Response time data is increasingly recognized for its potential to reveal the pace and conduct of examinees,offering valuable insights into educational and psychological assessments.Unusually rapid test completion may suggest irregular behavior,such as obtaining prior knowledge of certain test items ahead of his/her test.Current research indicates that the signal likelihood ratio(SLR)test outperforms other methods in maintaining type I error rates and enhancing statistical detection powers.This paper focuses on comparing the SLR with two novel test statistics designed to detect speed discrepancies. Using response time data,we developed two Bayesian-inspired statistics to assess variations in test-taking speed.To gauge the efficacy of these statistics in detecting prior knowledge of test items,we initiate our analysis with a well-known data set from real-world scenarios.This data set has been previously scrutinized in studies aimed at identifying item preknowledge,allowing us to benchmark our findings against existing literature.Employing the signal likelihood ratio(SLR),the Bayesian factor(BF),and the posterior probabilistic(PP)approaches,we scrutinize each examinee's response time data.Based on the flagged items marked in the dataset,the entire test is divided into two parts:the collection of normal items and the collection of flagged items.To more intuitively examine whether the"marked"abnormal examinees in the original dataset have differences in response speed during the test,the data of Form1 is analyzed as follows:(1)After excluding data with missing information and"marked"abnormal data,the log-normal time model is fitted to the data to obtain the item parameters for each item.(2)After excluding examinees with missing data,for the 41"marked"examinees in the dataset,speed parameter estimation is conducted based on all 170 questions in the test,106 non-leaked questions,and 64 leaked questions.The speed parameters obtained indicate that the examinees identified by the three methods all have speed differences.(3)After excluding examinees with missing data,all 1624 examinees in the test are analyzed using SLR,BF,and PP,and speed parameter estimation is conducted for the"marked"abnormal examinees. The outcomes are then juxtaposed with the marked"aberrant examinees"in the original data set.Interestingly,all three methods exhibit a more"conservative"stance compared to the original dataset's annotations.Specifically,BF,SLR,and PP identify 13,11,and 9 examinees,respectively.Moreover,the detection sets from these methods are inclusive,with BF encompassing both SLR and PP detection,and SLR encompassing PP detection.This suggests that the PP method is the most stringent in flagging abnormal examinee behavior,while BF is comparatively more lenient. Building on these findings,we designed a simulation study to further appraise the performance of the proposed methods.The results indicate that examinees with prior knowledge exhibit distinct response speeds on leaked versus normal items.The sensitivity of the three statistics—SLR,BF,and PP—varies,with BF being the most responsive to speed differences and PP the least.Targeted simulation experiments are conducted to assess the impact of varying degrees of speed differences due to item preknowledge,the prevalence of such preknowledge among examinees,and the proportion of known items within the total test under diverse conditions.A comprehensive comparison reveals that:(1)All three methods effectively control type I error rates;(2)A medium speed difference(U=.35 to.50)allows for high detection accuracy;(3)To accurately identify examinees with item preknowledge,they must have prior knowledge of at least 20％of the items;and(4)Given the study's parameters are known,the prevalence of preknowledge in the population is expected to have a minimal impact on test outcomes.The newly developed statistics demonstrate robust performance in detecting response speed differences during the examination process.
This study aimed to investigate the capacity of a large language model(LLM),specifically DeepSeek,for simulating regional psychological characteristics based solely on demographic information.In particular,it examined whether DeepSeek can preserve culturally distinct psychological patterns without reducing them to oversimplified,flattened profiles,with a focus on personality traits and subjective well-being across different regions of China.Utilizing a sample matched to demographic features from the 2018 China Family Panel Studies(CFPS2018)(N=2,943),the research generated artificial"virtual participants"with DeepSeek.The simulated dataset was compared to real human responses from CFPS to analyze regional differences in Big Five personality traits(openness,conscientiousness,extraversion,agreeableness,neuroticism)and subjective well-being. Methodologically,the empirical human dataset comprised adult participants from CFPS 2018,covering seven culturally and socioeconomically distinct Chinese regions(North China,Northeast,East China,Central China,South China,Southwest,and Northwest).Each region had an equal number of males and females aged from 18 to 65.Personality was measured using a simplified 15-item Chinese Big Five inventory,while subjective happiness was assessed using a single-item self-rating scale.Correspondingly,a matched virtual dataset of equivalent size and demographic distribution was generated using DeepSeek-V3-0324,with constructed prompts designed to mirror the demographics and cultural context of the actual participants.The virtual participants responded to identical psychological assessments,ensuring comparability. Results from independent-sample t-tests indicated overall similarity,while significant differences between human and AI-generated data in certain aspects.Specifically,the virtual dataset closely mirrored human data in terms of personality and happiness distributions,but exhibited significant differences in several traits.Simulated participants scored significantly lower in extraversion and openness(with medium to large effect sizes)and higher in agreeableness and neuroticism compared to human data.Happiness levels in the simulated dataset were consistently lower,suggesting limitations in DeepSeek's capacity to replicate subjective emotional experiences accurately. Further ANOVA analyses revealed that both datasets reflected significant regional differences in personality traits and happiness.For example,in human responses,the Southwest region demonstrated significantly higher extraversion,while the Northeast region exhibited higher subjective happiness.However,DeepSeek's simulated data diverged from these patterns,notably underestimating happiness in the Northeast and overestimating certain personality dimensions in economically