Evaluation and Program Planning最新文献

Research and development (R&D) is a crucial competency in both developing and developed countries. As a result, evaluating the performance of R&D programs has become a significant research topic for academic and governmental researchers. This study aims to investigate the impact of various factors, such as the characteristics of national R&D projects, research stages, technology types, and management institutions, on their performance. Specifically, we focus on identifying key factors that influence the efficiency of national R&D investments in South Korea. To achieve this, we compiled a dataset of 98,224 government-funded R&D projects conducted between 2016 and 2019. The dataset includes information on project characteristics (research stage, technology types, and management institutions) as well as outcomes (patent applications, patent registrations, publications, royalties, and sales). Through factorial Kruskal-Wallis tests, we found that the research stage and technology type significantly affected the project outcomes, while the research stage did not significantly influence royalty and sales amounts. Additionally, our analysis of South Korean research management institutions revealed variations in their overall performance, suggesting differences in management capabilities among institutions. Based on these findings, we provide insights into setting appropriate research goals for each project, considering their unique characteristics. Finally, we discuss the implications and limitations of this study.

This paper presents an analysis of survey data to examine the association between supervised structured mentoring and students’ intent to pursue a career in science. Data were collected from students in the 10 Building Infrastructure Leading to Diversity (BUILD) research training programs, developed through grants from the National Institutes of Health. Propensity score matching and multinomial logistic regression demonstrated that exposure to BUILD programs—meaning participation in undergraduate research, receipt of mentoring from a primary mentor, and/or participation as a funded scholar and/or associate of each BUILD site’s training program—was associated with increased intent to pursue a science career. These findings have implications for STEM program evaluation and practice in higher education.

Community organizing and base building groups operate as part of a larger ecosystem of organizations, each with complementary capacities necessary to build power and achieve social change. Analytic approaches to assessing power in organizational networks can generate data to inform strategy, identify gaps, and help nurture organizational ecosystems that support communities in building and exercising power. This article uses a network of 43 justice-focused organizations in the Bay Area, California and their 267 reported connections as a case study to assess the feasibility of measuring power building capacities using social network analyses. We evaluated network capacity for different power-building capacities and explored the relationships between organizations’ positions in the network and their access to capacity. We found that justice-focused organizations were more likely than their connections to have mature capacity for creating alliances and coalitions and for research/legal strategies, whereas their connections were more likely to report mature capacity for community organizing. Most participants in the network were connected within one degree to an organization that was mature in organizing and base building. These results highlight the potential to assess community power building capacities within networks of organizations to identify ecosystem strengths and weaknesses and opportunities for strategic development.

Cultivating alliances between specific sectors or fields with unrealized synergies is a promising strategy for systems change. Social network analysis is a useful tool for assessing whether such alliances build relationships between these previously disparate organizations. Two waves of valued network data were collected from the members (N = 25) of a justice system reform coalition composed of two types of community-based organizations: those involved in restorative justice practice and those involved in grassroots community organizing. Social network homophily analyses were employed to characterize the impact of alliance participation on relationships over time across three domains: working together, doing impactful work together, and sharing a philosophy about justice system reform. Results indicate marked increases in the prevalence of relationships between restorative justice and community organizing organizations across all domains, with the greatest increases occurring in perceptions of shared philosophy. Network structures at each time point differed by relational domain and organization type. Findings suggest that the alliance strengthened relationships between restorative justice and community organizing organizations, particularly in perceptions of shared philosophy, but that the magnitude of these changes varied depending on pre-existing interorganizational relationships and organization type. Findings challenge the idea that close working relationships between diverse members is critical to coalition effectiveness, pointing instead to the value of ambidextrous networks and alignment in members’ philosophy and vision.

Although traffic police enforcement is widely recognized as a key action in the road safety field, it can be a costly policy to implement. In addition, governments often impose budget constraints that can limit the resources available for activities such as law enforcement and surveillance. To evaluate the impact of human traffic control resources planning on traffic fatalities on Spanish NUTS-3 regions interurban roads, this paper uses an econometric model to investigate the performance of police enforcement intensity by focusing on two crucial traffic law infractions (i.e., speeding and drunk driving). After controlling for a range of economic, demographic, climate, and risk exposure variables, results highlight the relevance of visible, human, and in-person traffic law enforcement through regular vehicle patrols for reducing traffic crashes, with a non-significant effect of automatic enforcement. Our findings have important implications for traffic police resource management regarding the effective maintenance of patrol cars and plans to digitalize and automatize police administrative tasks and procedures.

