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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.

We report the results of an intervention that targeted anti-Roma sentiment in Hungary using an online perspective-taking game. We evaluated the impact of this intervention using a randomized experiment in which a sample of young adults played this perspective-taking game, or an unrelated online game. Participation in the perspective-taking game markedly reduced prejudice, with an effect-size equivalent to half the difference between voters of the far-right and the center-right party. The effects persisted for at least a month, and, as a byproduct, the intervention also reduced antipathy toward refugees, another stigmatized group in Hungary, and decreased vote intentions for Hungary's overtly racist, far-right party by 10%. Our study offers a proof-of-concept for a general class of interventions that could be adapted to different settings and implemented at low costs.

Background Because health professionals can end up being first responders to a mass casualty incident, they must train to improve preparedness and increase the preconditions of victim outcomes. Training and learning on how to handle a mass casualty incident is traditionally based on reading, lectures, training through computer-based scenarios, or sometimes through live simulations. Professionals should practice in realistic environments to narrow the theory–practice gap, and the possibility of repeating the training is important for learning. Virtual reality is a promising tool for realistic and repeatable simulation training, but it needs further evaluation. This study aimed to describe the acceptability and applicability of using VR for training in mass casualty incidents. Methods A mixed-methods evaluation design was used, where the qualitative and quantitative findings were embedded into the discussion with a realist inquiry approach. A virtual reality simulation with mass casualty incident scenarios, named GoSaveThem ( www.crash.nu ), was used, and the participants were directed to perform triage. After the simulation, the participants filled in a questionnaire with open-ended questions and ratings on technical aspects, learning experiences, and improvement of preparedness. Eleven of the participants underwent interviews. The qualitative data was analyzed either summarily or with a conventional content analysis. Data were extracted from computer recordings of how long it took for each participant to triage the first 10 victims and to what extent the triage for the first 10 victims was correct. Descriptive statistical analyses were done, and a comparison was made to see if there were any differences between age, sex, educational background, and previous experiences that affected the outcome of triaging. Results Training with virtual reality enables repeatable and realistic simulation training of mass casualty incidents. The participants expressed motivation to repeat the training and experience expanded virtual reality scenarios. This study shows that the acceptability and applicability of using VR for training MCIs were high overall in all examined dimensions for most users, with some exceptions.

Mobile phone applications (apps) offer motivation and support for self-management of diabetes mellitus (DM), but their use is limited by high attrition due to insufficient consideration of end-users perspectives and usability requirements. This study aimed to examine app usage and feature preferences among people with DM, and explore their recommendations for future inclusions to foster engagement with diabetes apps. The study was conducted internationally on adults with type 1 or type 2 DM using online questionnaire (quantitative) to investigate usage and preferences for app features that support diabetes self-management and semi structured telephone interview (qualitative) to explore suggestions on fostering engagement and specific educational information for inclusion into diabetes apps. Survey and interview data were analysed using descriptive/ inferential statistics and inductive thematic analysis respectively. A total of 217 respondents with type 1 DM (38.25%) or type 2 DM (61.8%), from 4 continents (Australia, Europe, Asia and America) participated in the survey. About half of the respondents (48%) use apps, mainly with features for tracking blood glucose (56.6%), blood pressure (51.9%) and food calories (48.1%). Preferred features in future apps include nutrient values of foods (56.7%), blood glucose (54.8%), physical exercise tracker (47%), health data analytics (42.9%) and education on diabetes self-management (40.6%). Irrespective of the type of DM, participants proposed future apps that are user friendly, support healthy eating, provide actionable reminders and consolidate data across peripheral health devices. Participants with type 1 DM recommended customised features with news update on developments in the field of diabetes. Nominated specific educational topics included tips on problem solving, use of insulin pump therapy, signs of diabetes complication and transitioning from paediatric into adult care. The study has highlighted patients' perspectives on essential components for inclusion in diabetes apps to promote engagement and foster better health outcomes.

