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Recent studies have shown that people who attend electronic dance music events and use drug checking services (DCS) are a predominantly white male, highly educated middle-class population. However, there is still a lack of data beyond sociodemographic characteristics that must be addressed. This paper aims to describe the drug use patterns and protective behavior strategies (PBS) used by testers and nontesters at Boom Festival 2018 and analyze the relationship between these behaviors and the decision to use the DCS.

This is an exploratory research based on a cross-sectional design using baseline data collected at the Boom Festival from testers (N = 343) and nontesters (N = 115).

Nontesters presented, in general, slightly higher frequencies of use for most drugs, whereas testers tended to adopt PBS more frequently. Moreover, testers planned their drug use more often than nontesters and set more limits on the amount of drugs they used in one session. Both of these behaviors work as predictors for using the DCS.

Our data suggest that DCS might not be easily accessible to all people who use drugs, reaching almost exclusively highly educated people that already apply several harm reduction strategies. Actions should be taken to promote service accessibility.

To the best of the authors’ knowledge, this paper is the first to compare the demographics, drug use and PBS adoption of DCS users with nonusers who attended the same festival.

Despite the increasing availability of financing programs for innovation, micro, small and medium-sized enterprises (MSMEs) often find it difficult to access credit for their projects. Among the reasons, the lack of the types of guarantees required by financial institutions stands out. Focused on this problem, in 2013, the Regional Bank for the Development of the Extreme South (BRDE) created a policy to stimulate innovation, making the required guarantees for financing operations of innovative companies more flexible: the BRDE Inova Program. This paper aims to analyze the guarantees used in the bank operations since the beginning of the program.

In the first stage of the research, the authors identified the guarantees used in each of the signed contracts, through a documentary survey. Next, semi-structured interviews showed the perceptions of the players involved in the innovation ecosystem of the state of Santa Catarina, regarding aspects related to the guarantees. Specifically, the authors investigated the following elements: strengths and limitations of the programs regarding access to credit for innovation; adequacy of existing guarantee mechanisms. To strengthen the conclusions, they used triangulated data collection in different stages.

The results showed that, on the one hand, the initiative helped BRDE to consolidate itself as the main financing agent of innovation in MSMEs; on the other hand, the need for traditional guarantees still plays a significant role for innovative MSMEs to access credit.

In addition to practical implications for the bank and other financing agents’ policies, this paper contributes to fill a gap in the literature on guarantee systems applied to the specificities of knowledge-intensive MSMEs.

People are increasingly responsible for making sound financial decisions to foster their financial satisfaction and well-being, which magnifies the importance of financial literacy, and this concept and measurement is still not yet crystallized in the literature, specifically capturing different behavior perceptions. Moreover, there is not a distinction based on different classifications of behavior, such as over or underconfidence, to understand the relation between literacy and decision process. To fill this gap, this paper aims to investigate whether the financial literacy conceptual model proposed applies similarly to every group independently of their previous self-confidence perception. For this purpose and quality control, OECD (2016) data were used with a final sample of 1,487 Brazilian citizens. Quantitative analysis technique using partial least squares structural equations path modeling and differences between groups using multi-group analysis was applied. In line with general studies, when analyzing the financial literacy usual model for the group as a whole, financial knowledge construct positively influences self-confidence, and both together positively affect financial behavior. However, for individuals with low financial knowledge and low self-confidence, as well as for those with too much or too little confidence, the model did not hold. Therefore, self-confidence perception influences the way financial knowledge is used for financial decisions and should be addressed in financial education and training to be more effective.

To operationalize the variables and test the paper’s hypotheses, the authors used the methodology developed in OECD (2016), based on the research instrument’s Brazilian application adapted from the questionnaire developed in OECD (2015), with data initially used and made available by Garber and Koyama (2016). Based on the recommendations of Hair Jr et al. (2017a, 2017b), the authors used partial least squares modeling PLS-PM (SmartPLS 3.2.6) to estimate the structural models.

Concerning structural relationships, the final model showed knowledge with a positive influence on self-confidence, self-confidence with a positive effect on behavior and knowledge with a positive influence on behavior, both directly and, through its relationship with self-confidence, indirectly. This underscores that, for the total sample, the greater people’s knowledge and self-confidence, the better their behavior. The unexpected absence of attitude in the final model, even allowing for potential measurement problems, brings up an important reflection on the mediating effect that the self-control variable may exert between attitude and behavior. A person may believe that saving for the future is important (attitude) but whether they actually save (behavior) may depend on self-control, which is needed to prevent immediate gains from being prioritized in practice.

