Machine learning algorithms for suicide risk: a premature arms race?

Who bought a gun during the COVID-19 pandemic in the United States?: Associations with QAnon beliefs, right-wing political attitudes, intimate partner violence, antisocial behavior, suicidality, and mental health and substance use problems

There was a large spike in gun purchases and gun violence during the first year of the COVID-19 pandemic in the United States. We used an online U.S. national survey (N = 1036) to examine the characteristics of people who purchased a gun between March 2020 and October 2021 (n = 103) and compared them to non-gun owners (n = 763) and people who own a gun but did not purchase a gun during the COVID-19 pandemic (n = 170). Compared to non-gun owners, pandemic gun buyers were younger and more likely to be male, White race, and to affiliate with the Republican party. Compared to non-gun owners and pre-pandemic gun owners, pandemic gun buyers exhibited extreme elevations on a constellation of political (QAnon beliefs, pro-gun attitudes, Christian Nationalism, approval of former President Donald Trump, anti-vax beliefs, COVID-19 skepticism; mean Cohen's d = 1.15), behavioral (intimate partner violence, antisocial behavior; mean d = 1.38), mental health (suicidality, depression, anxiety, substance use; mean d = 1.21), and personality (desire for power, belief in a dangerous world, low agreeableness, low conscientiousness; mean d = 0.95) characteristics. In contrast, pre-pandemic gun owners only endorsed more pro-gun attitudes (d = 0.67), lower approval of President Joe Biden (d = -0.41) and were more likely to be male and affiliate with the Republican party relative to non-gun owners. Pandemic gun buyers represent an extreme group in terms of political and psychological characteristics including several risk-factors for violence and self-harm.

Suicide risk detection using artificial intelligence: the promise of creating a benchmark dataset for research on the detection of suicide risk

Suicide is a leading cause of death that demands cross-disciplinary research efforts to develop and deploy suicide risk screening tools. Such tools, partly informed by influential suicide theories, can help identify individuals at the greatest risk of suicide and should be able to predict the transition from suicidal thoughts to suicide attempts. Advances in artificial intelligence have revolutionized the development of suicide screening tools and suicide risk detection systems. Thus, various types of AI systems, including text-based systems, have been proposed to identify individuals at risk of suicide. Although these systems have shown acceptable performance, most of them have not incorporated suicide theories in their design. Furthermore, directly applying suicide theories may be difficult because of the diversity and complexity of these theories. To address these challenges, we propose an approach to develop speech- and language-based suicide risk detection systems. We highlight the promise of establishing a benchmark textual and vocal dataset using a standardized speech and language assessment procedure, and research designs that distinguish between the risk factors for suicide attempt above and beyond those for suicidal ideation alone. The benchmark dataset could be used to develop trustworthy machine learning or deep learning-based suicide risk detection systems, ultimately constructing a foundation for vocal and textual-based suicide risk detection systems.

Association of HLA class II alleles with suicidal behavior in a Transylvanian population

Background: Suicide is a complex phenomenon determined by the interaction of various risk factors. The Major Histocompatibility Complex is the most polymorphic gene cluster of the entire human genome, being linked to both the regulation of the immune system and various psychiatric diseases. The aim of this study was to identify HLA-DQB1 and DRB1 alleles and genotypes susceptible to influence suicidal behavior.

Methods: We explored the association of HLA-DQB1 alleles with the suicidal behavior on a sample of 427 individuals (including 110 suicide attempters) from Transylvania, as well as the association of HLA-DRB1 alleles with the suicidal behavior on a sample of 271 individuals (including 50 suicide attempters), using the single specific primer-PCR (SSP-PCR) technique.

Results: We found that the HLA-DQB1*02, *03 and *06 alleles, the DQB1*02/*03, DQB1*02/*06, DRB1*12/*15 and DRB1*07/*13 genotypes, as well as the DQB1*06~DRB1*07 and DQB1*02~DRB1*13 haplotypes, were more frequent in suicide attempters. In contrast, the HLA-DQB1*04 and DQB1*13 alleles, the DQB1*02/*05 and DQB1*03/*05 genotypes and the DQB1*03~DRB1*13 haplotype were less frequent in the case group.

Conclusion: HLA-DQB1*02, *03 and *06 alleles and the DQB1*02/*03 and *02/*06 genotypes are susceptible to favor a suicide behavior, while the HLA-DQB1*04 and *13 alleles and the DQB1*02/*05 and *03/*05 genotypes were protective against such behavior. A similar analysis regarding the HLA-DRB1 alleles detected a possible risk for suicidal behavior among individuals possessing either the DRB1*12/*15 or the DRB1*07/*13 genotypes. DQB1*06~DRB1*07 and DQB1*02~DRB1*13 haplotypes were found susceptible to favor a suicidal behavior, while DQB1*03~DRB1*13 exhibited a protective influence.

The Potential Impact of Adjunct Digital Tools and Technology to Help Distressed and Suicidal Men: An Integrative Review

Suicidal men feel the need to be self-reliant and that they cannot find another way out of relationship or socioeconomic issues. Suicide prevention is of crucial importance worldwide. The much higher rate of suicide in men engenders action. The prelude is a subjective experience that can be very isolating and severely distressing. Men may not realize a change in their thinking and behaviors, which makes it more difficult to seek and get help, thereby interrupting a "downward spiral". Stoicism often prevents men from admitting to their personal struggle. The lack of "quality" connections and "non-tailored" therapies has led to a high number of men "walking out" on traditional clinical approaches. But there are complicated relationships in motivations and formative behaviors of suicide with regards to emotional state, psychiatric disorders, interpersonal life events and suicidal behavior method selection. Middle-aged and older men have alternated as the most at-risk of suicide. There is no one solution that applies to all men, but digital tools may be of assistance (e.g., video conferences, social networks, telephone calls, and emails). Digital interventions require higher levels of effectiveness for distress and suicidality but self-guided approaches may be the most suitable for men especially where linked with an integrated online suicide prevention platform (e.g., quick response with online chats, phone calls, and emails). Furthermore, technology-enabled models of care offer promise to advance appropriate linking to mental health services through better and faster understanding of the specific needs of individuals (e.g., socio-cultural) and the type and level of suicidality experienced. Long-term evidence for suicidality and its evaluation may benefit from progressing human computer-interaction and providing impetus for an eminent integrated digital platform.