Job-Related Problems Prior to Nurse Suicide, 2003-2017: A Mixed Methods Analysis Using Natural Language Processing and Thematic Analysis

Fostering Psychological Safety and Supporting Mental Health Among Cardiovascular Health Care Workers: A Science Advisory From the American Heart Association

The psychological safety of health care workers is an important but often overlooked aspect of the rising rates of burnout and workforce shortages. In addition, mental health conditions are prevalent among health care workers, but the associated stigma is a significant barrier to accessing adequate care. More efforts are therefore needed to foster health care work environments that are safe and supportive of self-care. The purpose of this brief document is to promote a culture of psychological safety in health care organizations. We review ways in which organizations can create a psychologically safe workplace, the benefits of a psychologically safe workplace, and strategies to promote mental health and reduce suicide risk.

Asking questions that are "close to the bone": integrating thematic analysis and natural language processing to explore the experiences of people with traumatic brain injuries engaging with patient-reported outcome measures

Introduction

Patient-reported outcomes measures (PROMs) are valuable tools for assessing health-related quality of life and treatment effectiveness in individuals with traumatic brain injuries (TBIs). Understanding the experiences of individuals with TBIs in completing PROMs is crucial for improving their utility and relevance in clinical practice.

Methods

Sixteen semi-structured interviews were conducted with a sample of individuals with TBIs. The interviews were transcribed verbatim and analysed using Thematic Analysis (TA) and Natural Language Processing (NLP) techniques to identify themes and emotional connotations related to the experiences of completing PROMs.

Results

The TA of the data revealed six key themes regarding the experiences of individuals with TBIs in completing PROMs. Participants expressed varying levels of understanding and engagement with PROMs, with factors such as cognitive impairments and communication difficulties influencing their experiences. Additionally, insightful suggestions emerged on the barriers to the completion of PROMs, the factors facilitating it, and the suggestions for improving their contents and delivery methods. The sentiment analyses performed using NLP techniques allowed for the retrieval of the general sentimental and emotional "tones" in the participants' narratives of their experiences with PROMs, which were mainly characterised by low positive sentiment connotations. Although mostly neutral, participants' narratives also revealed the presence of emotions such as fear and, to a lesser extent, anger. The combination of a semantic and sentiment analysis of the experiences of people with TBIs rendered valuable information on the views and emotional responses to different aspects of the PROMs.

Discussion

The findings highlighted the complexities involved in administering PROMs to individuals with TBIs and underscored the need for tailored approaches to accommodate their unique challenges. Integrating TA-based and NLP techniques can offer valuable insights into the experiences of individuals with TBIs and enhance the interpretation of qualitative data in this population.

The relationship between organizational support, professional quality of life, decent work, and professional well-being among nurses: a cross-sectional study

BACKGROUND

Nurses often face challenges such as inadequate welfare protection, injustice, and workplace adversity including violence, bullying, and sexual harassment. In this context, providing sufficient support to nurses is crucial for the promotion of their professional well-being. This study examines the direct and indirect effects of perceived organizational support on nurses' well-being, particularly highlighting the mediating roles of professional quality of life and the perception of decent work.

METHODS

A cross-sectional survey design was employed in this study. Convenience sampling was used to survey 792 nurses from five tertiary A-grade hospitals in Shanxi Province in January 2024. Data collection tools included a custom demographic survey, the Perceived Organizational Support Scale, Professional Quality of Life Scale, Decent Work Perception Scale, and Nurse Occupational Well-being Questionnaire. Descriptive statistics, correlation analysis, and mediation effect analyses were performed.

RESULTS

The findings demonstrate that perceived organizational support has a direct impact on nurses' occupational well-being (β = 0.323, p < 0.001). Additionally, professional quality of life and the perception of decent work play chain mediating roles between perceived organizational support and nurses' well-being (β = 0.019, BootLLCI = 0.010, BootULCI = 0.030).

CONCLUSIONS

This study highlighted the importance of organizational support in enhancing nurses' well-being. Professional quality of life and decent work were key mediators. Healthcare institutions should prioritize support measures to improve nurses' well-being. Future research should explore additional mediators and mechanisms to develop effective strategies for nursing policymakers and administrators.

