Moving beyond a limited follow-up in cost-effectiveness analyses of behavioral interventions

Background Cost-effectiveness analyses of behavioral interventions typically use a dichotomous outcome criterion. However, achieving behavioral change is a complex process involving several steps towards a change in behavior. Delayed effects may occur after an intervention period ends, which can lead to underestimation of these interventions. To account for such delayed effects, intermediate outcomes of behavioral change may be used in cost-effectiveness analyses. The aim of this study is to model cognitive parameters of behavioral change into a cost-effectiveness model of a behavioral intervention. Methods The cost-effectiveness analysis (CEA) of an existing dataset from an RCT in which an high-intensity smoking cessation intervention was compared with a medium-intensity intervention, was re-analyzed by modeling the stages of change of the Transtheoretical Model of behavioral change. Probabilities were obtained from the dataset and literature and a sensitivity analysis was performed. Results In the original CEA over the first 12 months, the high-intensity intervention dominated in approximately 58% of the cases. After modeling the cognitive parameters to a future 2nd year of follow-up, this was the case in approximately 79%. Conclusion This study showed that modeling of future behavioral change in CEA of a behavioral intervention further strengthened the results of the standard CEA. Ultimately, modeling future behavioral change could have important consequences for health policy development in general and the adoption of behavioral interventions in particular

Extending Social Learning Theories to Collectivist Cultures: The Effect of Behavior Modeling Training, Service Orientation and Language Skills on Service Skills and Behaviors

Although previous research has suggested that training approaches using behavior modeling yield better results than lecture-based approaches, these assumptions have not been tested in collectivist cultures. This study examined the effects of these alternative training methods for service knowledge and service behavior with a field experiment involving 117 Russian hotel employees. Despite no previous exposure to behavior modeling and no cultural context for service, the behavioral modeling training approach relative to the lecture-based approach yielded higher levels of both service knowledge and behavior. Since the setting was an English speaking hotel, difference in language ability were also considered and behavioral modeling was found to be a more effective training approach regardless of English ability. It also appears that service orientation is positively associated with both knowledge and behavior. The results indicate behavior modeling may be most helpful to those employees least predisposed to service or with lower language abilities

Behavioral synthesis from VHDL using structured modeling

This dissertation describes work in behavioral synthesis involving the development of a VHDL Synthesis System VSS which accepts a VHDL behavioral input specification and performs technology independent synthesis to generate a circuit netlist of generic components. The VHDL language is used for input and output descriptions. An intermediate representation which incorporates signal typing and component attributes simplifies compilation and facilitates design optimization.A Structured Modeling methodology has been developed to suggest standard VHDL modeling practices for synthesis. Structured modeling provides recommendations for the use of available VHDL description styles so that optimal designs will be synthesized.A design composed of generic components is synthesized from the input description through a process of Graph Compilation, Graph Criticism, and Design Compilation. Experiments were performed to demonstrate the effects of different modeling styles on the quality of the design produced by VSS. Several alternative VHDL models were examined for each benchmark, illustrating the improvements in design quality achieved when Structured Modeling guidelines were followed

Top-Down Behavioral Modeling Methodology of a Piezoelectric Microgenerator For Integrated Power Harvesting Systems

In this study, we developed a top/down methodology for behavioral and structural modeling of multi-domain microsystems. Then, we validated this methodology through a study case : a piezoelectric microgenerator. We also proved the effectiveness of VHDL-AMS language not only for modeling in behavioral and structural levels but also in writing physical models that can predict the experimental results. Finally, we validated these models by presenting and discussing simulations results.Comment: Submitted on behalf of EDA Publishing Association (http://irevues.inist.fr/handle/2042/16838

Behavioral Modeling and Fisheries Management

Because of the extreme uncertainty in fisheries biology, efforts to determine a stock-recruitment relationship have not been entirely successful. In the face of this certainty, this paper argues for a change in focus for fisheries economics from bioeconomic optimization toward goals which are more modest and more easily achievable. In particular, a satisficing approach to management is advocated, whereby efforts are made to reallocate some porportion of effort from overutilized to underutilized fisheries, with no attempt to determine the optimum. In order to achieve such a solution efficiently, managers must accurately predict the response of fishermen to public policy. This paper reports on a study which develops a discrete choice model to predict fishermen's supply response. Fishermen are shown to respond to economic incentives of expected returns and variability of returns, but only after these incentives surpass a substantial threshold.Institutional and Behavioral Economics,

On the Behavioral Modeling of Integrated Circuit Output Buffers

The properties of common behavioral macromodels for single ended CMOS integrated circuits output buffers are discussed with the aim of providing criteria for an effective use of possible modeling options

Modeling Behavioral Heterogeneity in Demand Theory

This paper is a first step in answering B. Villemeur\'s (1998,1999) and Hildenbrand\'s (1998) criticism of the notions of behavioral heterogeneity introduced in demand theory by Grandmont (1992) and Kneip (1999). As in the Grandmont-Kneip approach, we define a notion of behavioral heterogeneity such that if the population is sufficiently heterogeneous, the aggregate budget share function is proved to become insensitive to changes in prices and income. However, in contrast to the aforementioned literature, this insensitivity in the aggregate is not explained by any insensitivity property at the microeconomic level, but rather by a ``balancing effect\'\' : For any commodity, the negative effect on market budget share induced after a change in prices or income by individuals who decrease their budget share is compensated by the existence of individuals who increase their budget share.Aggregation; Behavioral heterogeneity; Large economy; Balancing effect; Insensitivity of maket budget shares to changes in prices and income.