Earthquakes to Floods: A Scoping Review of Health-related Disaster Research in Low- and Middle-income Countries
Notice bibliographique
Résumé
INTRODUCTION: Health-related disaster research is a relatively small; but growing field of inquiry. A better understanding of the scope and scale of health-related disaster research that has occurred in low- and middle-income countries (LMICs) would be useful to funders, researchers, humanitarian aid organizations, and governments as they strive to identify gaps, disparities, trends, and needs of populations affected by disasters. METHODOLOGY: We performed a scoping review using the process outlined by Arksey & O'Malley to assess the characteristics of peer-reviewed publications of empirical health-related disaster research conducted in LMICs and published in the years 2003-2012. RESULTS: Five hundred and eighty-two relevant publications were identified. Earthquakes were by far the most commonly researched events (62% of articles) in the review's timeframe. More articles were published about disasters in China & South Asia/South East Asia than all other regions. Just over half of the articles (51%) were published by research teams in which all the authors' primary listed affiliations were with an institution located in the same country where the research was conducted. Most of the articles were classified as either mental health, neurology and stress physiology (35%) or as traumatology, wounds and surgery (19%). In just over half of the articles (54%), data collection was initiated within 3 months of the disaster, and in 13% research was initiated between 3 and 6 months following the disaster. The articles in our review were published in 282 different journals. DISCUSSION: The high number of publications studying consequences of an earthquake may not be surprising, given that earthquakes are devastating sudden onset events in LMICs. Researchers study topics that require immediate attention following a disaster, such as trauma surgery, as well as health problems that manifest later, such as post-traumatic stress disorder. One neglected area of study during the review's timeframe was the impact of disasters on non-communicable and chronic diseases (excluding mental health), and the management of these conditions in the aftermath of disasters. Strengthening disaster research capacity is critical for fostering robust research in the aftermath of disasters, a particular need in LMICs.
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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 | 0,022 | 0,092 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,006 |
| Bibliométrie | 0,019 | 0,020 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».