prosperous East China. Additionally,regression analyses explored the relationship between personality traits and subjective happiness within both datasets.Human data indicated significant positive predictors of happiness as conscientiousness,extraversion,openness,and the negative predictor,neuroticism.The virtual data,however,showed different structural variations:openness and agreeableness positively predicted happiness,neuroticism negatively predicted happiness significantly more strongly,extraversion negatively predicted happiness,and conscientiousness had no significant predictive effect.Principal Component Analysis(PCA)further highlighted structural difference between the human and simulated datasets,particularly reflecting an overreliance on more linguistically salient and externally expressed traits in the AI-generated responses. These findings contribute significantly to the understanding of LLM applications in psychological research.Primarily,they demonstrate DeepSeek's general effectiveness in simulating broad psychological distributions,while also highlighting its limitations in capturing region-specific psychological structures shaped by the interplay of economic conditions,cultural norms,and psychological dispositions—limitations likely stemming from the model's training data,which insufficiently represents these layered contextual factors. The practical implications of this research are substantial.The use of DeepSeek as a tool for generating"virtual participants"could significantly reduce costs and logistical burdens associated with large-scale psychological research,enabling preliminary testing and refinement of research designs prior to field deployment.However,caution is recommended due to observed biases,including exaggerated cultural stereotypes and inadequate modeling of subjective emotional states.Future model iterations and methodological advancements should address these issues by incorporating richer,more culturally grounded training data and more precise affective modeling techniques. Despite these limitations,the research provides important methodological insights and theoretical contributions by introducing an innovative approach using LLM-generated virtual participants for psychological inquiry.It underscores the potential of DeepSeek and similar models for cost-effective large-scale research while highlighting crucial areas that require further refinement. In conclusion,this study validates the feasibility of employing large language models such as DeepSeek for simulating regional psychological structures,but also emphasizes the necessity for continued development to address culturally grounded and psychologically meaningful variations effectively.As training data and algorithms advance,these models may help reshape methodologies within personality and cross-cultural psychological research.
Background: Trust between spouses is one of the fundamental pillars of family formation, and couples facing the aftermath of betrayal require, above all, the construction of trust to mend their marital relationships. A review of the literature in this area indicates a lack of indigenous models for building trust among couples impacted by infidelity. Aims: The present research was conducted with the aim of providing a model of trust in couples affected by infidelity based on emotional schemas with the mediation of communication patterns and emotional expression. Methods: The research method was correlation type which was done in the from of structural modeling. The statistical population of this study is made up of all couples affected by infidelity who visited the counseling centers of Nowshahr, Chalus and Tonekabon between May and August 2021 the sample of the research was (300) men and women injured by infidelity (240 women and 60 men) who were selected by the available sampling method and couples trust questionnaires (IRS) Rempel et al. (1985), emotional schema (LESS) Leahy (2002), communication patterns (CPQ) Christensen and Salavy (1984) and emotional expressiveness (EEQ) completed King and Emmons (1990). The resulting data were analyzed by Pearson correlation method and structural equations with SPSS 26 and AMOS 24 software. Results: The findings of the research showed that the presented conceptual model had a good fit and was approved. Also, the results showed that compatible and incompatible schemas have a direct and significant effect on communication patterns, emotional expression and trust of couples (P<0.05); Also, regarding the indirect effects, compatible schemas through the expression of positive emotion and incompatible schemas through the mediation of positive emotion expression and intimacy expression had an indirect and significant effect on couples' trust (P<0.01). Conclusion: Considering the prominent role of trust, particularly trust restoration, in couples affected by infidelity, it is recommended to utilize the findings of this research to design and plan a psychotherapeutic intervention model. The aim is to enhance trust in couples impacted by infidelity, focusing on improving levels of adaptive emotional schemas, positive communication patterns, and effective emotional expression.
Background: It seems that despite the significant role of worry and uncertainty intolerance in occurrence, maintaining and intensify the symptoms of generalized anxiety disorder, few interventions have targeted such variables. Aims: The aim of the present study was to investigate the effectiveness of schema therapy on worry states and intolerance of uncertainty in patient with generalized anxiety disorder. Methods: The research method was a semi-experimental pretest-posttest design with a 45-day follow-up stage by control group. The study population included all people with generalized anxiety disorder referred to 40 psychological counseling centers in the 18th district of Tehran in 2023 which among those 34 cases were selected through available sampling and they were randomly divided into experimental and control groups. The Experimental group received schema therapy (Young, 2008) sessions for eight 90-minutes sessions. All participants were assessed by the generalized anxiety disorder scale- 7 item (Spitzer et al, 2006), Pen state worry questionnaire (Meyer et al, 1990) and Intolerance of Uncertainty Scale (Freeston et al, 1994). Data were analyzed by SPSS-24 software and MANOVA with repeated measure test. Results: The results demonstrated that schema therapy is effective in reducing worry states and intolerance of uncertainty (p< 0.01) and that this effect is long-lasting (p< 0.01). Conclusion: According to the findings of the study, therapists and clinical specialists should consider schema therapy as an effective treatment strategy for generalized anxiety disorder.
