Mood-tracking application as persuasive technology for reduction of occupational stress

Occupational stress is a major concern in the job performance of employees. The use of persuasive technologies is one way to prevent or reduce this stress. The present study developed a mood tracking application and tested its effect on stress reduction of employees. Twenty-six employees of a petrochemical company were divided into equally-sized groups of married and single participants. Employees' accommodations are different based on their marital status. Other variables effecting stress were same for both groups. An OSI-R questionnaire was used to collect data before and after four weeks of application use. In present pilot study, data analysis shows that this kind of persuasive technology can have a significant positive effect on single employees and help them to decrease and manage their stress; however, no meaningful results were recorded for the married group because they did not use the application as much as participants in the single group

Comparing Usability and User Acceptance of two Mobile Mood Tracking Applications with Different Input Methods

Self-monitoring technologies are new technological tool and have changed the interactions between humans and computers on mobile devices. However, the usability of mobile health apps is critically important to the use or abandonment of such applications. Usability and user acceptance analysis methods can play significant roles during the development life cycle. User acceptance and the usability of mood-tracking applications can be influenced by the mood-entering mode of the application. This pilot study compares two mood-tracking methods in different mobile applications, a self-reporting app and automatic mood detection from facial expression, to determine which input method is easier and more usable and acceptable to users. The applications were presented to participants before completing system usability scale and technology acceptance model questionnaires. The results show that the self-reporting application had a better usability score and innovation features; however, the automatic-mood-detection from facial expression app was rated higher on the pleasantness scale by users