Beyond Risk Prediction: Considering Upstream Universal Suicide Prevention to Decrease Risk and Increase Resilience
Year: 2026
Type: article
Abstract: Despite decades of research, suicide risk factors predict outcomes at chance levels, and there is a dearth of protective factor and resilience research, which limits the utility of risk-based approaches. Further, suicide prevention interventions primarily consist of individual psychotherapies and treating individuals after suicide-related outcomes occur. Unfortunately, there is a lack of upstream suicide prevention interventions targeting known suicide risk factors and aiming to increase well-being and resilience in the U.S. Thus, we discuss these problems in the field and the U.S. health care system and provide a possible solution. We propose using low-intensity, universal, and upstream prevention interventions, such as Stress Control. Stress Control is a classroom-style, Cognitive Behavior Therapy-based program shown to reduce "risk," stress, anxiety, and depression and boost well-being and resilience as part of a stepped-care model. Although Stress Control's suicide prevention effectiveness has not yet been directly assessed, we discuss how it could be a promising suicide prevention strategy with additional testing. A proposed mechanism for this reduction is building resilience to common risk factors and suicide ideation via evidence-based coping skills, thereby decreasing future suicide risk. We review current limitations and discuss how upstream, scalable, universal prevention interventions can help improve psychological resilience and reduce suicidal thoughts and behaviors, lowering the U.S. suicide rate. Implications and recommendations are discussed.
Source: Behavioral Sciences
DOI: 10.3390/bs16020243
Authors: Sarah Sparks, Cole Marvin, Regan Sweeney, Destiny Rojas, Sean M. Mitchell
Institution: Texas Tech University
Language: English
Subfield: Clinical Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,654
Awards: G2585272030, G8425973706
OpenAlex ID: W7128378700
