Background:Research on therapeutic processes has explored the elements that enhance psychotherapy’s effectiveness,particularly the role of common factors across various models.The therapist’s use of directiveness an...Background:Research on therapeutic processes has explored the elements that enhance psychotherapy’s effectiveness,particularly the role of common factors across various models.The therapist’s use of directiveness and support,as common variables,is crucial for effective treatment.Effective therapists adapt their level of directiveness and support according to the treatment phase,the issue being addressed,and the patient’s characteristics.This study examines the importance therapists attribute to directiveness and support,as well as its relationship with theoretical orientation,access to research publications,and stance on the similar effectiveness of different psychotherapeutic models.It aims to determine whether therapists’attributions regarding this variable are in line with the importance it is given in process research.Methods:Responses from 69 psychotherapists to the Psychotherapeutic Effectiveness Attribution Questionnaire(PEAQ-12),which assesses the importance therapists place on key psychotherapeutic process variables,including the directiveness and support provided,were analyzed.Theoretical orientations,ages,and experience levels were considered.Non-parametric tests,contingency tables,χ^(2)tests,t-tests,and ANOVAs were used to assess the variation in responses.Results:Common factors were often identified as key contributors to therapeutic healing,though these differences were not statistically significant(χ^(2)(2,N=67)=3.701,p=0.157).For the“directiveness and support from the therapist”variable,significant differences were observed:Cognitive-behavioral therapists valued directiveness and support more than psychodynamic therapists(t(20)=−3.569,p=0.002;Cohen’s d=1.18).Therapists who view cognitive-behavioral therapies as most effective also rated this variable higher(t(38)=3.816,p<0.001;Cohen’s d=1.21).Those regularly accessing specialized psychotherapy research publications valued this variable less than those who do so occasionally(t(64)=−2.693,p=0.009;Cohen’s d=0.65).Therapists who support the similar effectiveness of different models tend to favor common factors,including directiveness and support(χ^(2)(2,N=66)=12.522,p=0.002).Conclusions:Therapists express doubts about the factors influencing psychotherapy’s effectiveness,reflecting the ongoing debate.They align their views on the importance of directiveness and support with their theoretical orientation and positioning on the similar effectiveness of psychotherapies.The importance of analyzing therapists’attributions about the factors responsible for therapeutic change is emphasized,which will impact clinical practice.Advocacy for therapist flexibility and adaptation of therapy to the patient’s needs,including the level of directiveness and support provided,has been shown to be essential for effective psychotherapy.展开更多
Objectives:This study aims to develop the Directive and Nondirective Support Scale for Patients with Type 2 Diabetes(DNSS-T2DM)to measure diabetes-specific support and patients’preference as well as evaluate the cons...Objectives:This study aims to develop the Directive and Nondirective Support Scale for Patients with Type 2 Diabetes(DNSS-T2DM)to measure diabetes-specific support and patients’preference as well as evaluate the construct validity and reliability of the DNSS-T2DM.Methods:A cross-sectional study was conducted in Tongzhou District,Beijing,China from July to September 2015.A total of 474 participants who had been diagnosed as type 2 diabetes by physicians and completed the DNSS-T2DM were included.The original 11-item DNSS-T2DM contains five items on nondirective support(Items 1-5)and six items on directive support(Items 6-11).There were two parallel questions for each item with one to measure the preference for support(Preference part)and the other to measure the perception of support in reality(Reality part).The final DNSS-T2DM was determined based on the results of the exploratory factor analysis(EFA).The construct validity of the final DNSS-T2DM was evaluated by the confirmatory factor analysis(CFA).The reliability was evaluated by internal consistency with Cronbach’sαcoefficients.Results:A final 7-item DNSS-T2DM loaded on 2 factors with four items representing nondirective support and three items representing directive support was determined based on the EFA.The CFA indicated a satisfactory construct validity.The internal consistency of the 7-item DNSS-T2DM as well as the nondirective support items was satisfactory with Cronbach’sα≥7.00.70.Conclusions:Our study supported the validity and reliability of the 7-item DNSS-T2DM.Further studies on the application of the DNSS-T2DM in different settings and population are needed.展开更多
Machine learning has a powerful potential for performing the template attack(TA) of cryptographic device. To improve the accuracy and time consuming of electromagnetic template attack(ETA), a multi-class directed acyc...Machine learning has a powerful potential for performing the template attack(TA) of cryptographic device. To improve the accuracy and time consuming of electromagnetic template attack(ETA), a multi-class directed acyclic graph support vector machine(DAGSVM) method is proposed to predict the Hamming weight of the key. The method needs to generate K(K ? 1)/2 binary support vector machine(SVM) classifiers and realizes the K-class prediction using a rooted binary directed acyclic graph(DAG) testing model. Further, particle swarm optimization(PSO) is used for optimal selection of DAGSVM model parameters to improve the performance of DAGSVM. By exploiting the electromagnetic emanations captured while a chip was implementing the RC4 algorithm in software, the computation complexity and performance of several multi-class machine learning methods, such as DAGSVM, one-versus-one(OVO)SVM, one-versus-all(OVA)SVM, Probabilistic neural networks(PNN), K-means clustering and fuzzy neural network(FNN) are investigated. In the same scenario, the highest classification accuracy of Hamming weight for the key reached 100%, 95.33%, 85%, 74%, 49.67% and 38% for DAGSVM, OVOSVM, OVASVM, PNN, K-means and FNN, respectively. The experiment results demonstrate the proposed model performs higher predictive accuracy and faster convergence speed.展开更多
