Researchers in psychology and social sciences frequently face a challenge: comparing data from different questionnaires. For example, they may be combining cohort studies or longitudinal studies or pooling data for cross cohort research. Imagine trying to compare responses to “I often feel anxious” with “Feeling nervous, anxious or afraid” – even though they seem similar, they might not capture the same level of anxiety. This is where item harmonisation comes in.
Item harmonisation (item wise harmonisation) is the process of matching items across different questionnaires that measure the same construct (like anxiety) but use slightly different wording. It ensures researchers are truly comparing apples to apples, not apples to oranges.
However, traditional item harmonisation can be a nightmare. As the study by Hoffmann et al (2024) highlights, it often involves tedious manual work: sifting through lengthy PDFs and painstakingly transferring questions into spreadsheets. This is not only time-consuming but also prone to subjectivity depending on the researcher.
Harmony is a free online tool that leverages the power of natural language processing (NLP) and generative AI models to streamline item harmonisation.
Here’s how Harmony simplifies your work:
A recent study by Hoffmann et al (2024) underlines the importance of strategic item harmonisation. Their research compared various harmonisation techniques and found that a well-chosen approach, like expert-based semantic harmonisation, can significantly improve the accuracy of comparisons between questionnaires. This translates to more robust research findings**.
Stop wasting time on tedious item harmonisation tasks. Let Harmony do the heavy lifting and focus on what matters most – groundbreaking research. Try Harmony at https://harmonydata.ac.uk/app and experience the future of item harmonisation!
