Deaths of Despair: A Scoping Review on the Social Determinants of Drug Overdose, Alcohol-Related Liver Disease and Suicide
Bibliographic record
Abstract
BACKGROUND: There is a lack of consensus on the social determinants of Deaths of Despair (DoD), i.e., an increase in mortality attributed to drug overdose, alcohol-related liver disease, and suicide in the United States (USA) during recent years. The objective of this study was to review the scientific literature on DoD with the purpose of identifying relevant social determinants and inequalities related to these mortality trends. METHODS: Scoping review focusing on the period 2015-2022 based on PubMed search. Articles were selected according to the following inclusion criteria: published between 1 January 2000 and 31 October 2021; including empirical data; analyzed DoD including the three causes defined by Case and Deaton; analyzed at least one social determinant; written in English; and studied DoD in the USA context only. Studies were excluded if they only analyzed adolescent populations. We synthesized our findings in a narrative report specifically addressing DoD by economic conditions, occupational hazards, educational level, geographical setting, and race/ethnicity. RESULTS: Seventeen studies were included. Overall, findings identify a progressive increase in deaths attributable to suicide, drug overdose, and alcohol-related liver disease in the USA in the last two decades. The literature concerning DoD and social determinants is relatively scarce and some determinants have been barely studied. However different, however, large inequalities have been identified in the manner in which the causes of death embedded in the concept of DoD affect different subpopulations, particularly African American, and Hispanic populations, but blue collar-whites are also significantly impacted. Low socioeconomic position and education levels and working in jobs with high insecurity, unemployment, and living in rural areas were identified as the most relevant social determinants of DoD. CONCLUSIONS: There is a need for further research on the structural and intermediate social determinants of DoD and social mechanisms. Intersectional and systemic approaches are needed to better understand and tackle DoD and related inequalities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".