ArticleThe British journal of occupational therapy2022
Relationship between emotional words in electronic medical records and leave periods of users of a return-to-work program with depression.
Article in The British journal of occupational therapy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Machine learning in the analysis of mental health at work: a scoping review.Journal of occupational health · 2026Article
- Operationalising routinely collected patient data in research to further the pursuit of social justice and health equity: a team-based scoping review.BMC medical research methodology · 2025Article
- Relationship between duration of sick leave and time variation of words used in return-to-work programs for depression.Work (Reading, Mass.) · 2024Article
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Authors and funding
8 authors.
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Abstract
Introduction: We attempted to score data extracted from written medical records containing assessment results using natural language processing, and to clarify the relationship between duration of sick leave and the use of emotional words among return-to-work (RTW) program users on sick leave due to mental health problems. Method: Participants were users of an RTW program. We extracted textual data from their electronic medical records, and gave all words a score based on the following two considerations: positivity score (the degree of positive emotion a word has) and emotion score with respect to seven emotions (sadness, anxiety, anger, disgust, trust, surprise, and joy), with the score for each emotion measured for each word. We analyzed relationships between duration of sick leave and each score. Results: Forty-two users participated. The results showed that high positive scores (β = -0.42, Conclusion: Professional assessments based on occupational therapy and natural language processing of medical records may predict the appropriate timing of RTW.
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