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This workbook is a practical introduction to the skill of social research. It is intended for use in introductory sociology courses and may be combined with most of the standard textbooks in the field.

Reliable and accurate estimation of residential segregation between population groups is important for understanding the extent of social cohesion and integration in our society. Although there have been considerable methodological advances in the measurement of segregation over the last several decades, the recently developed measures have not been widely used in the literature, in part due to their complex calculation. To address this problem, we have implemented several newly proposed segregation indices in R, an open source software environment for statistical computing and graphics, as a package called seg. Although there are already a few standalone applications and add-on packages that provide access to similar methods, our implementation has a number of advantages over the existing tools. First, our implementation is flexible in the sense that it provides detailed control over the calculation process with a wide range of input parameters. Most of the parameters have carefully chosen defaults, which perform acceptably in many situations, so less experienced users can also use the implemented functions without too much difficulty. Second, there is no need to export results to other software programs for further analysis. We provide coercion methods that enable the transformation of our output classes into general R classes, so the user can use thousands of standard and modern statistical techniques, which are already available in R, for the post-processing of the results. Third, our implementation does not require commercial software to operate, so it is accessible to a wider group of people.

Algebraic Thinking (AT) and Computational Thinking (CT) are pivotal competencies in modern education, fostering problem-solving skills and logical reasoning among students. This study presents the initial hypotheses, theoretical framework, and key steps undertaken to explore characterized learning paths and assign practice-relevant tasks. This article investigates the relationship between AT and CT, their parallel development, and the creation of integrated learning paths. Analyses of mathematics and computer science/informatics curricula across six countries (Finland, Hungary, Lithuania, Spain, Sweden, and Türkiye) informed the development of tasks aligned with consolidated national curricula. Curricula were analysed using statistical methods, and content analysis to identify thematic patterns. To validate the effectiveness of the developed tasks for AT and CT, an assessment involving 208 students in K-12 across various grade levels (students aged 9–14) was conducted, with results analysed both statistically and qualitatively. Subsequently, a second quantitative study was carried out among teachers participating in a workshop, providing further insights into the practical applicability of the tasks. The research process was iterative, encompassing cycles of analysis, synthesis, and testing. The study also paid special attention to unplugged activities – tasks that help students learn CT without using computers or digital tools. A local workshop in Hungary, where 26 tasks were tested with students from different grade levels, showed that developing CT and AT effectively requires more time and practice, especially in key topics. The findings underscore the importance of integrating AT and CT through thoughtfully designed learning paths and tasks, including unplugged activities, to enhance students’ proficiency in these areas. This study contributes to the development of innovative educational programs that address the evolving digital competencies required in contemporary education.

HIV transmission among injecting and non-injecting drug users (IDU, NIDU) is a significant public health problem. Continuing propagation in endemic settings and emerging regional outbreaks have indicated the need for comprehensive and coordinated HIV prevention. We describe the development of a conceptual framework and calibration of an agent-based model (ABM) to examine how combinations of interventions may reduce and potentially eliminate HIV transmission among drug-using populations. A multidisciplinary team of researchers from epidemiology, sociology, geography, and mathematics developed a conceptual framework based on prior ethnographic and epidemiologic research. An ABM was constructed and calibrated through an iterative design and verification process. In the model, \"agents\" represent IDU, NIDU, and non-drug users who interact with each other and within risk networks, engaging in sexual and, for IDUs, injection-related risk behavior over time. Agents also interact with simulated HIV prevention interventions (e.g., syringe exchange programs, substance abuse treatment, HIV testing) and initiate antiretroviral treatment (ART) in a stochastic manner. The model was constructed to represent the New York metropolitan statistical area (MSA) population, and calibrated by comparing output trajectories for various outcomes (e.g., IDU/NIDU prevalence, HIV prevalence and incidence) against previously validated MSA-level data. The model closely approximated HIV trajectories in IDU and NIDU observed in New York City between 1992 and 2002, including a linear decrease in HIV prevalence among IDUs. Exploratory results are consistent with empirical studies demonstrating that the effectiveness of a combination of interventions, including syringe exchange expansion and ART provision, dramatically reduced HIV prevalence among IDUs during this time period. Complex systems models of adaptive HIV transmission dynamics can be used to identify potential collective benefits of hypothetical combination prevention interventions. Future work will seek to inform novel strategies that may lead to more effective and equitable HIV prevention strategies for drug-using populations.

To examine whether Facebook could support a community-based group lifestyle intervention for adults with serious mental illness. Participants with serious mental illness and obesity enrolled in a 6-month group lifestyle program were invited to join a secret Facebook group to support their weight loss and physical activity goals. Two peer co-facilitators moderated the Facebook group. The proportion of participants who achieved ≥5% weight loss or improved fitness was measured at follow-up. The relationship between this outcome and participants’ interactions in the Facebook group was examined. Interactions were defined as active contributions including posts, comments, or likes. Content of participants’ Facebook posts was also explored. Participants (n = 25) had major depression (44%), bipolar disorder (36%), and schizophrenia (20%). Nineteen (76%) participants joined the Facebook group, and contributed 208 interactions (70 posts; 81 comments; 57 likes). Participants who achieved ≥5% weight loss or improved fitness contributed more interactions in the Facebook group (mean = 19.1; SD = 20.5) compared to participants who did not (mean = 3.9; SD = 6.7), though this relationship approached statistical significance (t = −2.1; Welch’s df = 13.1; p = 0.06). Participants’ posts containing personal sharing of successes or challenges to adopting healthy behaviors generated more interaction compared to posts containing program reminders (p < 0.01), motivational messages (p < 0.01), and healthy eating content (p < 0.01). Facebook appears promising for supporting health behavior change among people with serious mental illness. These findings can inform social media initiatives to scale up health promotion efforts targeting this at-risk group.

