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      Financial toxicity among pediatric oncology families during therapy and early survivorship: a qualitative analysis

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          Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups.

          Qualitative research explores complex phenomena encountered by clinicians, health care providers, policy makers and consumers. Although partial checklists are available, no consolidated reporting framework exists for any type of qualitative design. To develop a checklist for explicit and comprehensive reporting of qualitative studies (in depth interviews and focus groups). We performed a comprehensive search in Cochrane and Campbell Protocols, Medline, CINAHL, systematic reviews of qualitative studies, author or reviewer guidelines of major medical journals and reference lists of relevant publications for existing checklists used to assess qualitative studies. Seventy-six items from 22 checklists were compiled into a comprehensive list. All items were grouped into three domains: (i) research team and reflexivity, (ii) study design and (iii) data analysis and reporting. Duplicate items and those that were ambiguous, too broadly defined and impractical to assess were removed. Items most frequently included in the checklists related to sampling method, setting for data collection, method of data collection, respondent validation of findings, method of recording data, description of the derivation of themes and inclusion of supporting quotations. We grouped all items into three domains: (i) research team and reflexivity, (ii) study design and (iii) data analysis and reporting. The criteria included in COREQ, a 32-item checklist, can help researchers to report important aspects of the research team, study methods, context of the study, findings, analysis and interpretations.
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            Socioeconomic disparities in health in the United States: what the patterns tell us.

            We aimed to describe socioeconomic disparities in the United States across multiple health indicators and socioeconomic groups. Using recent national data on 5 child (infant mortality, health status, activity limitation, healthy eating, sedentary adolescents) and 6 adult (life expectancy, health status, activity limitation, heart disease, diabetes, obesity) health indicators, we examined indicator rates across multiple income or education categories, overall and within racial/ethnic groups. Those with the lowest income and who were least educated were consistently least healthy, but for most indicators, even groups with intermediate income and education levels were less healthy than the wealthiest and most educated. Gradient patterns were seen often among non-Hispanic Blacks and Whites but less consistently among Hispanics. Health in the United States is often, though not invariably, patterned strongly along both socioeconomic and racial/ethnic lines, suggesting links between hierarchies of social advantage and health. Worse health among the most socially disadvantaged argues for policies prioritizing those groups, but pervasive gradient patterns also indicate a need to address a wider socioeconomic spectrum-which may help garner political support. Routine health reporting should examine socioeconomic and racial/ethnic disparity patterns, jointly and separately.
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              Measuring financial toxicity as a clinically relevant patient‐reported outcome: The validation of the COmprehensive Score for financial Toxicity (COST)

              BACKGROUND Cancer and its treatment lead to increased financial distress for patients. To the authors' knowledge, to date, no standardized patient‐reported outcome measure has been validated to assess this distress. METHODS Patients with AJCC Stage IV solid tumors receiving chemotherapy for at least 2 months were recruited. Financial toxicity was measured by the COmprehensive Score for financial Toxicity (COST) measure. The authors collected data regarding patient characteristics, clinical trial participation, health care use, willingness to discuss costs, psychological distress (Brief Profile of Mood States [POMS]), and health‐related quality of life (HRQOL) as measured by the Functional Assessment of Cancer Therapy: General (FACT‐G) and the European Organization for Research and Treatment of Cancer (EORTC) QOL questionnaires. Test‐retest reliability, internal consistency, and validity of the COST measure were assessed using standard‐scale construction techniques. Associations between the resulting factors and other variables were assessed using multivariable analyses. RESULTS A total of 375 patients with advanced cancer were approached, 233 of whom (62.1%) agreed to participate. The COST measure demonstrated high internal consistency and test‐retest reliability. Factor analyses revealed a coherent, single, latent variable (financial toxicity). COST values were found to be correlated with income (correlation coefficient [r] = 0.28; P<.001), psychosocial distress (r = ‐0.26; P<.001), and HRQOL, as measured by the FACT‐G (r = 0.42; P<.001) and by the EORTC QOL instruments (r = 0.33; P<.001). Independent factors found to be associated with financial toxicity were race (P = .04), employment status (P<.001), income (P = .003), number of inpatient admissions (P = .01), and psychological distress (P = .003). Willingness to discuss costs was not found to be associated with the degree of financial distress (P = .49). CONCLUSIONS The COST measure demonstrated reliability and validity in measuring financial toxicity. Its correlation with HRQOL indicates that financial toxicity is a clinically relevant patient‐centered outcome. Cancer 2017;123:476–484. © 2016 American Cancer Society.
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                Journal
                Supportive Care in Cancer
                Support Care Cancer
                Springer Science and Business Media LLC
                0941-4355
                1433-7339
                January 2025
                December 17 2024
                January 2025
                : 33
                : 1
                Article
                10.1007/s00520-024-09093-y
                c61042cc-8eff-4187-96b7-683e963200e5
                © 2025

                https://www.springernature.com/gp/researchers/text-and-data-mining

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