Perceived needs for the information communication technology (ICT)‐based personalized health management program, and its association with information provision, health‐related quality of life (HRQOL), and decisional conflict in cancer patients

Sim, Jin Ah; Chang, Yoon Jung; Shin, Aesun; Noh, Dong Young; Han, Wonshik; Yang, Han Kwang; Kim, Young Whan; Kim, Young Tae; Jeong, Sunjoo; Yoon, Jung Hwan; Kim, Yoon Jun; Heo, Daesuk; Kim, Tae You; Oh, Do Youn; Wu, Hong Gyun; Kim, Hak Jae; Chie, Eui Kyu; Kang, Keon Wook; Kim, Ju Han; Yun, Young Ho

doi:10.1002/pon.4367

Cited by 9 publications

(8 citation statements)

References 24 publications

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“…One important advantage of the RF model is that the computational complexity inherent in support-vector machines (SVMs) can be reduced via quadratic optimization. Therefore, for convenience of use in clinical settings, developing a comprehensive digital-based self-management program by including a prediction model can provide more information and help survivors' decisional support 53 .…”

Section: Discussionmentioning

confidence: 99%

The major effects of health-related quality of life on 5-year survival prediction among lung cancer survivors: applications of machine learning

Sim

Kim

et al. 2020

Sci Rep

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The primary goal of this study was to evaluate the major roles of health-related quality of life (HRQOL) in a 5-year lung cancer survival prediction model using machine learning techniques (MLTs). The predictive performances of the models were compared with data from 809 survivors who underwent lung cancer surgery. Each of the modeling technique was applied to two feature sets: feature set 1 included clinical and sociodemographic variables, and feature set 2 added HRQOL factors to the variables from feature set 1. One of each developed prediction model was trained with the decision tree (DT), logistic regression (LR), bagging, random forest (RF), and adaptive boosting (AdaBoost) methods, and then, the best algorithm for modeling was determined. The models' performances were compared using fivefold cross-validation. For feature set 1, there were no significant differences in model accuracies (ranging from 0.647 to 0.713). Among the models in feature set 2, the AdaBoost and RF models outperformed the other prognostic models [area under the curve (AUC) = 0.850, 0.898, 0.981, 0.966, and 0.949 for the DT, LR, bagging, RF and AdaBoost models, respectively] in the test set. Overall, 5-year disease-free lung cancer survival prediction models with MLTs that included HRQOL as well as clinical variables improved predictive performance. Globally, lung cancer has been the most common cancer for several decades 1. Due to advances in early detection and improved treatment strategies 1,2 , lung cancer mortality has decreased worldwide 3 , and Korean age-adjusted lung cancer mortality has decreased by 3.4% annually since 2012 4. With this increase in the number of cancer survivors, it has become important to classify these individuals into precise prognostic groups and provide them with appropriate information for better follow-up planning and personalized self-management. 5 Many lung cancer survivors have reported that they had diverse health difficulties 2,6 , and their health function or symptom burden was more severe than that of others 6. In fact, many recent studies have suggested that patient-reported outcomes (PROs), such as health-related quality of life (HRQOL) or clinical data, can provide clear prognostic information 7,8. In our previous study of disease-free lung cancer survivors 9,10 , we found that several HRQOL variables showed prognostic potential, and thus, HRQOL or lifestyle factors can be used to identify patients who could benefit from a specific intervention. Therefore, we aimed to predict lung cancer survivors' disease-free 5-year survival after primary treatment for lung cancer ended, i.e., the patient survived without any signs or symptoms of that cancer, such as local or regional relapses of the tumor or development of distant metastases, using a combination of sociodemographic, clinical and HRQOL variables.

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Section: Discussionmentioning

confidence: 99%

The major effects of health-related quality of life on 5-year survival prediction among lung cancer survivors: applications of machine learning

Sim

Kim

et al. 2020

Sci Rep

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“…Higher scores indicate higher DC, feeling more uninformed, feeling more unclear about personal values, feeling more unsupported, and feeling more ineffective at decision-making. Each subscale and the total score were dichotomized, with scores <25 associated with making a “good decision.” 54 The Korean version of the DCS was used in a previous study as a decision aid for the disclosure of terminal cancer 46,47,52 . Cronbach's α coefficient, which ranged from .78 to .92 in the original validation study, 53 was .95 in the present study.…”

