Harmony News
Now more than ever, the international research community are keen to determine whether their findings replicate across different contexts. For instance, if a researcher discovers a potentially important association between two variables, they may wish to see whether this association is present in other populations (e.g. different countries, or different generations). In an ideal world, this would be achieved by conducting follow-up studies that are harmonised by design. In other words, the exact same methodologies and measures would be used in a new sample, in order to determine whether the findings can be replicated.
New Discoveries for Patient and Public Involvement About one year ago I fully entered the world of secondary data analysis research – away from applied mental health research with creative data collection methods and small sample sizes, towards big data and complex analyses efforts to overcome what someone deemed not worth measuring (Wait, why are we not assessing emotion regulation in each and every study 1?) Of course, I know we can’t measure everything and the decision of what to measure in studies is one of the hardest to make.
When you input two questionnaires into Harmony, such as the GAD-7 and Beck’s Anxiety Inventory, Harmony is able to match similar questions and assign a number to the match. (I have written another blog post on how we measured Harmony’s performance in terms of AUC). So how does Harmony achieve this? Harmony uses techniques from the field of natural language processing to identify when two questions deal with a similar topic.