Whitepaper: The Science of Connection Petalz Mosaic

Product Team

August 14th, 2025 

Abstract

From the very beginning Petalz Mosaic has been developed as an evidence-informed digital platform designed to support emotional connection and reduce barriers to engagement among all digitally excluded populations.

The implications of this work extend beyond digital engagement. Social isolation has been identified as a significant risk factor for adverse health outcomes, while sustained connection to familiar people and experiences is associated with improved well-being. (Appendix A: Holt-Lunstad et al., 2015 “Social isolation and loneliness are associated with a significantly increased risk of mortality”). Developing systems that can reliably deliver this connection, without requiring technical ability, represents a critical and underexplored opportunity. The system we continue to develop is grounded in the hypothesis that reducing interaction complexity, while increasing the frequency and emotional relevance of content exposure, may influence observable engagement patterns and mood-related behaviors over time. (Appendix A: Fogg, 2009; Holt-Lunstad et al., 2015)

Rather than relying on conventional interaction models which have clearly failed specific demographics, we set out to ensure that Petalz Mosaic investigates new and innovative paradigms of passive and ambient engagement, where meaningful content is delivered without requiring active user navigation.

Observed Behavioral Patterns Informing Design

The Petalz platform has been informed by ongoing observation and real-world usage patterns across family communication contexts.

Our initial research led to some preliminary observations:

• Reduced interaction effort is associated with increased participation among certain demographics who face obstacles to digital engagement (Appendix A: Czaja et al., 2006; Mitzner et al., 2010)
• Studies have been done that demonstrate passive exposure to familiar, emotionally relevant content may sustain attention more effectively than active browsing (Appendix A: O’Brien & Toms, 2008)
• Recency and relational proximity appear to influence content engagement. Put simply, seeing regular updates from familiar people and moments helps individuals stay aware, engaged, and connected to their world. (Appendix A: Lindley et al., 2009)
• As a sidenote, we also observed that caregivers were often isolated and needed additional support. However, coordinated visibility among caregivers improves task follow-through and shared awareness, reducing burnout. (Appendix A: Pearlin et al., 1990)

These observations were the genesis of our system foundation and continue to inform ongoing hypothesis development and design. Drawing on our analysis of the existing research, we have developed the following approaches and will assess their effectiveness through continuous measurement, evaluation, and iterative system refinement.

1. Ambient Content Delivery Systems

Petalz is investigating whether a continuously available stream of family-generated content can support higher levels of engagement compared to conventional session-based interaction models. (Appendix A:Fogg, 2009; O’Brien & Toms, 2008)

This includes exploring:

• passive content consumption patterns
• temporal sequencing of content
• persistence of attention without active input
• importance of fresh content and messages to increase engagement

2. Contextual and Temporal Content Sequencing

The platform is designed to explore how content can be sequenced to maintain ongoing relevance, timeliness, and awareness of meaningful family events.

Rather than relying solely on static feeds or user-driven interaction, Petalz incorporates multiple contextual signals to prioritize content, including:

• temporal relevance (e.g., recent updates, daily activity – what are my loved ones doing today)
• significant family events (e.g., birthdays, milestones, commemorations)
• observed engagement patterns (e.g., viewing frequency, content interaction)

With these observations in mind, we designed a platform where the content is continuously evaluated to ensure that it remains current and meaningful. As content ages or shows limited engagement, it is gradually deprioritized in favor of more recent or relevant updates.

This approach requires the development of adaptive sequencing models capable of maintaining content freshness and relevance in environments with limited explicit user input. (Appendix A: O’Brien & Toms, 2008; Lindley et al., 2009)

3. Zero-Interaction User Experience Models

Petalz is engineering a system that minimizes or eliminates the need for conventional user interface interaction.