Artificial Intelligence and the National Violent Death Reporting System: A Rapid Review

As the awareness on violent deaths from guns, drugs, and suicides emerges as a public health crisis in the United States, attempts to prevent injury and mortality through nursing research are critical. The National Violent Death Reporting System provides public health surveillance of US violent deaths; however, understanding the National Violent Death Reporting System's research utility is limited. The purpose of our rapid review of the 2019-2023 literature was to understand to what extent artificial intelligence methods are being used with the National Violent Death Reporting System. We identified 16 National Violent Death Reporting System artificial intelligence studies, with more than half published after 2020. The text-rich content of National Violent Death Reporting System enabled researchers to center their artificial intelligence approaches mostly on natural language processing (50%) or natural language processing and machine learning (37%). Significant heterogeneity in approaches, techniques, and processes was noted across the studies, with critical methods information often lacking. The aims and focus of National Violent Death Reporting System studies were homogeneous and mostly examined suicide among nurses and older adults. Our findings suggested that artificial intelligence is a promising approach to the National Violent Death Reporting System data with significant untapped potential in its use. Artificial intelligence may prove to be a powerful tool enabling nursing scholars and practitioners to reduce the number of preventable, violent deaths.

Self-Harm by Nurses and Midwives - A Study of Hospital Presentations

Background: Nursing professionals are an occupational group at increased risk of suicide, but little is known about self-harm in this population. Aims: To investigate the characteristics of nurses and midwives who present to hospital following self-harm. Method: We used data from the Oxford Monitoring System for Self-Harm to identify nurses and midwives who presented to the general hospital in Oxford during 2010-2020 following an episode of self-harm and received a psychosocial assessment. Results: During the eleven-year study period, 107 presentations of self-harm involving 81 nurses and midwives were identified. Self-poisoning was the most common self-harm method (71.6%), with antidepressants and paracetamol most frequently involved. Many had consumed alcohol before (43.8%) or during (25.3%) the self-harm act. Some individuals had high or very high suicide intent scores (22/70, 31.4%). Common problems preceding self-harm included problems with a partner (46.9%), psychiatric disorder (29.6%), and problems with employment (27.2%), family (24.7%), and alcohol (23.5%). A range of aftercare options were offered following presentation. Limitations: This study was limited to data from a single hospital. Conclusion: Prevention and management of self-harm within this occupational group requires preventative strategies and availability of interventions addressing the range of factors that may contribute to self-harm, especially relationship problems, psychiatric disorders, employment problems, and alcohol misuse.

Predictors of Substance Use Risk in Nurse Anesthetists

BACKGROUND

Certified registered nurse anesthetists (CRNAs) are exposed daily to highly addictive substances and stressful work environments, placing them at risk for substance use disorders (SUDs). Previous research, which is scarce, indicated that drugs of choice were opioids and propofol. Therefore, the purpose of this study was to investigate predictors of SUD risk using the World Health Organization Alcohol, Smoking and Substance Involvement Screening Test.

METHOD

From June to July 2020, an online survey was sent via the American Association of Nurse Anesthesiology Research Survey Service to 3,000 CRNAs with a response of approximately 225 members.

RESULTS

CRNAs were found to be at a moderate risk for SUDs in the following categories: 10.27% for tobacco, 23.56% for alcohol, and 6.28% for cannabis. Regression analysis by substance category includes robust, differing models in this homogeneous sample. Predictors for all three models include a collection of demographic variables, religiosity, anxiety, difficulties due to anxiety, depression, substance use history, contact with the American Association of Nurse Anesthesiology Peer Assistance Program, and organizational support.

CONCLUSION

Over 10% of CRNAs are at risk for developing tobacco use disorder, and almost one quarter of those surveyed are at a moderate risk for developing alcohol use disorder. These data are of concern and may indicate a shift of preferred substances used by CRNAs from controlled substances to alcohol.

Understanding nurse suicide using an ideation-to-action framework: An integrative review

OBJECTIVE

The purpose of this integrative review was to explore, appraise and synthesize the current literature on correlates of suicide risk in nurses.

DESIGN

Integrative literature review.

DATA SOURCES

Cumulative Index to Nursing and Allied Health Literature (CINAHL), Joanna Briggs Institute, PubMed, PsycInfo and Scopus electronic databases were searched for abstracts published between 2005 and 2020. Reference lists were hand searched.

REVIEW METHODS

The integrative review was based on the Whittemore and Knafl review methodology. Primary qualitative and quantitative studies about suicidal behaviour in nurses published in peer-reviewed journals were included. The methodological quality of included articles was assessed using the Mixed Methods Assessment Tool.

