EVALUATION OF SUICIDAL BEHAVIOR AND DEPRESSION, INSIGHT AND DISEASE CHARACTERISTICS IN SCHIZOPHRENIA
Notice bibliographique
Résumé
Introduction: Suicide is a severe public health issue with high rates of morbidity and mortality. Schizophrenia also has a high suicide incidence, which is one of the main factors contributing to rising morbidity and mortality. For strategies to lower suicide rates, it is essential to understand the risk factors for suicide in people with schizophrenia. By evaluating the relationship between the risk of suicidal behavior and demographic factors, disease characteristics, depression, and insight in schizophrenia patients, in the light of literature information, this study aimed at preventing suicide in schizophrenia and set an example for future studies. Method: This study included 103 schizophrenia patients who underwent follow-up for at least 4 years in a community mental health center (CMHC). The study included patients who had the mental capacity to understand and complete the questionnaires, were not experiencing an acute psychotic attack, and gave their consent to participate. The patients were given the Three Components of Insight Scale (TCIS), Scale for Evaluation of Positive Symptoms in Schizophrenia (SAPS), Scale for Evaluation of Negative Symptoms in Schizophrenia (SANS), Calgary Depression Inventory in Schizophrenia (CDIS), and Suicide Behavior Scale (SBS). Results: 47% of patients demonstrated suicidal behavior, and 69% of patients were men. 46% of the group demonstrating suicidal behavior had severe or very severe suicidal ideation. Age and disease duration were revealed to be significant risk factors for suicidal behavior (p=0.033 and p=0.004, respectively), but gender, SBS, CDIS, SANS, SAPS, and TCIS scores had no significant effect. Age and suicidal behavior risk were found to be inversely correlated, with each unit of age increase reducing the risk of suicidal behavior by 0.929 times. The risk of suicidal behavior rises along with the duration of disease. With every one unit increase in the duration of disease, the risk of suicidal behavior increases by 1.133 times. Additionally, the group with severe-very severe suicidal ideation had significantly more severe depression scores than the group with mild-moderate (p=0.01). Discussion: More than half of the patients with schizophrenia who were followed up showed suicidal behavior, and approximately half of the group who had suicidal ideation showed severe suicidal ideation. Suicidal behavior was found to be correlated with age and duration of illness. While suicidal behavior increases age decreases and duration of illness increases.There was no significant correlation between insight, depression, gender, symptom severity and suicidal behavior in this population. In addition, depression scores were found to be statistically significantly higher in the group with severe-very severe suicidal ideation. According to the research, in individuals with schizophrenia who were being monitored, the frequency of suicidal behavior increased along with the severity of depression. Conclusion: It is crucial to identify the risk factors and protective factors for suicide in schizophrenia patients in order to develop interventions for them. Because suicidal behavior is a significant morbidity and mortality factor in schizophrenia.
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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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».