Ego depletion refers to the idea that self-control and decision-making abilities become depleted or diminished after engaging in prolonged or demanding cognitive tasks. When conducting research with humans, states such as stress are usually asked directly to the par- ticipants by using ecological momentary assessment (EMA). However, as those answers are self-reported, they are prone to bias due to the lack of user commitment or effort to assess the stress levels the best they can. This paper investigates the relationship between ego depletion and stress level reporting, specifically focusing on the bias in self-reported stress levels. The hypothesis tested in this study suggests that higher levels of ego depletion lead to greater bias in self-reported stress levels. Data collected by Berrocal et al. using EMA were analyzed to examine this hypothesis. The dataset included self-reporting stress levels by individ- uals being assessed and stress level reports from their peers. Data was collected using a mobile app, incorporating passive smartphone usage data alongside EMA responses. The hypothesis was tested and studied employing artificial intelligence algorithms. The results partially con- firmed the initial hypothesis, revealing that lower ego depletion was asso- ciated with reduced bias in stress level reporting. Notably, when analyz- ing data from working days, the morning period demonstrated the least bias compared to the afternoon. These findings suggest that individu- als have higher self-capacity and willingness to provide accurate stress level assessments during the morning hours. Challenges encountered in the research included limitations related to the holidays considered and potential confounders such as flexible time schedules or post-lunch sleepi- ness. This paper releases its data publicly, allowing for further examina- tion and replication of the findings. Future research is encouraged to expand upon these conclusions.