Leveraging data science to enhance suicide prevention research: a literature review

2021 ◽  
pp. injuryprev-2021-044322
Author(s):  
Avital Rachelle Wulz ◽  
Royal Law ◽  
Jing Wang ◽  
Amy Funk Wolkin
Keyword(s):  
Risk Factors ◽  
Literature Review ◽  
Injury Prevention ◽  
Suicide Prevention ◽  
Data Science ◽  
Population Level ◽  
Individual Risk ◽  
Prevention Research ◽  
Science Method ◽  
Individual Level

ObjectiveThe purpose of this research is to identify how data science is applied in suicide prevention literature, describe the current landscape of this literature and highlight areas where data science may be useful for future injury prevention research.DesignWe conducted a literature review of injury prevention and data science in April 2020 and January 2021 in three databases.MethodsFor the included 99 articles, we extracted the following: (1) author(s) and year; (2) title; (3) study approach (4) reason for applying data science method; (5) data science method type; (6) study description; (7) data source and (8) focus on a disproportionately affected population.ResultsResults showed the literature on data science and suicide more than doubled from 2019 to 2020, with articles with individual-level approaches more prevalent than population-level approaches. Most population-level articles applied data science methods to describe (n=10) outcomes, while most individual-level articles identified risk factors (n=27). Machine learning was the most common data science method applied in the studies (n=48). A wide array of data sources was used for suicide research, with most articles (n=45) using social media and web-based behaviour data. Eleven studies demonstrated the value of applying data science to suicide prevention literature for disproportionately affected groups.ConclusionData science techniques proved to be effective tools in describing suicidal thoughts or behaviour, identifying individual risk factors and predicting outcomes. Future research should focus on identifying how data science can be applied in other injury-related topics.

A Model for Analyzing Suicide Prevention

Crisis ◽  
2000 ◽  
Vol 21 (2) ◽  
pp. 80-89 ◽  
Author(s):  
Maila Upanne
Keyword(s):  
Risk Factors ◽  
Theoretical Model ◽  
Protective Factors ◽  
Suicide Prevention ◽  
Suicide Risk ◽  
Practical Work ◽  
Individual Risk ◽  
Self Assessment ◽  
Prevention Project ◽  
Individual Risk Factors

This study monitored the evolution of psychologists' (n = 31) conceptions of suicide prevention over the 9-year course of the National Suicide Prevention Project in Finland and assessed the feasibility of the theoretical model for analyzing suicide prevention developed in earlier studies [ Upanne, 1999a , b ]. The study was formulated as a retrospective self-assessment where participants compared their earlier descriptions of suicide prevention with their current views. The changes in conceptions were analyzed and interpreted using both the model and the explanations given by the subjects themselves. The analysis proved the model to be a useful framework for revealing the essential features of prevention. The results showed that the freely-formulated ideas on prevention were more comprehensive than those evolved in practical work. Compared to the earlier findings, the conceptions among the group had shifted toward emphasizing a curative approach and the significance of individual risk factors. In particular, greater priority was focused on the acute suicide risk phase as a preventive target. Nonetheless, the overall structure of prevention ideology remained comprehensive and multifactorial, stressing multistage influencing. Promotive aims (protective factors) also remained part of the prevention paradigm. Practical working experiences enhanced the psychologists' sense of the difficulties of suicide prevention as well as their criticism and feeling of powerlessness.

Universal Approaches to Youth Suicide Prevention

2017 ◽  
pp. 497-506
Author(s):  
Maggie G. Mortali
Keyword(s):  
Risk Factors ◽  
Suicide Prevention ◽  
Training Programs ◽  
Skills Training ◽  
Prevention Programs ◽  
Individual Risk ◽  
Whole School ◽  
School Based ◽  
Individual Risk Factors ◽  
Suicide Prevention Programs

This chapter focuses on suicide prevention programs that have taken a universal approach, targeting whole populations of adolescents regardless of individual risk factors. The aim of universal suicide prevention programs is to reduce risk factors or enhance protective factors across the entire population. One particularly widespread approach targets youth where they are most accessible—in the schools. Four types of universal prevention programs are especially common and continue to be the most widely used approach in schools: school-based screening programs, adult and peer gatekeeper training programs, skills training programs, and comprehensive or “whole school” programs. This chapter describes and critiques each type, gives examples, and discusses the assumptions under which these programs operate.

scholarly journals Community versus individual risk of SARS-CoV-2 infection in two municipalities of Louisiana, USA: An assessment of Area Deprivation Index (ADI) paired with seroprevalence data over time

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0260164
Author(s):  
Amy K. Feehan ◽  
Kara D. Denstel ◽  
Peter T. Katzmarzyk ◽  
Cruz Velasco ◽  
Jeffrey H. Burton ◽  
...  
Keyword(s):  
Risk Factors ◽  
New Orleans ◽  
Baton Rouge ◽  
Deprivation Index ◽  
Individual Risk ◽  
Individual Factors ◽  
Area Deprivation ◽  
Individual Level ◽  
Individual Risk Factors ◽  
Zip Code

Objective Determine whether an individual is at greater risk of severe acute respiratory distress syndrome coronavirus 2 (SARS-CoV-2) infection because of their community or their individual risk factors. Study design and setting 4,752 records from two large prevalence studies in New Orleans and Baton Rouge, Louisiana were used to assess whether zip code tabulation areas (ZCTA)-level area deprivation index (ADI) or individual factors accounted for risk of infection. Logistic regression models assessed associations of individual-level demographic and socioeconomic factors and the zip code-level ADI with SARS-CoV-2 infection. Results In the unadjusted model, there were increased odds of infection among participants residing in high versus low ADI (both cities) and high versus mid-level ADI (Baton Rouge only) zip codes. When individual-level covariates were included, the odds of infection remained higher only among Baton Rouge participants who resided in high versus mid-level ADI ZCTAs. Several individual factors contributed to infection risk. After adjustment for ADI, race and age (Baton Rouge) and race, marital status, household size, and comorbidities (New Orleans) were significant. Conclusions While higher ADI was associated with higher risk of SARS-CoV-2 infection, individual-level participant characteristics accounted for a significant proportion of this association. Additionally, stage of the pandemic may affect individual risk factors for infection.