RESULTS

Separate correlates of risk and protective factors were identified for suicidal ideation, suicide attempt and death by suicide in nurses.

IMPLICATIONS

Due to a number of factors at the individual, interpersonal and work levels, nurses are uniquely positioned to be at risk of dying by suicide. The ideation-to-action framework provides a theoretical guide to understand the interplay between correlates and the effect it has on increasing a nurses' capability for suicide.

CONCLUSIONS

This review integrates the empirical literature to elucidate the concept of suicidal behaviour as it applies to nurses.

Characterizing Female Firearm Suicide Circumstances: A Natural Language Processing and Machine Learning Approach

INTRODUCTION

Since 2005, female firearm suicide rates increased by 34%, outpacing the rise in male firearm suicide rates over the same period. The objective of this study was to develop and evaluate a natural language processing pipeline to identify a select set of common and important circumstances preceding female firearm suicide from coroner/medical examiner and law enforcement narratives.

METHODS

Unstructured information from coroner/medical examiner and law enforcement narratives were manually coded for 1,462 randomly selected cases from the National Violent Death Reporting System. Decedents were included from 40 states and Puerto Rico from 2014 to 2018. Naive Bayes, Random Forest, Support Vector Machine, and Gradient Boosting classifier models were tuned using 5-fold cross-validation. Model performance was assessed using sensitivity, specificity, positive predictive value, F1, and other metrics. Analyses were conducted from February to November 2022.

RESULTS

The natural language processing pipeline performed well in identifying recent interpersonal disputes, problems with intimate partners, acute/chronic pain, and intimate partners and immediate family at the scene. For example, the Support Vector Machine model had a mean of 98.1% specificity and 90.5% positive predictive value in classifying a recent interpersonal dispute before suicide. The Gradient Boosting model had a mean of 98.7% specificity and 93.2% positive predictive value in classifying a recent interpersonal dispute before suicide.

CONCLUSIONS

This study developed a natural language processing pipeline to classify 5 female firearm suicide antecedents using narrative reports from the National Violent Death Reporting System, which may improve the examination of these circumstances. Practitioners and researchers should weigh the efficiency of natural language processing pipeline development against conventional text mining and manual review.

Interdisciplinary Approach to Identify and Characterize COVID-19 Misinformation on Twitter: Mixed Methods Study

BACKGROUND

Studying COVID-19 misinformation on Twitter presents methodological challenges. A computational approach can analyze large data sets but is limited when interpreting context. A qualitative approach allows deeper analysis of content, but is labor-intensive and feasible only for smaller data sets.

OBJECTIVE

Identify and characterize tweets containing COVID-19 misinformation.

METHODS

Tweets geolocated to the Philippines (1 January to 21 March 2020) containing the words coronavirus, covid, and ncov, were mined using GetOldTweets3 Python library. This primary corpus (N=12,631) was subjected to biterm topic modeling (BTM). Key informant interviews (KII) were conducted to elicit examples of COVID-19 misinformation and determine keywords. Using nVivo and a combination of word frequency and text search using KII keywords, subcorpus A (n=5,881) was constituted and manually coded to identify misinformation. Constant comparative, iterative, and consensual analysis were used to further characterize these tweets. Tweets containing KII keywords were extracted from the primary corpus and processed to constitute subcorpus B (n=4,634), of which 506 tweets were manually labeled as misinformation. This training set was subjected to natural language processing to identify tweets with misinformation in the primary corpus. These tweets were further manually coded to confirm labeling.

RESULTS

BTM of the primary corpus revealed the following topics: uncertainty, lawmakers' response, safety measures, testing, loved ones, health standards, panic buying, tragedies other than COVID-19, economy, COVID-19 statistics, precautions, health measures, international issues, adherence to guidelines, and front-liners. These were categorized into four major topics: nature of COVID, contexts and consequences, people and agents of COVID, and COVID prevention and management. Manual coding of subcorpus A identified 398 tweets with misinformation in these formats: misleading content (n=179), satire and/or parody (n=77), false connection (n=53), conspiracy (n=47) and false context (n=42). Discursive strategies identified were humor (n=109), fear mongering (n=67), anger and disgust (n=59), political commentary (n=59), performing credibility (n=45), over-positivity (n=32) and marketing (n=27) . NLP identified 165 tweets with misinformation. However, manual review of these tweets showed that 115 tweets (69.7%) did not contain misinformation. .