This study examined the efficacy of using different types of mobile media apps to increase the receptive and expressive vocabulary development of 3-, 4-, and 5-year-old preschool children living in economically disadvantaged communities. Children and teachers in four Head Start classrooms participated in the quasi-experimental study, which included an 8-week intervention in which the children interacted with one of two types of apps: one classroom used four scaffolding-like vocabulary apps for an average of 1.8 h per day (n = 16) and one classroom used four open-ended vocabulary apps for an average of 1.3 h per day (n = 15). Two classrooms served as comparison groups (n = 18; n = 14) which used apps that were chosen by the Head Start program with no specific instructional method for approximately 1 h per day. Children’s vocabulary was assessed pre- and post-intervention using the PPVT-4, the EVT-2, and iPad Receptive and Expressive Vocabulary Assessments. Using a repeated measures analysis of variance with split plot analysis, children who used scaffolding-like vocabulary apps performed statistically significantly higher on the PPVT-4 than children who used open-ended vocabulary apps. There were no significant differences between groups on the EVT-2. The study contributed to the literature on teacher instruction of utilizing scaffolding-like apps to increase preschool vocabulary knowledge.

Hepatitis C virus (HCV) infection is endemic in people who inject drugs (PWID), with prevalence estimates above 60% for PWID in the United States. Previous modeling studies suggest that direct acting antiviral (DAA) treatment can lower overall prevalence in this population, but treatment is often delayed until the onset of advanced liver disease (fibrosis stage 3 or later) due to cost. Lower cost interventions featuring syringe access (SA) and medically assisted treatment (MAT) have shown mixed results in lowering HCV rates below current levels. However. little is known about the potential cumulative effects of combining DAA and MAT treatment. While simulation experiments can reveal likely long-term effects, most prior simulations have been performed on closed populations of model agents-a scenario quite different from the open, mobile populations known to most health agencies. This paper uses data from the Centers for Disease Control's National HIV Behavioral Surveillance project, IDU round 3, collected in New York City in 2012 to parameterize simulations of open populations. To test the effect of combining DAA treatment with SA/MAT participation, multiple, scaled implementations of the two intervention strategies were simulated. Our results show that, in an open population, SA/MAT by itself has only small effects on HCV prevalence, while DAA treatment by itself can lower both HCV and HCV-related advanced liver disease prevalence. More importantly, the simulation experiments suggest that combinations of the two strategies can, when implemented together and at sufficient levels, dramatically reduce HCV incidence. We conclude that adopting SA/MAT implementations alongside DAA interventions can play a critical role in reducing the long-term consequences of ongoing HCV infection.

The main purpose of this study was to design a model of sustainable social development based on social barriers in Bashagard County. The research method of the present study is a combination (quantitative-qualitative). In this study, the population of Bashagard city in the form of urban and rural areas was examined. Morgan table was used to determine the sample size and due to the infinity of the statistical population, the maximum number of samples is 384 people. In the qualitative section, 20 professors and experts in the field of urban and social sustainability development in universities (10 people) and the Cultural Heritage Organization (10 people) were interviewed. Data obtained from questionnaires using software SPSS and LISREL were processed and analyzed in a Windows environment at two levels descriptive statistics and inferential statistics. In order to analyze the data and determine the levels and rank of Bashagard city, a combination of different statistical techniques and descriptive indicators were used. Then, in order to design an appropriate model of sustainable development, structural equation modelling was used. Excel and SPSS statistical software were used for data analysis and LISREL software was used for structural equations and the model obtained from the study. The standard deviation of the findings also shows that the scattering rate of response to research items is above average (0.050). The output of the t-test shows that the calculated t-value (8.09) is greater than the standardized t-test of 1.96 and they are located in the H1 region and it can be said that at a significant level of 95% the research hypothesis is confirmed. This means that social factors have been effective in the underdevelopment of Bashagard County

Take a candid look into how some traditional liberal arts colleges have incorporated nontraditional adult degree programs. This volume of case studies shows how a number of small, independent universities addressed various administrative and service functions for their adult programs. When taken together, it captures the emulsive nature of this imperfect blend as well as the fluidity of solutions. This issue covers: ● The dynamics that an adult program can bring to an institution ● Colleges that combine the adult program within university-wide, centralized processes ● Colleges that have mostly autonomous programs ● Institutions that developed a hybrid model ● The current status of incorporating nontraditional programs into traditional colleges and universities. This is the 159th volume of this Jossey-Bass series. Addressed to higher education decision makers on all kinds of campuses, New Directions for Higher Education provides timely information and authoritative advice about major issues and administrative problems confronting every institution.

In several applied disciplines, as Economics, Marketing, Business, Sociology, Psychology, Political science, Environmental research and Medicine, it is common to collect data in the form of ordered categorical observations. In this paper, we introduce a class of models based on mixtures of discrete random variables in order to specify a general framework for the statistical analysis of this kind of data. The structure of these models allows the interpretation of the final response as related to feeling, uncertainty and a possible shelter option and the expression of the relationship among these components and subjects’ covariates. Such a model may be effectively estimated by maximum likelihood methods leading to asymptotically efficient inference. We present a simulation experiment and discuss a real case study to check the consistency and the usefulness of the approach. Some final considerations conclude the paper.