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Behavioral Prediction (behavioral + prediction)

Distribution by Scientific Domains

Medical Sciences	57%

Selected Abstracts

Non-adherence to immunosuppressive medication in renal transplant recipients within the scope of the integrative model of behavioral prediction: a cross-sectional study

CLINICAL TRANSPLANTATION, Issue 2 2010
Gabriela Schmid-Mohler
Schmid-Mohler G, Pechula Thut M, Wüthrich RP, Denhaerynck K, De Geest S. Non-adherence to immunosuppressive medication in renal transplant recipients within the scope of the integrative model of behavioral prediction: a cross-sectional study. Clin Transplant 2009 DOI: 10.1111/j.1399-0012.2009.01056.x © 2009 John Wiley & Sons A/S. Abstract:, Background:, Non-adherence to immunosuppressive medication is strongly associated with poor outcomes. Identifying the factors influencing it is a first step in developing adherence interventions. This study's objective was to investigate the prevalence of self-reported and collaterally-reported non-adherence to immunosuppressives, and, based on the Integrative Model of Behavioral Prediction, to explore the association between non-adherence, intention to adhere, attitudes, norms and self-efficacy. Methods:, This cross-sectional study included a convenience sample of 114 renal transplant recipients in follow-up care, one to five yr post-transplant. Non-adherence was measured by self-reports and collateral reports. Factors of the Integrative Model of Behavioral Prediction were assessed using a self-report questionnaire. Results:, Self-reports showed non-adherence of 23.7%; collateral reports showed 3.8%; and a combination of the two showed 26.4%. Logistic regression analysis showed that the attitude "Not all immunosuppressive drugs are necessary to prevent rejection" was less frequent in patients with higher intentions to adhere, with an odds ratio (OR) of 0.05 (95% CI 0.01,0.50). The barrier of "Forgetfulness/Interruption of daily routine" was associated with non-adherence, with an OR of 3.74 (95% CI 1.55,9.03). Conclusions:, Forgetfulness is the most powerful barrier against adherence. Intention to adhere plays a minor role in non-adherence in renal transplant recipients. [source]

Generality with specificity: the dynamic field theory generalizes across tasks and time scales

DEVELOPMENTAL SCIENCE, Issue 4 2008
Vanessa R. Simmering
A central goal in cognitive and developmental science is to develop models of behavior that can generalize across both tasks and development while maintaining a commitment to detailed behavioral prediction. This paper presents tests of one such model, the Dynamic Field Theory (DFT). The DFT was originally proposed to capture delay-dependent biases in spatial recall and developmental changes in spatial recall performance. More recently, the theory was generalized to adults' performance in a second spatial working memory task, position discrimination. Here we use the theory to predict a specific, complex developmental pattern in position discrimination. Data with 3- to 6-year-old children and adults confirm these predictions, demonstrating that the DFT achieves generality across tasks and time scales, as well as the specificity necessary to generate novel, falsifiable predictions. [source]

Non-adherence to immunosuppressive medication in renal transplant recipients within the scope of the integrative model of behavioral prediction: a cross-sectional study

Using Theory to Design Effective Health Behavior Interventions

COMMUNICATION THEORY, Issue 2 2003
Martin Fishbein
This article demonstrates the usefulness of two theories for the development of effective health communication campaigns. The integrative model of behavioral prediction focuses on changing beliefs about consequences, normative issues, and efficacy with respect to a particular behavior. Media priming theory focuses on strengthening the association between a belief and its outcomes, such as attitude and intention toward performing the behavior. Both the integrative model of behavioral prediction and media priming theory provide guidance with respect to the selection of beliefs to target in an intervention. The article describes the theories, shows how they can be applied to the selection of target beliefs, and, for each theory, defines the criteria for belief selection. The two theories as well as their appropriate analytic strategies are complementary rather than conflicting. [source]

Computational Modeling of Statistical Learning: Effects of Transitional Probability Versus Frequency and Links to Word Learning

INFANCY, Issue 5 2010
Daniel Mirman
Statistical learning mechanisms play an important role in theories of language acquisition and processing. Recurrent neural network models have provided important insights into how these mechanisms might operate. We examined whether such networks capture two key findings in human statistical learning. In Simulation 1, a simple recurrent network (SRN) performed much like human learners: it was sensitive to both transitional probability and frequency, with frequency dominating early in learning and probability emerging as the dominant cue later in learning. In Simulation 2, an SRN captured links between statistical segmentation and word learning in infants and adults, and suggested that these links arise because phonological representations are more distinctive for syllables with higher transitional probability. Beyond simply simulating general phenomena, these models provide new insights into underlying mechanisms and generate novel behavioral predictions. [source]

Comparing leading theoretical models of behavioral predictions and post-behavior evaluations

PSYCHOLOGY & MARKETING, Issue 12 2008
Juliette Richetin
This study aimed at comparing the predictive power of the Theory of Planned Behavior (TPB), the Model of Goal-Directed Behavior (MGB), and the Extended Model of Goal-Directed Behavior (EMGB) for observed and self-reported behaviors concerning consumer nondurables. More specifically, the three models were compared in terms of their predictive power for intention and for behavioral desire (only MGB and EMGB). Additionally, the validity of four different models for predicting post-behavior evaluations was examined. Results showed that the EMGB is the most powerful in predicting both intention and behavioral desire. Moreover, results revealed that, as expected, all three models showed a better predictive power for SRB than for observed behavior. Finally, results demonstrated that post-behavior evaluations are both online and memory-based. ©2008 Wiley Periodicals, Inc. [source]