Background: It is very important to pay attention to the issues of young people, especially their psychological problems. During the COVID-19 pandemic, access to smartphones led to aggression, violence, and addiction among many students. Therefore, by using appropriate treatment methods, it is necessary to act in a way that reduces the severity of these problems. Aims: The present study aims to investigate the effectiveness of treatment based on commitment and acceptance on domestic violence, aggression and mobile addiction in first secondary students. Methods: The present study was an applied study in terms of purpose and quasi-experimental methodology in a series of pretest-posttest designs with a control group. The statistical population included all high school students in Sanandaj in the academic year 2023-2024. The sample consisted of 30 high school students in Sanandaj who were selected by convenience sampling method and were randomly assigned to two experimental (15 people) and control (15 people) groups. The experimental group received 8 sessions of acceptance and commitment therapy, while the control group did not receive any intervention. Data were collected using the Adolescent Violence Questionnaire (Sadat Hajati et al., 2008), Aggression Questionnaire (Zahedifar et al., 1997) and Mobile Phone Addiction Questionnaire (Savari, 2014). The collected data were analyzed using multivariate analysis of covariance using SPSS-27 software. Results: The results of multivariate analysis of covariance showed that the scores of the relaxation group in violence, aggression, and mobile phone addiction decreased compared to the control group. In other words, acceptance and commitment therapy is effective in reducing violence, aggression, and addiction to mobile phones in adolescents (P< 0.05). Conclusion: According to the findings of the research, the approach of acceptance and commitment education can be used as an effective program for reducing and managing anger, violence, and mobile phone addiction in adolescents in counseling centers and psychological services, by counselors and social workers.
Background: One of the most influential factors in creativity is brain waves. Among brain waves, alpha and theta waves are considered the most effective in fostering creativity in individuals. Alpha wave activity represents the dominant oscillatory activity of the human brain and is associated with fundamental and complex cognitive functions such as divergent thinking. Previous research has often conceptualized creativity as a cohesive concept that can be assessed using questionnaires, which may not seem sufficient for the underlying mechanism. Aims: The aim of the present study was to investigate the differences in the patterns of alpha and theta brain waves in the posterior regions of the right hemisphere during divergent and convergent thinking. Methods: The current study employed a semi-experimental pre-test-post-test design with a two-month follow-up period. The research population consisted of all graduate students aged 20 to 46 years in psychology and cognitive sciences at Payam Noor University and the Cognitive Sciences Research Institute in 2023. The sample included 32 participants (16 men and 16 women) selected using purposive sampling and randomly assigned to experimental conditions (divergent and convergent). The research instruments included the Chapman Superiority Scale (Chapman, 1987), a 64-channel Ant EEG system, tasks for divergent thinking (snake counting, alternate uses), and tasks for convergent thinking (number counting, Tower of London). Results: The repeated measures analysis of variance showed significant differences between the two study conditions (divergent and convergent) in the posterior region. The difference between divergent and convergent conditions was statistically significant in favor of divergent thinking for both alpha (P< 0.05) and theta (P< 0.01) bands. Conclusion: The findings of the present study can provide a basis for further investigations into brainwave neurofeedback and other quantitative electroencephalogram (QEEG) components, such as absolute power, coherence in other frequency bands, in relation to divergent and convergent thinking differences.
Background: The literature review in the field of elementary school teachers and factors influencing their profession, such as job burnout, mental health, social capital, and work-family conflict, has shown that there has been no study to date examining gender differences among elementary school teachers in Tehran in these aspects. Aims: The aim of this research was the considering of gender differences in burnout, family- work conflict, mental health, and psychological capital in Tehran elementary teachers. Methods: the method of this research was Descriptive, in kind of post event and casual- comparative research. Statistical society in this research consists of all elementary school teachers in Tehran (12656 teachers) and sample was 400 teachers (233 female & 177 male) were selected by equal assignment Stratified sampling method (each region 50 teachers). Research instruments consist of Masalas' burnout questionnaire, Carlsons' family- work conflict questionnaire, and Goldberg & Hillier mental health questionnaire, and Luthans, Psychological capital questionnaire. Analyzing methods were mean, standard deviation, skewness, courtesies, and Independent T-test. Results: There are significant gender difference in burnout, psychological capital, and family- work conflict. Burnout, psychological capital, and family- work conflict in female teachers, were significantly more than men teachers were. However, there are no significant gender difference in mental health. Conclusion: Nowadays, women alongside the key role in family and nurturing children are present in society as the strong and competent work force. Presence of problem in these tow domains is traumatic. According to this research finding and by considering women teachers high rate of this variables, providing psychological counseling services, psychological workshops for female teachers, and making flexible working hours are effective for decreasing burnout and family- work conflict.