CONCLUSIONS

An interdisciplinary approach was used to identify tweets with COVID-19 misinformation. NLP mislabeled tweets, likely due to tweets written in Filipino or a combination of Filipino and English languages. Identifying formats and discursive strategies of tweets with misinformation required iterative, manual, and emergent coding by human coders with experiential and cultural knowledge of Twitter. An interdisciplinary team composed of experts in health, health informatics, social science, and computer science, combined computational and qualitative methods to gain a better understanding of COVID-19 misinformation on Twitter. .

CLINICALTRIAL

Research utility and limitations of textual data in the National Violent Death Reporting System: a scoping review and recommendations

BACKGROUND

Many studies of injury deaths rely on mortality data that contain limited contextual information about decedents. The National Violent Death Reporting System (NVDRS) is unique among such data systems in that each observation includes both quantitative variables and qualitative texts (called "narratives") abstracted from original source documents. These narratives provide rich data regarding salient circumstances that can be used to inform prevention efforts. This review provides a comprehensive summary of peer-reviewed research using NVDRS narratives over the past 20 years, including the limitations of these texts and provides recommendations on utilizing and improving narrative quality for researchers and practitioners.

MAIN BODY

Studies that used narratives to examine deaths related to suicide, homicide, undetermined intent, accidental firearm, or legal intervention were identified by a title/abstract screening, followed by a full-text review. The search was conducted on English-language, peer-reviewed literature and government reports published from 2002 to 2022 in PubMed, PsycInfo, Scopus, and Google Scholar. Abstracted elements focused on the methodologies used to analyze the narratives, including approaches to explore potential biases in these texts. Articles were abstracted independently by two reviewers, with disagreements resolved through consensus discussion. During the 20-year period, 111 articles used narratives. Two-thirds studied suicide (n = 48, 43%) and homicides (n = 25, 23%). Most studies analyzed the narratives using manual review (n = 81, 73%) and keyword searches (n = 9, 8%), with only 6 (5%) using machine learning tools. Narratives were mainly used for case finding (n = 49, 44%) and characterization of circumstances around deaths (n = 38, 34%). Common challenges included variability in the narratives and lack of relevant circumstantial details for case characterization.

CONCLUSION

Although the use of narratives has increased over time, these efforts would be enhanced by detailed abstraction of circumstances with greater salience to injury research and prevention. Moreover, researchers and practitioners would benefit from guidance on integrating narratives with quantitative variables and standardized approaches to address variability in the completeness and length of narratives. Such efforts will increase the reliability of findings and set the stage for more widespread applications of data science methods to these texts.

Reflexive thematic analysis of job-related problems associated with pharmacist suicide, 2003-2019

BACKGROUND

Few qualitative studies have focused on suicide and specific job-related problems associated with suicide in pharmacists. Greater knowledge of specific work-related stressors amongst pharmacists could inform suicide prevention strategies.

OBJECTIVE

To identify job-related stressors associated with pharmacist suicides and compare stressors to those previously reported in physicians and nurses.

METHODS

Free-text law enforcement and medical examiner data for pharmacist suicides were extracted from the National Violent Death Registry (NVDRS) for 2003-2019. Reflexive thematic analysis was deployed via a deductive approach utilizing codes and themes found in previous research on nurse and physician suicides. New codes were also identified through inductive coding.

RESULTS

A total of 291,872 suicides occurred between 2003 and 2019, of which 392 were pharmacist deaths. Of these, 62 pharmacist suicides were coded with job-related problems. Almost all deductive themes/codes extracted from nurses and physicians were present in pharmacists. Common codes found in the pharmacist dataset that were also found previously in physicians and nurses were: history of mental health, substance use disorder, hopelessness impending or proceeding job loss, and access to lethal weapons and/or drugs. Novel codes were added through inductive content analysis. Codes novel to pharmacists were: verbalized suicidal ideation (SI) or intent, diversion for the purpose of suicide, and the fear of job loss. Disciplinary action at the institutional level was associated with the fear of job loss and cited as the event triggering suicide completion.

CONCLUSION

Pharmacists have similar job-related stressors associated with suicide as physicians and nurses. Evaluating the process of disciplinary action is warranted. Future research is indicated to evaluate causal relationship between work-related stressors and mental health outcomes leading to suicide in pharmacists.

