Dying young: Excess morbidity and mortality in individuals with severe mental illness and what we should be doing about it
Notice bibliographique
Résumé
“We talk about people with mental illness, and people with diabetes, and smokers and the obese, and so on and so on. We’re talking about the same people – just with different labels.”– Health care professional [1, p. 6]Severe mental illness (SMI) most commonly refers to mental disorders with a psychotic component and significantly reduced functioning despite the presence of inherent differences in risk factors, etiologies, and treatments [1]. The most common disorders that fall under this term include schizophrenia and bipolar disorder [1]. Over a decade of research into the morbidity and mortality of individuals with SMI has consistently revealed mortality rates two to three times higher and a life expectancy of 25-30 years shorter compared to the general population [1-4]. Contrary to popular belief, the main causes of early death are not drug overdose or suicide, but rather, preventable illnesses such as cardiovascular disease, diabetes, and HIV/AIDS [1,3,5-7]. Incidence of other preventable conditions, such as obesity and respiratory disease, is also much higher among patients with SMI, and when present, is associated with a more severe course of mental illness and a reduced quality of life [3,8]. Such findings bring significant questions: what is the cause of this disparity in mortality/ morbidity? What can health care professionals do to help reduce this gap?A recent report by the Early Onset Illness and Mortality Working Group [1] outlines several factors that may contribute to poor physical health of people with SMI. Some factors, such as those related to the mental illness itself (e.g., cognitive impairment, a lack of communication skills, medication side-effects) and socioeconomic status (e.g., poverty, poor education) may be less amenable to modification, but should nevertheless be a target for action. Other contributing factors include behaviour and lifestyle (e.g., physical inactivity, obesity, tobacco smoking), and poor preventative medical care (e.g., disparity in quality of medical care), both of which are more easily modifiable with the assistance of medical care practitioners. Here we will summarize the factors responsible for poor physical health in SMI, specifically focusing on the mental illness itself, socioeconomic status, behaviour and lifestyle, health care system barriers, and insufficient preventative medical care. We will then propose future directions and ways in which medical students and current medical professionals can help reduce this gap.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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) | 0,000 | 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 tête enseignante, 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 ».