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Record W4411312057 · doi:10.2196/75651

Awareness and Attitudes of University Students in Bangladesh Toward Cancer: Cross-Sectional Study

2025· article· en· W4411312057 on OpenAlexvenueno aff
Maliha Tabassum, Nafisa Farhin, Afsana Afrose, Mahfuza Moin Surovy, Rubaiya Tasnim, Most Humayra Affia Heaven, Munima Haque

Bibliographic record

VenueJMIR Formative Research · 2025
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsnot available
Fundersnot available
KeywordsPreprintCross-sectional studyPsychologyMedicineComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.170
GPT teacher head0.524
Teacher spread0.354 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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