Subjects: Other Disciplines >> Synthetic discipline submitted time 2023-10-09 Cooperative journals: 《心理科学进展》
Abstract： Eudaimonic well-being occurs when people's life activities align with deeply held values, and they positively engage in activities to realize their potential. Eudaimonic well-being is characterized by a sense of purpose and meaning. It has become a flourishing arena of scientific inquiry and clinical practice. However, eudaimonic enhancement remains neglected in positive psychology. The self-determination theory (SDT) proposes that mindfulness is possibly the most centrally discussed intrapersonal factor influencing the pathway to enhance eudaimonic well-being. This review aims to explore the mechanisms by which mindfulness positively affects eudaimonic well-being. Investigating this question not only provides an essential extension of self-determination theory but also adds to our understanding of the value and generative manifestations of mindfulness. In addition, it may provide a theoretical foundation for developing mindfulness interventions focusing solely on eudaimonic enhancement. Recent research has found that mindfulness can be effective in improving well-being. Mindfulness traits were particularly strong in relation to eudaimonic well-being; meditators reported significantly higher levels of eudaimonic well-being orientation than non-meditators; and mindfulness traits moderated the negative relationship between stressful events and eudaimonic well-being. Attention awareness and acceptance can influence eudaimonic well-being by promoting positive qualities and experiencing fewer negative emotions in response to stress. Mindfulness-based training has been shown to improve eudaimonic well-being in clinical groups with psychological and physical symptoms, and non-clinical groups of middle school students, workers, and athletes. However, it is noteworthy that mindfulness training improved eudaimonic well-being only when practiced over a long period. The low intensity and short duration of this training may not have produced changes in eudaimonic well-being. Based on the S-ART model, self-determination theory, mindfulness-to-meaning theory, and empirical literature, this review proposed a model of mindfulness-self-regulation-eudaimonic well-being. Attention awareness and acceptance together explain how mindfulness positively affects eudaimonic well-being by improving cognitive regulation. Cognitive regulation processes include meta-awareness, Which reduces experiential fusion; cognitive reappraisal and perspective taking, which changes maladaptive self-schemas; and self-inquiry, which reduces cognitive reification. Moreover, mindfulness also positively affects eudaimonic well-being by improving emotional regulation. Emotional regulation processes include cognitive reappraisal, which reduces negative semantic narrative patterns and emotions during stressful events; savoring increasing positive emotions. Finally, mindfulness had a positive effect on eudaimonic well-being by improving behavioral regulation. Behavioral regulation processes include changing behavioral goals, such as increasing internal behavioral goals and decreasing external behavioral goals; and it also includes improving autonomous behavior, which involves reducing cognitive distortion and negative emotion-driven behavior, reducing automatic behavior, and transforming forced behavioral regulation. Furthermore, mindfulness positively affects eudaimonic well-being by promoting cognitive regulation, improving emotional regulation, and further improving behavioral regulation. Future research could focus on many aspects. First, different effects of the basic components of mindfulness could be analyzed, to further resolve the paradox between single-component and two-component views. Further analyzing of the role of attention awareness and acceptance is required when considering whether individuals experience stressful events and whether such events cause negative emotions. The single-component view of mindfulness requires an additional explanation of the differential roles of attention and awareness. Second, the mechanisms through which mindfulness benefits eudaimonic well-being can be explored. Mindfulness-to-meaning theory needs to be further validated using a variety of research methods, such as ecological momentary assessment, as the savoring and reappraisal hypotheses remain controversial. Besides improving autonomous behavior consistent with values in behavioral regulation, mindfulness may also improve behavioral abilities, like problem-focused thinking and coping competence. Third, researchers should develop targeted mindfulness-based training programs to improve eudaimonic well-being and identify the boundary conditions of the main effect from four aspects: practitioner, practice, relationship, and culture.
Subjects: Psychology >> Psychological Measurement submitted time 2023-04-22
Abstract： Test mode effect (TME) refers to the difference in test function caused by the administration of the same test in different test modes. The existence of TME will have an impact on test fairness, selection criteria and test equating, so it is of great significance to accurately detect and interpret TME. By systematically sorting out the source, detection (including the experimental design and detection methods) and research results of TME, the methodology of TME research is comprehensively demonstrated. Further interpretation of the TME model, expansion of the test modes in TME research, and application of TME research results to largescale educational assessment programs in China, are important future development directions in the field of TME.
Subjects: Psychology >> Developmental Psychology submitted time 2023-03-28 Cooperative journals: 《心理科学进展》
Abstract： Item position effect (IPE) refers to the item parameter non-invariance when the same item is placed at different positions of the tests, after controlling for the influence of random errors. The presence of IPE causes the violation of the critical parameter invariance assumption made in item response theory, making the applications such as test equating and computerized adaptive testing at risk. At present, the existing researches in this field mainly focus on the detection and modeling of IPE. However, more research efforts are needed to further explain the consequences of the detected IPE and to provide an in-depth discussion of IPE under different scenarios, which is of great importance to both basic research and practical applications.