Key areas of technical investigation:

• state persistence without navigation
• continuous content delivery without session initiation. Kiosk functionality for those unable to initiate an application
• system reliability in unattended usage environments. The ability to run for days and weeks without interruption

This represents a departure from traditional human-computer interaction paradigms and introduces challenging design constraints. (Appendix A: Czaja et al., 2006)

4. Distributed Family Coordination Systems

Petalz includes a shared coordination layer designed to support multiple participants contributing to a common care or communication context. It was difficult to separate the isolation experienced by some demographics with the associated demands on the caretaker(s). It was a natural extension to incorporate shared care, or the Petalz Share the Care feature.

This involves:

• real-time synchronization of user-generated tasks across devices, with notifications to create awareness and generate positive peer pressure to contribute
• role-based access and permissions, complete with device notifications
• event-driven task coordination with temporal triggers and chat capabilities

The system must maintain consistency across distributed users while supporting and encouraging participation. (Appendix A: Pearlin et al., 1990)

Measurement Framework

To truly be successful, we recognize that Petalz Mosaic must be developed with the ability of evaluating system effectiveness through observable behavioral patterns and interaction data. This is our intention.

Our Core Hypothesis

Improving caregiver capacity and system coordination leads to measurable improvements in user well-being. (Appendix A: Cacioppo & Cacioppo, 2014; Holt-Lunstad et al., 2015)

This is what we aim to validate, quantify, and apply.

What We’re Studying

1. User Daily Experience

Measurement efforts are expected to include:

• Sense of connection to familiar people and ongoing life events 
• Emotional responsiveness to incoming content and interactions 
• Reduction in observable signs of isolation, confusion, or disengagement 
• Sustained participation in daily rhythms and surrounding environment

2. Caregiver Capacity

Measurement efforts are expected to include:

• Perceived level of support and shared responsibility across the care network 
• Clarity and confidence in decision-making within daily care situations 
• Reduction in coordination burden and fragmentation of communication 
• Sustained ability to manage responsibilities without signs of overload or burnout

3. Care System Performance

Measurement efforts are expected to include:

• Communication efficiency between family members
• Role clarity and task ownership
• Consistency in care routines
• Time to resolve care-related decisions

Analytical Framework Based on Observed and Derived Metrics

• Engagement Metrics

Petalz Mosaic measures engagement through patterns of passive and active interaction with content, including:

• frequency and duration of content exposure
• recurrence of passive viewing sessions
• interaction with specific content types – static, motion, personal
• repeat engagement with particular contributors

These metrics help inform how content is sequenced and presented over time. (Appendix A: O’Brien & Toms, 2008)

• Participation Metrics

In addition to individual engagement, Petalz Mosaic will evaluate the level and consistency of participation across the family network, including:

• number of active contributors within a network
• consistency of content contribution over time
• utilization of coordination features
• responsiveness to shared tasks and shared prompts

• Adaptive Notification Strategy (“Nudges”)

Petalz Mosaic incorporates a structured notification framework—referred to as Nudges—designed to encourage timely participation without introducing excessive interruption or fatigue. (Appendix A: Fogg, 2009)

Rather than applying a fixed notification model, Petalz Mosaic provides users with the ability to adjust notification frequency according to their individual preferences, while the system evaluates responsiveness to support ongoing refinement of notification strategies. This includes exploring individualized thresholds for notification fatigue and engagement sensitivity.

Current areas of investigation include:

• the effectiveness of different notification types (e.g., reminders, prompts, time-based triggers, and contextual events)
• optimal timing and frequency of notifications across different users
• the relationship between notification exposure and subsequent engagement behavior
• user-specific tolerance levels for repeated prompts

Petalz Mosaic is also introducing the capability to measure and compare the effectiveness of multiple notification strategies, with the goal of continuously refining how and when Nudges are delivered.

• Mood-Related Behavioral Indicators

Petalz Mosaic plans to develop capabilities to capture user-reported mood indicators and explore how these may relate to patterns of content exposure and interaction.

