I lead the Harmony Research Group (harmonyresearchgroup.com) at Lund University. Our research spans three broad areas:

• Developing Research Methods using Artificial Intelligence (AI), which includes leveraging large language models, natural language processing (NLP), and machine learning (ML).

• Well-Being including harmony in life, balance, and sustainable well-being.

• Mental Health Issues focusing on depression, anxiety, and stress.

Artificial Intelligence (AI)

The language people use contains a wealth of valuable psychological information for research. Our work uses AI to quantify the meaning of language:

• Natural Language Processing (NLP): Enables the quantification of language meaning.
• Machine Learning (ML): Examines the relationships between language and numerical variables or outcomes.

Using these methods, we’ve developed and validated an approach where individuals can describe their state of mind using natural language. This computational language assessment approach complements traditional closed-ended rating scales by allowing us to measure, describe, and differentiate psychological constructs effectively.

In collaboration with international teams of computer scientists, we’ve developed R packages tailored for social scientists to analyze language:

• talk (r-talk.org): Transforms audio recordings into text (speech-to-text) or embeddings (numeric representations).
• text (r-text.org): Converts digital text into word embeddings using large language models.
• topics (r-topics.org): Visualizes language in topics and word clouds.

Well-Being and Harmony in Life

Our research on subjective well-being explores various ways to conceptualize and measure well-being and happiness. We are currently investigating the relationships between harmony in life, balance, satisfaction with life, and happiness. Building on this, we are exploring how these constructs connect to a broader sense of sustainable well-being and the potential social and environmental consequences of pursuing different types of well-being.

Mental Health Issues

Our research on mental health issues focuses on assessing depression, anxiety, and stress using best-estimate assessments (see our LEADING Statement Guidelines). We also develop precision mental health algorithms to identify the right treatment at the right time for the right person.