Development of a Structural Model for Breast Cancer Information Dissemination among Sri Lankan Undergraduates
Abstract
Background: Breast cancer is a leading public health concern in Sri Lanka, and access to reliable information is essential for early detection. Non-medical female undergraduates, especially those in the social sciences, often engage in community education. While not a formal policy, their potential role in awareness efforts warrants examining their information behaviour. This study aimed to develop a statistically validated structural model for the effective dissemination of breast cancer-related information, focusing on six constructs: Information Need, Satisfaction, Impact, Information Source, Information Dissemination, and Medium of Information.
Methods: A cross-sectional quantitative design was adopted, collecting data from five selected state universities using stratified self-weighting random sampling guided by Krejcie and Morgan's (1970) table. Data were collected using a structured, validated questionnaire (Cronbach's alpha = 0.876) administered via Google Forms. Analysis was conducted using SPSS v23 and SmartPLS 3.2.6. Partial Least Squares Structural Equation Modelling (PLS-SEM) was used to assess the measurement and structural models, focusing on validity, reliability, and model fit.
Results: The model initially included 38 indicators, later refined to 33. Bootstrapped analysis (5,000 resamples) confirmed 9 of 11 hypotheses; the moderating effects of the Medium of Information were not significant.
Conclusion: The findings revealed that Satisfaction significantly contributed to the perceived Impact, while Information Need and Dissemination showed no direct effect. The validated model provides a foundation for designing culturally relevant, evidence-based awareness programs grounded in reliable information sources tailored to Sri Lankan undergraduates.
Full text article
References
National Cancer Control Programme (NCCP). Cancer Incidence Data. Ministry of Health, Sri Lanka. (2021).
World Health Organization (WHO). Global Health Observatory Data Repository. Geneva, Switzerland: WHO; 2022.
Ali, S. (2021, November 4). Women under 35 face higher risk of breast cancer. The Hill. https://thehill.com/changing-america/well-being/prevention-cures/579830-women-under-35-face-higher-risk-of-breast-cancer/
Krejcie RV, Morgan DW. Determining sample size for research activities. Educ Psychol Meas. 1970; 30(3):607-610.
Batenburg, A., & Das, E. (2014). An experimental study on the effectiveness of disclosing stressful life events and support messages: When cognitive reappraisal support decreases emotional distress, and emotional support is like saying nothing at all. PLoS ONE, 9(12), e114169. https://doi.org/10.1371/journal.pone.0114169.
Kang H. (2013). The prevention and handling of the missing data. Korean journal of anesthesiology, 64(5), 402–406. https://doi.org/10.4097/kjae.2013.64.5.402
Anderson JC, Gerbing DW. Structural equation modeling in practice: A review and recommended two-step approach. Psychol Bull. 1988; 103(3):411-423.
Hair JF, Hult GTM, Ringle C, Sarstedt M. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage Publications; 2017.
Ramayah T, Lee JWC, In JBC. Network collaboration and performance in the tourism sector. Serv Bus. 2011; 5(4):411-428.
Rahman MS, Taghizadeh SK, Ramayah T, Osman N. Modeling the Impact of customer factors on customer satisfaction and loyalty: An application to hotel services. Int J Consum Stud. 2016; 40(3):289-301.
Hair JF, Sarstedt M, Hopkins L, Kuppelwieser VG. Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. Eur Bus Rev. 2019;26(2):106-121.
Wong KK. Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Mark Bull. 2013; 24(1):1-32.
Henseler J, Ringle CM, Sarstedt M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. J Acad Mark Sci. 2015; 43(1):115–135.
Dijkstra TK, Henseler J. Consistent partial least squares path modeling. MIS Q. 2015; 39(2):297-316.
Eveland, W. P. Jr. (2003). A “mix of attributes” approach to the study of media effects and new communication technologies. Journal of Communication, 53(3), 395–410. https://doi.org/10.1111/j.1460-2466.2003.tb02598.x
Slater, M. D. (2007). Reinforcing spirals: The mutual influence of media selectivity and media effects and their Impact on individual behavior and social identity. Communication Theory, 17(3), 281–303. https://doi.org/10.1111/j.1468-2885.2007.00296.x
Anwar, M. M., & Khalil, D. M. (2020). Breast cancer knowledge, attitude and practice among medical and non-medical university students. Journal of Public Health, 29(4), 871–878. https://doi.org/10.1007/s10389-020-01197-z
World Health Organization. (2017). Strategic framework for effective communications. https://www.who.int/publications/i/item/strategic-framework-for-effective-communications
World Health Organization. (2009). Milestones in health promotion: Statements from global conferences. https://www.who.int/publications/i/item/9789241564139
United Nations Educational, Scientific and Cultural Organization. (2017). Five laws of media and information literacy. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000246719
United Nations Educational, Scientific and Cultural Organization. (2001). Universal declaration on cultural diversity. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000127162
Norsa’adah, B., Rampal, K. G., Rahmah, M. A., Abdullah, N. N., & Naing, N. N. (2011). Diagnosis delay of breast cancer and its associated factors in Malaysian women. BMC Cancer, 11, 141. https://doi.org/10.1186/1471-2407-11-141
Okobia, M. N., Bunker, C. H., Okonofua, F. E., & Osime, U. (2006). Knowledge, attitude and practice of Nigerian women towards breast cancer: A cross-sectional study. World Journal of Surgical Oncology, 4, 11. https://doi.org/10.1186/1477-7819-4-11
Gupta, A., Shridhar, K., & Dhillon, P. K. (2015). A review of breast cancer awareness among women in India: Cancer literate or awareness deficit? European journal of cancer, 51(14), 2058–2066. https://doi.org/10.1016/j.ejca.2015.07.008
Maree, J. E., & Wright, S. C. (2010). How would early detection be possible? An enquiry into cancer related knowledge, understanding and health seeking behaviour of urban Black women in Tshwane, South Africa. European journal of oncology nursing, 14(3), 190–196. https://doi.org/10.1016/j.ejon.2009.10.009
Authors
Copyright (c) 2025 Archives of Breast Cancer
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright©. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 International License, which permits copy and redistribution of the material in any medium or format or adapt, remix, transform, and build upon the material for any purpose, except for commercial purposes.