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Exercise Stage of Change and Self-Efficacy in Primary Care: Implications for Intervention 总被引:1,自引:0,他引:1
Rita Cowan Everett Logue Lori Milo Paula J. Britton William Smucker 《Journal of clinical psychology in medical settings》1997,4(3):295-311
Multiple chronic diseases are caused or complicated by a sedentary lifestyle. Thus, an important and challenging application of psychology in clinical settings is changing the behavior of sedentary primary care patients. This study focused on exercise stage of change and self-efficacy in a sample of adult family practice patients recruited while waiting for their scheduled physician appointment. Regarding exercise stage of change, 15% of respondents were in the Precontemplation stage, 26% in the Contemplation stage, 50% in the Preparation stage, 7% in the Action stage, and 13% in the Maintenance stage. Mean self-efficacy scores for exercise were significantly higher among respondents in the Action and Maintenance stages of change. These cross-sectional data are consistent with the hypothesis that movement through the exercise stages of change could be encouraged by clinical interventions that increase exercise self-efficacy. The identification of multiple personal opportunities for increasing exercise self-efficacy may be clinically useful in this context. Recommendations for psychologists in primary care settings in their work with physicians are offered. 相似文献
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形成性测量模型(Formative Model, FM)是指标变异导致潜变量变异的模型, 反映性测量模型(Reflective Model, RM)是潜变量变异导致指标变异的模型。FM在模型界定、识别和估计、信效度评价以及模型应用等方面均与RM存在极大的不同。模型界定错误会使参数估计发生偏差, 影响统计结论的有效性, 应当审慎考虑指标和潜变量之间的关系, 选择恰当的测量模型。进一步揭示两者的区别和误用带来的偏差, 完善FM的识别和估计、信效度评价方法、对变量含义的解释以及高阶FM的理论解释和模型估计是未来的研究方向。 相似文献
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Models carry the meaning of science. This puts a tremendous burden on the process of model selection. In general practice,
models are selected on the basis of their relative goodness of fit to data penalized by model complexity. However, this may
not be the most effective approach for selecting models to answer a specific scientific question because model fit is sensitive
to all aspects of a model, not just those relevant to the question. Model Structural Adequacy analysis is proposed as a means
to select models based on their ability to answer specific scientific questions given the current understanding of the relevant
aspects of the real world. 相似文献
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We add a limited but useful form of quantification to Coalition Logic, a popular formalism for reasoning about cooperation
in game-like multi-agent systems. The basic constructs of Quantified Coalition Logic (QCL) allow us to express such properties as “every coalition satisfying property P can achieve φ” and “there exists a coalition C satisfying property P such that C can achieve φ”. We give an axiomatisation of QCL, and show that while it is no more expressive than Coalition Logic, it is nevertheless
exponentially more succinct. The complexity of QCL model checking for symbolic and explicit state representations is shown
to be no worse than that of Coalition Logic, and satisfiability for QCL is shown to be no worse than satisfiability for Coalition
Logic. We illustrate the formalism by showing how to succinctly specify such social choice mechanisms as majority voting,
which in Coalition Logic require specifications that are exponentially long in the number of agents. 相似文献