Temporal trends in calls for suicide attempts to poison control centers in France during the COVID-19 pandemic: a nationwide study
Bibliographic record
Abstract
Concerns have been raised about early vs. later impacts of the COVID-19 pandemic on suicidal behavior. However, data remain sparse to date. We investigated all calls for intentional drug or other toxic ingestions to the eight Poison Control Centers in France between 1st January 2018 and 31st May 2022. Data were extracted from the French National Database of Poisonings. Calls during the study period were analyzed using time trends and time series analyses with SARIMA models (based on the first two years). Breakpoints were determined using Chow test. These analyses were performed together with examination of age groups (≤ 11, 12-24, 25-64, ≥ 65 years) and gender effects when possible. Over the studied period, 66,589 calls for suicide attempts were received. Overall, there was a downward trend from 2018, which slowed down in October 2019 and was followed by an increase from November 2020. Number of calls observed during the COVID period were above what was expected. However, important differences were found according to age and gender. The increase in calls from mid-2020 was particularly observed in young females, while middle-aged adults showed a persisting decrease. An increase in older-aged people was observed from mid-2019 and persisted during the pandemic. The pandemic may therefore have exacerbated a pre-existing fragile situation in adolescents and old-aged people. This study emphasizes the rapidly evolving situation regarding suicidal behaviour during the pandemic, the possibility of age and gender differences in impact, and the value of having access to real-time information to monitor suicidal acts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".