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

Racial/Ethnic Disparities in HRQoL and Associated Risk Factors in Colorectal Cancer Survivors: With a Focus on Social Determinants of Health (SDOH)

PURPOSE

This study aimed to understand how health-related quality of life (HRQoL) differs by race/ethnicity in colorectal (CRC) survivors. We aimed to 1) examine racial/ethnic disparities in HRQoL, and 2) explore the roles of social determinants of health (SDOH) risk factors for HRQoL differ by racial/ethnic groups.

METHODS

In 2,492 adult CRC survivors using Behavioral Risk Factor Surveillance System (BRFSS) survey data (from 2014 to 2021, excluding 2015 due to the absence of CRC data), we used the Centers for Disease Control and Prevention (CDC) HRQoL measure, categorized into "better" and "poor." Multivariate logistic regressions with prevalence risk (PR) were employed for our primary analyses.

RESULTS

Compared with non-Hispanic Whites (NHW), non-Hispanic Blacks (NHB) (PR = 0.61, p = .045) and Hispanics (PR = 0.32, p < .001) reported worse HRQoL in adjusted models. In adjusted models, unemployed/retired and low-income levels were common risk factors for worse HRQoL across all comparison groups (NHW, NHB, non-Hispanic other races, and Hispanics). Other SDOH associated with worse HRQoL include divorced/widowed/never married marital status (non-Hispanic other races and Hispanics), living in rural areas (NHW and NHB), and low education levels (NHB and Hispanics). Marital status, education, and employment status significantly interacted with race/ethnicity, with the strongest interaction between Hispanics and education (PR = 2.45, p = .045) in adjusted models.

CONCLUSION

These findings highlight the need for culturally tailored interventions targeting modifiable factors (e.g., social and financial supports, health literacy), specifically for socially vulnerable CRC survivors, to address the disparities in HRQoL among different racial/ethnic groups.

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

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.

Exploring the independent association of employment status to cancer survivors' health-related quality of life

BACKGROUND

Having a job has been associated with better Health-Related Quality of Life (HRQOL) in cancer survivors. However, the sociodemographic and disease-related profiles characterizing the survivors being employed and those having better HRQOL largely overlap. The present study aims to discern the degree to which employment status is independently associated with cancer survivors' HRQOL or if it mainly reflects the impact of other sociodemographic and cancer-related variables.

METHODS

Cross-sectional study on a heterogeneous sample of 772 working-age survivors of adult-onset cancer. An instrument specifically designed to assess HRQOL in cancer survivors and Multivariate Variance Analysis (MANOVA) were used.

RESULTS

Survival phase, cancer type, and employment status showed the main effects on cancer survivors' HRQOL. In particular, being employed (vs unemployed) had the greatest positive association with HRQOL, affecting ten of the twelve HRQOL domains considered. Also, interaction effects highlighted the role of age (younger) and marital status (single) as risk factors for a greater negative impact of variables affecting the survivor's HRQOL.

CONCLUSIONS

The application of a multivariate methodology sheds new light on two relevant issues for the cancer survivor's HRQOL: (i) the existence of differences between diagnostic groups that are not attributed to other variables such as sex, and (ii) the important and independent role that employment status plays. Comprehensive cancer survivorship care should focus more on high-risk groups and include having a job as an essential aspect to consider and prompt. The fact that the employment status is susceptible to change represents a valuable opportunity to care for the wellbeing of this population.

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

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.

Identifying the Knowledge Structure and Trends of Nursing Informatics: A Text Network Analysis

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.

Un-Meetings as tools for translational idea generation: A semantic content analysis of an Opioid Crisis Un-Meeting

Background

Team development and idea generation are key intertwined steps in translational science that need a framework to accommodate unstructured, participatory interactions. To this end, we introduced Un-Meetings to the Clinical and Translational Science Awards (CTSA) Program, innovative events that facilitate cross-disciplinary idea generation and informal discussions between translational scientists, policy makers, community members, advocates, and public health professionals. Here we describe a mixed methods study to characterize the conceptual diversity and clusterization of ideas generated through an Opioid Crisis Un-Meeting.

Methods

An Un-Meeting targeting translation science approaches to the opioid crisis were hosted at the University of Rochester Center for Leading Innovation and Collaboration (CLIC). We used semantic analysis and conceptual mapping of keywords to analyze how attendee-led idea generation sessions identified topics for breakout discussions.

Results

One hundred and two individuals from 40 institutions proposed 150 unique ideas that were grouped into 23 breakout sessions. Network analysis showed that diverse pools of experts were bridged by topics addressing the complexities of the opioid crisis. Two clusters emerged: (1) systems, contexts, and community engagement, and (2) technologies, innovations, and treatment advancements.

Conclusions

The cross-disciplinary nature of topic areas that bridge across thematic communities provide opportunities for CTSA programs to engage and support development of diverse translational teams. Potential opportunities for team building include technological advancements of opioid prevention, treatment, surveillance, systems approaches, and studies focusing on special populations and health disparities. The analysis method here may be useful in identifying naturally emerging teams of experts and community gaps when addressing large problems.

Web-Based Research Trends on Child and Adolescent Cancer Survivors Over the Last 5 Years: Text Network Analysis and Topic Modeling Study

Background

Being diagnosed with cancer during childhood or adolescence can disrupt important periods in an individual’s physical, psychosocial, and spiritual development and potentially reduce the quality of life (QOL) after treatment. Research is urgently required to improve the QOL for child and adolescent cancer survivors, and it is necessary to analyze the trends in prior research reported in international academic journals to identify knowledge structures.

Objective

This study aims to identify the main keywords based on network centrality, subgroups (clusters) of keyword networks by using a cohesion analysis method, and the main theme of child and adolescent cancer survivor–related research abstracts through topic modeling. This study also aims to label the subgroups by comparing the results of the cohesion and topic modeling.

Methods

A text network analysis method and topic modeling were used to explore the main trends in child and adolescent cancer survivor research by structuring a network of keyword (semantic morphemes) co-occurrence in the abstracts of articles published in 5 major web-based databases from 2016 to 2020. A total of 1677 child and adolescent cancer survivor–related studies were used for data analyses. Data selection, processing, and analyses were also conducted.

Results

The top 5 keywords in terms of degree and eigenvector centrality were risk, control interval, radiation, childhood cancer treatment, and diagnosis. Of the 1677 studies used for data analyses, cluster 1 included 780 (46.51%) documents under risk management, cluster 2 contained 557 (33.21%) articles under health-related QOL and supportive care, and cluster 3 consisted of 340 (20.27%) studies under cancer treatment and complications.

Conclusions

This study is significant in that it confirms the knowledge structure based on the main keywords and cross-disciplinary trends in child and adolescent cancer survivor research published in the last 5 years worldwide. The primary goal of child and adolescent cancer survivor research is to prevent and manage the various aspects of the problems encountered during the transition to a normal life and to improve the overall QOL. To this end, it is necessary to further revitalize the study of the multidisciplinary team approach for the promotion of age-specific health behaviors and the development of intervention strategies with increased feasibility for child and adolescent cancer survivors.