Abstract
BackgroundCertain demographic factors have long been cited to confer risk or protection for suicidal thoughts and behaviors. However, many studies have found weak or non-significant effects. Determining the effect strength and clinical utility of demographics as predictors is crucial for suicide risk assessment and theory development. As such, we conducted a meta-analysis to determine the effect strength and clinical utility of demographics as predictors.MethodsWe searched PsycInfo, PubMed, and GoogleScholar for studies published before January 1st, 2015. Inclusion criteria required that studies use at least one demographic factor to longitudinally predict suicide ideation, attempt, or death. The initial search yielded 2,541 studies, 159 of which were eligible. A total of 752 unique statistical tests were included in analysis.ResultsSuicide death was the most commonly studied outcome, followed by attempt and ideation. The average follow-up length was 9.4 years. The overall effects of demographic factors studied in the field as risk factors were significant but weak, and that of demographic factors studied as protective factors were non-significant. Adjusting for publication bias further reduced effect estimates. No specific demographic factors appeared to be strong predictors. The effects were consistent across multiple moderators.ConclusionsAt least within the narrow methodological constraints of the existing literature, demographic factors were statistically significant risk factors, but not protective factors. Even as risk factors, demographics offer very little improvement in predictive accuracy. Future studies that go beyond the limitations of the existing literature are needed to further understand the effects of demographics.
Highlights
The national suicide rate in the United States has risen 24% since 2000, reaching 13.4 deaths per 100,000 in 2014
The overall effects of demographic factors studied in the field as risk factors were significant but weak, and that of demographic factors studied as protective factors were non-significant
Future studies that go beyond the limitations of the existing literature are needed to further understand the effects of demographics
Summary
The national suicide rate in the United States has risen 24% since 2000, reaching 13.4 deaths per 100,000 in 2014 Both completed suicide and non-fatal self-injuries cast tremendous burden on the health care system, resulting in approximately $48.3 billion economic loss annually [1]. Under such circumstances, there is an urgent need to identify risk and protective factors for suicidal behaviors in order to allocate treatment resources to high-risk individuals. Research has long noted distinct suicide rates in different demographic groups Unraveling these differences will inform risk assessment, and increase understanding of suicidal thoughts and behaviors. We conducted a meta-analysis to determine the effect strength and clinical utility of demographics as predictors
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