Notice bibliographique
Résumé
A recent issue of the journal Science, marking it's 125 th anniversary, has been devoted to 125 questions: What don't we know?".One of the questions addressed the relevance of genetic variation to personal health, acknowledging that genetic dissection of diseases such as cancer, asthma and heart disease is galloping ahead, whereas progress in other disorders such as depression is much slower.Evaluating physical, social and mental impacts of disease, depression was the fourth leading cause on the Global Burden of Illness list in 1990 and is predicted to be the number ONE leading cause in the year 2020.The morbidity associated with depression in women is even greater.Not only do twice as many women suffer from the disorder when compared to men, but they also have a higher rate of comorbid conditions, both physical and mental.From the age of menarche until well after menopause women also suffer from specific mood disorders including premenstrual dysphoria, perinatal and perimenopausal depression, as well as mood and anxiety disorders associated with infertility and pregnancy loss.Women endure more eating disorders, generalized anxiety disorder (GAD), posttraumatic stress disorder (PTSD), and autoimmune diseases.Women are also less tolerant to alcohol use and have a higher prevalence of pain disorders.They are influenced to a greater degree by seasonality, suffer more from jet lag and from shift-work, and last but not least metabolize drugs differently than men.Most of this very valuable information has only been gathered in the last 30 years but much more still needs to be learned.Some of the bigger questions to be answered are obvious: why is it that women are more vulnerable, more at risk to develop these disorders?What causes the sex/gender discrepancy?How can we better identify those who are at risk?What preventative measures can be put in place?And last but not least: how can we "tailor" better female specific treatments/interventions?In addition, the still much-debated question of nature versus nurture seems even more relevant to the higher prevalence of mood and anxiety disorders in women.The evolutionary perspective suggests that possible male-female asymmetries in preference for certain types of relationships, a differential investment in reproduction and childrearing, as well as social options (or the lack of), all contribute to the fact that women are more vulnerable to mood (major depression and dysthymia) as well as anxiety disorders (especially GAD and PTSD).Women are exposed to uncontrollable stressors, both psychological and physical, including violence, abuse and rape, from an early age on, much more often than men.Although such stressful life events may influence the onset and course of depression, GAD and/or PTSD, not all women who encounter stressful situations develop these disorders.It is suggested that an individual's response to environmental insults is moderated by her genetic makeup. 1 Thus, complex psychiatric disorders are probably not caused by genes alone.The hypothesis of a gene-by-environment interaction is very promising.It "accommodates" genetic polymorphism/ vulnerability, environmental pathogens as well as stressful life Editorial Saúde mental da mulher: o que não sabemos?Women's mental health: what don't we know?
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 | 0,012 | 0,043 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,002 |
| Méta-épidémiologie (sens large) | 0,007 | 0,004 |
| Bibliométrie | 0,007 | 0,004 |
| Études des sciences et des technologies | 0,006 | 0,004 |
| Communication savante | 0,010 | 0,005 |
| Science ouverte | 0,005 | 0,002 |
| Intégrité de la recherche | 0,030 | 0,028 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,004 |
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 ».