Association Between Suicide-Related Outcomes and Primary Care Outpatient Visits: Impact of Mental Health Screening and Interventions
Bibliographic record
Abstract
Suicide remains a major public health concern, although most individuals who experience suicidal thoughts and ideations have contacted primary care shortly before committing suicide. This systematic review highlights the importance of suicide risk screening and prevention interventions in primary care contexts. Nevertheless, despite the different primary care practices being widely employed in the screening of different mental health concerns, including depression, most individuals feel unprepared or uncomfortable with screening for suicide risk. Therefore, the objective of this study is to systematically examine and synthesize existing evidence on the relationship between suicide-related outcomes (including suicidal ideation, suicide attempts, and suicide deaths) and primary care outpatient visits, with particular emphasis on the impact of mental health screening and intervention practices implemented within these settings. To attain the objective, a systematic search was conducted in PubMed, Google Scholar, Web of Science, Scopus, and Embase for peer-reviewed studies published between 2010 and 2025. Studies were included if they examined suicide-related outcomes (ideation, attempts, or death) in relation to primary care visits and incorporated data on mental health screening or interventions in these settings. Two reviewers independently screened articles, extracted data, and assessed methodological quality using standardized tools. Due to study heterogeneity, a narrative synthesis was used. Thus, of the 15 studies meeting inclusion criteria, most reported that a significant proportion of individuals who died by suicide had contact with primary care providers within one year before death. However, the implementation of mental health screening or suicide risk assessments during these visits was inconsistent. Studies that incorporated structured screening tools or brief interventions within primary care showed a potential reduction in suicide-related outcomes, although evidence quality varied. Primary care outpatient visits represent a pivotal point for suicide prevention. Enhanced integration of mental health screening and intervention practices in these settings may improve early detection and reduce suicide risk. Further high-quality, longitudinal research is needed to establish effective strategies for routine suicide prevention in primary care.
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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 | 0.012 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.009 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".