Delivering trauma and rehabilitation interventions to women and children in conflict settings: a systematic review
Bibliographic record
Abstract
Background: In recent years, more than 120 million people each year have needed urgent humanitarian assistance and protection. Armed conflict has profoundly negative consequences in communities. Destruction of civilian infrastructure impacts access to basic health services and complicates widespread emergency responses. The number of conflicts occurring is increasing, lasting longer and affecting more people today than a decade ago. The number of children living in conflict zones has been steadily increasing since the year 2000, increasing the need for health services and resources. This review systematically synthesised the indexed and grey literature reporting on the delivery of trauma and rehabilitation interventions for conflict-affected populations. Methods: A systematic search of literature published from 1 January 1990 to 31 March 2018 was conducted across several databases. Eligible publications reported on women and children in low and middle-income countries. Included publications provided information on the delivery of interventions for trauma, sustained injuries or rehabilitation in conflict-affected populations. Results: A total of 81 publications met the inclusion criteria, and were included in our review. Nearly all of the included publications were observational in nature, employing retrospective chart reviews of surgical procedures delivered in a hospital setting to conflict-affected individuals. The majority of publications reported injuries due to explosive devices and remnants of war. Injuries requiring orthopaedic/reconstructive surgeries were the most commonly reported interventions. Barriers to health services centred on the distance and availability from the site of injury to health facilities. Conclusions: Traumatic injuries require an array of medical and surgical interventions, and their effective treatment largely depends on prompt and timely management and referral, with appropriate rehabilitation services and post-treatment follow-up. Further work to evaluate intervention delivery in this domain is needed, particularly among children given their specialised needs, and in different population displacement contexts. PROSPERO registration number: CRD42019125221.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".