Underweight is one form of indicators of under-nutrition, which results from the poor nutrient intake and underlying health problems. Its impact is beyond an individual and extends to a country level. It has been known from the literature that underweight has a negative effect on income and development of a country. In the context of Ethiopia, factors predicting underweight remain unknown and there is a paucity of evidence on geographical distribution of underweight among individuals aged 15-49 years. Therefore, the aim of this study was to examine the geographic distribution of underweight and its associated factors among individuals aged 15-49 years in Ethiopia. Secondary data analysis was done on a data set consisting of 28,450 individuals and obtained from the Ethiopian Demography and Health Survey (EDHS) 2016. The spatial distribution of underweight across the country was identified by ArcGIS software. Hotspots analysis was done using Getis-Ord Gi* statistic within ArcGIS. In SaTScan software, the Bernoulli model was fitted by Kulldorff's methods to identify the purely spatial clusters of underweight. A binary logistic regression was applied to determine factors associated with being underweight. In Ethiopia, the spatial distribution of underweight was clustered with Global Moran's I  =  0.79 at p-value < 0.0001. The highest underweight clusters were observed in Tigray, Gambella, eastern part of Amhara, and western and central part of Afar regions. Male individuals [AOR = 1.21; 95% CI: (1.15 1.28)], never married [AOR = 1.14; 95% CI: (1.05, 1.24)], rural residents [AOR = 1.32; 95% CI: (1.18, 1.47)], rich [AOR = 0.85; 95% CI: (0.76, 0.94)], cigarette smoking [AOR = 1.25; 95% CI: (1.07, 1.46)], drinking treated water [AOR = 0.91; 95% CI: (0.83, 0.99)] and open filed defecation [AOR = 1.17; 95% CI: (1.08, 1.26)] were found to have a significant association with being underweight. There was a significant clustering of underweight among individuals aged 15-49 years. Gender, age, marital status, place of residence, wealth index, cigarette smoking, using untreated water and types of toilet were the significant factors of being underweight. Therefore, effective public health interventions like building safe and supportive environments for nutrition, providing socio-economic protection and nutrition-related education for poor and rural resident would be better to mitigate these situations and associated risk factors in hot spot areas. In addition, policymakers should strengthen and promote nutrition sensitive policies and activities in order to alleviate the underlying and basic causes of underweight.

Programming skills (PS) are indispensable abilities in the information age, but the current research on PS cultivation mainly focuses on the teaching methods and lacks the analysis of program features to explore the differences in learners’ PS and guide programming learning. Therefore, the purpose of this study aims to explore horizontal differences and vertical changes in PS of learners aged 18 to 25 and facilitate the discovery of programming features and behaviors to guide the acquisition of PS through an experiment of statistical analysis and cluster analysis of 2,400 Python programs in four programming tasks. The research found the characteristics and main differences of PS reflected in the function call, interactive loop and several structures nesting. Simple programming task to medium-difficulty programming task is the most important link in programming learning. Furthermore, the research also showed that the difference in program structure is the core and foundation. The difference in type and quantity in simple structure, nested structure and mixed-use of structures is regular, which is an important factor to determine whether the program runs efficiently and whether the programming task can be solved. Finally, some heuristic ideas were put forward to help learners optimize programs and solve programming difficulties, which was of great guiding significance to PS learning.

The Royal Statistical Society was founded to address social problems ‘through the collection and classification of facts’, leading to many developments in the collection of data, the development of methods for analysing them and the development of statistics as a profession. Nearly 200 years later an explosion in computational power has led, in turn, to an explosion in data. We outline the challenges and the actions needed to exploit those data for the public good, and to address the step change in statistical skills and capacity development necessary to enable our vision of a world where data are at the heart of understanding and decision making.

This article estimates individual treatment effects (ITE) and its probability distribution in a triangular model with binary-valued endogenous treatments. Our estimation procedure takes two steps. First, we estimate the counterfactual outcome and hence, the ITE for every observational unit in the sample. Second, we estimate the ITE density function of the whole population. Our estimation method does not suffer from the ill-posed inverse problem associated with inverting a nonlinear functional. Asymptotic properties of the proposed method are established. We study its finite sample properties in Monte Carlo experiments. We also illustrate our approach with an empirical application assessing the effects of 401(k) retirement programs on personal savings. Our results show that there exists a small but statistically significant proportion of individuals who experience negative effects, although the majority of ITEs is positive. Supplementary materials for this article are available online.

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.

The Tathmini GBV study was a cluster randomized trial to assess the impact of a comprehensive health facility- and community-based program delivered through the HIV/AIDS program platform on reduction in gender-based violence and improved care for survivors. Twelve health facilities and surrounding communities in the Mbeya Region of Tanzania were randomly assigned to intervention or control arms. Population-level effects were measured through two cross-sectional household surveys of women ages 15-49, at baseline (n = 1,299) and at 28 months following program scale-out (n = 1,250). Delivery of gender-based violence services was assessed through routine recording in health facility registers. Generalized linear mixed effects models and analysis of variance were used to test intervention effects on population and facility outcomes, respectively. At baseline, 52 percent of women reported experience of recent intimate partner violence. The odds of reporting experience of this violence decreased by 29 percent from baseline to follow-up in the absence of the intervention (time effect OR = 0.71, 95% CI: 0.57-0.89). While the intervention contributed an additional 15 percent reduction, the effect was not statistically significant. The program, however, was found to contribute to positive, community-wide changes including less tolerance for certain forms of violence, more gender equitable norms, better knowledge about gender-based violence, and increased community actions to address violence. The program also led to increased utilization of gender-based violence services at health facilities. Nearly three times as many client visits for gender-based violence were recorded at intervention (N = 1,427) compared to control (N = 489) facilities over a 16-month period. These visits were more likely to include provision of an HIV test (55.3% vs. 19.6%, p = .002). The study demonstrated the feasibility and impact of integrating gender-based violence and HIV programming to combat both of these major public health problems. Further opportunities to scale out GBV prevention and response strategies within HIV/AIDS service delivery platforms should be pursued. Trial Registration: Pan African Clinical Trials Registry No. PACTR201802003124149.