Individuals at high-risk of suicide vary substantially from one another. Over time, risk factors for suicide may change within the same individual. Despite these differences, most treatments for suicidal thoughts assume that the same intervention works equally well for all individuals at high-risk of suicide. Intensive longitudinal data combined with network science, integrated with coaching, could be used to personalize suicide prevention interventions to make them more effective and efficient. This K23 Career Development application involves refining and testing a novel personalized treatment for individuals at high-risk called PeRsonalizEd Clinical Intervention for Suicidal Events or PRECISE. PRECISE leverages idiographic statistical techniques adopted from network science applied to ecological momentary assessment data to inform the tailoring of Safety Planning and skills from Dialectical Behavior Therapy, two existing evidence-based treatments for suicide. In Aim 1, a user-centered design approach will be used to refine PRECISE. Following the refinement of the intervention, informed by data from a case series in Aim 1, the investigators will then conduct a randomized controlled trial comparing two different intensities of personalization. In the low-intensity arm, the 8-week treatment will be tailored based on an initial two-week burst of ecological momentary assessment and one idiographic model. In the high-intensity arm, participants complete eight weeks of ecological momentary assessment and idiographic models are generated between each session. Coaches use the idiographic models to identify an individuals' drivers of suicidal thoughts and conduct behavioral chain analyses to tailor specific skills to then teach, shape, and reinforce in their individual clients. Assessments are completed pre-treatment, 8-weeks post-enrollment, and 16-weeks enrollment. The investigators hypothesize that both arms will demonstrate clinically significant reductions in suicidal ideation, but the high-intensity arm will be superior to the low-intensity arm in reducing ideation. Furthermore, the investigators anticipate that increases in effective emotion regulation skills and reductions in negative affect will account for the decrease in suicidal ideation. As individuals learn more effective emotion regulation strategies, they will experience less distress and thereby lower levels of suicidal ideation. This project is responsive to Objective 3.2 of the NIMH Strategic Plan and is integrated with a mentored research training plan focused on 1) suicide specific rigorous clinical trials, 2) user centered design in digital health, and 3) applications of network science to intensive longitudinal data. The project and training goal will support the Candidate's overarching goal to become a clinician-scientist engaged in independent research on personalized, impactful, rapid acting suicide prevention interventions for at risk adults.

Inclusion Criteria:

• 18-65 years old
• Endorsement of active suicidal ideation on the Columbia Suicide Severity Rating Scale (>2 or past month thoughts of killing self or attempt in past month)
• English fluency
• Willingness to provide contact information for a key information to be contacted as part of our risk and safety plan.

Exclusion Criteria:

• Past year exposure to DBT
• Moderate/severe substance use disorder within the past thirty days
• Dementia, mild cognitive impairment and/or traumatic brain injury
• Lack of capacity to consent to research and/or under conservatorship.

The study data manager will ensure all data is uploaded to the NIMH National Data Archive in accordance with existing guidelines and upload timelines (also see Resource Sharing). Anonymous data may also be uploaded to public repositories (e.g., Open Science Framework, Github) to facilitate data sharing with other researchers and ensure accuracy in reporting results.

Data will be uploaded to the Open Science Framework by 03/31/2030 and will be shared indefinitely.