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 r=0.40 used as a pragmatic feasibility benchmark. Mean absolute error (MAE) and root mean squared error (RMSE) were also calculated on the original workday happiness scale from 0 to 10. RESULTS: A total of 81.8% (9/11) of the participants met or exceeded the feasibility benchmark of r=0.40. Positive correlations were observed for 81.8% (9/11) of the participants; for 9.1% (1/11) of the participants, the correlation coefficient could not be calculated because the self-reported score remained constant, and 9.1% (1/11) showed a small negative correlation. Participant-level correlations ranged from -0.06 to 0.65 for the BERT model and from -0.05 to 0.81 for the local large language model. Error-based metrics also varied across participants: BERT MAE ranged from 1.04 to 2.78, and RMSE ranged from 1.25 to 3.50, whereas Llama MAE ranged from 0.76 to 4.39, and RMSE ranged from 1.06 to 4.64. 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.