Abstract

Suicide continues to be a critical concern for society as one of the leading causes of death in the United States, increasing from 10.4 to 13.5 per 100,000 from 2000 to 2016. This risk is further increased up to 8 times for individuals with Autism Spectrum Disorder. Suicidal thoughts and behaviors have been difficult to predict on a moment-by-moment basis, in part due to technological challenges. Suicidal ideation has been identified as an important indicator of suicidal behavior and an important measurement for predicting suicide in both neurotypical individuals and individuals with autism spectrum disorder. In particular, sleep disturbances are one risk factor for suicidal behavior. Important aims of this study include identifying personalized predictors of leading up to suicidal ideation, including how sleep activity patterns affect suicidal ideation, and how these risk factors differ between those with autism spectrum, socially anxious groups. This will give further insight into predictors of suicidal ideation, providing a better understanding for predicting changes in suicidal ideation, with aims to bring more clarity in this at-risk population and improve treatment options. To observe predictors of both long-term and short-term changes in suicidal ideation, I will analyze longitudinal data. The data includes daily phone questionnaires and actigraphy data tracking using GENEActiv wearable devices that includes sleep from individuals with autism spectrum and social anxiety with a history of suicidal ideation, and neurotypical individuals who are tracked over 24-36 weeks. Results of analysis indicate that sleep duration is not a significant predictor of suicidal ideation intensity, and that there is no difference between the autism spectrum and social anxiety groups in the predictive ability of sleep. Limitations of this study include local convenience sampling which includes a large majority of white participants, part of the study and data collected occurring during the COVID-19 pandemic, and potential response bias for such a sensitive topic. This study shows overall that there is a working model for this type of analysis, however many more features of sleep including movement during sleep and waking during sleep need to be analyzed to see if there is any predictive power in information from actigraphy, which would be a low invasive method for detecting increases in suicidal ideation risk.

Degree

MS

College and Department

Family, Home, and Social Sciences; Psychology

Rights

https://lib.byu.edu/about/copyright/

Date Submitted

2023-08-22

Document Type

Thesis

Handle

http://hdl.lib.byu.edu/1877/etd12883

Keywords

Suicide, Autism Spectrum Disorder, Social Anxiety, Ecological Momentary Assessment, Actigraphy

Language

english

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