Background: A review of previous studies has shown that psychological factors such as disease acceptance and emotional self-regulation have a significant effect on the exacerbation of irritable bowel syndrome and its therapeutic consequences. Among the effective methods for increasing disease acceptance and improving emotional self-regulation, we can mention relaxation training and awareness and emotional expression training. Aims: The present study was conducted with the aim of comparing the efficacy of relaxation training and awareness and emotional expression training on disease acceptance and emotional self-regulation in patients with irritable bowel syndrome. Methods: The current research design was a semi-experimental pre-test-post-test type with a control group and a two-month follow-up. The statistical population of the study included all patients with irritable bowel syndrome who referred to the gastroenterology Subspecialty offices in northwest Tehran from 2021 to July 2022, who had received the diagnostic criteria of irritable bowel syndrome. Using the purposeful sampling, 60 patients with irritable bowel syndrome were selected, And then they were randomly divided into three groups of 20 people (two experimental groups and one control group). The tools used in this research was the Chronic Illness Acceptance Questionnair (Beacham et al., 2015) and Emotional self-regulation (affective style) questionnaire (Hofmann & Kashdan, 2010). Also, for the first experimental group, relaxation training, For the second experimental group, awareness and emotional expression training in 8 sessions of 90 minutes it was held virtually. In order to analyze the research data, the Analysis of variance with repeated measures and SPSS-26 software was used. Results: The findings showed that compared to relaxation training, awareness and emotional expression training increase disease acceptance in people with irritable bowel syndrome. The difference in the efficacy of relaxation and awareness and emotional expression on the components of commitment to engaging in activities (P= 0.004) and Willingness to endure (P= 0.034) and consequently on the total score of disease acceptance (P= 0.001) was significant. Also, the results showed that relaxation training is not an effective method for improving emotional self-regulation in patients with irritable bowel syndrome, however, the difference between the effect of relaxation training and awareness and emotional expression training on the factors of adjusting (P= 0.011), concealing (P= 0.001) and tolerating (P= 0.008) is significant. Conclusion: Based on the findings of the present study, it seems awareness and emotional expression training is a more effective method to increase disease acceptance and improve emotional self-regulation in irritable bowel syndrome patients compared to relaxation training.
Background: All marriages may experience boredom or continue married life with poor quality; which is definitely associated with ideas about separation, it is important to attention to the destructive effects of this phenomenon and treat it in time. Aims: The purpose of this research was to determine, through the examination of couples' personal experiences, the effect of an educational program on mitigating marital tedium among those who are disillusioned with married life. Methods: The study used a quasi-experimental design, using a post-test, pre-test, and 6-month follow-up methodology. The research included 30 couples diagnosed with marital burnout in 2022. The participants were recruited by purposive selection, and then randomly divided into an experimental and a control group, each consisting of 15 people. The participants completed the Pines (2002) 20-item marital discomfort questionnaire, which served as the tool for measuring the variables. Then, the participants of experimental group in ten 90-min sessions of group training of training package, which was conducted using predictive indicators of marital burnout, based on the lived experiences of distressed couples, using the phenomenology by the author. The analysis of mixed covariance using SPSS version 23 software was used to analyze the data. Results: Based on the value of F= 58.48, which was significant at the P< 0.01 level, the results indicated that 68% of the changes in the variance of marital happiness were affected by an intervention. Conclusion: Considering the effectiveness of the educational package, this package can be used in psychological centers to educate couples and improve their interactions to reduce marital dissatisfaction.
Background: Fear of flying is one of the categories of phobias that can have a negative effect on people. This fear can be caused by many factors such as behavioral functions, brain and emotion regulation. Since air travel is safer than traveling with other vehicles, therefore, treating this disorder is very important. Aims: This research was conducted with the aim of determining the effectiveness of virtual reality program on behavioral functions, emotional regulation and brain functions by FNIRS in the treatment of aerophobia. Methods: The current research design was a semi-experimental pre-test-post-test type with an experimental group (virtual reality training) and a control group (13 people in each group) with a 1-month follow-up. The statistical population of this research included all people with fear of flying who were invited to cooperate in 1402 and 1403 in the city of Tehran through a call on Instagram and Telegram social networks. The fear of flying questionnaire (Bournas et al., 1999), emotion regulation questionnaire (Gross and John, 2003) and functional near infrared spectroscopy (NIRS) were used to collect data, as well as the 5-session protocol (One session per week and 60 minutes each session) virtual reality program was used for intervention. The data were analyzed with the methods of analysis of variance with repeated measurements and t-test. SPSS version 26 software was used for data analysis. Results: The findings indicated that the virtual reality program improved behavioral functions (p< 0.01), but it had no significant effect on emotional regulation and brain activity indicators (p> 0.01). Conclusion: In general, the virtual reality program is very important in improving the fear of flying and can improve the behavioral functions of a person, and as a result, people can use the plane without fear of flying, and this method can be used to treat the fear of flying.
