Search results

Breakfast consumption is associated with a range of beneficial health outcomes including improved overall diet quality, lower BMI, decreased risk of chronic disease, and improved cognitive function. Although there are many models of health and social behaviour, there is a paucity of research utilising these in breakfast consumption and very few studies that directly compare these models. This study aims to compare the theory of planned behaviour (TPB) and the health action process approach (HAPA) in predicting breakfast consumption.

University students (N=102; M=19.5 years) completed a questionnaire measuring demographics, TPB and HAPA motivational variables, and intentions. Behaviour and HAPA volitional variables were measured four weeks later.

Using structural equation modelling, it was found that the TPB model was a superior fit to the data across a range of model indices compared to the HAPA. Both models significantly predicted both intentions and behaviour at follow up; however, the TPB predicted a higher proportion of the variance in breakfast consumption (47.6 per cent) than the HAPA (44.8 per cent). Further, the volitional variables did not mediate the intention-behaviour gap, and the data were not an adequate statistical fit to the model compared to the TPB.

The results support the use of the TPB and show that some aspects of the HAPA are useful in predicting breakfast consumption, suggesting that risk perception and self-efficacy be targeted in interventions to increase behaviour. The volitional variables did not appear to mediate breakfast consumption indicating that intention is still the strongest predictor, at least in this behaviour.

The current study is the first to compare the TPB and HAPA in predicting breakfast consumption.

The theory of planned behaviour (TPB) considers the interrelationship between such concepts as beliefs, attitudes, norms, intentions and behaviour (Ajzen, 1991; Ajzen and Fishbein, 1975). Based on a review of academic sources, this paper aims to analyse the efficacy of the TPB for predicting people’s intentions when choosing a travel destination.

Surprisingly, only 15 studies were identified that used TPB to predict the choice of travel destination, though the theory has been used in other areas of tourism analysis.

Mixed results were found in the studies. Therefore, the adequacy of the TPB for predicting travellers’ intentions of choosing a destination may be questioned. However, there is nothing in the TPB suggesting that all the constructs of the model must contribute equally, significantly and simultaneously to behavioural intentions.

To achieve a more comprehensive understanding of the intentions in question, the TPB model may have to be extended to suit different settings. The decision-making process of choosing a destination is a complicated one; therefore, researchers’ attention should not only consider travellers’ intentions but also the direct effect of intentions on the actual behaviour.

The purpose of this paper is to test whether, in the context of blood donation, the predictive ability of the theory of planned behaviour (TPB) extends from behavioural intention to actual donation behaviour, and whether extended versions of the TPB perform better than the standard version.

Intentions to donate blood predicted by the TPB are compared with an accurate measure of blood donation behaviour obtained following a mobile blood drive by the New Zealand Blood Service.

When the observed outcome is donation behaviour rather than behavioural intention, the TPB model's performance drops. Extending the variables in the model to include moral obligation and past behaviour does not improve its predictive ability, and neither does the use of belief‐based variables.

The TPB is much less effective in predicting blood donation behaviour than it is in predicting intentions to donate blood. But only actual donation behaviour yields medical supplies. This study suggests that to advance the goal of increasing donation rates, attention needs to turn to methods other than the TPB to identify variables that do predict donation behaviour.

The present study gathered one of the largest samples used for TPB blood donation research; this enabled predictions made using the TPB to be tested against actual behaviour, rather than behavioural intention, the measure typically used in blood donation studies. Because blood donation is a low‐incidence behaviour, previous studies have been hampered by small sample sizes, that inevitably contain few donors, and no measure of actual donation behaviour.

Aggression has been introduced as one of the serious problems in public health. The purpose of this paper is to evaluate the ability of the extended theory of planned behavior (TPB) to predict the physical and verbal aggression behavior.

