Self-Reported Patterns of Use of Alcohol and Drugs After Suicide Bereavement and Other Sudden Losses: A Mixed Methods Study of 1,854 Young Bereaved Adults in the UK
Bibliographic record
Abstract
Background: Bereavement, particularly by suicide, is associated with an excess risk of mortality and of physical and psychological morbidity. Use of alcohol as a coping mechanism is suggested as a contributing factor. However, studies describing substance use after bereavement rely on diagnostic data, lacking a more fine-grained understanding of patterns of substance use when grieving. We aimed to use mixed methods to compare patterns of substance use after bereavement by suicide and other sudden deaths among young adults in the UK. Methods: Using an online survey throughout 37 UK higher education institutions we collected free text responses from 1,854 young adults who had experienced sudden bereavement. We conducted content analysis of free text responses to an open question about patterns of alcohol and drug use following the bereavement, measuring frequencies of coded categories. Collapsing these categories into binary outcomes reflecting increased use of alcohol or drugs, we used multivariable logistic regression to quantify the associations between mode of bereavement and increased post-bereavement substance use. Results: Of 1,854 eligible respondents, 353 reported bereavement by suicide, 395 by accidental death, and 1,106 by sudden natural causes. The majority of the sample reported no increase in their use of alcohol (58%) or unprescribed drugs (85%) after the bereavement. Overall 33% had increased their alcohol use at some point after the bereavement, whilst 12% had increased their use of drugs. People bereaved by suicide were significantly more likely to describe an increase in substance use (adjusted OR=1.29; 95% CI=1.00-1.66; p=0.049) than people bereaved by sudden natural causes, as were people bereaved by non-suicide unnatural deaths (adjusted OR= 1.32; 95% CI=1.03-1.68; p=0.026). Conclusions: Just under half of young UK adults who experience sudden bereavement increase their alcohol use afterwards, and very few increase their use of drugs. People bereaved by suicide or non-suicide unnatural deaths may be more likely than people bereaved by sudden natural causes to use substances as part of the grieving process, and may have a greater need for monitoring of potential harms. Understanding the reasons for substance use will help primary care and bereavement practitioners screen and address needs appropriately.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".