How useful are the stages of change for targeting interventions? randomized test of a brief intervention to reduce smoking

Objectives. To see whether the stages of change are useful for targeting a brief intervention to reduce smoking based on implementation intentions. A second objective was to rule out demand characteristics as an alternative explanation for the findings of intervention studies based on the transtheoretical model and implementation intentions. Design. Participants (N = 350) were randomized to a passive control condition (questionnaire only), active control condition (questionnaire-plus-instruction to plan to quit) or experimental condition (questionnaire, plan to quit, form an implementation intention). Their behavior and psychosocial orientation to quit were measured at baseline and 2-month follow-up. Main Outcome Measures. Theory of planned behavior variables, nicotine dependence and quitting. Results. Significantly more people quit smoking in the experimental condition than in the control conditions, and the planning instructions changed intention to quit and perceived control over quitting, but not behavior. Stage of change moderated these effects such that implementation intentions worked best for individuals who were in the preparation stage at baseline. Conclusion. Harnessing both motivational and volitional processes seems to enhance the effectiveness of smoking cessation programs, although further work is required to clarify inconsistencies in the literature using the stages of change.</p

MANAGEMENT OF INTENSIVE FORAGE-BEEF PRODUCTION UNDER YIELD UNCERTAINTY

Forage production variability is incorporated into a decision theory framework for a beef producer in East Texas. The results suggest that the least risky, and also the most profitable, approach to intensive forage beef production is to plan for relatively poor weather conditions and low forage production. This results in a more diverse forage system and a smaller herd size than would be found optimal under the assumption of constant average forage production. These results also demonstrate that the assumption of constant average forage production may results in grossly exaggerated estimates of expected net returns.Livestock Production/Industries, Risk and Uncertainty,

OPTIMAL STOCKING OF RANGELAND FOR LIVESTOCK PRODUCTION WITHIN A DYNAMIC FRAMEWORK

A dynamic model is constructed and utilized to illustrate the interactions of several primary dynamic ecologic and economic relationships that are important in effective rangeland management. Within this context, the implications of various range management strategies are explored.Livestock Production/Industries,

Economic Value of Groundwater Resources and Irrigated Agriculture in the Oklahoma Panhandle

An economic optimization model was developed using available groundwater resources in the Oklahoma Panhandle to estimate value of water for irrigated agriculture in the area. The model will serve as policy tool to analyze alternative water management strategies and conservation programs to assess the economic impact of depleting Ogallala Aquifer.Ogallala Aquifer, Irrigated Agriculture, Groundwater Conservation, Water Management Policy, Oklahoma Panhandle, Resource /Energy Economics and Policy,

The dynamics of crop yields in the U. S. Corn Belt as effected by weather and technological progress

Producers of agricultural products, policy makers, and consumers alike have a keen interest in what will happen to crop yields in the future. This study attempts to carefully analyze past trends in crop yields in five Corn Belt states, Illinois, Indiana, Iowa, Missouri, and Ohio, and how they have been affected by weather and technological progress over time;State average yields for corn grain, corn silage, soybeans, small grains, and meadow (leguminous hay) are modeled as a system of equations where yields are functions of weather, technological progress, and nitrogen application. Time series data on yields, nitrogen and corn prices, nitrogen application, and weather are collected. Time is used as a proxy variable for technological progress and the models from all five states are estimated using three stage least squares regression. The estimated models do a good job of fitting the 1951-1980 time series data and they illustrate that technological progress and weather are the most important factors that affect yields;The prospects of favorable future weather are analyzed by regressing weather variables from 1930-1980 or dummy variables for each state and for periods of abnormally favorable weather. These models are able to explain only a small portion of the total variance in weather, but they do indicate that the periods during 1942-1952 and 1961-1973 can be characterized as more cool and wet, and generally more favorable to crop yields than average. However, attempts to use this information to project future weather would be ludicrous;The prospects of future yield increases as a result of technological progress are examined by looking at some of the major factors that affect crop yields. It can be seen that technological progress is a large and complex set of interacting conditions, occurrences and activities that cannot be easily modeled, described, or projected. Attempts to project future yields must be based on various assumptions about future technological progress;Yields are projected for the year 2000, using the estimated models, under six different scenarios based on various assumptions about future technological progress, weather, and nitrogen application. In general, with the noted exception of wheat, there is little evidence found in the time series data that would indicate a leveling off of Corn Belt crop yields in the near future

Commentary on taguchi's parameter design with dynamic characteristics

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93684/1/4680120203_ftp.pd