Let’s Move Towards Precision Suicidology
Abstract
Purpose of review Suicidal behaviour remains a critical public health issue, with limited progress in reducing suicide rates despite various prevention efforts. The introduction of precision psychiatry offers hope by tailoring treatments based on individual genetic, environmental, and lifestyle factors. This approach could enhance the effectiveness of interventions, as current strategies are insufficient-many individuals who die by suicide had recently seen a doctor, but interventions often fail due to rapid progression of suicidal behaviour, reluctance to seek treatment, and poor identification of suicidal ideation.Recent findings Precision medicine, particularly through the use of machine learning and 'omics' techniques, shows promise in improving suicide prevention by identifying high-risk individuals and developing personalised interventions. Machine learning models can predict suicidal risk more accurately than traditional methods, while genetic markers and environmental factors can create comprehensive risk profiles, allowing for targeted prevention strategies. Stratification in psychiatry, especially concerning depression, is crucial, as treating depression alone does not effectively reduce suicide risk. Pharmacogenomics and emerging research on inflammation, psychological pain, and anhedonia suggest that specific treatments could be more effective for certain subgroups. Ultimately, precision medicine in suicide prevention, though challenging to implement, could revolutionise care by offering more personalised, timely, and effective interventions, potentially reducing suicide rates and improving mental health outcomes. This new approach emphasizes the importance of suicide-specific strategies and research into stratification to better target interventions based on individual patient characteristics.
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Prior reviews indicate the relevance of cognitive-behavioural and mindfulness-based strategies for psychological pain and identify psychological pain as both a state and trait phenomenon.
“Overall, prior reviews [53,54,55,56,57] indicate the relevance of cognitive-behavioural and mindfulness-based strategies and identify psychological pain as both a state and trait phenomenon, supporting psychological pain as a meaningful intervention target.”
From Targeting Psychological Pain After a Suicide Attempt: Scoping Review and Intervention Protocol (2026) · cites this paper as [54]
Psychological pain domains-states and traits-are clinically relevant and modifiable through psychotherapeutic intervention.
“domains—states and traits—are clinically relevant and modifiable through psychotherapeutic intervention, underscoring the centrality of psychological pain in suicide risk and the need for targeted interventions aimed at broadening emotional and behavioural coping repertoires.”
From Targeting Psychological Pain After a Suicide Attempt: Scoping Review and Intervention Protocol (2026) · cites this paper as [54]
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- Authors
- Courtet, P., & Saiz, P. A.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- Corresponding author
- Courtet, Philippe
- ORCID
- Courtet, Philippe
- Venue
- Current Psychiatry Reports
- Published
- 2025-03-18
- Volume
- 27
- Issue
- 5
- Pages
- 374-383
- ISSN
- 1523-3812 (ISSN-L)
- 1535-1645
- OpenAlex
- W4408589998
- Cited by
- 7
- References
- 67
- Citations by year
- 2026: 6 · 2025: 1
- FWCI
- 1.54
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Current Psychiatry Reports (publishedVersion)
- PubMed (publishedVersion)
- HAL (submittedVersion)
- Topics
- Social Sciences › Psychology › Clinical Psychology › Suicide and Self-Harm Studies
- Health Sciences › Medicine › Psychiatry and Mental health › Bipolar Disorder and Treatment
- Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
- Keywords
- suicide prevention, precision psychiatry, machine learning, pharmacogenomics, genetic risk markers, depression, inflammation, psychological suffering, anhedonia, personalized interventions, omics
- MeSH terms
- Machine Learning, Suicide Prevention, Humans, Suicide, Precision Medicine, Suicidal Ideation
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