This includes examining whether different types of content—such as highly personal, time-sensitive communications (e.g., Daily Messages)—are associated with observable differences in engagement and reported experience. (Appendix A: Cacioppo & Cacioppo, 2014; Holt-Lunstad et al., 2015)

Petalz Mosaic is also exploring the use of AI-assisted methods to capture this information in a non-intrusive and user-appropriate manner, with the goal of minimizing burden while preserving meaningful insight.

Any such data collection would be voluntary, non-clinical, and used to support ongoing system refinement rather than diagnostic interpretation.

These indicators are interpreted as non-clinical, observational signals, not diagnostic measures.

Technical Uncertainty

The development of Petalz Mosaic involves multiple areas of technical uncertainty.

These include:

• determining how to prioritize content in the absence of explicit user interaction signals
• identifying reliable proxies for emotional relevance in passive environments
• maintaining engagement without introducing cognitive or operational burden
• balancing system automation with user transparency and control

Addressing these uncertainties requires iterative experimentation, algorithm development, and system-level design innovation.

Privacy, Ethics, and Responsible Design

Petalz Mosaic is being developed with a strong emphasis on privacy, proportionality, and responsible interpretation of behavioral data.

Guiding principles include:

• collecting only data necessary to improve system performance
• avoiding unsupported or clinical interpretations of behavioral patterns
• maintaining transparency regarding system behavior and measurement approaches
• preserving the privacy and integrity of family-generated content

All research and measurement approaches are intended to evolve responsibly over time.

Conclusion

Petalz Mosaic is being developed as a research-informed system at the intersection of human-computer interaction, digital communication, and behavioral observation. Simply put, we want to enrich the lives of some of our dearest demographic!

Learn more about our research and participate in the Petalz Case Study

Appendix A: References

Cacioppo, J. T., & Cacioppo, S. (2014). Social relationships and health: The toxic effects of perceived social isolation. Social and Personality Psychology Compass, 8(2), 58–72. https://doi.org/10.1111/spc3.12087

Czaja, S. J., Charness, N., Fisk, A. D., Hertzog, C., Nair, S. N., Rogers, W. A., & Sharit, J. (2006). Factors predicting the use of technology: Findings from the Center for Research and Education on Aging and Technology Enhancement (CREATE). Psychology and Aging, 21(2), 333–352. https://doi.org/10.1037/0882-7974.21.2.333

Fogg, B. J. (2009). A behavior model for persuasive design. In Proceedings of the 4th International Conference on Persuasive Technology (pp. 1–7). https://doi.org/10.1145/1541948.1541999

Holt-Lunstad, J., Smith, T. B., Baker, M., Harris, T., & Stephenson, D. (2015). Loneliness and social isolation as risk factors for mortality: A meta-analytic review. Perspectives on Psychological Science, 10(2), 227–237. https://doi.org/10.1177/1745691614568352

Lindley, S. E., Harper, R., & Sellen, A. (2009). Desiring to be in touch in a changing communications landscape: Attitudes of older adults. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 1693–1702). https://doi.org/10.1145/1518701.1518962

Mitzner, T. L., Boron, J. B., Fausset, C. B., Adams, A. E., Charness, N., Czaja, S. J., Dijkstra, K., Fisk, A. D., Rogers, W. A., & Sharit, J. (2010). Older adults talk technology: Technology usage and attitudes. Computers in Human Behavior, 26(6), 1710–1721. https://doi.org/10.1016/j.chb.2010.06.020

O’Brien, H. L., & Toms, E. G. (2008). What is user engagement? A conceptual framework for defining user engagement with technology. Journal of the American Society for Information Science and Technology, 59(6), 938–955. https://doi.org/10.1002/asi.20801

Pearlin, L. I., Mullan, J. T., Semple, S. J., & Skaff, M. M. (1990). Caregiving and the stress process: An overview of concepts and their measures. The Gerontologist, 30(5), 583–594. https://doi.org/10.1093/geront/30.5.583