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Enregistrement W2130789467 · doi:10.1093/ije/dyp203

Commentary: Explaining enormous variations in rates of disorder in trauma-focused psychiatric epidemiology after major emergencies

2009· letter· en· W2130789467 sur OpenAlexaffabout
Danielle Rodin, Mark van Ommeren

Notice bibliographique

RevueInternational Journal of Epidemiology · 2009
Typeletter
Langueen
DomainePsychology
ThématiqueMigration, Health and Trauma
Établissements canadiensUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésContext (archaeology)PsychiatryDepression (economics)EpidemiologyMental healthMedicinePsychiatric epidemiologyPsychology

Résumé

récupéré en direct d'OpenAlex

There has been a surge of interest in the last 20 years in the mental health effects of conflict and other major disasters in lowand middle-income countries (LAMIC). In particular, post-traumatic stress disorder (PTSD) and major depression have received substantial attention. It has become evident that there are large, unexplained variations in prevalence rates identified through trauma-focused psychiatric epidemiology in such settings. For example, Mollica et al.’s classic study found prevalence rates of PTSD of 15% among genocide-exposed Cambodians, while Neugebauer et al.’s sophisticated report in this issue of the Journal identifies rates of 53–62% of PTSD in genocide-exposed Rwandans. The wide variation in the prevalence rates in studies of PTSD and depression may be attributable to differences in context, methodology or both. Discussion sections of reports often highlight only a few factors that could explain the size of obtained rates. Although peer review helps shape discussion sections, authors usually have enormous discretion in deciding what factors to report. Readers are left with the challenge of tracking all reported and unreported methodological and contextual factors that could explain a study’s results. We have developed a scheme that may help to systematically identify factors influencing the size of observed prevalence rates of disorders in populations affected by major emergencies in LAMIC. The scheme may prove useful for readers and journal peer reviewers alike. The scheme, which we will apply below to Neugebauer et al.’s study, was built as follows. We searched the following medical, psychiatry and speciality journal websites: American Journal of Psychiatry; Archives of General Psychiatry; British Journal of Psychiatry; British Medical Journal; Culture Medicine and Psychiatry; JAMA, Journal of Traumatic Stress, Lancet, Psychological Medicine; Social Science and Medicine; and Transcultural Psychiatry for studies published after 1998 with data collected on depression or PTSD among civilians after major emergencies in LAMIC (references available upon request). Of 43 studies, 11 (26%) pertained to major natural disasters and 32 (74%) pertained to major human-made disasters (e.g. war). All articles were original contributions, and 40 (93%) made comments explaining the magnitude of findings in the articles’ discussion sections. In addition, we reviewed editorials, commentaries and letters to the editor linked to the identified articles. We thematically analysed discussion sections of all papers. We categorized authors’ explanations for observed rates as (i) either methodological or contextual in nature and (ii) explaining either relatively higher or lower observed rates. In addition, we categorized some explanations as (iii) reflecting general methodological limitations causing uncertainty in the validity of the study, with unknown impact on the magnitude of observed rates. Table 1 provides an overview of the explanations for relatively high or low rates ascribed in these studies. We studied the research reported in this issue of the Journal and rated different methodological and contextual factors in the study from 1 (not a factor in explaining size of obtained rate) to 5 (definitive factor in explaining size of obtained rate) (see bracketed numbers in Table 1). If no information was available in the paper on an element, then we rated it 3. Starting with the cell in the bottom left, we will discuss here ratings of 4 and 5, which are of main interest in explaining findings. The study took place in 1995 in a context (recent genocide that was preceded and followed by violence, fears of revenge killings, ongoing mass displacements, risk of cholera outbreaks, etc.) that not only involved mass loss and trauma but also a highly stressful recovery * Corresponding author. Department of Mental Health and Substance Abuse, World Health Organization, Geneva, Switzerland. E-mail: vanommerenm@who.int 1 Faculty of Medicine, University of Toronto, Toronto, Canada. 2 Department of Mental Health and Substance Abuse, World Health Organization, Geneva, Switzerland. Published by Oxford University Press on behalf of the International Epidemiological Association

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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,007
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesIntégrité de la recherche
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,247
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0070,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0030,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,003
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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.

Tête enseignante Opus0,060
Tête enseignante GPT0,397
Écart entre enseignants0,337 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeObservationnel
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations60
Publié2009
Routes d'admission2
Résumé présentoui

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