Identification of the Knowledge Structure of Cancer Survivors’ Return to Work and Quality of Life: A Text Network Analysis

Kim, Kisook; Lee, Ki-Seong

doi:10.3390/ijerph17249368

Cited by 9 publications

(6 citation statements)

References 33 publications

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“…“Patient,” “data,” “health,” “system,” and “technology” showed high frequency and centrality (Table 1), implying that they appear regularly in research alongside a large number of other keywords. Keywords with high betweenness centrality are those with a high connectivity of research subdomains, thus acting as bridges between other nodes 35 …”

Section: Resultsmentioning

confidence: 99%

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Identifying the Knowledge Structure and Trends of Nursing Informatics

Park¹,

Park²

2022

CIN: Computers, Informatics, Nursing

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With the advent of the information age and technological development, the importance of digital health technologies has increased. Subsequently, nursing informatics has been developed to enhance the effectiveness of healthcare information management and communication. This study aimed to identify the nursing informatics knowledge structure and research trends through quantitative analysis using text network analysis. Here, we analyzed 14 225 studies published by 2020. The knowledge structure of nursing informatics and changes therein were clarified by identifying and analyzing the core keywords, topics, and changes in the topics of related studies over time. We identified “patient,” “health,” “system,” and “information” as core keywords connecting other keywords. Over time, the networks between “information,” “communication,” and “technology” strengthened, and “patient safety” and “quality” have recently emerged as research keywords. This change indicates an increase in the importance of nursing education on technology. Similar changes appeared in the topic analysis, showing an increased proportion of research related to system and technology and nursing education. These results can broaden a systematic understanding of nursing informatics research. Furthermore, given these findings, the importance of nursing informatics on patient safety and nursing education—based on the development of systems and technology—can be expected to continue growing.

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Section: Resultsmentioning

confidence: 99%

“…Keywords with high betweenness centrality are those with a high connectivity of research subdomains, thus acting as bridges between other nodes. 35 …”

Section: Resultsmentioning

confidence: 99%

Identifying the Knowledge Structure and Trends of Nursing Informatics

Park¹,

Park²

2022

CIN: Computers, Informatics, Nursing

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“…We asked each respondent about the factors affecting RTW [ 7 , 9 , 11 , 12 , 17 , 18 , 19 ]: sex, age of onset, stage of cancer, treatment (surgery, radiation therapy, and pharmacotherapy), number of years since the diagnosis, support from family and friends, consultation with others, use of peer support, employment status at diagnosis, informing the workplace that you have cancer, support from the workplace, provision of information on continued employment via the medical staff, and continued employment. In the current study, a leave of absence was treated as a continuation of employment in the same workplace.…”

Section: Methodsmentioning

confidence: 99%

Income Change One Year after Confirmed Cancer Diagnosis and Its Associated Factors in Japanese Patients

Murakami

Kanda

Ngatu

et al. 2022

IJERPH

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The number of patients who survive for a long time after cancer diagnosis is rapidly increasing; however, such patients experience major problems such as returning to work and changes in their income. This study aimed to determine the extent of income changes of cancer patients during the first year after cancer diagnosis and identify the influencing factors. From November 2019 through January 2020, we conducted a multicenter, self-administered anonymous survey of cancer patients in Kagawa Prefecture, Japan. The number of questionnaires collected was 483 (recovery rate 60.4%), and the number of participants who met the inclusion criteria was 72. Mean year-on-year income level one year since cancer diagnosis was 66% (SD: 32%; median: 70%). Cancer stage (p = 0.016), employment status at diagnosis (p = 0.006), and continued employment at the same workplace (p = 0.001) were associated with income change. Findings from this study showed that cancer patients lost one-thirds of their income one year after their diagnosis. It was related to the stage of their illness, employment status, and continued employment at their workplace just before the diagnosis. Employers should provide cancer patients with the support they need to keep them employed.

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“…Traditional literature analysis methods have been criticized for their inability to comprehensively identify central themes and major discussions [6]. In response, recent academic research has explored the use of big data analysis techniques, such as text network analysis and topic modeling, to identify research trends in specific fields [7]. Keyword network analysis is a technique that extracts significant words from text, identifies connections between them, and restructures them into a visual network [8].…”

Section: Introductionmentioning

confidence: 99%

Research trends in the Korean Journal of Women Health Nursing from 2011 to 2021: a quantitative content analysis

Nho

Park

2023

Korean J Women Health Nurs

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Purpose: Topic modeling is a text mining technique that extracts concepts from textual data and uncovers semantic structures and potential knowledge frameworks within context. This study aimed to identify major keywords and network structures for each major topic to discern research trends in women’s health nursing published in the Korean Journal of Women Health Nursing (KJWHN) using text network analysis and topic modeling.Methods: The study targeted papers with English abstracts among 373 articles published in KJWHN from January 2011 to December 2021. Text network analysis and topic modeling were employed, and the analysis consisted of five steps: (1) data collection, (2) word extraction and refinement, (3) extraction of keywords and creation of networks, (4) network centrality analysis and key topic selection, and (5) topic modeling.Results: Six major keywords, each corresponding to a topic, were extracted through topic modeling analysis: “gynecologic neoplasms,” “menopausal health,” “health behavior,” “infertility,” “women’s health in transition,” and “nursing education for women.”Conclusion: The latent topics from the target studies primarily focused on the health of women across all age groups. Research related to women’s health is evolving with changing times and warrants further progress in the future. Future research on women’s health nursing should explore various topics that reflect changes in social trends, and research methods should be diversified accordingly.

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Identification of the Knowledge Structure of Cancer Survivors’ Return to Work and Quality of Life: A Text Network Analysis

Cited by 9 publications

References 33 publications

Identifying the Knowledge Structure and Trends of Nursing Informatics

Identifying the Knowledge Structure and Trends of Nursing Informatics

Income Change One Year after Confirmed Cancer Diagnosis and Its Associated Factors in Japanese Patients

Research trends in the Korean Journal of Women Health Nursing from 2011 to 2021: a quantitative content analysis

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