Estimating Longitudinal Changes in Workday Happiness From Daily Report Texts Among Employees: Retrospective Feasibility Study.

Background: Workday happiness is associated with workplace performance and burnout, but frequent questionnaire-based assessment is burdensome in real-world workplace settings. Free-text daily reports may provide a lower-burden way to monitor day-to-day changes in workday happiness. Objective: This study aimed to examine whether daily diary text can be used to estimate longitudinal within-person changes in workday happiness and explore text-related factors associated with model performance, such as average sentence length and lexical diversity. Methods: We collected free-text daily reports and self-reported workday happiness scores from employees in 2 Japanese companies. Company A provided training data from 92 participants over 2 months (1725 reports), and company B provided test data from 11 participants over 6 months (652 reports). We used 2 text-based approaches: a bidirectional encoder representations from transformers (BERT)-based regression model trained on company A data and a locally deployed Japanese large language model (Llama) used in a zero-shot setting. Model performance was evaluated for each participant using the Pearson correlation coefficient between self-reported and estimated workday happiness scores, with Results: A total of 81.8% (9/11) of the participants met or exceeded the feasibility benchmark of Conclusions: Our study suggests that daily report text supports low-burden, longitudinal estimation of individual-level workday happiness. However, performance varied across participants, and further work is needed to improve generalizability, reduce attrition, address possible measurement bias, and clarify appropriate workplace use.