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| Funder | Medical Research Council |
|---|---|
| Recipient Organization | University College London |
| Country | United Kingdom |
| Start Date | Aug 31, 2022 |
| End Date | Jan 15, 2025 |
| Duration | 868 days |
| Number of Grantees | 3 |
| Roles | Co-Investigator; Principal Investigator; Award Holder |
| Data Source | UKRI Gateway to Research |
| Grant ID | MR/W029766/1 |
Research needs to be efficient and rigorous to inform evidence-based emergency response. Qualitative data provides public health authorities with key insight into behaviours, beliefs, and contextual factors that shape complex and, often, unprecedented situations. However, qualitative research is frequently excluded from emergency response research plans due to misconceptions around the length of time it requires, its biases, and the level of training required to carry it out properly.
Valuable qualitative data is therefore not used to its full potential in decision-making processes, putting at risk the applicability of findings for each context. This project will refine, consolidate and disseminate the first method for the rapid analysis of large qualitative datasets, so big qualitative data can be routinely used to inform response efforts in the context of emergencies.
Our multidisciplinary team based at University College London and Oxford University is strategically well placed to carry out this work due to our state of the art knowledge about research methods, our large international network of researchers, and popular training courses in English and Spanish. The project will consist of four steps, each resulting in concrete outputs that address the sub-aims of the study: (1) We will review the literature and learn from other methods designed for the rapid analysis of qualitative data.
We will use this information to design LISTEN, an analysis method that combines digital tools to manage and visualise large volumes of data, and collaborative approaches to involve stakeholders in the interpretation of findings. (2) We will test LISTEN on three existing datasets (a large interview study capturing the experiences healthcare workers delivering care during the COVID-19 pandemic in the UK, social media data on Long Covid, and open-ended survey responses about the impact of environmental disasters on mental health in Peru). (3) We will evaluate the quality of LISTEN by studying the successful involvement of people with lived experience, the reliability of findings across multiple researchers and teams, and the financial and infrastructure resources required to conduct LISTEN analysis. (4) We will then host an online international symposium to present LISTEN to a global network and we will develop an accessible toolkit and teaching materials to promote the future use of LISTEN by other teams.
Our project is informed by co-production principles, and our team is committed to open science. We will convene a Consultation Group of experts including researchers, clinicians, policymakers, emergency response experts and lived experience researchers, to advise across all stages of the project. Our primary outputs will include a dynamic website and a project page on the Open Science Framework (OSF) to share openly available and accessible study results.
Establishing the LISTEN method will shift the focus of emergency response from quantitative indicators, to rich indicators developed from the bottom-up. This will have a deep impact on the sensitivity of emergency response to local needs, as well as local capacities, increasing the potential for speedy societal and economic community recovery.
University of Oxford; University College London
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