The study aims at ascertaining the conditional selection of key indicators affecting severe, moderate, mild, and no anaemia levels for women of reproductive age in India. The secondary data for levels of anaemia and personal records of individuals collected for India from the 7th phase of District Health Survey program of the United States Agency for International Development data depository. The data was cleaned and summarised using frequency and percentages. Then the variables were tested for association with levels of anaemia using the Chi-square (χ2) test. The multinomial logistic regression model was employed to ascertain the key indicators through a conditional selection of reference categories. Results suggest that severe anaemia was significantly prevalent among women in the reproductive stage, especially among the 15–29 age groups. Secondary and higher education had a negative effect on the severity of severe, moderate, and mild anaemia. The poorest wealth index stratum had higher and more significant severe anaemia, and households with two adults of the opposite sex had a significant negative effect (β = −0.116, OR = 0.89, p < 0.001) on severe anaemia level while having a significant positive effect on moderate and mild anaemia. Rural households were associated negatively and significantly with moderate and mild anaemia, and nuclear household structures had a higher prevalence of severe anaemia. Therefore, these indicators across different levels of anaemia should be considered for a faster rate of reduction at the national level. Despite several initiatives by the public sector, the anaemia level has remained elevated among women of reproductive age. Education, wealth index, age, pregnancy, relationship structure, household structure, and place of residence were found to be key indicators for the level of anaemia. The significant variables will act as a crucial input to formulate cost-effective public interventions and finally encourage the faster reduction of anaemia levels.

The evaluation of Responsible Research and Innovation (RRI) actions presents important challenges for the key stakeholders engaged in the process of RRI implementation, such as policy makers, programme managers, and researchers. While there is a considerable body of literature on the conceptualization of responsibility in research and a plethora of attempts to practice RRI, there is a need for increased attention to the monitoring and evaluation of case studies of RRI implementations in research organisations, in particular regarding their structural change effects. This paper aims to discuss a contextualised developmental framework for evaluating RRI implementation in research organisations, with a specific focus on achieving structural change through tailor-made action plans. The framework, developed through RRI evaluation work in the field of biosciences, adopts a systemic and process-oriented perspective, encompassing participatory, anticipatory, reflexive, and responsive dimensions. Concrete empirical examples from bioscience organizations are provided to illustrate how the framework relates to specific conditions, experiences, and solutions, demonstrating how conceptual insights have emerged from real-life practices and data analysis. While the framework was initially customized for the specific contexts of six bioscience research organizations, it holds potential for broader relevance and applicability in addressing challenges related to RRI design, implementation, and evaluation.

The main purpose of the study is to develop an estimation model using machine learning algorithms and to ensure the effective and efficient implementation of home health care service planning in hospitals with these algorithms. The necessary approvals for the study were obtained. The data set was created by obtaining patient data (except for data such as Turkish Republic identification number) from 14 hospitals providing Home Health Care Services in the city of Diyarbakır. The data set was subjected to necessary pre-processing and descriptive statistics were applied. For the estimation model, Decision Tree, Random Forest and Multi-layer Perceptron Neural Network algorithms were used. It was found that the number of days of home health care service, which the patients received, varied depending on their age and gender. It was observed that the patients were generally in the disease groups that required Physiotherapy and Rehabilitation treatments. It was determined that the length of service for patients can be predicted with a high reliability rate (Multi-Layer Model Acc: 90.4%, Decision Tree Model Acc: 86.4%, Random Forest Model Acc: 88.5%) using machine learning algorithms. In the light of the findings and data patterns obtained in the study, it is thought that effective and efficient planning will be made in terms of health management. In addition, it is believed that estimating the average length of service for patients will contribute to strategic planning of human resources for health, and to reducing medical consumables, drugs and hospital expenses.

Gathering evidence on complex workplace health promotion interventions faces methodological challenges. Therefore, the application of logic models as a theory of change is recommended to support outcome and process evaluations. The present study explores challenges and opportunities of applying logic models in application-oriented intervention research on workplace health promotion. A focus group (n = 6), consisting of scientists and workplace health promotion practitioners, was conducted using a semi-structured interview guide. The recorded qualitative data were transcribed and analysed using the structuring content analysis method. According to the focus group, logic models provide several opportunities for planning and evaluating complex workplace health promotion interventions. Logic models support the communication between science and practice, and have benefits for the provider of workplace health promotion interventions. The main challenges in working with logic models were dealing with the complex and constantly developing intervention and with the derivation and implementation of reasonable evaluation methods. The focus group exposed repeated application and a shared understanding between stakeholders as facilitators for working with logic models. In conclusion, at the science-practice interface, logic models could enhance the integrative understanding and the further development of evidence-based workplace health promotion.

The benefits of physical activity (PA) in managing chronic diseases are largely demonstrated. To encourage a sustainable PA practice for inactive patients with chronic diseases, France has recently implemented PA resumption programs, in which patients can participate with a medical prescription but which are time-limited. In the literature, the effectiveness of those exercise referral schemes to foster sustainable PA practice is still mixed. The present study aims at capitalizing the experience of eight resumption programs to understand what makes the programs work, adherence mechanisms and the post-program referral scheme. Questionnaires and semi-structured interviews informed those intervention mechanisms analysed using thematic analysis. This study provides insights into expertize in patient management among these programs, currently due to key findings as the employment of adapted PA teachers, their training and the use of mechanisms for program adherence (practice conditions, emphasize progress and feelings generated by exercise, the relational and social aspect of practice). Other key findings are a lack of clarity in program objectives which is an area of improvement, and a broad diversity of referral (transmitting contact details, contacting the club, intervention of a third-party association or physical presence) that need further exploration.