Barriers to cancer screening uptake and approaches to overcome them: a systematic literature review
Notice bibliographique
Résumé
Introduction: Cancer screening programs play a crucial role in early detection, improving survival rates and reducing the burden of advanced cancer. However, uptake remains inconsistent due to multifaceted barriers. This systematic review aimed to identify factors that impact cancer screening uptake across multiple tumor types and interventions to overcome barriers to cancer screening uptake. Methods: (May 2012 to May 2022) to identify observational studies that reported factors associated with screening uptake in adults, worldwide, with no tumor-specific restrictions. Records identified were screened by two independent reviewers. Included studies were data extracted by two reviewers and the results were reported narratively, focusing on identifying factors that acted as barriers or facilitators to cancer screening uptake, along with potential interventions to improve screening uptake. Results: Overall, 811 studies were identified from the SLR that reported factors influencing the uptake of screening programs, with 658 studies covering screening programs for breast, cervical, lung, colorectal, gastric and prostate cancers. Barriers to cancer screening included: being unmarried, experiencing higher deprivation, lower socioeconomic status and rural living conditions. Facilitators to cancer screening included: older age, poor perception of health, previous cancer history, family history of cancer, previous cancer screening history, having knowledge of the disease, positive attitudes to screening, perceived cancer risk, higher education level, having children, higher income, higher socioeconomic status, having health insurance, urban residence, having access to care, and recommendations for screening by primary care physicians. Mixed findings were identified for race and ethnicity, employment and smoking status. Targeted educational programs were the most suggested strategy to overcome barriers to cancer screening uptake. Conclusion: Barriers to cancer screening across multiple tumor types are complex, spanning demographic and patient-level factors, social and economic factors, provider and community challenges, and access to health care. While certain barriers are shared across tumor types, others are unique, reflecting the specific requirements of screening for different tumors. Addressing these barriers requires multi-level strategies that integrate both universal and cancer-specific approaches. Targeted interventions and supportive policies can increase screening participation, facilitate earlier cancer diagnosis, and reduce disparities in cancer outcomes.
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 | 0,025 | 0,120 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,008 | 0,010 |
| Bibliométrie | 0,015 | 0,016 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,003 | 0,003 |
| 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 ».