User Preferences for Interaction Timing in Smartwatch Sleep Hygiene Games

Research Background and Issues

• Identified Problems or Challenges:
  Research has found that the design of current sleep hygiene games typically focuses on usage during the evening or before bedtime, lacking studies on the scheduling of game features and interactions across different time periods (e.g., daytime, early morning, or even during sleep). Additionally, it remains unclear how players' time preferences for game features influence their sleep behaviors. Studies indicate that although existing sleep games emphasize maintaining nighttime sleep habits, the optimal interaction times are still ambiguous.

• Significance:
  Good sleep hygiene is crucial for health, and the combination of smartwatches and gamified interventions offers a potential opportunity to help users develop healthy sleep habits. Understanding the optimal interaction times for different game features can enhance user engagement and the behavioral correction effectiveness of the games.

• Research Motivation:
  This study aims to explore users' time preferences for various features of smartwatch-driven sleep hygiene games and how to optimize these features based on time scheduling. By designing three sleep hygiene games (Hero's Sleep Journey, Sleepland, and Sleep Tamagochi), the research further investigates how to flexibly adjust interaction schedules to meet user preferences.

Solutions

• Proposed Methods or Solutions:
  The authors designed and tested three sleep hygiene games (Hero's Sleep Journey, Sleepland, and Sleep Tamagochi) and conducted workshops with users to understand their preferences for game features during different times of the day (morning, daytime, evening, before bedtime, and during sleep).

• Innovations:

  1. Conducting a fine-grained study on user interaction needs across different time periods.
  2. Incorporating gamification and passive game elements (e.g., idle game modes) to minimize disruptions to users' schedules.
  3. Including four functional categories—"Planning," "Behavior Triggers," "Reflection," and "Rewards"—to influence user behavior from a psychological perspective.

• Implementation Steps and Key Techniques:

  1. Game and Feature Design: Based on Cognitive Behavioral Therapy for Insomnia (CBT-I), three games and multiple game features were designed, with each feature categorized by "Planning," "Triggers," "Reflection," and "Rewards."
  2. User Workshops: User preferences for using these features at different times were collected through design workshops.
  3. Data Analysis: Heatmaps and affinity diagram analysis were used to identify user interaction preferences and underlying motivations at different times.
  4. User Experience Validation: Qualitative data analysis was used to gain deeper insights into the reasoning behind participants' preferences.

Research Findings

• Specific Findings:

  1. Morning and daytime are more suitable for features requiring high attention, while the evening is better for low-engagement features; during sleep, users generally prefer passive interactions.
  2. Users showed a clear post-behavior preference for reflection and reward features, while they preferred to engage with planning or trigger features before performing actions.
  3. Users' daily routines and energy levels significantly influenced their time preferences for different features.

• Advantages Over Existing Solutions:

  1. Emphasizing the detailed alignment between game feature design and users' physiological and psychological states throughout the day.
  2. Introducing passive interaction designs (e.g., idle games) for sleep-period interactions, reducing disruptions while enhancing the behavioral correction potential of the games.

• Experimental or Evaluation Results:

  1. Morning use of reflection reports or reward features was highly appreciated by users.
  2. Evening and pre-bedtime were suitable for behavior-triggering features, such as task reminders and schedule checks, effectively prompting user actions.
  3. Interactions during sleep (e.g., reward score calculations), though limited, showed significant potential, especially when combined with idle game mechanisms.

• Limitations and Future Directions:

  1. Homogeneous Participant Sample: Participants were primarily young university students with high technological proficiency and a gender imbalance; future studies should test a more diverse user group.
  2. Subjective Feedback in Experiments: This study relied solely on user preference reports, lacking behavioral data and effectiveness validation in real-world settings.
  3. Further Validation of Passive Interaction Mechanisms: Future research should explore how to effectively integrate passive game features into real-world applications for sleep behavior correction.

Conclusion

This study reveals user interaction preference patterns for smartwatch-driven sleep hygiene game features across different time periods, providing critical data to support the design of user-centered gamified intervention strategies. By optimizing interaction schedules and incorporating passive game elements, the research offers innovative directions for the development of sleep health technologies and provides specific design recommendations for better integration with users' daily routines.