Harnessing data to improve employee well-being — Brad Smith // meQuilibrium

Show Notes

• 01:39
  meQuilibrium and improving employee wellbeing through data

  meQuilibrium uses cognitive data to assess employees' cognitive styles and resilience factors. They help businesses identify well-being risks and opportunities within their workforce and assist individuals in upskilling to improve their overall well-being and performance.
• 03:15
  meQuilibriums cognitive data collection and individualized wellbeing journeys

  meQuilibrium collects cognitive data through a five-minute assessment. This data, covering factors like positivity and problem-solving ability, is used to create individualized well-being journeys for each user, with unique skill-building modules designed to address specific areas of improvement.
• 05:01
  meQuilibrium's assessment questions and customization

  Assessment questions cover topics such as positivity, challenge-seeking, and social support. The core assessment consists of 60 standard questions to ensure comparable data across their user population, but some customization is allowed based on specific customer interests.
• 07:16
  Employee privacy and data protection in meQuilibrium assessments

  meQuilibrium clearly communicates in the terms and marketing materials that individual assessment data will not be shared with employers. Instead, data is only reported in aggregated form, assuring employees that their information remains confidential.
• 08:18
  meQuilibriums strict data security measures

  Access to individual-level data is restricted to a small number of authorized personnel, and data is treated as protected health information. meQuilibrium follows standard security practices and conducts background checks on employees to prevent accidental leaks or unauthorized access.
• 09:29
  meQuilibrium's approach to mitigating business risks using cognitive data

  meQuilibrium leverages cognitive data to improve individual well-being via self-care and supportive management. "Workforce Intelligence" enables HR to detect organizational resilience and behavioral health risks, while "Intelligent Navigation" enhances EAP utilization.
• 14:18
  meQuilibrium's individual level reports and insights

  Users receive a profile highlighting their go-to emotional response during stress, strengths, and weaknesses. While most users are unsurprised by their stress personality, some exploration is required for their go-to emotions and the 18 resilience factors.
• 18:08
  How meQuilibrium's platform helps employees improve their emotional wellbeing

  meQuilibrium teaches cognitive behavioral techniques, like reframing, to help employees identify and replace unhelpful thoughts with reality-based ones. The platform's scenarios and exercises foster metacognition, enabling better emotional response management.
• 20:23
  meQuilibrium's skill building micro learning modules

  Within the platform, users can access modules with activities to recognize and change their dysfunctional thinking patterns. Users can also schedule future activities and reassess their progress every 90 days to track improvements over time.
• 22:51
  meQuilibrium's ability to archive user data and its mood boosting chatbot

  The meQuilibrium app archives your past activities, including gratitude statements and vignettes. The platform's chatbot can remind users of these past entries, offering personalized support and acting as a digital resilience coach to help individuals manage their well-being.
• 23:59
  meQuilibrium's use of AI in chat features and recommendations

  meQuilibrium is exploring the integration of generative AI in its chat features to provide more conversational and interactive interactions with users. They currently use ML for content recommendations based on user behavior, with ongoing efforts to enhance its role in optimizing user experience.
• 25:33
  meQuilibrium's continuous learning and personalization

  meQuilibrium continuously updates its understanding of users beyond the initial assessment. It offers reassessments at the 90-day mark, adapting users' journeys to reflect their progress and learning from their preferences and past interactions to provide personalized recommendations.