Abstract PO-120: Need for more sociodemographic data in qualitative childhood cancer research: Findings from a scoping review
Notice bibliographique
Résumé
Abstract Childhood cancer is increasingly recognized as a global health priority. In comparison with other childhood diseases, researchers have long- emphasized–the need to include children in empirical studies on cancer diagnosis, treatment, and recovery, particularly through the use of qualitative methods (Bluebond-Langner 1978). Children's inclusion originated from the theoretical perspective that adults may not understand the needs of children and that, to understand children's perspectives, we must engage and involve them in the research process. Given the new focus on global childhood cancer, we ask if and how sociodemographic factors, such as age, ethnicity, financial status and other categories, have been included in qualitative research with children who have cancer. Reporting ofn the inclusion and analysis of these factors is necessary to address disparities; research on adult cancer has shown that sociodemographic factors shape experiences with cancer diagnosis, treatment, and survival. The authors conducted a scoping review of qualitative studies involving children in cancer research between 2007-2019. Articles were retrieved from Ovid Medline, Embase, and CINAHL. Article titles and abstracts were screened and included in full text review if they were cancer related, used qualitative methods, and included participants aged 6 to 11. Additional articles that met the inclusion criteria but were found after the database search were considered and coded. A total of 88 articles were screened, with 76 articles met the inclusion criteria the full text retrieved for coding. Articles were coded for reported sociodemographic factors of children and their caretakers involved in the study. Further, each study's identified sociodemographic categories were analyzed for their significance/importance to the respective study. Results show gaps in sociodemographic reporting and analysis (e.g., factors such as race, education, financial status not reported or included in analysis), little research being conducted in under-resourced areas (e.g., studies outside of the US, Canada, Europe), and frameworks used in the reviewed articles exclude the social/environmental context as a contributing factor in medical care. With the popular frameworks in current childhood studies, including Humanistic Nursing Theory and phenomological theory, adding sociodemographic reporting and analysis can contribute to childhood cancer research by increasing the variety and number of children to whom the research findings will be contextually relevant. Reporting the inclusion of these factors in children's cancer research is needed to highlight populations who have been traditionally underrepresented, and to identify areas for future research examining how sociodemographic factors impact the cancer care experience. We hope in identifying these gaps and opportunities for future research, this work will invite childhood cancer research to expand its reach and combat disparities that exist within cancer diagnosis, care, and survival. Citation Format: Sarah Burack, Eric M. Wiedenman, Melanie Ward, Lindsay Kaufman, Thembekile Shato, Jean Hunleth. Need for more sociodemographic data in qualitative childhood cancer research: Findings from a scoping review [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-120.
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 | 0,103 | 0,354 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,004 |
| Bibliométrie | 0,026 | 0,030 |
| Études des sciences et des technologies | 0,003 | 0,004 |
| Communication savante | 0,013 | 0,013 |
| Science ouverte | 0,003 | 0,006 |
| Intégrité de la recherche | 0,004 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
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 ».