JMIR Publications

ABSTRACT

Background:

Temporal fluctuations in distress and suicidal ideation, across daily, weekly, and seasonal cycles, may influence the use and effectiveness of digital suicide prevention tools. Understanding patterns of app engagement, perceived suffering, and affective expression can inform the design of proactive, personalized digital interventions impacting on adherence and efficacy.

Objective:

To examine temporal patterns of engagement with two core components of the suicide prevention app SERO, specifically the safety plan and the PRISM™-S self-assessment, using three years of interaction log data, assessing variations across circadian, weekly, and seasonal cycles and evaluating the sentiment of free-text responses submitted immediately after PRISM™-S self-assessments.

Methods:

We analyzed anonymized interaction logs from the SERO app collected over three years (November 2022–December 2025). Engagement metrics included frequency of use of the safety planning functionality and PRISM™-S self-assessment entries. Free-text responses provided after PRISM™-S assessments were analyzed using automated sentiment classification. Temporal analyses examined variations by hour of day, day of week, and season. One-way ANOVAs, post hoc tests, and Pearson correlations were used to examine patterns and associations between perceived suffering and sentiment.

Results:

A total of 1,076 users engaged with the SERO app’s safety planning functionality, generating 3,502 entries, with Coping Strategies and Warning Signs showing the highest mean interactions and Personal Beliefs the lowest. Separately, 1,212 app users accessed the PRISM™-S self-assessment, producing 2,329 entries (mean distance 12.91 cm, 95% CI 12.39-13.42), with most app users recording only one or two registrations. Safety planning engagement showed clear diurnal patterns, peaking in the afternoon (14:00-15:00) and lowest at night (00:00-03:00), whereas PRISM™-S scores were stable across time. Sentiment analysis revealed predominantly negative affect (mean=-0.41), correlated with PRISM™-S distance, and most negative at night (specifically at 23:00, and 2:00-5:00). Seasonal effects were small but significant for PRISM™-S , with lowest perceived suffering in summer.

Conclusions:

Digital suicide prevention tools can support consistent, routine-like coping, but periods of increased vulnerability, particularly at night, may be underaddressed. Integrating automated sentiment analysis alongside self-assessments could enable personalized, time-adaptive interventions that detect changes in emotional state and deliver timely, tailored support, strengthening proactive engagement and resilience.