Optimizing the scientific study of suicide with open and transparent research practices

The State of Open Science Practices in Psychometric Studies of Suicide: A Systematic Review

The adoption of open science practices (OSPs) is crucial for promoting transparency and robustness in research. We conducted a systematic review to assess the frequency and trends of OSPs in psychometric studies focusing on measures of suicidal thoughts and behavior. We analyzed publications from two international databases, examining the use of OSPs such as open access publication, preregistration, provision of open materials, and data sharing. Our findings indicate a lack of adherence to OSPs in psychometric studies of suicide. The majority of manuscripts were published under restricted access, and preregistrations were not utilized. The provision of open materials and data was rare, with limited access to instruments and analysis scripts. Open access versions (preprints/postprints) were scarce. The low adoption of OSPs in psychometric studies of suicide calls for urgent action. Embracing a culture of open science will enhance transparency, reproducibility, and the impact of research in suicide prevention efforts.

A scoping review of counseling interventions for suicide prevention in Africa: Few studies address this life-saving aspect of mental health treatment

BACKGROUND

Nearly 800,000 people die by suicide each year, with 77 % occurring in low- and middle-income countries. Suicide is underestimated in many African settings due to challenges in data collection, stigma, and policies that promote silence; nonetheless, rates of suicide in Africa are consistently higher than global averages.

METHODS

We conducted a scoping review of counseling interventions assessing suicide outcomes among adults in Africa using MEDLINE, Embase, PsycINFO, African Index Medicus, CABI Global Health, and Proquest databases. Study screening and data extraction was informed by the JBI Manual for Evidence Synthesis.

RESULTS

Of 2438 abstracts reviewed, 33 studies met criteria for full-text review and 13 were included in the analysis. Interventions served several populations, including people living with HIV, out of school youth, university students, and women undergoing obstetric fistula repair. There was a near-equal split in individual versus group counseling modalities and the use of professional versus lay counselors. The majority of interventions had primary outcomes focused on other mental health or social variables with a secondary focus on suicide. Mechanisms of change for suicide prevention were poorly articulated.

LIMITATIONS

The review was limited to English-language studies conducted after 2001 and excluded qualitative studies and those with fewer than 10 participants.

CONCLUSIONS

There is a clear paucity of research in this area, particularly in the lack of randomized clinical trials and studies with suicide prevention as their primary outcome. Researchers should seek to develop or adapt evidence-based, culturally-resonant interventions to reduce the burden of suicide on the African continent.

Understanding Suicide over the Life Course Using Data Science Tools within a Triangulation Framework

Suicide and suicidal behaviors are important global health concerns. Preventing suicide requires a nuanced understanding of the nature of suicide risk, both acutely during periods of crisis and broader variation over the lifespan. However, current knowledge of the sources of variation in suicide risk is limited due to methodological and conceptual challenges. New methodological approaches are needed to close the gap between research and clinical practice. This review describes the life course framework as a conceptual model for organizing the scientific study of suicide risk across in four major domains: social relationships, health, housing, and employment. In addition, this review discusses the utility of data science tools as a means of identifying novel, modifiable risk factors for suicide, and triangulation as an overarching approach to ensuring rigor in suicide research as means of addressing existing knowledge gaps and strengthening future research.

Translating promise into practice: a review of machine learning in suicide research and prevention

In ever more pressured health-care systems, technological solutions offering scalability of care and better resource targeting are appealing. Research on machine learning as a technique for identifying individuals at risk of suicidal ideation, suicide attempts, and death has grown rapidly. This research often places great emphasis on the promise of machine learning for preventing suicide, but overlooks the practical, clinical implementation issues that might preclude delivering on such a promise. In this Review, we synthesise the broad empirical and review literature on electronic health record-based machine learning in suicide research, and focus on matters of crucial importance for implementation of machine learning in clinical practice. The challenge of preventing statistically rare outcomes is well known; progress requires tackling data quality, transparency, and ethical issues. In the future, machine learning models might be explored as methods to enable targeting of interventions to specific individuals depending upon their level of need-ie, for precision medicine. Primarily, however, the promise of machine learning for suicide prevention is limited by the scarcity of high-quality scalable interventions available to individuals identified by machine learning as being at risk of suicide.

The relationship between daily positive future thinking and past-week suicidal ideation in youth: An experience sampling study

Reduced positive future thinking has been associated with suicidal ideation and behavior in adults, and appears to be exacerbated by negative affect. Yet, this has received little attention in youth. Prior research has also focused on longer-term future thinking, e.g., months and years, and relied on lab-based assessments. Using the experience sampling method (ESM), we investigated whether short-term future thinking in daily life was associated with suicidal ideation in youth and explored the role of affect in the future thinking-suicidal ideation relationship. A community sample of N = 722 adolescent twins and their non-twin siblings completed ESM as part of the TwinssCan study (n = 55 with, and n = 667 without, past-week suicidal ideation). Participants completed self-report questionnaires, including on past-week suicidal ideation as part of the SCL-90. Subsequently, daily future thinking was assessed each morning for six days with ESM. To investigate the relationship between daily positive future thinking and past-week suicidal ideation, we estimated a mixed-effects linear regression model with a random intercept for participant, including age and sex as covariates. The relationship between daily positive future thinking, past-week suicidal ideation, and average positive and negative affect from the previous day was investigated by estimating two separate mixed-effects linear regression models (one for negative affect, one for positive affect), with a random intercept for participant, and random slopes for average positive and negative affect. Our results showed that participants reporting higher past-week suicidal ideation also reported significantly less daily positive future thinking during the ESM period, and this association remained significant when controlling for previous-day average positive and negative affect. Higher average positive affect from the previous day was significantly associated with higher positive future thinking. Although average negative affect from the previous day was associated with lower positive future thinking, this association was not statistically significant. Our findings indicate that short-term future thinking relates to suicidal ideation among a non-clinical sample of adolescents. Future research should investigate the directionality of the future thinking-suicidal ideation relationship, in order to investigate whether impaired future thinking may be an early warning signal for escalating suicidal ideation in youth.