World War II Blues: The Long–lasting Mental Health Effect of Childhood Trauma
Bibliographic record
Abstract
There has been a revival of warfare and threats of interstate war in recent years as the number of countries engaged in armed conflict surged dramatically, reaching to levels unprecedented since the end of Cold War.This is happening at a time when the global burden of mental health illness is also on the rise.We examine the causal impact of early life exposure to warfare on long-term mental health, using novel data on the amount of bombs dropped in German cities by Allied Air Forces during World War II (WWII) and German Socioeconomic Panel.Our identification strategy leverages a generalized difference-in-differences design, exploiting the plausibly exogenous variation in the bombing intensity suffered by German cities during the war as a quasiexperiment.We find that cohorts younger than age five at the onset of WWII or those born during the war are in significantly worse mental health later in life when they are between ages late 50s and 70s.Specifically, an increase of one-standard deviation in the bombing intensity experienced during WWII is associated with about a 10 percent decline in an individual's long-term standardized mental health score.This effect is equivalent to a 16.8 percent increase in the likelihood of being diagnosed with clinical depression.Our analysis also reveals that this impact is most pronounced among the youngest children including those who might have been in-utero at some point during the war.Our investigation further suggests that measures capturing the extent of destruction in healthcare infrastructure, the increase in the capacity burden of the healthcare system, and wealth loss during WWII exacerbate the adverse impact of bombing exposure on long-term mental health, while the size of war relief funds transferred to municipalities following the war has a mitigating impact.Our findings are robust across a variety of empirical checks and specifications.With the mental health impact of childhood exposure to warfare persisting well into the late stages of life, the global burden of mental illness may be aggravated for many years to come.Our findings imply that prioritizing children and a long-term horizon in public health planning and response may be critical to mitigating the adverse mental health consequences of exposure to armed conflict.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".