Predicting Suicidality (1 CE)
Number of Credits: 1
This course is for: Clinical Psychologists, Counselors, School Psychologists, and LMFTs
Course By: Michael Parent, PhD
Content By: Ribeiro, J. D., Huang, X., Fox, K. R., Walsh, C. G., & Linthicum, K. P. (2019). Predicting imminent suicidal thoughts and nonfatal attempts: The role of complexity. Clinical Psychological Science, 7, 941-957. doi: 10.1177/2167702619838464
Course Description: Suicide is a major public health issue. In the current study, researchers used machine learning to examine suicide risk over 28 days among a sample of over 1000 adults recruited from online forums for mental health support. The researchers found that suicidal ideation was relatively temporally stable, that baseline suicidal ideation was the best predictor of future suicidal ideation, and that suicidal thoughts and behaviors arise as a result of complex interactions of biopsychosocial factors. Future research may explore how to incorporate machine learning into clinical tools for care providers.
- Identify two problems with prior research on the prediction of risk for suicide
- Evaluate the results of the present study with regard to prediction of risk for suicide
- Identify the recommendations of the authors with regard to future research on prediction of suicide risk
- Read and understand Predicting imminent suicidal thoughts and nonfatal attempts: The role of complexity.
- Review the Course Description and Learning Objectives.
- Review the findings of this study with regard to predicting risk for suicidal thoughts and behaviors.
- Complete the post-test questions. Recall that answers should be based on the referenced article.
- Return to the referenced article for any missed questions and/or to understand prediction of suicidal thoughts and behaviors.
|Board Approvals||American Psychological Association (APA), NBCC, Florida Board - Social Work, MFT, Counseling, and Psychology, NYSED - Social Work, MFT and Counseling Only, American Academy of Health Care Providers in the Addictive Disorders|
|CE Format||Online, Text-Based|