The Harmony team is working on Harmony Discovery, which will allow social scientists to find datasets about Anhedonia across data platforms. Harmony Discovery is due in 2025 and will extend the functionality of Harmony.
Preview of Harmony Discovery
Anhedonia, experiencing a reduced interest in previously enjoyable activities and a decreased ability to experience pleasure, is a significant symptom of various mental health conditions. For researchers studying mental health, locating the relevant datasets related to Anhedonia can be a daunting task. Here is where Harmony Discovery comes into play.
Harmony Discovery is an advanced tool designed to assist researchers, primarily in the social sciences, in uncovering datasets about a wide range of topics, including Anhedonia. The tool leverages large language model technology to match variable names and questionnaire items.
Harmony Discovery is integrated with a host of data sources, including the UK Longitudinal Linkage Collaboration (UKLLC), Closer, the Catalogue of Mental Health Measures, Health Data Research UK (HDR UK), and Administrative Data Research UK (ADR UK). This connectivity offers researchers a powerful conduit to discover diverse datasets related to Anhedonia.
Harmony Discovery can guide researchers to datasets like the INCA trial, which compares two types of chemotherapy in treating patients with DLBCL. While the trial is not directly related to Anhedonia, it nonetheless includes relevant data linked to mental health.
Another dataset is ‘Gen Z and Beyond: A Survey for Every Generation, 2021-2023.’ This exploratory study centres around the Zoroastrian community, focusing on the deep-rooted challenges faced by it. Again, while not explicitly about Anhedonia, the data within could potentially be leveraged for analysis on this aspect of mental health.
To sum up, whether studying the direct impacts of Anhedonia or exploring this symptom in the wider context of mental health, Harmony Discovery is a crucial tool for researchers. By offering a streamlined channel to a broad collection of datasets, it greatly simplifies and accelerates the research process.
