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Internet Searches for Affect‐Related Terms: An Indicator of Subjective Well‐Being and Predictor of Health Outcomes across US States and Metro Areas
Author(s) -
Ford Michael T.,
Jebb Andrew T.,
Tay Louis,
Diener Ed
Publication year - 2018
Publication title -
applied psychology: health and well‐being
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.276
H-Index - 31
eISSN - 1758-0854
pISSN - 1758-0846
DOI - 10.1111/aphw.12123
Subject(s) - affect (linguistics) , neuroticism , the internet , psychology , mental health , personality , applied psychology , well being , clinical psychology , social psychology , psychiatry , computer science , world wide web , communication , psychotherapist
Background The present study explored the potential for internet search data to serve as indicators of subjective well‐being ( SWB ) and predictors of health at the state and metro area levels. We propose that searches for positive and negative affect‐related terms represent information‐seeking behavior of individuals who are experiencing emotions and seeking information about them. Method Data on the frequency of Google searches for 15 affect terms were collected from Google's Trends website (trends.google.com). These were paired with data on health, self‐reported emotions, psychological well‐being, personality, and Twitter postings at the state and metro area levels. Results Several internet search scores correlated with indicators of cardiovascular health and depression. Some search term scores also correlated strongly with self‐reported emotions, well‐being metrics, neuroticism, per capita income, and Twitter postings at the state or metro area level. Multiple regression analyses suggest that affect searches predict depression rates at the metro area level beyond the effects of income and other well‐being measures. Conclusion The results highlight the promise and challenges of using internet search data at the aggregate level for physical and mental health assessment and surveillance.