Awareness and Attitudes of University Students in Bangladesh Toward Cancer: Cross-Sectional Study
Notice bibliographique
Résumé
Background: Early detection and awareness are critical in reducing the burden of cancer. However, a significant proportion of university students in Bangladesh remains inadequately informed about cancer risks and preventive measures. Objective: This study aimed to assess knowledge gaps and evaluate the attitudes of Bangladeshi university students toward cancer, its prevention, risk factors, and care for affected individuals. Methods: A descriptive, cross-sectional survey was conducted among 530 university students aged 20 to 35 years across Bangladesh. Data were collected using an ethically approved, structured internet-based questionnaire between December 2022 and March 2024. The questionnaire assessed sociodemographics, cancer knowledge, awareness of risk factors, personal or familial cancer experiences, and attitudes toward cancer care and policy. Descriptive statistics and chi-square tests were used to analyze categorical data, with a significance threshold of P<.05. Results: Most participants were aged 21-25 years (406/530, 76.6%) and female (320/530, 60.4%), with the majority enrolled in undergraduate programs (82.8%, 439/530). While 60.8% (322/530) considered themselves somewhat knowledgeable about cancer, only 11.9% (63/530) were very knowledgeable, and 93.6% (496/530) had never undergone any cancer screening. Despite this, 74.3% (394/530) had personal or familial exposure to cancer, with carcinoma reported by 52.8% (280/530) of those affected. Awareness of established risk factors was inconsistent-smoking (90.9%, 482/530) and radiation (86.6%, 459/530) were widely recognized, but only 38.9% (206/530) acknowledged aging, 35.3% (187/530) obesity, and 29.2% (155/530) infectious agents as risk factors. Reproductive factors were least recognized, with just 10.2% (54/530) identifying having more children as a risk factor. Gender differences were significant in cancer-related attitudes. For example, 51.5% (273/530) of female participants versus 33.4% (177/530) of male participants felt comfortable around patients with cancer (P=.01), and 57.2% (303/530) of female participants versus 35.8% (190/530) of male participants supported increased government funding for cancer care (P=.03). Furthermore, 55.1% (292/530) of females and 35.5% (188/530) of males stressed the need for enhanced cancer awareness programs (P=.05). Only 6.4% (34/530) of all participants reported undergoing any form of cancer screening, highlighting a disconnect between awareness and preventive action. Conclusions: This study reveals critical gaps in cancer awareness among university students in Bangladesh, with pronounced disparities in knowledge of nonmodifiable risk factors and significant gender-based differences in attitudes toward cancer care. These findings highlight the urgent need for targeted, gender-sensitive educational programs and policy interventions to promote preventive practices, early detection, and equitable cancer care. Such initiatives must emphasize lesser-known risk factors, reduce stigma, and foster more inclusive, culturally competent health education strategies to mitigate the growing cancer burden in Bangladesh.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».