scholarly journals Practice Note: ‘If Only All Women Menstruated Exactly Two Weeks Ago’: Interdisciplinary Challenges and Experiences of Capturing Hormonal Variation Across the Menstrual Cycle

2020 ◽  
pp. 725-732
Author(s):  
Lauren C. Houghton ◽  
Noémie Elhadad
Keyword(s):  
Public Health ◽  
Breast Cancer ◽  
Risk Factors ◽  
Menstrual Cycle ◽  
Chronic Diseases ◽  
Data Science ◽  
Population Level ◽  
Hormonal Profiles ◽  
Menstrual Health ◽  
Vast Variation

Abstract Houghton and Elhadad offer a new and needed perspective on approaches for measuring the menstrual cycle and identifying underlying hormonal profiles that can help determine risk factors for chronic diseases such as breast cancer and endometriosis. The authors discuss methods that have been applied historically and how those have shown vast variation in menstrual cycle characteristics around the globe. They then review and explore how innovation in technologies can be used to detect and disseminate new menstrual cycle knowledge. Additionally, the authors show how interdisciplinary efforts across anthropology, public health, and data science can leverage the advances in mobile menstrual tracking and hormone measurement to better characterize the menstrual cycle at the population level. This analysis concludes with a breakdown of how personalized menstrual norms and predictions can help individuals to be better stewards of their own menstrual health.

scholarly journals A unifying framework for depression: Bridging the major biological and psychosocial theories through stress

2013 ◽  
Vol 36 (4) ◽  
pp. 170 ◽  
Author(s):  
Amrita Roy ◽  
M Karen Campbell
Keyword(s):  
Risk Factors ◽  
Psychosocial Stress ◽  
Structural Changes ◽  
Population Level ◽  
Brain Regions ◽  
Multiple Systems ◽  
Individual Level ◽  
The Social ◽  
Chronic Psychosocial Stress ◽  
Social Causes

Several mechanisms for the development of depression have been proposed, and a comparative examination reveals considerable overlap. This paper begins by summarizing the conclusions drawn in the literature on the major biological theories: HPA-axis hyperactivity, the monoamine theory, the cytokine hypothesis/ macrophage theory, and structural changes to relevant brain regions and neurons. It then discusses the role of psychosocial stress as a bridge between the pathophysiology of depression and its predominantly psychosocial risk factors, touching upon theories offered in psychology and in population health. This paper further proposes a unifying framework which integrates the major theories. The multiple systems involved, and the directional complexity among them, likely help to explain the wide-ranging symptoms associated with depression, and the wide variety of comorbid medical conditions. They may also contribute to challenges in treatment, the diversity in symptoms and treatment outcomes among individuals, and the high rates of symptom persistence and relapse. The apparent bi-directionality of associations may suggest the existence of positive-feedback loops which aggravate symptoms; however, further bench research is required to confirm such phenomena. A better understanding of these interweaving associations is warranted. Additionally, given the significant influence of socioeconomic and psychosocial factors on the aetiology of depression, population-level interventions that address the social determinants of health are required. Current individual-level pharmacologic approaches are designed to treat pathophysiology once it is underway, and current individual-level non-pharmacologic interventions (such as talk therapy) are designed to moderate the relationship between psychosocial stress and pathophysiology. In contrast, a key strategy for primary prevention lies in population-level interventions that address the predominantly social causes of one of depression’s most notable risk factors: chronic psychosocial stress.

scholarly journals How host heterogeneity governs tuberculosis reinfection?

2012 ◽  
Vol 279 (1737) ◽  
pp. 2473-2478 ◽  
Author(s):  
M. Gabriela M. Gomes ◽  
Ricardo Águas ◽  
João S. Lopes ◽  
Marta C. Nunes ◽  
Carlota Rebelo ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Population Level ◽  
Underlying Mechanism ◽  
Individual Risk ◽  
Model Framework ◽  
Differential Host ◽  
Individual Level ◽  
Relative Contribution ◽  
The Individual ◽  
Epidemiology Studies

Recurrent episodes of tuberculosis (TB) can be due to relapse of latent infection or exogenous reinfection, and discrimination is crucial for control planning. Molecular genotyping of Mycobacterium tuberculosis isolates offers concrete opportunities to measure the relative contribution of reinfection in recurrent disease. Here, a mathematical model of TB transmission is fitted to data from 14 molecular epidemiology studies, enabling the estimation of relevant epidemiological parameters. Meta-analysis reveals that rates of reinfection after successful treatment are higher than rates of new TB, raising an important question about the underlying mechanism. We formulate two alternative mechanisms within our model framework: (i) infection increases susceptibility to reinfection or (ii) infection affects individuals differentially, thereby recruiting high-risk individuals to the group at risk for reinfection. The second mechanism is better supported by the fittings to the data, suggesting that reinfection rates are inflated through a population phenomenon that occurs in the presence of heterogeneity in individual risk of infection. As a result, rates of reinfection are higher when measured at the population level even though they might be lower at the individual level. Finally, differential host recruitment is modulated by transmission intensity, being less pronounced when incidence is high.

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