Not All Nudges Land: Behavioral Controllability and Elaboration Quality in AI-Supported Journaling
AI journaling tools can tailor prompts to a person's own sensed behavior, but it is unclear which behaviors respond to them. We analyzed 369 journal entries from an eight-week passive sensing study. An LLM labeled each entry as expressing an intention to change a behavior or not, and we measured follow-through against 26 sensor features with a 3-day before/after comparison. Responsiveness depended most on whether a behavior involves other people. Behaviors that depend on others improved in only 15 to 22% of cases, while behaviors a person can act on alone improved more often, up to 50 to 63%, though unevenly. How users wrote mattered less. No single text feature separated improved from un...
| Authors | Nadia Mehjabin, Henry Kautz, Subigya Nepal |
|---|---|
| Primary category | cs.HC |
| Published | 12 August 2026 |
| Last updated at source | 12 August 2026 |
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