American Academy of Nursing Expert Panel Consensus Statement on leveraging equity in policy to improve recognition and treatment of mental health, substance use disorders, and nurse suicide

Rates of nurse mental health and substance use disorders are high. Heightened by the COVID-19 pandemic, nurses are challenged to care for patients in ways that often jeopardize their own health and increase risks for their families. These trends exacerbate the epidemic of suicide in nursing underscored by several professional organization clarion calls to nurses' risk. Principles of health equity and trauma-informed care dictate urgent action. The purpose of this paper is to establish consensus among clinical and policy leaders from Expert Panels of the American Academy of Nursing about actions to address risks to mental health and factors contributing to nurse suicide. Recommendations for mitigating barriers drew from the CDC's 2022 Suicide Prevention Resource for Action strategies to guide the nursing community to inform policy, education, research, and clinical practice with the goals of greater health promotion, risk reduction, and sustainment of nurses' health and well-being are provided.

Suicide, self-harm, and suicide ideation in nurses and midwives: A systematic review of prevalence, contributory factors, and interventions

BACKGROUND

Nurses have been identified as an occupational group at increased risk of suicide. This systematic review examines the prevalence of, and factors influencing, suicide and related behaviours among nurses and midwives (PROSPERO pre-registration CRD42021270297).

METHODS

MEDLINE, PsycINFO, and CINAHL were searched. Articles published from 1996 onwards exploring suicidal thoughts and behaviours among nurses and midwives were included. Quality of included studies was assessed. Articles were subjected to narrative synthesis informed by suicide data examined, study design, and quality. PRISMA guidelines were followed.

RESULTS

A total of 100 studies were eligible for inclusion in the review. Articles examining suicide exclusively among midwives were absent from the literature. Several studies confirmed that nursing professionals, especially female, are at increased risk of suicide, particularly by self-poisoning. Factors contributing to risk include psychiatric disorders, alcohol and substance misuse, physical health problems, and occupational and interpersonal difficulties. In studies of non-fatal suicidal behaviours, including during the COVID-19 pandemic, psychiatric, psychological, physical and occupational factors were contributory. There has been little investigation of interventions for prevention of suicide in nurses.

LIMITATIONS

Only articles published in English language were reviewed.

CONCLUSIONS

The findings highlight the risk of suicide in nurses. They also show a combination of factors contribute to suicide and non-fatal suicidal behaviour in nurses, with psychiatric, psychological, physical health, occupational and substance misuse (especially alcohol) problems being particularly important. The limited evidence regarding prevention measures indicates a major need to develop primary and secondary interventions for this at-risk occupational group, for example, education regarding enhancing wellbeing and safe alcohol use, alongside accessible psychological support.

Psychosocial Factors Associated With Alcohol Use Among Nurses: An Integrative Review

Background

Understanding alcohol use among nurses may inform interventions related to the coping mechanisms nurses use for workplace stress and trauma. Alcohol use can be caused by a variety of factors and has serious implications on a nurse's personal health and professional practice. Understanding psychosocial factors and preventive measures may assist in the development of interventions to improve coping mechanisms and reduce the incidence of alcohol misuse.

Purpose

To review the psychosocial factors and preventive measures associated with alcohol use among nurses.

Methods

For this integrative review, systematic searches were conducted in CINAHL, PubMed, PsychNet, and ProQuest Central. Included studies were peer-reviewed and addressed alcohol use among nurses in the United States. Articles were appraised using methods-specific tools indicated by the Whittemore and Knafl framework. Data were extracted and themes identified using constant comparison.

Results

Of 6,214 nonduplicate articles screened, 78 were selected for full-text review and 13 were included after application of inclusion criteria. Synthesis resulted in four themes: (1) occupational stress and trauma, (2) workplace characteristics, (3) mental health implications, and (4) protective factors. The data show that workplace stress and trauma contribute to alcohol use among nurses. Night shifts, rotating shifts, and shift length are factors related to alcohol use, as are mental health problems such as anxiety, depression, trauma, and suicide. Protective factors that reduce alcohol use among nurses include faith, resilience, and perceived organizational support.

Conclusion

Alcohol use among nurses presents challenges for the nursing profession and regulatory bodies with specific and interrelated phenomena related to the role and identity of nurses. A better understanding of these factors through research will facilitate a healthier nursing workforce that is better prepared to take on the rewards and challenges of a nursing career.

