal social influence on problem behavior, parental monitoring and family factors (conflict and involvement) were key parenting practices that influenced this developmental process.     

The adoption of physical activity and eating behaviors among persons with obesity and in the general population: the role of implicit attitudes within the Theory of Planned Behavior

Obesity can be prevented by the combined adoption of a regular physical activity (PA) and healthy eating behaviors (EB). Researchers mainly focused on socio-cognitive models, such as the Theory of Planned Behavior (TPB), to identify the psychological antecedents of these behaviors. However, few studies were interested in testing the potential contribution of automatic processes in the prediction of PA and EB. Thus, the main objective of this study was to explore the specific role of implicit attitudes in the pattern of prediction of self-reported PA and EB in the TPB framework, among persons with obesity and in adults from the general population. One hundred and fifty-three adults participated to this cross-sectional study among which 59 obese persons (74% women, age: 50.6 ± 12.3 years, BMI: 36.8 ± 4.03 kg m^–²) and 94 people from the general population (51% women; age: 34.7 ± 8.9 years). Implicit attitudes toward PA and EB were estimated through two Implicit Association Tests. TPB variables, PA and EB were assessed by questionnaire. Regarding to the prediction of PA, a significant contribution of implicit attitudes emerged in obese people, β = .25; 95%[CI: .01, .50]; P = .044, beyond the TPB variables, contrary to participants from the general population. The present study suggests that implicit attitudes play a specific role among persons with obesity regarding PA. Other studies are needed to examine which kind of psychological processes are specifically associated with PA and EB among obese people.     

Conscientiousness and fruit and vegetable consumption: exploring behavioural intention as a mediator

Clear associations have emerged between conscientiousness and health behaviours, such that higher levels of conscientiousness are predictive of beneficial health behaviours. This study investigated the conscientiousness-fruit and vegetable consumption relationship and whether behavioural intention mediated this relationship. A large sample of adults (N = 2136) completed an online battery of questionnaires measuring conscientiousness, behavioural intentions to consume fruit and vegetables, together with self-reported behaviour. Correlation analysis revealed that conscientiousness and each of its facets were positively associated with behavioural intention and self-reported behaviour. Hierarchical multiple regression analyses revealed that after controlling for age, gender and education, total conscientiousness, and the facets of responsibility, industriousness, order and virtue predicted self-reported behaviour. Further analysis revealed that in line with the Theory of Planned Behaviour, behavioural intention fully mediated the conscientiousness-fruit and vegetable behaviour relationship. In conclusion, low levels of conscientiousness were found to be associated with lower fruit and vegetable intentions, with the latter also associated with fruit and vegetable consumption.     

Drivers discuss ecodriving feedback: Goal setting,framing, and anchoring motivate new behaviors

Ecodriving, defined here as the adoption of energy efficient driving styles and practices (primarily moderating accelerations and decelerations, reducing top speeds, and improved maintenance practices), has long been recognized as a potential source of reductions in transportation energy use. Estimates of energy savings attributed to ecodriving range widely, from less than 5% to as high as 20% depending on the driving and experimental context. To explore the effects on ecodriving of interaction between drivers and in-vehicle energy feedback, a customized, interactive energy feedback interface was deployed in a field test with real-world drivers. This paper presents the results of interviews with 46 Plug-in Hybrid Electric Vehicle (PHEV) drivers who were given the ecodriving feedback interface for a multi-week trial including an interface off (baseline) and on (treatment) condition. This paper relies specifically on self-reports of driver motivations and behaviors to better understand what types of information motivated new ecodriving behavior; a future paper will investigate quantitative fuel consumption effects. Driver interviews at the conclusion of the study revealed that the introduction of feedback led three fourths of drivers to change driving styles to maximize on-road efficiency, at least in the short term. In addition, this study finds that the context of the feedback information, provided by a built-in goal or other contextualizing information such as a comparison value, is important for both comprehension and motivation. Personalization of the information allowed different drivers to access pertinent information, increasing the motivational value of the information. Instantaneous performance feedback such as real-time energy economy or power is used primarily for experimentation and learning of new ecodriving behaviors, whereas average performance feedback is used primarily for goal-setting and goal achievement. In addition, the direct comparison of personalized driver goals and average performance created a game-like experience that encouraged high achievement. Finally, the driver interviews revealed that feedback frames driving as a time to act in an efficient manner.     