Section: Methodsmentioning

confidence: 65%

“…The EORTC QLQ-INFO 25 is a reliable and valid self-reported instrument 45 . The Korean version of the EORTC QLQ-INFO25, developed through the process of translation and reverse translation, has been used in previous studies of patients with cancer 46,47 . The EORTC QLQ-INFO25 consists of 12 subscales, including 4 multi-item scales (information about disease, medical tests, treatment, and other services) and 8 single-item scales, which evaluate cancer patients' perception of information 45 .…”

Section: Methodsmentioning

confidence: 99%

“…Decisional conflict was measured using the Korean version of the Decisional Conflict Scale (DCS), which assesses the quality of the decision-making process 52 . The DCS is a reliable and valid self-reported instrument, 53 with the Korean version developed through the process of translation and reverse translation 46,47,52 . A decisional situation of adopting regular exercise and a healthy diet was provided to the participants before administering the questionnaire.…”

Section: Methodsmentioning

confidence: 99%

“…translation and reverse translation, has been used in previous studies of patients with cancer. 46,47 The EORTC QLQ-INFO25 consists of 12 subscales, including 4 multi-item scales (information about disease, medical tests, treatment, and other services) and 8 single-item scales, which evaluate cancer patients' perception of information. 45 For clarity of interpretation, all subscale and item scores were linearly transformed using the EORTC standard scoring manual to a scale from 0 to 100, 48 with higher scores associated with more positive patient perceptions of the level of information provided and satisfaction with that information.…”

Section: Data Collectionmentioning

confidence: 99%

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Information Provision, Decision Self-efficacy, and Decisional Conflict in Adopting Health Behaviors Among Patients Treated for Colorectal Cancer

Lee

Bryant‐Lukosius

2021

Cancer Nurs

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BackgroundHealth promotion is necessary to mitigate the negative consequences of colorectal cancer and its treatment. Rates of behavior modification are low in populations of cancer patients. Studies are needed to determine the factors, such as decisional conflict, which influence adoption of healthy behaviors following a cancer diagnosis.ObjectiveTo examine the effects of information provision, decision self-efficacy, and decisional conflict on the adoption of healthy behaviors among patients with colorectal cancer.MethodsThis cross-sectional study focused on 251 patients with colorectal cancer in South Korea. Information provision, decision self-efficacy, and decisional conflict were measured using validated instruments. Patients rated their decisional conflict related to the adoption of behaviors that include regular exercise and a balanced diet.ResultsMost participants (73%) reported low satisfaction with the amount of information received. Of the participants, 64% had low decision self-efficacy, and 80% experienced decisional conflict. The perception of a higher level of information provision was associated with greater decision self-efficacy (odds ratio, 4.63; 95% confidence interval, 1.61-13.35). Higher decision self-efficacy was associated with lower decisional conflict (odds ratio, 5.19; 95% confidence interval, 2.33-11.59).ConclusionReceiving adequate information is important for promoting patients' confidence in making decisions about their health and reducing decisional conflict in the adoption of healthy lifestyle changes following a cancer diagnosis.Implication for PracticeOncology nurses should assess patient information needs and promote decision self-efficacy, thus empowering patients diagnosed with colorectal cancer to make lifestyle decisions that improve their health and quality of life.

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Study of the uses of Information and Communication Technologies by Pain Treatment Unit Physicians

et al. 2017

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Adequate use of Information and Communication Technologies (ICTs) in health has been shown to save the patient and caregiver time, improve access to the health system, improve diagnosis and control of disease or treatment. All this results in cost savings, and more importantly, they help improve the quality of service and the lives of patients. The purpose of this study is to analyse the differences in the uses of this ICTs between those physicians that belong to Pain Treatment Units (PU) and other physicians that work in pain not linked to these PUs. An online survey, generated by Netquest online survey tool, was sent to both groups of professionals and the data collected was statistical analysed through a logistic regression methodology which is the Logit binomial model. Our results show that those physicians that belong to PUs use ICTs more frequently and consider it more relevant to their clinical practice.

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Perceived needs for the information communication technology (ICT)‐based personalized health management program, and its association with information provision, health‐related quality of life (HRQOL), and decisional conflict in cancer patients

Abstract: We found that higher income, information provision experience, problematic HRQOL, and decisional conflicts are significantly associated with the need for an ICT-based tailored self-management program.

Cited by 9 publications

References 24 publications

The major effects of health-related quality of life on 5-year survival prediction among lung cancer survivors: applications of machine learning

The major effects of health-related quality of life on 5-year survival prediction among lung cancer survivors: applications of machine learning

Information Provision, Decision Self-efficacy, and Decisional Conflict in Adopting Health Behaviors Among Patients Treated for Colorectal Cancer

Study of the uses of Information and Communication Technologies by Pain Treatment Unit Physicians

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