Background: Marital orientation refers to assessing individuals' optimistic or pessimistic attitudes toward marriage. Among the influential factors shaping young people's marital orientation are the relationships they have with others before marriage, as well as their psychological capital. In past studies, family friendship has also been identified as one of the influential factors. However, to date, no model has been proposed for marital orientation based on the relationships between these components. Aims: The aim of the current research was to model marital orientation based on psychological capital and premarital relationship attitudes with the mediation of family friendship. Methods: The present research was descriptive and employed correlational structural equation modeling. The statistical population of the study included all single students of Islamic Azad University in Isfahan province. Considering the number of research variables and conventional statistical methods, a sample of 500 individuals (303 females and 197 males) was selected using stratified random sampling method. Participants completed questionnaires on marital orientation (Guanji, 2020), psychological capital (Luthans, 2007), premarital relationship attitudes (Kourdeloo, 2001), and family friendship (Hashemi Garmdarreh, 2019). The data were analyzed using SPSS and AMOS software. Results: The findings indicate that among the predictor and mediator variables, optimism, resilience, and self-efficacy, as well as family friendship, have a direct relationship with marital orientation (p< 0.05). Additionally, psychological capital and premarital relationship attitudes can predict marital orientation through the family friendship variable (p< 0.05). Conclusion: Based on the results obtained, it can be said that the higher the levels of psychological capital and family friendship among students, the more optimistic their orientation towards marriage will be. Considering the results, the family friendship variable plays an important and influential mediating role in the relationship between psychological capital and premarital relationship attitudes with marital orientation.
Background: By relying on talents and abilities, instead of focusing on diseases, positive psychology has opened its place in psychology literature and has become more important with the increasing progress of societies and the spread of materialism. In Martin Seligman's theory, happiness is one of the most important concepts in positive psychology and refers to a person's feeling of happiness and satisfaction. Aims: The current research was conducted with the aim of providing a model for happiness based on Martin Seligman perspective. Methods: The method of the current research was qualitative, which was carried out using the grounded theory method. The statistical population in the review section of Seligman's theory was the content of the book "Prosperity of Positive Psychology: A New Understanding of the Theory of Happiness and Well-Being", all of its content was carefully examined by researchers, and in the expert section, the statistical population included all positive psychology specialists in Tehran. It was in 1402 that they were identified by snowball sampling and by asking the opinion of 10 of these experts, their opinions on the subject under study were examined. Results: In the present study, causal, contextual and intervening factors of happiness were identified. On the other hand, strategies for focusing on strengths, practicing gratitude, practicing acceptance of suffering, setting goals and weekly or monthly planning, establishing and maintaining positive relationships and meaningful connections with others, practicing living in the present and valuing the present moments and sports activities and mobility Physical activity was identified as a means of happiness. Finally, it was found that happiness brings various consequences, including improving mood, improving health, improving relationships, increasing creativity, success at work, maintaining mental balance, and increasing motivation. Conclusion: The findings of the present study showed that Martin Seligman's genuine happiness is consistent with the opinion of experts in the field of positive psychology; Because both emphasize that happiness, satisfaction and inner peace can be achieved through spiritual connection with God and following religious and moral principles and a positive attitude towards life.
Background: In Iran, marriages between Iranian women and Afghan immigrant men are on the rise; however, there is limited information available regarding domestic violence against Iranian women with Afghan immigrant spouses. Domestic violence is a serious social and public health issue that requires a precise understanding of the influential factors in this context. Aims: This study aimed to identify the factors influencing domestic violence against Iranian women with Afghan immigrant spouses. This study could contribute to improving policies and prevention programs aimed at addressing domestic violence in these communities. Methods: The present study utilized a descriptive phenomenological approach. The target population consisted of all Iranian women who were victims of domestic violence with Afghan immigrant spouses residing in Tehran province. The sampling method was a snowball technique, ultimately resulting in interviews conducted with 14 participants. Data collection utilized semi-structured, in-depth interviews, and the collected data were analyzed using a seven-step Colaizzi method. Results: The results indicated that factors such as personal characteristics of women (such as age, education, and economic status), characteristics of Afghan spouses (economic, cultural, and social), and family and social factors (such as cultural pressures and societal attitudes) play a role in increasing domestic violence against Iranian women with Afghan immigrant spouses. Conclusion: Given the findings of this study, it appears that a precise understanding of the factors influencing domestic violence in this community is crucial. This study can aid in formulating policies and prevention programs against domestic violence towards Iranian women with Afghan spouses, leading to improvements in their social and health-related conditions
Background: Differences between age groups is a very important issue that can be the source of various cultural and social phenomena and issues. Aims: The purpose of this research was to investigate the intergenerational social capital and its dimensions among men and women in Tuyserkan city. Methods: The research method was a survey and the data collection tool was a researcher-made questionnaire. The statistical population included men and women over 15 years of age in Tuyserkan city in 2019, of which 392 were selected by cluster sampling. Results: Data analysis was done with ANOVA, Independent T-test, and Path Analysis in SPSS-25 software. The results showed that there is a difference between generations in terms of social capital and the older generation has more social capital; there is a difference between women and men in terms of social capital, and men have more social capital than women. There is a difference between age groups in terms of social capital, and the age group of 66 to 75 years has more social capital. Also, there is a relationship between income and social capital (P < 0.05). Conclusion: In short, it can be said that there is a relationship between intergenerational variables, gender, age groups, income, type of job, marital status, level of education, place of residence, age of marriage, presence in society, and social capital; There is a difference between men and women as well as between different generations in terms of the variables of age of marriage, presence in society, economic capital, individual and social freedoms, social trust, and social mobility.
