The purpose of this study is to revise and further develop an attitude towards person with intellectual disability scale (APIDs). The further development of this scale was mainly based on Community Living Attitude Scale (CLAS) and Attitude towards Intellectual Disability Questionnaire (ATTID). The study examined the psychometric properties of the proposed measuring instrument in terms of its factorial validity and internal consistency reliability. The confirmatory factor analysis showed that the proposed five-factor model did not fit the data well. Exploratory factorial analysis was then conducted to re-examine the structure. The results suggested a three-factor structure, i.e. sociality, capacity, and protection. The internal consistency reliability was good for sociality and capacity but needs further improvement for protection. The cultural and social landscape within a population affects the factorial structure an attitude scale. The use of APIDs was also discussed. 相似文献
There is a growing use of noncognitive assessments around the world, and recent research has posited an ideal point response process underlying such measures. A critical issue is whether the typical use of dominance approaches (e.g., average scores, factor analysis, and the Samejima's graded response model) in scoring such measures is adequate. This study examined the performance of an ideal point scoring approach (e.g., the generalized graded unfolding model) as compared to the typical dominance scoring approaches in detecting curvilinear relationships between scored trait and external variable. Simulation results showed that when data followed the ideal point model, the ideal point approach generally exhibited more power and provided more accurate estimates of curvilinear effects than the dominance approaches. No substantial difference was found between ideal point and dominance scoring approaches in terms of Type I error rate and bias across different sample sizes and scale lengths, although skewness in the distribution of trait and external variable can potentially reduce statistical power. For dominance data, the ideal point scoring approach exhibited convergence problems in most conditions and failed to perform as well as the dominance scoring approaches. Practical implications for scoring responses to Likert-type surveys to examine curvilinear effects are discussed. 相似文献
Psychometric functions are typically estimated by fitting a parametric model to categorical subject responses. Procedures to estimate unidimensional psychometric functions (i.e., psychometric curves) have been subjected to the most research, with modern adaptive methods capable of quickly obtaining accurate estimates. These capabilities have been extended to some multidimensional psychometric functions (i.e., psychometric fields) that are easily parameterizable, but flexible procedures for general psychometric field estimation are lacking. This study introduces a nonparametric Bayesian psychometric field estimator operating on subject queries sequentially selected to improve the estimate in some targeted way. This estimator implements probabilistic classification using Gaussian processes trained by active learning. The accuracy and efficiency of two different actively sampled estimators were compared to two non-actively sampled estimators for simulations of one of the simplest psychometric fields in common use: the pure-tone audiogram. The actively sampled methods achieved estimate accuracy equivalent to the non-actively sampled methods with fewer observations. This trend held for a variety of audiogram phenotypes representative of the range of human auditory perception. Gaussian process classification is a general estimation procedure capable of extending to multiple input variables and response classes. Its success with a two-dimensional psychometric field informed by binary subject responses holds great promise for extension to complex perceptual models currently inaccessible to practical estimation.
Environmental issues are some of the most pressing threats the world is facing nowadays. In this context, motivating individual pro-environmental behavior becomes highly relevant. One strategy is to harness people's pro-environmental dispositions (e.g., biospheric values, pro-environmental attitudes). Although acknowledging the need to behave pro-environmentally lies at the core of these dispositions, the extent to which they are reflected in day-to-day pro-environmental practices fluctuates to a great extent. How to bridge this gap between dispositions and behaviors in pro-environmentalism? This research tests a novel psychological solution, that is, to heighten subjective feelings of power. Power depicts people's control over their own and others’ outcomes. Two studies (total N = 338, with n = 200 in Study 1 and n = 138 in Study 2) manipulated people's situational sense of high versus low power (by recalling and writing about relevant incidents), measured pro-environmental dispositions (biospheric values in Studies 1 and 2; attitude toward a specific environmental cause in Study 2), and examined their effects on pro-environmental behaviors (spending time on environmental persuasion in Study 1 and spending money on environmental donation in Study 2). Overall, both studies revealed that pro-environmental dispositions predicted pro-environmental behaviors, but only when the actors were prompted to experience a high instead of a low sense of power. The findings illuminate power as an important and viable communication tactic—to orient people toward their dispositions and practice what they preach in pro-environmentalism. 相似文献