Finite Mixtures of Hidden Markov Models for Longitudinal Responses Subject to Drop out

Abstract

Drop out is a typical issue in longitudinal studies. When the missingness is non-ignorable, inference based on the observed data only may be biased. This paper is motivated by the Leiden 85+ study, a longitudinal study conducted to analyze the dynamics of cognitive functioning in the elderly. We account for dependence between longitudinal responses from the same subject using time-varying random effects associated with a heterogeneous hidden Markov chain. As several participants in the study drop out prematurely, we introduce a further random effect model to describe the missing data mechanism. The potential dependence between the random effects in the two equations (and, therefore, between the two processes) is introduced through a joint distribution specified via a latent structure approach. The application of the proposal to data from the Leiden 85+ study shows its effectiveness in modeling heterogeneous longitudinal patterns, possibly influenced by the missing data process. Results from a sensitivity analysis show the robustness of the estimates with respect to misspecification of the missing data mechanism. A simulation study provides evidence for the reliability of the inferential conclusions drawn from the analysis of the Leiden 85+ data.     

Interpersonal effects of parents and adolescents on each other’s health behaviours: a dyadic extension of the theory of planned behaviour

Objective: Interpersonal relationships are important predictors of health outcomes and interpersonal influences on behaviours may be key mechanisms underlying such effects. Most health behaviour theories focus on intrapersonal factors and may not adequately account for interpersonal influences. We evaluate a dyadic extension of the Theory of Planned Behaviour by examining whether parent and adolescent characteristics (attitudes, subjective norms, perceived behavioural control and intentions) are associated with not only their own but also each other’s intentions/behaviours.

Design: Using the Actor-Partner Interdependence Model, we analyse responses from 1717 parent-adolescent dyads from the Family Life, Activity, Sun, Health, and Eating study.

Main Outcome Measures: Adolescents/parents completed self-reports of their fruit and vegetable consumption, junk food and sugary drinks consumption, engagement in physical activity, and engagement in screen time sedentary behaviours.

Results: Parent/adolescent characteristics are associated with each other’s health-relevant intentions/behaviours above the effects of individuals’ own characteristics on their own behaviours. Parent/adolescent characteristics covary with each other’s outcomes with similar strength, but parent characteristics more strongly relate to adolescent intentions, whereas adolescent characteristics more strongly relate to parent behaviours.

Conclusions: Parents and adolescents may bidirectionally influence each other’s health intentions/behaviours. This highlights the importance of dyadic models of health behaviour and suggests intervention targets.     

Sociodemographic,Cognitive, and Emotional Determinants of Two Health Behaviors during SARS-CoV-2 Outbreak: An Online Study among French-Speaking Belgian Responders during the Spring Lockdown

To contain the SARS-CoV-2 infection rate, health authorities have encouraged the population to enhance protective behaviors such as physical distancing and handwashing. Behavioral sciences emphasize the role of sociocognitive determinants to explain health behaviors, while largely ignoring emotional factors. In a large online study (N > 4000), we investigated the role of sociodemographic, cognitive, emotional, and social factors that can facilitate or hinder handwashing and limitation of social contacts. Data were collected from March 18 until April 19, 2020, which corresponds to the spring lockdown and the first peak of the pandemic in Belgium. Logistic regressions showed that sociodemographic factors (gender, age, level of education) and the dimensions of the Theory of Planned Behavior (intentions, attitudes, perceived behavioral control and subjective norms) had a strong impact on health behaviors, but that emotional factors explained an additional part of the variance. Being more attentive/determined and frightened/anxious, along with scoring higher on health anxiety were related to a higher frequency of handwashing. In contrast, being enthusiastic/happy was related to lower adherence to limiting social contacts. Our results suggest that the type of predictors and the direction of associations depend on the type of health behavior considered. The role of specific emotional factors in addition to more classical predictors is discussed. The study offers new perspectives regarding the factors that are associated with the adherence to behaviors recommended to adopt when faced with a pandemic.     

Untangling the Theory of Planned Behavior's auxiliary assumptions and theoretical assumptions: Implications for predictive and intervention studies

It has been asserted that the Theory of Planned Behavior (TPB) is better at behavioral prediction than it is behavioral change. However, the performance of a theory depends not only on the theoretical propositions, but the auxiliary assumptions attached to the theory. It is because of such auxiliary assumptions, which are required to bridge the gap between nonobservational terms at the level of theory and the observational terms at the level of the empirical hypothesis, that we believe critiques of the TPB's utility are misguided. We argue that a failure to separate theoretical assumptions from auxiliary assumptions leads to this false assumption. We suggest the importance of distinguishing between the auxiliary assumptions required for prediction studies and the auxiliary assumptions required for intervention studies. We believe that in attaching sound auxiliary assumptions to intervention studies, the TPB is equally effective at facilitating behavior change as it is behavior prediction.