In this research, 462 teenagers were evaluated through the demographic questionnaire along with the main structures of the TPB as a predictor of behavior. After one month of follow-up, physical and verbal aggression was evaluated. Demographic data were analyzed descriptively by SPSS21 and predictability of the structures for intention and behavior of the physical and verbal aggression was analyzed by AMOS.

Mean and standard deviation of participants’ age were 14.70 and 1.12 years, respectively. In this research, 22.5% of the participants did not show physical aggression over the last one month and 20% of them did not show verbal aggression over the last month. Path analysis revealed that the variables of the TPB predicted 61% and 32% of variance of intention and physical aggression behavior, respectively, while these variables could describe 43% and 22% of the variance of intention and verbal aggression behavior, respectively. All of the concepts could be significant predictors of the behaviors. Subjective norms were the best predictor of the intention for physical and verbal aggression. Intention and perceived behavioral control were good predictors of physical and verbal aggression.

Given the role of subjective norms in intention and also the role of intention and perceived behavioral control of people for aggression, it can be concluded that emphasis on social and psychological education about subjective norms, peer groups and self-control can help reduce this problem.

A few studies have predicted behavior occurrence in the future. Given the lack of focus on the role of constructs that may bring about future behaviors, the current research was conducted to use the structures of the TPB to predict behavioral intention as well as perpetration of physical and verbal aggressive behaviors, independently.

Although researchers have suggested that aggression is multiply determined, most studies examine only a small set of predictors, focusing on either situational or individual or reciprocal motives. Research has not studied extensively the relative strength of multiple antecedent sets. Using questionnaire data (n = 366), the current study examines eleven antecedents of employees engaging in aggression: situational antecedents (i.e., procedural, distributive, and interpersonal justice; organizational, work group, and job related stress), individual difference antecedents (i.e., Type A behavior, trait anger, reactions to anger), and reciprocal effects (i.e., being the target of aggression). Individual difference antecedents and being the target of aggression influence the frequency with which employees report engaging in aggression. Situational antecedents are not significant predictors once other antecedents are taken into account.

This study aims to test the contributions of a new type of resilience, Trait Negotiation Resilience (TNR; Nelson et al., 2016), to negotiators’ effective behavior, perception of opponent and negotiation outcomes.

A laboratory study (N = 98; 49 dyads) featuring a mixed-motive negotiation task. Participants self-reported TNR (emotional skills, social sensitivity, intrinsic motivation for self-improvement and a sense of purpose to life events) up to a week before negotiating. After the negotiations, they rated their opponents on resilient, effective personal attributes and reported their own subjective value (SV). Trained judges watched the negotiations, coded objective outcomes and rated negotiators on dimensions of effective negotiation behavior. Statistical analyses accounted for dyadic interdependence.

TNR predicted higher levels of effective negotiation behavior, which, in turn, fully mediated TNR’s favorable contribution to negotiated value. TNR also predicted higher levels of SV, and this contribution was partially mediated by perceiving effective personal attributes in the opponent.

The sample size was moderate and it consisted of undergraduate students, most of them female.

Evidence on the contribution of a personality construct to both outcome and process negotiator variables; contribution to the research of specific types of resilience.

The new product development process comprises a series of information‐gathering phases intended to reduce the uncertainty which surrounds the management of innovation. To the extent that this is a rational process, new product failures can be attributed to a lack of high quality, relevant information for decision making. In view of the particularly high failure rate for consumer non‐durables, it makes sense to look critically at the quality of market research information employed in new product decision making. Concept and product tests, which rely heavily on measures of attitude and intention, are very frequently used to gain such information relatively early in the innovative process, but, while they have sometimes been indicted for their inability to predict managerially‐useful aspects of new brand choice, there appears to have been no attempt at understanding why they are often ineffective. Without this understanding it is impossible to suggest an alternative approach. There is no panacea for the problem of predicting consumer choice in new product development but there is great need to come to grips with this problem. This article attempts to provide the necessary understanding and suggests an alternative means of conceptualising the attitude — intentions — behaviour relationship in marketing.