Subjects: Psychology >> Developmental Psychology submitted time 2023-03-28 Cooperative journals: 《心理科学进展》
Abstract： Explanatory item response theory models (EIRTM) refer to a family of item response theory (IRT) models that are constructed based on the generalized linear mixed models and nonlinear mixed models. EIRTM can be utilized to address various measurement problems by incorporating predictors into IRT models. First, the relevant concepts and parameter estimation methods of EIRTM are introduced in this paper, followed by the procedures regarding how to use EIRTM to account for the item position effect, test mode effect, differential item functioning, local person dependence, and local item dependence. Next, an example is provided to illustrate the use of EIRTM. Finally, the shortcomings and potential applications of EIRTM are discussed.
Subjects: Psychology >> Social Psychology submitted time 2023-03-28 Cooperative journals: 《心理科学进展》
Abstract： Computerized classification testing (CCT) can adaptively classify test-takers into two or more different categories, and it has been widely used in qualifying tests and clinical psychology or medical diagnosis. As an essential part of CCT, the termination rule determines when the test is to be stopped and to which category the test-taker is ultimately classified into, directly affecting the test efficiency and classification accuracy. According to the theoretical basis of the termination rules, existing rules can be roughly divided into the likelihood ratio, Bayesian decision theory, and confidence interval rules. And their core ideas are constructing hypothesis tests, designing loss functions, and comparing the relative positions of confidence intervals, respectively. At the same time, when constructing specific termination rules, the requirement of different test scenarios (e.g., the number of categories and the number of tests’ dimensions) should also be considered. There are advantages and disadvantages to each of the three types of termination rules. Specifically, the likelihood ratio rule is based on the likelihood ratio test, with better theoretical properties. However, the method requires prior determination of the indifference interval and the type I and II error rates, introducing the impact of subjective factors. Also, it is more challenging to extend the method in complex test situations, such as multidimensional and multicategory CCT. Bayesian decision theory rules make classification decisions based on the loss function. It can dynamically optimize the decision from a more global perspective since it works backward from the final stage of the test. In addition, the variety of loss functions makes the method very flexible in form and makes it easy to be applied to different test situations. However, in practice, the flexibility will inevitably result in the uncertainty of the choice of loss function, and the inappropriate loss function may be biased. The confidence interval method is the most straightforward because of its relatively simple principle and low computational effort. However, this method is less robust and has a relatively low test efficiency. Currently, CCT is mainly applied in eligibility tests and clinical medicine questionnaires. In eligibility tests, all three types of termination rules have the potential to be widely applied. However, in practice, the principles of the likelihood ratio rule and the Bayesian decision theory rule are not easily understood by the general public, and these methods are also accompanied by the problem of over-exposure of items for their preference of cut-point based item selection methods. Therefore, the confidence interval rule, which is relatively simple in principle and has alleviated item exposure, has been widely used in existing qualifying tests. Bayesian decision theory rules are more applicable in clinical questionnaires because of their finer control over various classification losses. The following can be considered for future research on CCT termination rules. First, Bayesian decision theory rules can be improved by considering non-statistical constraints with the help of the flexibility of its loss function. Second, termination rules can be developed for multidimensional and multicategory CCT to meet more practical needs. Third, termination rules that integrate response time can be developed to improve test efficiency and classification accuracy. Fourth, it is possible to construct termination rules under the framework of machine learning.
