Привет Гармония! 哈莫尼可以让中英文和谐！ שלום הרמוני Harmony peut aussi harmoniser les instruments en français. We’re happy to share some exciting news with you. Harmony now supports at least 8 languages: Portuguese, French, German, Spanish, Russian, Chinese, and Hebrew. This means that you can use Harmony to compare and harmonise questionnaire data across studies that are written in different languages. I evaluated Harmony’s ability to match the GAD-7 in 11 languages to the English version.
Many psychologists believe that mental illnesses can vary across cultures. In 1904, Emil Kraepelin initiated the field of comparative psychiatry after studying mental health disorders in Java, writing that “Die Eigenart eines Volkes wird auch in der Häufigkeit und klinischen Gestaltung seiner Geistesstörungen zum Ausdruck kommen,” meaning “The peculiarity of a people[ethnic group] will also be expressed in the frequency and clinical form of its mental disorders.”[1] More than a century later, the emergence of global mental health research projects has opened a number of debates about the applicability of psychiatric categories to different cultural settings, such as those in the Diagnostic and Statistical Manual of Mental Disorders (DSM) series[2].
Harmony was able to reconstruct the matches of the questionnaire harmonisation tool developed by McElroy et al in 2020 with the following AUC scores: childhood 84%, adulthood 80%. Harmony was able to match the questions of the English and Portuguese GAD-7 instruments with AUC 100% and the Portuguese CBCL and SDQ with AUC 89%. Harmony was also evaluated using a variety of transformer models including MentalBERT, a publicly available pretrained language model for the mental healthcare domain.
Semantic text matching is a task in natural language processing involving estimating the semantic similarity between two texts. For example, if we had to quantify the similarity between “I feel nervous” and “I feel anxious”, most people would agree that these are closer together than either sentence is to “I feel happy”. A semantic text matching algorithm would be able to place a number on the similarity, such as 79%.
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.