Background: Systematic review of research shows that infidelity and marital infidelity cause the most damage to the relationship between spouses and addition to marital conflicts, it can even destroy the relationship. Despite numerous studies on the treatment of marital infidelity, there is a research gap regarding the efficacy of schema therapy based on mindfulness on the emotional reactivity and internal shame of betrayed women. Aims: The present study was conducted with the aim of the efficacy of schema therapy based on mindfulness on the emotion reactivity and internal shame of betrayed women. Methods: The method of the present research was practical in terms of purpose and semi-experimental in terms of method, pre-test-post-test with control group and three-month follow-up. The statistical population of this research included all women who needed psychological services in the second half of 2022 due to their husband's infidelity in the city of Bandar Abbas. Among all psychological and counseling service centers in Bandar Abbas city, 30 women who had referred to ten centers due to infidelity of their husbands were selected by the available sampling method and were randomly replaced in the experimental group and the control group. To collect data, emotional reactivity questionnaires (Knock et al. 2008) and internal shame (Cook, 1993) were used. The participants of the experimental group received 10 sessions of mindfulness-based schema therapy based on Van Vrieskwijck et al. (2015). Also, the data were analyzed by variance analysis with repeated measurements using SPSS-22 software. Results: The findings showed that schema therapy based on mindfulness was effective on the emotional reaction and internal shame of betrayed women. (p< 0.01). Also, the findings showed that this intervention had the greatest impact on internal shame. Conclusion: Based on the results of the present study, it can be argued that schema therapy based on mindfulness is effective on the emotional reaction and internal shame of betrayed women, and this therapeutic intervention can be used to moderate the emotional reaction and internal shame of betrayed women in counseling centers.
Background: Post-COVID-19 neurological sequelae may have a long-term negative impact on cognitive functions and quality of life in recovered patients. Cognitive stimulation based on computer tasks combined with transcranial direct current stimulation (tDCS) is a promising approach to address cognitive impairments and consequently improve the quality of life in these individuals. However, research literature on the effectiveness of this combined method has gaps that require further investigation. Aims: This study aimed to compare the impact of cognitive stimulation based on computer tasks with and without transcranial direct current stimulation on the health-related quality of life in recovered COVID-19 patients. Methods: This research was conducted in the form of a semi-experimental pre-test-post-test design with a control group and a one-month follow-up. The sample size of the study consisted of 45 patients recovered from covid-19 in Mashhad city, who were selected by available sampling method and randomly divided into 3 groups of 15 including computerized cognitive stimulation group, computerized cognitive stimulation combined with single-site anodal electrical stimulation (tDCS) and computerized cognitive stimulation with artificial electrical stimulation (Sham). Participants completed the Weir and Sherburne (1992) SF-36 Health-Based Quality of Life Short Form before and after the intervention. Analysis of variance with repeated measurements and SPSS 24 software were used for data analysis. Results: Both methods of cognitive stimulation based on computer tasks alone and in combination with (tDCS) increased the average scores of the quality of life and its subscales in those who recovered from the acute stage of covid-19 (p=0.05)and this increase was stable in the one-month follow-up phase. In addition, there was no significant difference between the effectiveness of the two treatments in improving the quality of life. Conclusion:Computerized cognitive stimulation alone and together with transcranial brain stimulation can lead to improvement of health-related quality of life in those who have recovered from covid-19 disease. This enables us to enhance and update current rehabilitation programs to meet patient needs.
