Suicide remains a global cause of mortality, presenting challenges in detection and prevention despite known warning signs. This work aimed to improve personal security management by leveraging machine learning advancements to identify suicidal ideation in written communications. Using a design science approach, six machine learning models based on the RoBERTa model were developed with different hyperparameter values. These models were trained on a well-balanced dataset comprising 1,114 instances of suicide letters and social media posts. The model achieving the highest accuracy (0.919) and F1 score (0.919) during training was evaluated on a dataset consisting of posts from the subreddits r/terraluna and r/Terra_Luna_crypto. These posts were published during a period when the cryptocurrency Terra Luna experienced a crash, leading to reported cases of alleged suicides. The fine-tuned model demonstrated a reasonably high accuracy (0.841) and weighted F1 score (0.913) when tested on this real-world dataset. Additionally, a smaller test was conducted on selected posts (34 posts) from this dataset containing mentions of specific words. The model achieved an accuracy of 0.852, and a weighted F1 score of 0.887 when classifying these posts. There exist a considerable potential for further research and development in this field. By expanding and improving the dataset used in this project, incorporating additional features and contextual information, the accuracy and practicality of the model in real-life situations can be greatly enhanced. The ultimate objective is to create a resilient system that genuinely assists in the prevention of suicide. The results of this work offer hope and optimism for a future where advanced technology, combined with human compassion, addresses one of the most pressing public health issues of our time.

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Suicide ideation and suicide impact a rapidly rising number of individuals each year, however our society has not envisioned a way to increase help-seeking behaviors to decrease these numbers. The literature discusses many barriers and hurdles to help-seeking, but the focus of SI within the context of help-seeking has not been studied in depth. The purpose of this qualitative study was to increase knowledge on the process through which individuals determine how and whom to ask for help when experiencing SI. Two sections of themes were found: things that encourage individuals to seek or continue to seek help, and things that discourage individuals from seeking help or encourage them to discontinue seeking help.

Suicide is the second leading cause of death worldwide for adolescents and emerging adults. Despite knowledge of distal risk factors for suicide (i.e., childhood maltreatment), there is a dearth of developmentally informed psychobiological theories of suicide that test potentially modifiable proximal risk factors. Utilizing a multi-method design, this study integrates cognitive and biological risk factors into a model of suicide risk following maltreatment. Undergraduates completed a screener assessing medical history, trait reward and threat sensitivities, history of suicidal thoughts and behaviors (STBs), and childhood maltreatment. Participants without a history of autoimmune disease completed a reward and threat-salient acute stress task with pre- and post-task blood draws to measure peripheral inflammatory biomarkers. Utilizing ecological momentary assessment, a subset of participants with a history of suicidal ideation completed daily measures (three per day) of STBs and state reward and threat sensitivities for two-weeks before completing follow-up measures of STBs. Mediation models found that inflammatory reactivity to acute stress did not explain the relationship between maltreatment and ideation across the two-week follow-up, but those participants with greater TNF-α reactivity to an acute stress task reported more severe ideation at the study visit. Moderated mediation models showed that the association between inflammatory reactivity and suicidality was not significantly amplified by reward or threat sensitivity. But, at trait and state levels, those with histories of maltreatment who were less sensitive to rewards and more aware of potential threats experienced the most severe ideation. This investigation aimed to understand the processes that immediately precede STBs to inform future prevention and intervention efforts. / Psychology

Nursing students' knowledge deficits, lack of experience, personal biases, and anxiety can ultimately create vulnerability, avoidance, and discriminatory behaviours toward people experiencing a mental health disruption. Nursing students express the need for more innovative educational opportunities to refine skills and enhance knowledge specific to suicidal identification and risk assessment. Virtual simulation has increased significantly within healthcare education to supplement, enhance, and support learning since the beginning of the COVID-19 pandemic. A virtual simulation education module focused on suicidal ideation and assessment of risk was designed and implemented to strengthen the learning, preparedness, and confidence of nursing students providing care in a mental health setting. The purpose of this study is to explore the perceived effectiveness of a suicidal ideation – assessment of risk virtual simulation module for undergraduate nursing students. The sample consisted of third-year nursing students enrolled in a mental health in nursing course from Ottawa, Ontario (N = 130). The research design is a mixed methods explanatory sequential design whereby the dominant data resides in the quantitative portion of the research study. The research study was divided into Phase I, referred to as the quantitative portion, and Phase II, referred to as the qualitative portion. In Phase I, the effectiveness of the virtual simulation focused on suicidal ideation and assessment of risk and were measured using the Simulation Effectiveness Tool-Modified (SET-M). The SET-M is a 19-item quantitative Likert scale tool used to measure the effectiveness of a simulation and its components after its completion. In Phase II, semi-structured interviews were the primary method for qualitative data collection to provide greater insight into Phase I of the research study. The quantitative findings demonstrated a simulation experience that was supportive of the nursing students’ learning, specifically in relation to nursing skills and assessments, problem- solving, clinical decision-making, and communication skills. The quantitative results demonstrated the importance of structure and guidance to achieve the desired outcomes of the simulation. Thematic analysis of the semi-structured interviews revealed that the virtual simulation on suicidal ideation and assessment of risk was associated with increases in learning, preparedness, confidence, knowledge, critical reflection, and a decrease in anxiety regarding suicide ideation and assessment of risk. The virtual simulation module on suicidal ideation and assessment of risk reinforces the need for various educational modalities to engage and increase the preparedness of nursing students entering clinical placement.

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