This paper aims to test whether overall and specific healthy eating behaviors and intentions could be better predicted by expanding the theory of planned behavior (TPB) to include a healthy eater identity. Major health organizations suggest increasing consumption of fruits, vegetables and whole grains to address the growing number of overweight and obese individuals, yet researchers have questioned the degree to which existing behavioral intervention programs sufficiently explain healthy eating behaviors.

Adult women (N = 79) completed questionnaires related to TPB components and healthy eater identity. Participants then recorded food consumption for four days using food diaries and food frequency questionnaires.

Using hierarchical multiple regressions, the authors demonstrated that identity as a healthy eater was a significant predictor of healthy eating intentions beyond the TPB components and a significant predictor of fruit and low-fat dairy consumption and overall healthy eating behaviors.

Despite the limitation of correlational data from a homogenous population, results support previous research and add to existing literature by demonstrating the unique contribution identity has in predicting specific healthy diet behaviors of fruit and low-fat dairy consumption.

Findings advance our understanding of how young women think about nutrition and underscore which healthy eating behaviors might need to be directly targeted in interventions if such behaviors fall outside of the scope of common conceptions of what it means to be a “healthy eater”.

This paper aims to predict the behaviour of the vehicles in a mixed driving scenario. This proposes a deep learning model to predict lane-changing scenarios in highways incorporating current and historical information and contextual features. The interactions among the vehicles are modelled using long-short-term memory (LSTM).

Predicting the surrounding vehicles' behaviour is crucial in any Advanced Driver Assistance Systems (ADAS). To make a decision, any prediction models available in the literature consider the present and previous observations of the surrounding vehicles. These existing models failed to consider the contextual features such as traffic density that also affect the behaviour of the vehicles. To forecast the appropriate driving behaviour, a better context-aware learning method should be able to consider a distinct goal for each situation is more significant. Considering this, a deep learning-based model is proposed to predict the lane changing behaviours using past and current information of the vehicle and contextual features. The interactions among vehicles are modeled using an LSTM encoder-decoder. The different lane-changing behaviours of the vehicles are predicted and validated with the benchmarked data set NGSIM and the open data set Level 5.

The lane change behaviour prediction in ADAS is gaining popularity as it is crucial for safe travel in a mixed driving environment. This paper shows the prediction of maneuvers with a prediction window of 5 s using NGSIM and Level 5 data sets. The proposed method gives a prediction accuracy of 97% on average for all lane-change maneuvers for both the data sets.

This research presents a strategy for predicting autonomous vehicle behaviour based on contextual features. The paper focuses on deep learning techniques to assist the ADAS.

Purpose: Prior work has convincingly argued that social inequalities arise from the basic human tendency to place others into social categories with different cultural meanings and to allocate resources unequally across those categories. However, few studies have sought to identify the micro-level mechanisms that sustain and justify this categorical inequality. In this research, I show how affect control theory (ACT) can be used to generate novel predictions about the interaction processes that perpetuate stratification.

Methodology/Approach: I present a series of analyses based in ACT that examine (1) whether categorical inequality is reflected in cultural sentiments for social groups, (2) whether patterns of normative behavior and social treatment vary based on category membership, and (3) whether interactions produce different emotions based on category membership.

Findings: Analysis 1 identifies four distinct patterns of cultural meanings that differentiate the groups studied. Analyses 2 and 3 show how these differences in cultural meanings produce categorical inequality through interpersonal behavior and emotional experiences in normative social encounters. Unequal cultural meanings for social groups correspond with their positionality in the social order and support patterns of situated behavior and emotions that keep groups with different levels of status and power separate and unequal.

Originality/Value: This research shows how social norms constrain and enable actions and emotions by members of different social categories, how they depend on the combinations of actors who appear together in a given social encounter, and how they contribute to the reproduction of inequality in ways not well accounted for by earlier work.