Suicide-related internet use among mental health patients who died by suicide in the UK: a national clinical survey with case–control analysis
Notice bibliographique
Résumé
Background: Suicide-related internet use (SRIU) has been shown to be linked to suicide. However, there is limited research on SRIU among mental health patients, who are at 4 to 7 times increased risk of suicide compared to the general population. This study aims to address this gap by exploring the prevalence of SRIU among mental health patients who died by suicide in the UK and describing their characteristics. Methods: The study was carried out as part of the National Confidential Inquiry into Suicide and Safety in Mental Health (NCISH). Data were collected on sociodemographic, clinical, suicide characteristics and engagement in SRIU of patients who died by suicide between 2011 and 2021. The study utilised a case-control design to compare patients who engaged in suicide-related internet use with those who did not. Findings: The presence or absence of SRIU was known for 9875/17,347 (57%) patients; SRIU was known to be present in 759/9875 (8%) patients. The internet was most often used to obtain information on suicide methods (n = 523/759, 69%) and to visit pro-suicide websites (n = 250/759, 33%) with a significant overlap between the two (n = 152/759, 20%). Engaging in SRIU was present across all age groups. The case-control element of the study showed patients who were known to have engaged in SRIU were more likely to have been diagnosed with autism spectrum disorder (OR = 2.13, 95% CI: 1.43-3.18), have a history of childhood abuse (OR = 1.70, 95% CI: 1.36-2.13) and to have received psychological treatment (OR = 1.43, 95% CI: 1.18-1.74) than controls. Additionally, these patients were more likely to have died on or near a salient date (OR = 2.11, 95% CI: 1.61-2.76), such as a birthday or anniversary. Interpretation: The findings affirm SRIU as a feature of suicide among patients of all ages and highlight that clinicians should inquire about SRIU during assessments. Importantly, as the most common type of SRIU can expand knowledge on suicide means, clinicians need to be aware of the association between SRIU and choice of methods. This may be particularly relevant for patients approaching a significant calendar event. Funding: The Healthcare Quality Improvement Partnership.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».