Cognitive computational modeling quantifies human mental processes using mathematical frameworks,thereby translating cognitive theories into testable hypotheses.Modern cognitive modeling involves four interconnected stages:defining models by formalizing symbolic theories into generative computational frameworks,collecting data through hypothesis-driven experiments,inferring parameters to quantify cognitive processes,and evaluating or comparing models.Parameter inference,a critical step that facilitates the integration of models and data,has traditionally relied on maximum likelihood estimation(MLE)and Bayesian methods like Markov Chain Monte Carlo(MCMC).These approaches depend on explicit likelihood functions,which become computationally intractable for complex models—such as those with nonlinear parameters(e.g.,learning dynamics)or hierarchical/multimodal data structures. To address these challenges,simulation-based inference(SBI)emerged,leveraging parameter-data mappings via simulations to bypass likelihood calculations.Early SBI methods,however,faced computational redundancy and scalability limitations.Recent advances in neural simulation-based inference(NSBI),or neural amortized inference(NAI),harness neural networks to pretrain parameter-data relationships,enabling rapid posterior estimation. Despite its advantages,NSBI remains underutilized in psychology due to technical complexity.This work focuses on neural posterior estimation,one of three NSBI approaches alongside neural likelihood estimation and neural model comparison.Neural posterior estimation operates in two phases:training and inference.During the training phase,parameters are sampled from prior distributions,and synthetic data are generated using the model;a neural network is then trained to approximate the true posterior from these training pairs.In the inference stage,real data are input to the trained network to generate parameter samples.The BayesFlow framework enhances neural posterior estimation by integrating normalizing flows-flexible density estimators-and summary statistic networks,enabling variable-length data handling and unsupervised posterior approximation.Its GPU-accelerated implementation further boosts efficiency. Neural posterior estimation has expanded the scope of evidence accumulation models(EAMs),one of the most widely used framework in cognitive modeling.First,it enables large-scale behavioral analyses,as demonstrated by von Krause et al.(2022),who applied neural posterior estimation to drift-diffusion models(DDMs)for 1.2 million implicit association test participants.By modeling condition-dependent drift rates and decision thresholds,they revealed age-related nonlinear cognitive speed changes,peaking at age 30 and declining post-60.Neural posterior estimation completed inference in 24 hours versus MCMC's 50+hours for a small subset,demonstrating its scalability. Second,neural posterior estimation supports dynamic decision-making frameworks,exemplified by Schumacher et al.(2023),who combined high-level dynamics with low-level mechanisms using recurrent neural networks(RNNs).Their simultaneous estimation of hierarchical parameters achieved over 0.9 recovery correlations and superior predictive accuracy compared to static models. Finally,neural posterior estimation facilitates neurocognitive integration,as shown by Ghaderi-Kangavari et al.(2023),who linked single-trial EEG components(e.g.,CPP slope)to behavior via shared latent variables like drift rate.This approach circumvented intractable likelihoods and revealed associations between CPP slope and non-decision time. NSBI enhances cognitive modeling by enabling efficient analysis of complex,high-dimensional datasets.Its key limitations include model validity risks(biased estimates from incorrect generative assumptions),overfitting concerns(overconfident posteriors on novel data),and upfront training costs for amortized methods.Future work should refine validity checks-such as detecting model misspecification-and develop hybrid inference techniques.NSBI's potential extends to computational psychiatry and educational psychology,promising deeper insights into cognition across domains.By addressing complexity barriers,NSBI could democratize advanced modeling for interdisciplinary research,advancing our understanding of human cognition through scalable,data-driven frameworks.
Process data captures the nuances of human-computer interaction within computer-based learning and assessment systems,reflecting the intricacies of participants'problem-solving behaviors.Among the various forms of process data,action sequences are particularly critical as they meticulously outline each step of a participant's problem-solving journey.However,the inherent non-standardization of action sequences,characterized by variation in data length across participants,poses significant challenges to the direct application of conventional psychometric models,such as item response theory models and diagnostic classification models(DCM).These conventional psychometric models are typically appropriate for structured data,necessitating adaptations for analyzing process data.One common adaptation is the key-action coding method,which involves identifying whether each participant's data includes critical problem-solving actions,and coding this presence or absence numerically(e.g.,"1"for"contains"and"0"for"does not contain").Zhan and Qiao(2022)introduced a key-action coding method to facilitate the application of DCMs to process data,aiming to determine participants'proficiency in problem-solving skills.However,their method did not consider the detrimental effects of misconceptions on problem-solving performance.Misconceptions,defined as false understandings based on personal experiences,often lead to incorrect responses in problem-solving scenarios.Recognizing and addressing these misconceptions,alongside assessing problem-solving skills,can provide deeper insights into the root causes of errors,enabling the implementation of targeted educational interventions.Despite the critical role of misconceptions in shaping problem-solving outcomes,few if any studies have integrated misconception analysis into the problem-solving process. To address this gap,this study introduces a novel key-action coding method that incorporates both problem-solving skills and misconceptions,thereby enhancing the utility of DCMs in process data analysis.This method was evaluated using an illustrative example involving the"Tickets"assessment item from PISA 2012,comparing our approach with that of Zhan and Qiao(2022).Our model defined eight attributes—four related to problem-solving skills and four to misconceptions—and included 28 phantom items based on the assessment's scoring rules.This is in contrast to the original four attributes and ten phantom items in Zhan and Qiao's method.Our analysis used four different DCMs:DINA,DINO,ACDM,and GDINA,with model-data fit assessed using metrics such as AIC,BIC,CAIC,and SABIC.A chi-square test evaluated the statistical differences in model fit,while item quality and classification reliability were measured using the item differentiation index and the classification accuracy index,respectively. The findings demonstrate that:(1)The GDINA model exhibited the best relative fit,suggesting that the relationship between problem-solving skills and misconceptions in determining item responses is intricately complex and transcends simple conjunctive relationships(as shown in Table 3).