Suicidal ideation among mental health patients at hospital discharge: prevalence and risk factors
Bibliographic record
Abstract
BACKGROUND: Evidence indicates that suicide risk is much higher for psychiatric patients in the weeks immediately following discharge from the hospital. It is, therefore, crucial to evaluate suicide risk accurately at discharge to provide supportive and lifesaving interventions as appropriate. AIM: In this study, the prevalence and risk factors for suicide ideations were examined among patients ready to be discharged from psychiatric units in Alberta province, Canada. METHODS: Researchers conducted face-to-face meetings with potential participants to determine if they were interested in participating. Eligible individuals in this epidemiological cross-sectional study used an online quantitative survey to assess suicide ideations using the appropriate question contained in the Patient Health Questionnaire (PHQ-9) scale. Information was also gathered regarding patient demographics, clinical information, and responses to the Generalized Anxiety Disorder (GAD-7), and World Health Organization Well-Being Index (WHO-5) questionnaires. RESULTS: We recruited 1,004 patients from an initial pool of 1,437 patients. We found that the prevalence of suicidal ideation among patients about to be discharged was 48.9%, i.e., nearly half of all patients had active suicidal thinking prior to discharge. We found that factors that were most significantly associated with this were age, ethnicity, employment status, primary mental health diagnoses, anxiety, and poor well-being at baseline. CONCLUSION: Here, in a large cohort of psychiatric patients in Alberta, Canada, we found that nearly half of patients being discharged from an acute psychiatric unit reported suicidal ideation. Given the increased short-term risk to this group, there is an urgent need for additional research on the underlying reasons and reliable predictors of suicidal ideation in these patients. Additionally, appropriate interventions and supportive services must be provided both prior and after discharge to mitigate this substantial risk.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".