Employee Assistance Programs: A Misunderstood and Underused Resource for Nurses

As the focus on nurse well-being evolves, an important consideration is the role of an organization's employee assistance program (EAP). Employee assistance programs are historically underused by employees and are not understood in terms of the depth of services and partnerships they can offer. Nurse executives have a key role in maximizing EAP services and utilization as ones who refer staff and who can influence and decide on an EAP partner and related programs and services. This column discusses how EAPs can be a significant tool for nurse leaders in supporting employees.

Entangled: A mixed method analysis of nurses with mental health problems who die by suicide

Nurses die by suicide at a higher rate than the general population. Previous studies have observed mental health problems, including substance use, as a prominent antecedent before death. The purpose of this study was to explore the characteristics of nurses who died by suicide documented in the death investigation narratives from the National Violent Death Reporting System from 2003 to 2017 using thematic analysis and natural language processing. One thousand three hundred and fifty-eight subjects met these inclusion criteria. Narratives from 601 subjects were thematically analyzed and 2544 individual narratives were analyzed using natural language processing. The analyses revealed five themes: "mental health treatment," "poor general health and chronic pain," "substance use," "worsening mental health after bereavement," and "repeating a family member's suicide." Mental health/substance use, chronic illness, and chronic pain were seen to coexist in a complex, interdependent manner that appeared to be entangled in the nurses' narratives before death. These findings echo the need for reducing the stigmatization of mental health problems in nursing and removing barriers to help-seeking behaviors as early preventative interventions. Future research is needed to determine if a comprehensive healthcare integration approach to address these entangled problems would reduce suicide vulnerability in nurses and improve their quality of life.

A Critical Review of Text Mining Applications for Suicide Research

Purpose of Review

Applying text mining to suicide research holds a great deal of promise. In this manuscript, literature from 2019 to 2021 is critically reviewed for text mining projects that use electronic health records, social media data, and death records.

Recent Findings

Text mining has helped identify risk factors for suicide in general and specific populations (e.g., older adults), has been combined with structured variables in EHRs to predict suicide risk, and has been used to track trends in social media suicidal discourse following population level events (e.g., COVID-19, celebrity suicides).

Summary

Future research should utilize text mining along with data linkage methods to capture more complete information on risk factors and outcomes across data sources (e.g., combining death records and EHRs), evaluate effectiveness of NLP-based intervention programs that use suicide risk prediction, establish standards for reporting accuracy of text mining programs to enable comparison across studies, and incorporate implementation science to understand feasibility, acceptability, and technical considerations.

The Nurse Leader's Role in Nurse Substance Use, Mental Health, and Suicide in a Peripandemic World

Nurses are known to be at an increased risk of death by suicide, and recent studies have found links between nurse suicide, substance use, mental health issues, and job problems. Because of stigma, inaccessibility of resources, and regulatory and legal issues, nurses are unlikely to seek help unless a crisis forces them into treatment. The purpose of this article is to review the current understanding of nurse suicide, the psychological impact of the novel coronavirus (COVID-19) pandemic, the strategic planning approach to identify the needs of nurses, and promising interventions and practices. Evidence-based strategies to intervene at the personal, institutional, and regulatory levels should be employed to reduce nurse suicide by focusing not only on suicide but also on treatment of substance and mental health issues, as well as a renewed focus on disciplinary procedures that may place nurses in immediate danger of death by suicide. Nurse leaders have a moral obligation to provide proactive, meaningful interventions to reduce the risk of death by suicide among nurses.

[How Should We Approach Nurse Suicide in Korea: With the Aspect of Prevention-Intervention-Postvention Management]

Recently, nurse suicide has emerged as one of the major issues. We tried to review the status of nurse suicide and its management in Korea through inspecting related web sites, news articles, and research. However, there were no sufficient reports or statistics along with the research throughout the country. Moreover, there were no organized nurse suicide management systems or programs including suicide prevention, suicide intervention, suicide postvention management. In other countries, there were various trials and successful experiences about nurse suicide programs, and those have been managed in organized and integrated ways. It gave us a lot of implications. To effectively prevent and manage the nurse suicide in Korea, nursing workforce, nursing managers, and nursing researchers should be concerned about nurse suicide. Furthermore, discussions and the research must be made actively. Based on such efforts, appropriate programs, organized manage systems, and policies must be devised at institution and national level.