Trajectories of suicide risk in virtual therapy for college students: A retrospective study
Year: 2026
Type: article
Study design: Observational Study
Abstract: Objective: This study examined time-to-initial-remission of suicide risk among college students engaging in virtual psychotherapy. Using routine measurement-based care data, survival analytic methods characterized remission across therapy visits and explored whether remission timing differed by gender or race/ethnicity. Methods: Data were drawn from a retrospective cohort of U.S. college students using a digital mental health platform. Self-harm and suicidal ideation were screened at each visit using item 9 of the Patient Health Questionnaire-9 (PHQ-9). Positive screens were followed by administration of the Columbia-Suicide Severity Rating Scale (C-SSRS) to assess suicide risk comprehensively. Time-to-initial remission was modeled separately for PHQ-9 Item 9 and the C-SSRS, with remission defined as the first transition from endorsement to non-endorsement for each measure. Kaplan-Meier survival curves estimated time-to-initial-remission by visit number, and Cox proportional hazards models examined demographic differences. Results: A majority of students achieved initial remission in self-harm and suicidal ideation (77.2%) and suicide risk (83.9%). Across both measures, remission most frequently occurred early in care, with 50% of students transitioning to non-endorsement after the first visit. Survival curves showed a steep initial decline followed by a gradual tail, indicating many students experienced rapid resolution of suicide risk while a subset continued to endorse ideation. Exploratory demographic analyses revealed similar remission trajectories across gender and race/ethnicity, although it took non-binary students an average of 0.79 more sessions to reach initial remission of suicide risk. Conclusions: Modeling initial remission as a time-to-event outcome provides a more granular characterization of suicide risk resolution than traditional pre-post approaches and supports the value of routinely collected longitudinal data for informing monitoring expectations and clinical decision-making.
Source: Digital Health
Institution: American University
Language: English
Subfield: Clinical Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,000
OpenAlex ID: W7213543370