HealthCare Access Barrier (HCAB) framework for the barriers to cancer care during conflicts: perspective from Iraq
Bibliographic record
Abstract
The Iraqi population has lived under four decades of conflicts, warfare and political instability. The health consequences of the protracted conflict continue to persist. This work critically analyses Iraq's barriers to delivering and accessing cancer care during the conflicts that Iraq passed through from 1980 to 2017. To identify the barriers to accessing and delivering cancer care services, we used the HealthCare Access Barriers framework, which categorises the barriers into three groups: financial, structural and cognitive. Moreover, a structured search was performed in multidisciplinary databases. To produce a comprehensive body of literature, further materials were retrieved using alternative methods, such as hand-searching and snowballing. The key findings and themes identified in the literature were issues related to funding and affordability (within the financial), destruction and inaccessibility of facilities, therapeutic and diagnostic shortages, workforce and human resources and lack of national guidelines and awareness programmes (within the structural), awareness and knowledge and finally attitudes and beliefs (within the cognitive). These results demonstrated that the barriers to cancer care delivery are complex and inter-related. The financial and structural barriers were particularly intertwined with the protracted conflict, but this relationship was not demonstrable within the findings of the cognitive barriers. We concluded that the barriers facing the delivery and access to cancer care in Iraq are intertwined mainly with its protracted conflict. To ensure that future generations do not continue to pay the price of war, improved reconstructive efforts and further research are necessary.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".