Development and evaluation of a sustainable video health education program for newly diagnosed breast cancer patients in Malaysia

Islam, Tania; Musthaffa, S.; See, Mee-Hoong; Filza, Jasmine; Jamaris, Suniza; Cheng, Mao Li; Harun, Fatimah; Din, N. Abdullah; Rahman, Zarinah Abd; Mohamed, K.N.; Ho, Gwo Fuang; Kaur, Ranjit; Taib, Nur Aishah Mohd

doi:10.1007/s00520-020-05776-4

Cited by 12 publications

(7 citation statements)

References 31 publications

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“…The statistical tests (e.g., t -test, ANOVA) are used to interpret the results based on measures such as p -value (significant difference). Biostatisticians and medical scientists perform statistical analysis using conventional software tools [ 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 ] because healthcare providers’ main objective is to focus on analysis based on hypothesis testing in the context of patient care to check if treatments or drugs yield positive outcomes or how to control certain risk factors for a particular disease. Therefore, they barely explore or pay attention to the use of advanced computer science applications and automated predictive tools such as Predict, CancerMath and Adjuvant.…”

Section: Resultsmentioning

confidence: 99%

Theory and Practice of Integrating Machine Learning and Conventional Statistics in Medical Data Analysis

et al. 2022

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The practice of medical decision making is changing rapidly with the development of innovative computing technologies. The growing interest of data analysis with improvements in big data computer processing methods raises the question of whether machine learning can be integrated with conventional statistics in health research. To help address this knowledge gap, this paper presents a review on the conceptual integration between conventional statistics and machine learning, focusing on the health research. The similarities and differences between the two are compared using mathematical concepts and algorithms. The comparison between conventional statistics and machine learning methods indicates that conventional statistics are the fundamental basis of machine learning, where the black box algorithms are derived from basic mathematics, but are advanced in terms of automated analysis, handling big data and providing interactive visualizations. While the nature of both these methods are different, they are conceptually similar. Based on our review, we conclude that conventional statistics and machine learning are best to be integrated to develop automated data analysis tools. We also strongly believe that machine learning could be explored by health researchers to enhance conventional statistics in decision making for added reliable validation measures.

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Section: Resultsmentioning

confidence: 99%

Theory and Practice of Integrating Machine Learning and Conventional Statistics in Medical Data Analysis

et al. 2022

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“…The positive reception to this video is consistent with the growing body of evidence supporting video education in breast cancer RT education literature. Several recent studies have demonstrated educational videos to be a superior form of breast cancer RT education, leading to substantial improvements in patient self-reported knowledge [ 7 , 8 , 13 ], post-consult anxiety [ 7 , 8 , 13 , 14 ], heightened confidence in providers [ 7 ] and better decision-making [ 7 ]. However, of these studies, only one single-arm study of 20 participants targeted the initial RO consult and reported the 7.5-min video to be a feasible intervention that decreased patient-reported anxiety [ 14 ].…”

Section: Discussionmentioning

confidence: 99%

“…Traditional verbal and print material is often inadequate in capturing this, giving rise to an appetite for modalities that appeal to preferences for visual learning and extend patient education beyond merely a verbal discussion and generic written material [ 4 ]. The evolving area of breast cancer RT education literature is increasingly recognising video technology as an opportunity to remediate the limitations of current educational modalities [ 7 , 8 , 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

The Development and Evaluation of an Educational Video for Breast Cancer Patients Requiring Adjuvant Radiation Therapy

Moussa,

Jimenez,

Wang

et al. 2024

J Canc Educ

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Patient education and informed consent are required prior to adjuvant radiation therapy (RT) for early breast cancer (EBC), and include the role, rationale, potential toxicities and practicalities of the treatment process. Current education of patients about RT is verbal, in the form of a consultation by a radiation oncologist, often supplemented with print or online materials. This approach is limited by its doctor-dependency and non-standardised nature. Video education is being recognised increasingly as an opportunity to remediate this and appeal to patients’ preference for visual learning. The purpose of this study was to design and produce a video as an educational adjunct for EBC patients’ viewing prior to adjuvant RT, and to evaluate its acceptability through content analysis of three online focus group discussions, among ten participants with EBC requiring RT. After qualitative content analysis of the focus group transcripts, data were summarised into three main categories: (1) understanding of RT, (2) ease of engagement with the video and (3) anxiety and preparedness for RT. The 18-min video was positively received by all participants, and discussion feedback was used to inform improvements to the video. This focus group study demonstrated that the video was well understood, informative and acceptable to EBC patients in preparing them for RT. The effectiveness of the video in improving knowledge and alleviating distress in preparation for therapy will be further evaluated in an ethics-approved biphasic quasi-experimental study.

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“…In a nationwide survey on digitization in the outpatient sector, respondents most commonly reported using e-mail only [ 23 ]. The main obstacles from the point of view of physicians are the security gaps in information technology (IT), the significant costs and the effort involved in the introduction of digital media technologies and an unfavorable cost–benefit ratio [ 24 ]. Respondents of our survey saw security vulnerabilities in IT as a rather minor problem.…”

Section: Discussionmentioning

confidence: 99%

Telemedicine as a Therapeutic Option in Sports Medicine: Results of a Nationwide Cross-Sectional Study among Physicians and Patients in Germany

Hertling

Loos

Graul

2021

IJERPH

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Background: Worldwide, the number of treatments in the field of sports medicine is increasing. However, the COVID-19 pandemic has changed everyday life. Many consultations had to be cancelled, postponed, or converted to a virtual format. Telemedicine in sports medicine could support physicians. This study analyzes the use and perception of telemedicine applications among physicians and patients in the field of sports medicine in Germany. Methods: This prospective cross-sectional study was based on a survey of sports medicine physicians and patients in Germany during the COVID-19 pandemic. Descriptive statistics were calculated. Results: We analyzed the responses of 729 patients and 702 sports medicine physicians. Most believed that telemedicine is useful. Both physicians and patients rated their knowledge of telemedicine as unsatisfactory. The majority of respondents said they do not currently use telemedicine but would like to do so. Patients and physicians reported that their attitude had changed positively towards telemedicine and that their usage had increased due to COVID-19. The majority in both groups agreed on implementing virtual visits in stable disease conditions. Telemedicine was considered helpful for follow-up monitoring and prevention by both groups. Conclusion: Telemedicine in sports medicine has seen limited use but is highly accepted among physicians and patients alike. The absence of a structured framework is an obstacle to effective implementation. Training courses should be introduced to improve the limited knowledge regarding the use of telemedicine. More research in telemedicine in sports medicine is needed. This includes large-scale randomized controlled trials, economic analyses and explorations of user preferences.

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Development and evaluation of a sustainable video health education program for newly diagnosed breast cancer patients in Malaysia

Cited by 12 publications

References 31 publications

Theory and Practice of Integrating Machine Learning and Conventional Statistics in Medical Data Analysis

Theory and Practice of Integrating Machine Learning and Conventional Statistics in Medical Data Analysis

The Development and Evaluation of an Educational Video for Breast Cancer Patients Requiring Adjuvant Radiation Therapy

Telemedicine as a Therapeutic Option in Sports Medicine: Results of a Nationwide Cross-Sectional Study among Physicians and Patients in Germany

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