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BackgroundEvidence-based clinical intake tools (EBCITs) are structured assessment tools used to gather information about patients and help health care providers make informed decisions. The growing demand for personalized medicine, along with the big data revolution, has rendered EBCITs a promising solution. EBCITs have the potential to provide comprehensive and individualized assessments of symptoms, enabling accurate diagnosis, while contributing to the grounding of medical care. ObjectiveThis work aims to examine whether EBCITs cover data concerning disorders and symptoms to a similar extent as physicians, and thus can reliably address medical conditions in clinical settings. We also explore the potential of EBCITs to discover and ground the real prevalence of symptoms in different disorders thereby expanding medical knowledge and further supporting medical diagnoses made by physicians. MethodsBetween August 1, 2022, and January 15, 2023, patients who used the services of a digital health care (DH) provider in the United States were first assessed by the Kahun EBCIT. Kahun platform gathered and analyzed the information from the sessions. This study estimated the prevalence of patients’ symptoms in medical disorders using 2 data sets. The first data set analyzed symptom prevalence, as determined by Kahun’s knowledge engine. The second data set analyzed symptom prevalence, relying solely on data from the DH patients gathered by Kahun. The variance difference between these 2 prevalence data sets helped us assess Kahun’s ability to incorporate new data while integrating existing knowledge. To analyze the comprehensiveness of Kahun’s knowledge engine, we compared how well it covers weighted data for the symptoms and disorders found in the 2019 National Ambulatory Medical Care Survey (NMCAS). To assess Kahun’s diagnosis accuracy, physicians independently diagnosed 250 of Kahun-DH’s sessions. Their diagnoses were compared with Kahun’s diagnoses. ResultsIn this study, 2550 patients used Kahun to complete a full assessment. Kahun proposed 108,523 suggestions related to symptoms during the intake process. At the end of the intake process, 6496 conditions were presented to the caregiver. Kahun covered 94% (526,157,569/562,150,572) of the weighted symptoms and 91% (1,582,637,476/173,4783,244) of the weighted disorders in the 2019 NMCAS. In 90% (224/250) of the sessions, both physicians and Kahun suggested at least one identical disorder, with a 72% (367/507) total accuracy rate. Kahun’s engine yielded 519 prevalences while the Kahun-DH cohort yielded 599; 156 prevalences were unique to the latter and 443 prevalences were shared by both data sets. ConclusionsECBITs, such as Kahun, encompass extensive amounts of knowledge and could serve as a reliable database for inferring medical insights and diagnoses. Using this credible database, the potential prevalence of symptoms in different disorders was discovered or grounded. This highlights the ability of ECBITs to refine the understanding of relationships between disorders and symptoms, which further supports physicians in medical diagnosis.

Abstract With about 1200 individuals murdered, the massacre of October 7th was one of the deadliest terrorist attacks in modern history. The mental health consequences of terrorist attacks have been documented. However, little is known of the impact of the potentially morally injurious experience (PMIE) of betrayal––in which individuals feel betrayed by leaders they once trusted––on levels of psychological burden in the aftermath of such an attack. In this national prospective cohort study, we examined to what extent the PMIE of betrayal exacerbates the risk for posttraumatic stress disorder (PTSD) and depression in the wake of the October 7th terrorist attack. A representative sample of 710 Israeli adults (362 female, 51.1%), Jews (557, 79.9%) and Arabs (153, 20.1%), aged 18–85 (M = 41.01, SD = 13.72) completed validated self-report questionnaires assessing PTSD, depression, and PMIE-betrayal at two timepoints: T1, in August 2023 (6–7 weeks before the attack) and T2, in November 2023 (5–6 weeks after the attack). In two hierarchical logistic regressions, we found that experience of PMIE-betrayal predicted diagnoses of both PTSD (OR 1.92, 95% CI 1.26–2.92) and depression (OR 2.03, 95% CI 1.37–3.01) at T2, beyond probable PTSD/depression at T1 and demographic and trauma-related variables. Moreover, in two repeated-measure analyses predicting PTSD/depression symptoms, we found significant interactions between PTSD/depression trajectories and PMIE-betrayal, meaning that the increase of PTSD/depression symptoms was significantly higher among participants experiencing betrayal in the context of the attack. Our study highlights the impact of PMIE of betrayal on the dramatic increase in psychopathology following the October 7th terror attack on Israel’s population. Clinicians treating individuals coping with PTSD and depression should attend to their patients’ possible exposure to betrayal following the attack. Moreover, national leaders and policymakers should take significant steps to repair the public’s betrayal experience.

Suicide, one of the top causes of life lost in developed countries, is a major health problem, especially today, with the dramatic increase in mental health difficulties that was triggered during the Coronavirus pandemic (COVID-19). Opportunely, the recent emergence of internet-based crowdsourcing platforms (e.g., Amazon’s Mechanical Turk) may accelerate research on suicide prevention, however, this type of suicide research online involves a difficult ethical challenge: how to keep participants’ safe without compromising their privacy. To address this ethical challenge, a consortium of experts from multiple research institutions was assembled. The consortium discussed the advantages and disadvantages for participants involved in crowdsourcing-based studies that address suicide risk. This discussion resulted in a consensual step-by-step protocol for researchers who wish to conduct suicide research online, using the crowdsourcing platforms. This article provides a detailed description of the protocol and outlines key ethical arguments that led to its formulation. Unresolved issues are discussed as well and other researchers are encouraged to implement the proposed protocol and suggest further improvements. It is our hope that the current protocol will facilitate the research on large and diverse populations online and thus contribute to the global efforts to reduce suicide rates around the world.

Being a man has been recognized as a salient risk factor for suicide. Adopting uncompromised masculine perceptions (i.e., conforming to the masculine gender role norms) may restrict emotional expressiveness in men, which, in turn, may contribute to depression and somatization symptoms. We examined the moderating role of psychological flexibility and alexithymia in the relationship of masculinity with depression and somatization symptoms. A sample of 119 men completed measures of masculinity, alexithymia (difficulty identifying and delivering subjective feelings), psychological flexibility, depression, and somatization symptoms in a cross-sectional design study. Psychological flexibility levels moderated the relationship between masculinity and depression symptoms: Masculinity contributed as positively associated with depression symptoms when psychological flexibility was low, but no such association was found at moderate or high levels of psychological flexibility. As a cognitive factor promoting adaptive emotional regulation, psychological flexibility might reduce depression symptoms among inflexible masculine men. Clinical implications relate to diagnosing at-risk subgroups and their treatment.

Suicide prevention is a priority globally. Community nurses are on the frontline of healthcare, and thus well placed to identify those at risk of suicide and act to prevent it. However, they are often ill-equipped to do so. This study examines whether depression management training for nurses may also help them manage suicide-risk patients. Method: This quasi-experimental study used a questionnaire that included a randomly assigned textual case vignette, measures related to patient descriptions portrayed in the vignette, and demographic and clinical/training information. The participants were 139 Israeli nurses who were mostly Jewish, Israeli-born, and married women working as community nurses. Almost half had completed depression management training (DMT) in their routine work. Results: Nurses who completed depression management training were more likely than non-trainees to query the patient regarding mental status and suicide plans and were more likely to refer them to appropriate further treatment. The graduate nurses also reported higher self-competence and more positive attitudes regarding their ability to assess depression and suicide risk than nurses who had not received depression management training. Discussion: The results highlight the importance of depression management training, as suicide assessment and referral are among the major steps to suicide prevention.