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This paper aims to analyze the socioeconomic impacts of infectious diseases based on uncertain behaviors of social and effective subsystems in the countries. The economic impacts of infectious diseases in comparison with predicted gross domestic product (GDP) in future years could be beneficial for this aim along with predicted social impacts of infectious diseases in countries.

The proposed uncertain SEIAR (susceptible, exposed, infectious, asymptomatic and removed) model evaluates the impacts of variables on different trends using scenario base analysis. This model considers different subsystems including healthcare systems, transportation, contacts and capacities of food and pharmaceutical networks for sensitivity analysis. Besides, an adaptive neuro-fuzzy inference system (ANFIS) is designed to predict the GDP of countries and determine the economic impacts of infectious diseases. These proposed models can predict the future socioeconomic trends of infectious diseases in each country based on the available information to guide the decisions of government planners and policymakers.

The proposed uncertain SEIAR model predicts social impacts according to uncertain parameters and different coefficients appropriate to the scenarios. It analyzes the sensitivity and the effects of various parameters. A case study is designed in this paper about COVID-19 in a country. Its results show that the effect of transportation on COVID-19 is most sensitive and the contacts have a significant effect on infection. Besides, the future annual costs of COVID-19 are evaluated in different situations. Private transportation, contact behaviors and public transportation have significant impacts on infection, especially in the determined case study, due to its circumstance. Therefore, it is necessary to consider changes in society using flexible behaviors and laws based on the latest status in facing the COVID-19 epidemic.

The proposed methods can be applied to conduct infectious diseases impacts analysis.

In this paper, a proposed uncertain SEIAR system dynamics model, related sensitivity analysis and ANFIS model are utilized to support different programs regarding policymaking and economic issues to face infectious diseases. The results could support the analysis of sensitivities, policies and economic activities.

• A new system dynamics model is proposed in this paper based on an uncertain SEIAR model (Susceptible, Exposed, Infectious, Asymptomatic, and Removed) to model population behaviors;

• Different subsystems including healthcare systems, transportation, contacts, and capacities of food and pharmaceutical networks are defined in the proposed system dynamics model to find related sensitivities;

• Different scenarios are analyzed using the proposed system dynamics model to predict the effects of policies and related costs. The results guide lawmakers and governments' actions for future years;

• An adaptive neuro-fuzzy inference system (ANFIS) is designed to estimate the gross domestic product (GDP) in future years and analyze effects of COVID-19 based on them;

• A real case study is considered to evaluate the performances of the proposed models.

A new system dynamics model is proposed in this paper based on an uncertain SEIAR model (Susceptible, Exposed, Infectious, Asymptomatic, and Removed) to model population behaviors;

Different subsystems including healthcare systems, transportation, contacts, and capacities of food and pharmaceutical networks are defined in the proposed system dynamics model to find related sensitivities;

Different scenarios are analyzed using the proposed system dynamics model to predict the effects of policies and related costs. The results guide lawmakers and governments' actions for future years;

An adaptive neuro-fuzzy inference system (ANFIS) is designed to estimate the gross domestic product (GDP) in future years and analyze effects of COVID-19 based on them;

A real case study is considered to evaluate the performances of the proposed models.

This study aimed to investigate the determinants of healthy lifestyle behavior in married people. It also sought to propose an integrative model that incorporates variables from two theoretical models, namely, the theory of planned behavior (TPB) and the health belief model (HBM), as well as two additional variables, namely habit and body image dissatisfaction.

Questionnaires were used to gather data, and structural equation modeling (SEM) was applied for statistical analysis. Data were collected from 404 respondents using several assessment tools, including the Health Belief Model Scale, the Theory of Planned Behavior Scale, the Healthy Lifestyle Belief Scale, the Body Area Scale, and the Creature of Habit Scale.

The findings showed that perceived severity is the predictor of a healthy lifestyle attitude, followed by subjective norm, perceived behavior control, and healthy lifestyle attitude as the primary attendants of intention. Meanwhile, it was found that a healthy lifestyle attitude is a significant mediator in the perceived severity and healthy lifestyle intention relationship. The suggested model outperforms the original TPB and HBM models in predictive ability, proving its utility and efficacy in describing healthy lifestyle behavior.

Adding constructs in the TPB and HBM models contributed considerably to improving the understanding of healthy lifestyle behavior among married people. Governments and policymakers might utilize the findings to design and execute a new program or a sustained healthy lifestyle for married people.

This paper aims to explore the extent to which the internet has created new opportunities for Iranian women in Tehran. It analyses both challenges and opportunities offered to Iranian women by the internet as a means of economic empowerment.

This paper adopts a qualitative approach and based on 13 semi-structured interviews with female internet users between the ages of 20 and 55 years. The qualitative data was collected through open-ended questions in face-to-face interviews. This study uses ethnography as a research tool to explore the question of whether the internet has made a difference in the economic lives of Iranian women.

Result reveals that the internet and working online have significant impact on the economic lives of Tehrani women by enabling them to engage in new forms of online business. This technology is being used for online advertising to attract more clients, to establish business contacts with peers and to manage households positively.

The result of the research cannot be regarded as applicable to all women in Iran, as the opportunity to access online economic activities is only available to those women who are highly trained and well-educated. In addition, the result of the research may not reflect the barriers that women from different social classes and ethnic groups have faced in the achievement of economic empowerment online.

The study highlights that due to a generally lack of computer proficiency, women in these areas are unable to effectively maximise their participation in the online economic sphere. This barrier must be removed by enhancing women’s computer literacy and ICT (information, communication and technologies) and establishing development networking programme centres for internet skills training.

The internet has created opportunity for Iranian women to expand their participation in the online economic sphere. However, research in the field of online economic activities in Iran, especially concerning women working online, is scant. The key contribution of this paper is to fill the gap in this area of study, in particular offering insights into the ways in which women use the internet to overcome the boundaries of physical space and become empowered.

This study aims to meta-analytically investigate the impact of educational technology interventions on the development of creative thinking in educational settings. In recent years, the debate among researchers has persisted regarding the impact of various educational technologies, including interactive learning environments, digital instruction and platforms, and educational games and robotics, on students' creative thinking in diverse educational settings due to inconsistent findings.

This study, conducting a meta-analysis by synthesizing 35 relevant empirical studies with 2,776 participants, aims to investigate the association between educational technology interventions and the Torrance Tests of Creative Thinking (TTCT) and its subscales (fluency, flexibility, originality and elaboration).

No evident publication bias was found. From a general perspective, the results demonstrate a moderate level of influence of educational technology on the overall TTCT scale, with high heterogeneity attributed to the adopted instruments, mixed methods and target outcomes. Additionally, the results indicate that only three of the TTCT subscales (fluency, flexibility and originality) are influenced by educational technologies. Among the interventions, interactive learning environments yielded medium to the largest mean effect size. Furthermore, moderator analyses suggest that the effects of interventions on two subscales of TTCT (flexibility and originality) are moderated by school types, research design and the duration of intervention. The conclusion drawn is that interventions promoting students' creative thinking in different educational settings are efficacious.

Despite the low homogeneity of the results, which might have influenced the findings, the large fail-safe N suggests that these findings are robust. The study examined potential causes of heterogeneity and emphasized the importance of further research in this area.