Subjects: Psychology >> Social Psychology submitted time 2023-03-27 Cooperative journals: 《心理学报》
Abstract： Computerized classification testing (CCT) is a subset of computerized adaptive testing (CAT), and it aims to classify examinees into one of at least two possible categories that denote results such as pass/fail or non-mastery/partial mastery/mastery. Therefore, CCTs focus on increasing the accuracy of classification which is different from CATs designed for precise measurement. The termination rule is one of the key components of CCT. However, as pointed out by Nydick (2013), most CCTs (i.e., UCCTs) were designed under unidimensional item response theory (IRT), in which the unidimensionality assumption is easily violated in practice. Thus, researchers then began to construct multidimensional CCT termination rules (i.e., MCCT) based on multidimensional IRT. To date, however, these rules still have some deficiencies in terms of classification accuracy or test efficiency. Most current studies on termination rules of MCCT are based on termination rules of UCCT. In UCCTs, termination rules require setting a cut point, θ0θ0{{\theta }_{0}}, of the latent trait to calculate the statistics; and when they are extended from UCCT to MCCT, the cut point will become a classification bound curve or even a surface (i.e., g(θ)=0g(θ)=0g(\theta )=0). At this time, a question is how to convert the curve or surface into θ0θ0{{\theta }_{0}}. To this end, the projected sequential probability ratio test (P-SPRT), constrained SPRT (C-SPRT; Nydick, 2013), and multidimensional generalized likelihood ratio (M-GLR) were respectively proposed to solve the problem in different ways. Among them, P-SPRT and C-SPRT choose specific points on g(θ) as the approximate cut point, θ^0θ^0{{\hat{\theta }}_{0}}, by projecting into Euclidean space or constraining on g(θ) respectively; as for M-GLR, because the generalized likelihood ratio statistic can be calculated without a cut point, it can be directly employed in MCCT. To overcome the limitation that P-SPRT may lead to unstable results at the beginning of the test, this study proposed the Mahalanobis distance-based SPRT (Mahalanobis-SPRT). In addition, stochastic curtailment is a technique for shortening the test length by predicting whether the classification of participants will change as the test continues. This article also combined M-GLR with the stochastic curtailment and proposed M-GLR with stochastic curtailment (M-SCGLR). A full-scale simulation study was conducted to (1) compare both the Mahalanobis-SPRT and M-SCGLR with the P-SPRT, C-SPRT, M-GLR, and multidimensional stochastically curtailed SPRT (M-SCSPRT) under varying conditions; (2) compare the classification performance of the above six termination rules for participants with specific abilities to explore whether there is a significant difference in the sensitivity of various rules to classify specific participants. To achieve the first research objective, three levels of correlation between dimensions (ρ=0, 0.5, and 0.8), two item bank structures (within-item multidimensionality and between-item multidimensionality), and two kinds of classification boundary (compensatory boundary and non-compensatory boundary) were considered; to achieve the second objective, 36 specific ability points (θ1,θ2)(θ1,θ2)({{\theta }_{1}},{{\theta }_{2}}) were generated where θ1,θ2∈{−0.5,−0.3,−0.1,0.1,0.3,0.5}θ1,θ2∈{−0.5,−0.3,−0.1,0.1,0.3,0.5}{{\theta }_{1}},{{\theta }_{2}}\in \{-0.5,-0.3,-0.1,0.1,0.3,0.5\}. The results showed that: (1) when the compensatory classification function was used, the Mahalanobis-SPRT led to higher classification accuracy and similar test length to the rules without stochastic curtailment; (2) under almost all conditions, the M-SCGLR not only possessed higher precision but also maintained the short test length, compared to M-SCSPRT that also uses stochastic curtailment; (3) the six termination rules showed a consistent change in the sensitivity of the precision and test length to specific participants. To sum up, two new MCCT termination rules (Mahalanobis-SPRT and M-SCGLR) are put forward in this article. Although the simulation results are very promising, several research directions merit further investigation, such as the development of MCCT termination rules for more than two categories, and the construction of MCCT termination rules by incorporating process data like the response time.
Subjects: Materials Science >> Materials Science (General) submitted time 2023-03-18 Cooperative journals: 《材料研究学报》
Abstract： Three high-performance continuous fibers PBO, Armos and Twaron were on-line modified by atmospheric air dielectric barrier discharge (DBD) plasma. Then the modified fibers were characterized by X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), atomic force microscopy (AFM), measurements of single fiber tensile strength (SFTS) and interlaminar shear strength (ILSS) in terms of their surface chemical composition, morphology, roughness and tensile strength, as well as interfacial adhesion properties of fiber reinforced composites respectively. Results showed that the oxygen and nitrogen content, and the roughness of fiber surface after DBD plasma modification with PBO, Armos and Twaron were all increased, and the ILSS of their composites were enhanced by 18.6%, 10.2% and 24.8%, respectively. However, it is important to note that there were significant differences in the increment of oxygen and nitrogen content as well as the etching effect of the surface for the three modified fibers, which might be related to the difference of their molecular structures and thermal performances. Apparently, the atmospheric air dielectric barrier discharge (DBD) plasma treatment is proved to be an effective means to improve the surface performance of the fibers while no harm to their SFTS and thereby the ILSS of the composite composed of a resin with the three fibers may obviously be enhanced.
Subjects: Psychology >> Psychological Measurement submitted time 2021-11-16
Abstract： Computerized classification testing (CCT) has been widely used in eligibility testing and clinical psychology since it can efficiently classify participants. As an essential part of CCT, the termination rule determines when the test is to be stopped and what category the participants are ultimately classified into, directly affecting the test efficiency and classification accuracy. The existing termination rules can be roughly divided into the likelihood ratio, Bayesian decision theory, and confidence interval rules. And their core ideas are constructing hypothesis tests, designing loss functions, and comparing the relative positions of confidence intervals, respectively. Based on these ideas, in different test situations, CCT termination rules have various specific forms. Future research can further extend Bayesian rules, construct rules for multicategory MCCT, integrate process data into termination rules, and build rules under the framework of machine learning. In addition, from the perspective of practical requirement, all three types of rules have the potential to be applied in the eligibility test, while the clinical questionnaire tends to choose Bayesian rules.
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Subjects: Psychology >> Psychological Measurement submitted time 2021-04-14
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Peer Review Status:Awaiting Review
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