Despite an emerging body of scholarship on applying generative AI (GenAI) to qualitative data analysis, this area remains underdeveloped. This article evaluates how GenAI can support thematic analysis using a publicly available interview dataset from Lumivero. It introduces Guided AI Thematic Analysis (GAITA), an adaptation of King et al.’s (2018) Template Analysis. This framework positions researchers as a reflexive instrument and intellectual leader while thoroughly guiding GPT-4 in four stages: data familiarization; preliminary coding; template formation and finalization; and theme development. Additionally, the article proposes the ACTOR framework, a simple approach to combining different effective prompting techniques when working with GenAI for qualitative research purposes. Findings reveal GenAI’s capacity for analyzing the data, generating codes, subcodes, clusters, and themes, along with its adaptive learning and interactive assistance in organizing unstructured data and developing trustworthiness. However, this model has some key limitations in terms of its restricted context window for processing large datasets, its inconsistent outputs requiring multiple prompt attempts, the need to move across workspaces, and the lack of relevant training data for qualitative research purposes.

Artificial intelligence (AI) tools have been used to improve the productivity of evidence review and synthesis since at least 2016, with EPPI‐Reviewer and Abstrackr being two prominent examples. However, since the release of ChatGPT by OpenAI in late 2022, the use of generative AI for research, especially for text‐based data analysis, has exploded. In this article, we used a critical reflection approach to document and evaluate the capacity of different generative AI tools such as ChatGPT, GPT for Google Sheets and Docs, Casper AI, and ChatPDF to assist in the early stages of a rapid evidence review process. Our results demonstrate that these tools can boost research productivity in formulating search strings and screening literature, but they have some notable weaknesses, including producing inconsistent results and occasional errors. We recommend that researchers exercise caution when using generative AI technologies by designing a thorough research strategy and review protocol to ensure effective monitoring and quality control.

Despite the growth of disaster scholarship, the topic of how and why climate‐related disasters and extreme weather events vary among people with different types of disabilities remains unexplored. To help fill the gap, this study draws on a larger research project that was co‐designed by Water Sensitive Cities Australia at Monash University and the Hanoi Association of People with Disabilities, Vietnam. It utilised the dataset of a rapid evidence review of 33 studies, key informant interviews with 26 local stakeholders, and 52 interviews with people with various disabilities in Hanoi and Nghe An province, Vietnam. Using thematic analysis, we identified eight themes pertaining to socially‐constructed difficulties facing people with disabilities: barriers to accessing disaster risk information and warnings; difficulties in understanding emergencies; challenges in communicating needs; evacuation and mobility hurdles; decreased sense of belonging and isolation; increased risk of getting sick; increased risk of developing mental health and behavioural disorders; and disrupted livelihood and loss of income.

Since the late 1980s, social theorists championed for the birth of a new era, in which societies were increasingly exposed to growing global risks. The presence of increasing risks including natural disasters, technological errors, terrorist attacks, nuclear wars and environmental degradation suggests that human beings are becoming increasingly vulnerable. Therefore, an understanding of vulnerability is crucial. Vulnerability is often considered as the potential to suffer from physical attacks. This approach, however, has limited capacity to explain many forms of suffering including not only physical aspects, but also mental, social, economic, political and social dimensions. This chapter draws on the vulnerability literature to present an overarching framework for the book. It starts with an outline of the concept origins, then discusses its relationship with the risk society thesis before forming conceptualisation. The chapter then points out the key similarities and differences between vulnerability and other concepts such as risk, disaster, poverty, security and resilience. The authors rework an existing “security” framework to develop a new definition of the concept of vulnerability. Finally, the authors look into the root causes and the formation of vulnerability within social systems.

In Vietnam, it is commonly believed that gender norms, sex labour segregation, and structural organization of social institutions often favour male dominance while restricting women’s roles in domestic spheres. However, there is a scant literature of Vietnamese scholarship on the determinants of gender role attitudes, especially geographical disparities. This paper aims to fill this void by using a nationally representative survey with 8288 respondents. Our findings suggested that age, marital status, religion, education, living area, region, ethnicity, and personal monthly income are the factors that predicted gender attitudes. In terms of regional disparities, we found that Northerners were more permissive in their gender attitudes than Southerners, which may be explained by distinct historical and political trajectories in Northern and Southern Vietnam during the last century. There were, however, inconsistent patterns among different age cohorts whereby region significantly impacted the attitudes of women born before the end of the French War in 1954, men born after the Reunification in 1975, as well as both men and women born between 1954 and 1975.