Cancer research in vulnerable populations: A call for collaboration and sustainability from MENATC countries.
Notice bibliographique
Résumé
e13649 Background: Cancer is a major burden across the Middle East and North Africa including Turkey and Cyprus (MENATC). Many MENATC countries experience acute and chronic emergencies, including COVID-19 pandemic, disasters, political instability, fragility, as well as chronic conflict that result in cumulative vulnerability to the region. This study examines the current level and the potential for cancer research among vulnerable populations in the MENATC, including its challenges, and gaps. Furthermore, it tries to ascertain cancer practitioners’ views on what defines vulnerability in the MENATC. Methods: Recurrent expert-driven meetings were held to conceptualize the study approach and highlight the barriers to conducting clinical cancer research among vulnerable populations in the MENATC. A self-administered online survey questionnaire was circulated to over 500 cancer practitioners in twenty-three MENATC countries. The survey covered: Demographic and general information, Clinical practice, Research capacity, Vulnerable populations, and logistics. Results: Half of the respondents considered clinical research in vulnerable cancer patients a key concern, while 24.5% did not. Out of the total respondents, 21.8% had worked on research that explicitly included vulnerable populations. About 60% of respondents reported seeing vulnerable populations during their daily practice. Lack of funding (60%), lack of protected time (42%), and lack of research training (35%) were the top three main reasons for research scarcity and major research challenges. Over half of the respondents agreed that recent wars/conflicts worsened the conditions for vulnerable populations. The top five ranked vulnerability groups were geriatric, terminally ill, mental health-related, chronically ill, and socioeconomically deprived patients, while the lower five ranked groups were LGBTQ+ community, veterans, divorced individuals or widowed women, prisoners, and ethnic minorities patients. Conclusions: This is the first study in the MENATC region to look at the status of and potential for research among vulnerable populations. The study highlights the challenges faced by cancer practitioners in the MENATC in research, especially among vulnerable populations. We believe that these limitations in research will negatively impact the outcomes for vulnerable communities in the region. Lack of research funding and training of cancer practitioners in the MENATC are major factors negatively affecting cancer outcomes which could lead to health improvement failure. Geopolitical, economic, and cultural differences clearly define the most vulnerable populations in cancer research. Addressing cancer disparities in the MENATC is a complex and pressing issue. By working together and providing the necessary resources, we can improve cancer research outcomes for the most vulnerable populations in the region.
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 | 0,123 | 0,137 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,008 | 0,009 |
| Communication savante | 0,015 | 0,019 |
| Science ouverte | 0,004 | 0,034 |
| Intégrité de la recherche | 0,015 | 0,018 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,029 | 0,006 |
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 ».