文摘Background:Research on therapeutic processes has explored the elements that enhance psychotherapy’s effectiveness,particularly the role of common factors across various models.The therapist’s use of directiveness and support,as common variables,is crucial for effective treatment.Effective therapists adapt their level of directiveness and support according to the treatment phase,the issue being addressed,and the patient’s characteristics.This study examines the importance therapists attribute to directiveness and support,as well as its relationship with theoretical orientation,access to research publications,and stance on the similar effectiveness of different psychotherapeutic models.It aims to determine whether therapists’attributions regarding this variable are in line with the importance it is given in process research.Methods:Responses from 69 psychotherapists to the Psychotherapeutic Effectiveness Attribution Questionnaire(PEAQ-12),which assesses the importance therapists place on key psychotherapeutic process variables,including the directiveness and support provided,were analyzed.Theoretical orientations,ages,and experience levels were considered.Non-parametric tests,contingency tables,χ^(2)tests,t-tests,and ANOVAs were used to assess the variation in responses.Results:Common factors were often identified as key contributors to therapeutic healing,though these differences were not statistically significant(χ^(2)(2,N=67)=3.701,p=0.157).For the“directiveness and support from the therapist”variable,significant differences were observed:Cognitive-behavioral therapists valued directiveness and support more than psychodynamic therapists(t(20)=−3.569,p=0.002;Cohen’s d=1.18).Therapists who view cognitive-behavioral therapies as most effective also rated this variable higher(t(38)=3.816,p<0.001;Cohen’s d=1.21).Those regularly accessing specialized psychotherapy research publications valued this variable less than those who do so occasionally(t(64)=−2.693,p=0.009;Cohen’s d=0.65).Therapists who support the similar effectiveness of different models tend to favor common factors,including directiveness and support(χ^(2)(2,N=66)=12.522,p=0.002).Conclusions:Therapists express doubts about the factors influencing psychotherapy’s effectiveness,reflecting the ongoing debate.They align their views on the importance of directiveness and support with their theoretical orientation and positioning on the similar effectiveness of psychotherapies.The importance of analyzing therapists’attributions about the factors responsible for therapeutic change is emphasized,which will impact clinical practice.Advocacy for therapist flexibility and adaptation of therapy to the patient’s needs,including the level of directiveness and support provided,has been shown to be essential for effective psychotherapy.
文摘Objectives:This study aims to develop the Directive and Nondirective Support Scale for Patients with Type 2 Diabetes(DNSS-T2DM)to measure diabetes-specific support and patients’preference as well as evaluate the construct validity and reliability of the DNSS-T2DM.Methods:A cross-sectional study was conducted in Tongzhou District,Beijing,China from July to September 2015.A total of 474 participants who had been diagnosed as type 2 diabetes by physicians and completed the DNSS-T2DM were included.The original 11-item DNSS-T2DM contains five items on nondirective support(Items 1-5)and six items on directive support(Items 6-11).There were two parallel questions for each item with one to measure the preference for support(Preference part)and the other to measure the perception of support in reality(Reality part).The final DNSS-T2DM was determined based on the results of the exploratory factor analysis(EFA).The construct validity of the final DNSS-T2DM was evaluated by the confirmatory factor analysis(CFA).The reliability was evaluated by internal consistency with Cronbach’sαcoefficients.Results:A final 7-item DNSS-T2DM loaded on 2 factors with four items representing nondirective support and three items representing directive support was determined based on the EFA.The CFA indicated a satisfactory construct validity.The internal consistency of the 7-item DNSS-T2DM as well as the nondirective support items was satisfactory with Cronbach’sα≥7.00.70.Conclusions:Our study supported the validity and reliability of the 7-item DNSS-T2DM.Further studies on the application of the DNSS-T2DM in different settings and population are needed.
基金supported by the National Natural Science Foundation of China(61571063,61202399,61171051)
文摘Machine learning has a powerful potential for performing the template attack(TA) of cryptographic device. To improve the accuracy and time consuming of electromagnetic template attack(ETA), a multi-class directed acyclic graph support vector machine(DAGSVM) method is proposed to predict the Hamming weight of the key. The method needs to generate K(K ? 1)/2 binary support vector machine(SVM) classifiers and realizes the K-class prediction using a rooted binary directed acyclic graph(DAG) testing model. Further, particle swarm optimization(PSO) is used for optimal selection of DAGSVM model parameters to improve the performance of DAGSVM. By exploiting the electromagnetic emanations captured while a chip was implementing the RC4 algorithm in software, the computation complexity and performance of several multi-class machine learning methods, such as DAGSVM, one-versus-one(OVO)SVM, one-versus-all(OVA)SVM, Probabilistic neural networks(PNN), K-means clustering and fuzzy neural network(FNN) are investigated. In the same scenario, the highest classification accuracy of Hamming weight for the key reached 100%, 95.33%, 85%, 74%, 49.67% and 38% for DAGSVM, OVOSVM, OVASVM, PNN, K-means and FNN, respectively. The experiment results demonstrate the proposed model performs higher predictive accuracy and faster convergence speed.