The findings reported so far concern the study’s total sample. However, as expected from the literature review that provides the basis for the sixth and the most important hypothesis, respondents were found to be heterogeneous in terms of knowledge and self-confidence levels. These differences were evaluated by means of multi-group analyses that indicated that the model does not apply to respondents with low knowledge and low self-confidence and to those who are over- and underconfident. This implies inferring that financial education programs may be of little use if they only address technical knowledge development and fail to consider behavioral aspects such as those related to self-confidence, as this paper points out, and others. This signals the importance of diagnosing people’s profiles to enable developing solutions capable of minimizing the presence of behavioral biases. This need to be studied further.

The results imply inferring that financial education programs may be of little use if they only address technical knowledge development and fail to consider behavioral aspects such as those related to self-confidence, as this paper points out, and others. Models must be reviewed in light of natural diferences of cognition and lead to customized financial education.

This signals the importance of diagnosing people’s profiles to enable developing solutions capable of minimizing the presence of behavioral biases. Therefore, not only training topics in personal finance but also a deeper education program since the kindergarden must be considered.

Its practical contribution is to suggest the development of financial education programs that also take account of the potential presence of behavioral biases, which may prevent the misallocation of (scarce) public- and private-sector funds stemming from a limited focus on developing the population’s actual financial knowledge.

Progress toward health equity is necessary to reduce health disparities, and health literacy is key to achieving this goal. Because libraries provide access to knowledge and insights about their communities, they are effective partners in advancing health equity and implementing programs to reduce health disparities. A literature review on library programs and activities that focus on promoting health equity was conducted.

A literature review on library programs and activities concerning health equity and social determinants of health was conducted. Relevant literature was identified from searches of databases, library publications and grey literature.

The authors found 224 eligible sources and many types of libraries advancing health equity. Libraries frame their role in advancing health equity through external programs in three ways: (1) providing access to high-quality health information, (2) delivering health literacy training and resources and (3) connecting their communities with community health services. Libraries also advance health equity by focusing on internal library operations and providing research services focused on cultural humility and competence as they apply to health care.

This literature review will help the National Library of Medicine (NLM) develop a strategy to support libraries advancing health equity through information made available by programs and activities of NLM and the Network of the National Library of Medicine.

The present study investigates the effect of foreign direct investment (FDI) and governance quality on carbon emissions in the Economics Community of West African States (ECOWAS).

To achieve the objective of this research, panel data for dependent and explanatory variables over the period 2005–2016, collected in the World Development Indicators (WDI) database and World Governance Indicators (WGI), are analyzed using the generalized method of moments (GMM). Also, the panel-corrected standard errors (PCSE) method is applied to the four segments of the overall sample to analyze the stability of the results.

The findings of this study are: (1) FDI inflows have a negative effect on carbon emissions in ECOWAS and (2) The interaction between FDI inflows and governance quality have a negative effect on carbon emissions. These results show the decreasing of environmental damage by increasing institutional quality. However, the estimation results on the country subsamples show similar and non-similar aspects.

This study suggests that policymakers in the ECOWAS countries should strengthen their environmental policies while encouraging FDI flows to be environmentally friendly.

The subject has rarely been explored in West Africa, with gaps such as the lack of use of institutional variables. This study contributes to the literature by drawing on previous work to examine the role of good governance on FDI and the CO2 emission relationship in the ECOWAS, which have received little attention. However, this research differs from previous work by subdividing the overall sample into four groups to test the stability of the results.

The purpose of this study is to examine the extent to which dynamic network analysis (DNA), text mining and natural language processing (NLP) are helpful research tools in identifying the key actors in a complex international crisis. The study uses these tools to identify the key actors in the Syrian crisis as a case study to validate the proposed algorithm.

To achieve its main purpose, the study uses a collection of three methodologies, namely, DNA, text mining and NLP.

The results of the analysis show four key actors in the Syrian crisis, namely, Russia, the USA, Turkey and China. The results also reveal changes in their powerful positions from 2012 to 2016, which matches the changes that occurred in the real world. The matching between the findings of the proposed algorithm and the real world events that happened in Syria validate our proposed algorithm and proves that the algorithm can be used in identifying the key actors in complex international crises.

The importance of the study lies in two main points. It proposes a new algorithm that mixes NLP, network extraction from textual unstructured data and DNA to understand and monitor changes occurring in a complex international crisis. It applies the proposed algorithm on the Syrian crisis as a case study to identify the key actors and hence validate the proposed algorithm.