Nathan Massicot

BACKGROUND Recent advances in digital health, including Artificial Intelligence-driven interventions, offer new opportunities for remote monitoring, patient-reported outcomes, and even direct treatment. Despite the growing adoption of digital health interventions (DHI), the concept of sustainability in this context remains under-theorized and fragmented in the literature. A clear understanding of sustainability is essential to ensure that DHIs can deliver enduring clinical, organizational, and societal value beyond initial implementation. Here, sustainability refers to ensuring that DHIs remain ethically, equitably, and environmentally responsible while delivering lasting health benefits and minimizing negative societal and environmental impacts. OBJECTIVE To study which frameworks have been applied in digital health for measuring or ensuring sustainability of DHI as well as to assess which dimensions of sustainability have been currently considered and to what extent. METHODS We conducted a scoping review as a concise synthesis of how existing models and frameworks address sustainability in the context of DHI. We examined peer-reviewed papers from 5 databases that described a sustainability framework in the context of digital health. The process followed PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guideline and PRISMA-S (Preferred Reporting Items for Systematic Reviews and Meta-Analyses literature search extension) checklist. Information on the frameworks was extracted including the considered sustainability factors. RESULTS Of 292 records, 53 studies were included and considered for data synthesis. Sustainability was rarely defined in these papers but invoked the concept only implicitly. Sustainability was basically used as a synonym for continued use rather than a multidimensional construct. Correspondingly, frameworks typically addressed usability and user acceptance. The social and technological dimensions of sustainability were addressed most frequently by the included frameworks, while ecological and economic dimensions remained rarely considered. In particular, UTAUT and TAM frameworks were extended by concepts of trust, risk, individual and health-related factors and contextual influences. CONCLUSIONS The current landscape of frameworks applied for sustainability in DHI do not represent the multidimensionality of the concept of sustainability as it would be necessary for ensuring a sustained use of DHI. Future work should therefore focus on strengthening the multidimensional view for addressing sustainability aspects throughout the entire DHI lifecycle.

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, thereby impacting adherence and efficacy. This study aimed to examine temporal patterns of engagement with 2 core components of the suicide prevention app SERO (Suicide Prevention: a Uniform Effort, Resource-Oriented; BFH, Lucerne Psychiatry), specifically the safety plan and the PRISM-S (Pictorial Representation of Illness and Self-Measure-Suicidality) self-assessment, using 3 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. We analyzed anonymized interaction logs from the SERO app collected over 3 years (November 2022 to December 2025). Engagement metrics included the 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 the hour of the day, day of the week, and season. One-way ANOVAs, post hoc tests, and Pearson correlations were used to examine patterns and associations between perceived suffering and sentiment. A total of 1076 users engaged with the safety planning functionality of the SERO app, generating 3502 entries, with coping strategies and warning signs showing the highest mean interactions and personal beliefs the lowest. Separately, 1212 app users accessed the PRISM-S self-assessment, producing 2329 entries (mean distance 12.91, 95% CI 12.39-13.42 cm), with most app users recording only 1 or 2 registrations. Safety planning engagement showed clear diurnal patterns, peaking in the afternoon (2 PM to 3 PM) and being lowest at night (midnight to 3 AM), whereas PRISM-S scores were stable across time. Sentiment analysis revealed predominantly negative affect (mean score of -0.41, SD 0.51, 95% CI -0.44 to -0.39), correlated with PRISM-S distance, and was most negative at night (specifically at 11 PM) and during the afternoon (2 PM to 5 PM). Seasonal effects were small but significant for PRISM-S, with the lowest perceived suffering in summer. Digital suicide prevention tools can support routine patterns of coping behavior, but periods of increased reported distress, particularly at night, may be underaddressed. Integrating automated sentiment analysis alongside self-assessments could potentially enable personalized, time-adaptive interventions that detect changes in emotional state and deliver timely, tailored support, thereby strengthening proactive engagement and resilience.

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.