“Studying adoption: research traditions, present and future directions”
Jesús Palacios, University of Seville, Spain
The research on adoption has continued to progress since its inception. Research questions have evolved, as have the conceptual frameworks and data analysis tools. Examining the changing trends in adoption research, which of the old questions remain relevant, and what new questions are being raised can be an excellent way to delve into adoption research. Each new study is situated within a tradition to which it contributes and enriches. Examining both the adoption research traditions and how the interests of the participants fit within them will be an excellent way to start this pre-ICAR9 activity.
“Using artificial intelligence tools in applied family research: Do the benefits outweigh the challenges?”
Ana Catarina Canário, University of Porto, Portugal
Technological developments take place rapidly and have led us into an era of constant transformative change. In this context, artificial intelligence (AI) is increasingly becoming a driving force in the evolution of human knowledge. Multiple generative and assistive AI tools have been disseminated at scale and are widely available. Yet, it is critical to understand how researchers can leverage such technologies effectively in their work, in a way that increases, rather than displaces, critical thinking, integrity, and accountability.
In this pre-conference workshop, we will present a summary of international recommendations on the ethical and practical use of AI in research. Participants will engage in active discussions on the benefits and challenges of using AI tools in applied family research, explicitly addressing the issues of training, ethical use, and transparent integration into research workflows. We will also look into specific tools that support academic writing and research methods, and delve into examples of research focusing on the responsible use of AI and technologies to develop tools and resources for family support service provision.
By the end of the workshop, participants will be able to: 1) identify key international guidelines on the use of AI in research; 2) identify assistive AI tools relevant for research; and 3) critically evaluate the benefits and challenges of integrating AI into the research workflow, while identifying the ethical safeguards necessary to promote research integrity.
“Modern Missing Data Analysis: From Theory to Practice in R”
Tiago Ferreira & Filipa Nunes
Missing data are a constant in applied research and, when mishandled, can lead to biased estimates, loss of statistical power, and invalid conclusions. This hands-on workshop provides an introduction to modern missing data analysis, moving from foundational theory to practical implementation in R. Participants will examine why missing data constitute a statistical issue, including a critical review of traditional ad hoc approaches such as deletion and single imputation. Core missing data mechanisms are introduced conceptually, with emphasis on their implications for valid statistical inference. The workshop then focuses on modern solutions under the missing at random assumption, including multiple imputation and full-information maximum likelihood. Through applied examples in R, participants will learn how to diagnose missing-data patterns, implement multiple imputation, and estimate models using full information maximum likelihood. By the end of the session, participants will be able to select, justify, and implement appropriate strategies for handling missing data in their own applied research.