National and regional prevalence of posttraumatic stress disorder in sub-Saharan Africa: A systematic review and meta-analysis
Notice bibliographique
Résumé
BACKGROUND: People living in sub-Saharan Africa (SSA) are disproportionately exposed to trauma and may be at increased risk for posttraumatic stress disorder (PTSD). However, a dearth of population-level representative data from SSA is a barrier to assessing PTSD. This manuscript sought to calculate pooled PTSD prevalence estimates from nationally and regionally representative surveys in SSA. METHODS AND FINDINGS: The search was conducted in PubMed, Embase, PsycINFO, and PTSDpubs and was last run between October 18, 2019, and November 11, 2019. We included studies that were published in peer-reviewed journals; used probabilistic sampling methods and systematic PTSD assessments; and included ≥ 450 participants who were current residents of an SSA country, at least 50% of whom were aged between 15 and 65 years. The primary outcomes were point prevalence estimates of PTSD across all studies, and then within subgroups. The protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO) (registration number CRD42016029441). Out of 2,825 unique articles reviewed, 25 studies including a total of 58,887 eligible participants (54% female) in 10 out of the 48 countries in SSA were identified. Most studies enrolled any adult aged 18 years or older. However, some studies only enrolled specific age brackets or persons as young as 15 years old. Six studies were national surveys, and 19 were regional. There were 4 key findings in the meta-analysis: (1) the overall pooled prevalence of probable PTSD was 22% (95% CI 13%-32%), while the current prevalence-defined as 1 week to 1 month-was 25% (95% CI 16%-36%); (2) prevalence estimates were highly variable, ranging from 0% (95% CI 0%-0%) to 74% (95% CI 72%-76%); (3) conflict-unexposed regions had a pooled prevalence of probable PTSD of 8% (95% CI 3%-15%), while conflict-exposed regions had a pooled prevalence of probable PTSD of 30% (95% CI 21%-40%; p < 0.001); and (4) there was no significant difference in the pooled prevalence of PTSD for men and women. The primary limitations of our methodology are our exclusion of the following study types: those published in languages other than English, French, and Portuguese; smaller studies; those that focused on key populations; those that reported only on continuous measures of PTSD symptoms; and unpublished or non-peer-reviewed studies. CONCLUSIONS: In this study, PTSD symptoms consistent with a probable diagnosis were found to be common in SSA, especially in regions exposed to armed conflict. However, these studies only represent data from 10 of the 48 SSA countries, and only 6 studies provided national-level data. Given the enormous heterogeneity expected across the continent, and also within countries and regions, this review cannot speak to rates of PTSD in any regions not included in this review. Thus, substantial gaps in our knowledge of PTSD prevalence in SSA remain. More research on population-level prevalence is needed to determine the burden of trauma symptoms and PTSD in SSA and to identify acceptable and feasible approaches to address this burden given limited mental healthcare resources.
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 | 0,018 | 0,044 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,018 | 0,037 |
| Bibliométrie | 0,011 | 0,011 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».