Personalizing Mobile Apps for Health Behavioral Change According to Personality: Cross-Sectional Validation of a...

Area of Science:

• Digital Health
• Human-Computer Interaction
• Behavioral Science

Background:

• Mobile health (mHealth) apps utilize features like tracking and reminders to promote healthy lifestyles.
• Personalized messaging in mHealth apps enhances user engagement and retention.
• The Big Five personality traits are linked to preferences for specific mHealth app mechanisms, informing personalization strategies.

Purpose of the Study:

• To validate a proposed preference matrix for mHealth apps.
• To examine if literature-based associations between Big Five personality traits and app mechanisms align with user preferences in an experimental setting.

Main Methods:

• A cross-sectional online survey collected demographic data, mHealth usage, and Big Five personality traits.
• Participants selected preferred mechanisms from mockups illustrating 15 features.
• Logistic and ordinal logistic regression analyses, adjusted with Bonferroni correction, assessed associations between personality traits and mechanism preferences.

Main Results:

• Conscientiousness significantly predicted preferences for collection (OR 1.87), competition (OR 3.22), and rewards (OR 2.36) mechanisms.
• Agreeableness (OR 1.93) and neuroticism (OR 1.97) also predicted preferences for competition and rewards, respectively.
• Self-monitoring, progression, challenge, and quest mechanisms were widely preferred across participants, irrespective of personality.

Conclusions:

• The study partially validates the mHealth app preference matrix.
• Conscientiousness is a key predictor for engagement with gamified mHealth features.
• A combination of universal and personality-specific mechanisms is valuable for optimizing mHealth app design.