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Managing Mood: Analyzing Emotional Triggers with Data-Driven Insights

This project explores mood management by identifying and mitigating upset triggers in daily life. By hypothesizing that reducing reactions to specific situations can lead to less anxiety and anger, we developed a smartphone app to track emotional responses. Over 33 weeks, we collected 723 entries, examining triggers such as interactions with a spouse or coworker. Our analysis revealed that upset intensity may correlate with the proximity to other negative experiences. This research aims to provide actionable strategies for emotional resilience and wellbeing.

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Managing Mood: Analyzing Emotional Triggers with Data-Driven Insights

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Presentation Transcript

  1. “We Never Fight on Wednesdays!” Mood management through reducing Upset Triggers

  2. Environment • Hypothesis: “Happier if I train myself to react with less anxiety/anger in specific situations.” • Smart phone app capture and export to excel • 33 weeks of data • 723 entries

  3. Mechanism

  4. Log Entry Volume

  5. Triggers in Total 26% 5% 5% 11% 24% 14%

  6. Triggers - Wife

  7. Triggers – Coworker by hour

  8. Trend - Travel

  9. Direct vs Self Induced

  10. Direct/Self Induced Over Time

  11. Followup Studies • Hypothesis: “Intensity of upsets is result of proximity to other upsets (ie in a bad mood).” • Hypothesis: “Training out of upset intensity takes a predictable number of interventions.”

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