(2)The integration of both problem-solving skills and misconceptions allows for a more detailed classification of participants,enabling the identification of specific factors that influence problem-solving success and failure,thereby facilitating targeted remedial interventions tailored to individual needs(as illustrated in Figure 4).(3)The incorporation of misconceptions modestly enhances the reliability of diagnostic classifications(as detailed in Table 4).(4)There is a moderate to high negative correlation between participants'mastery of misconceptions and their raw scores,underscoring that misconceptions adversely affect students'overall problem-solving performance(as shown in Figure 3).In summary,this study introduces a key-action coding approach that incorporates misconceptions and examines its application in the diagnostic classification analysis of process data,specifically focusing on action sequences.This approach enables researchers to pinpoint specific factors that influence problem-solving outcomes and offers methodological support for targeted interventions.Enhancing participants'problem-solving performance requires not only improving their skills but also addressing the negative impacts of misconceptions. The innovation of this paper is primarily reflected in three aspects:(1)It marks the first integration of misconceptions into the methodology of process data analysis,significantly broadening the applicability of the technique.(2)It pioneers the investigation of how misconceptions negatively influence the problem-solving process,thereby enriching our understanding of the mechanisms underlying process data generation.(3)It expands the application of diagnostic classification models and underscores their practical value in analyzing process data,thereby enhancing the efficacy and scope of educational assessments.
Background: Psychological analysis of the behavior of war commanders in the mythological and heroic period of Ferdowsi's Shahnameh and Homer's Iliad and Odyssey. Aims: In this article, the psychological analysis of war commanders' behavior in the mythological and heroic period of Ferdowsi's Shahnameh and Homer's Iliad and Odyssey is discussed. Methods: The research method is library-based and based on document research and its type is analytical-descriptive. Examining the confrontation among commanders shows that the element of confrontation in these stories is very prominent and bold, and in fact, the plot of each of these historical stories is based on confrontation. Results: The type of confrontations in these stories, due to their historical nature, is mainly the type of confrontation between human characters and especially war commanders, and the motivations of the confrontation between the characters are often things such as power struggle, desire to conquer the country, trying to Establishing justice and fighting against oppression, seeking revenge, fighting against Enirani and other races, etc. From the point of view of Adler's personality theory, the war commanders in these two works sometimes have an inferiority complex and in order to cover their weaknesses, they have turned to showing power and opening up the country. Conclusion: In general, although the selected stories are historical stories, the components of Lévi-Strauss's approach and theory can be seen in them, and the motivation of these characters is not only the motivations mentioned in historical books, but ideals and goals. Also, their personality type and psychological characteristics have a direct impact on these confrontations, which have been examined by Alfred Adler.
Background: Illness Anxiety Disorder (IAD), is a type of worry about the existence or occurrence of serious medical diseases. worry, alexithymia, intolerance of uncertainty and cognitive emotion regulation strategies can be effective factors in the development and persistence of mental disorders such as illness anxiety. Since individuals with IAD suffer from many problems, identifying the influencing and predicting factors of IAD simultaneously in research are considered important. Aims: The purpose of the present study was to predict illness anxiety symptoms based on worry, alexithymia, intolerance of uncertainty and cognitive emotion regulation strategies. Methods: The present study was descriptive correlation and the statistical population included all people living in Tehran between the ages of 20 and 60 in 2021. A total of 414 individuals (344 females, 70 males) participated in the study. Participants were asked to complete the Illness Anxiety Scale (Besharat, 2011), Penn State Worry Questionnaire (Meyer et al., 1990), Toronto Alexithymia Scale-20 (Bagby et al., 1994), Intolerance of Uncertainty Scale (Carleton et al., 2007) and Cognitive Emotion Regulation Questionnaire (Garnefski & Kraaij, 2007). The data were analyzed by Pearson correlation coefficient and stepwise regression methods by SPSS27. Results: worry, alexithymia, intolerance of uncertainty and maladaptive emotion regulation strategies had a significant positive association with illness anxiety symptoms (P< 0.05). This result was reversed for adaptive emotion regulation strategies; revealing that this type of strategies had a significant negative association with illness anxiety symptoms (P< 0.05). Furthermore, the cognitive emotion regulation strategies were removed from the model due to the lack of predictive power, but worry, alexithymia and intolerance of uncertainty have the ability to predict the illness anxiety symptoms. Conclusion: Based on the research findings, worry, alexithymia and intolerance of uncertainty can predict illness anxiety symptoms. These results can be useful in the prevention, diagnosis and treatment of IAD.
