Low-Burden Digital Phenotyping of Affective Risk: Positive Emoji Usage, Speech Rate, and Sleep Relate to College Student Mental Health

Mental health problems tied to negative affective experiences are common among emerging adults, yet conventional symptom questionnaires provide only distal snapshots of dynamic affective processes that unfold in daily life. Using the novel Meet Pandora smartphone application, we examined how everyday affective experiences and passive markers relate to depressive symptoms (PHQ), anxiety symptoms (GAD), and psychological flourishing in college students ( N  = 120; N _observations (PHQ/GAD) = 372, N _observations (flourishing) = 792). We tested three data channels (self-report, voice-derived features, and behavioral indicators) and disaggregated within-person fluctuations from between-person differences using multilevel models. Across outcomes, the proportion of positive emojis selected to reflect one’s affective state emerged as the most consistent signal. On days when participants used a higher-than-usual proportion of positive emojis, they reported lower depression and anxiety, and individuals with higher average positive emoji use reported lower symptoms and higher flourishing. Positive emoji use also moderated change over time in flourishing, such that flourishing increased across the study period only among participants with relatively high positive emoji proportions. In contrast, passive features showed more selective associations. Speech rate (words per minute) was linked to lower symptom burden and higher flourishing in some models, and longer average sleep duration was associated with lower anxiety and higher flourishing. Overall, results highlight the value of separating within- from between-person effects when linking digital markers to mental health and suggest that low-burden indicators of positive affect may be especially informative for scalable temporal monitoring of affective risk and wellbeing in young adults.