Evidence map›Paper›PMID 37024607›Full record

ArticleJournal of cancer education : the official journal of the American Association for Cancer Education2023

Development of a Japanese Scale that Evaluates the Level of Nursing Support Provided to Patients for Decision-Making in Cancer Clinical Trials.

Izumi Kohara, Noriko Fujiwara, Shuko Tamaki, Hiroko Nakahama, Akiko Nosaki, Miki Hosoya, Midori Yabuki, Mayumi Yamamoto, Chiemi Kojima, Keiichi Fujiwara

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Article in Journal of cancer education : the official journal of the American Association for Cancer Education, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Izumi KoharaSchool of Nursing, Jichi Medical University, Tochigi, Japan. ikohara@jichi.ac.jp.ORCID http://orcid.org/0000-0002-5882-9917
Noriko FujiwaraDepartment of Palliative Medicine and Advanced Clinical Oncology, IMSUT Hospital, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.ORCID http://orcid.org/0000-0001-8201-9490
Shuko TamakiDepartment of Nursing, Saitama Medical University International Medical Center, Saitama, Japan.
Hiroko NakahamaDepartment of Nursing National Cancer Center Hospital, Tokyo, Japan.ORCID http://orcid.org/0000-0002-7053-955X
Akiko NosakiGraduate School of Nursing, Chiba University, Chiba, Japan.ORCID http://orcid.org/0000-0003-4156-6636
Miki HosoyaDepartment of Nursing National Cancer Center Hospital, Tokyo, Japan.
Midori YabukiDepartment of Nursing, Saitama Medical University International Medical Center, Saitama, Japan.
Mayumi YamamotoDepartment of Nursing, Jichi Medical University Hospital, Tochigi, Japan.
Chiemi KojimaDepartment of Nursing National Cancer Center Hospital, Tokyo, Japan.
Keiichi FujiwaraDepartment of Gynecologic Oncology, Saitama Medical University International Medical Center, Saitama, Japan.ORCID http://orcid.org/0000-0002-7388-0243

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical nurses need learning programs that are useful in nursing support for patients' decision-making (NSPDM) regarding cancer clinical trials (CCTs). The usefulness of the learning program can be evaluated if the practices of NSPDM before and after participation in the learning program can be compared. We developed a scale to measure the level of self-assessed NSPDM regarding participation in a CCT. Thirty-two items of scale were developed in Japanese based on previous literature. Based on the results of a pilot study, items with similar meanings were removed and the validity of the 26 scale items was statistically examined in terms of construct validity and reliability. The study population was clinical nurses and included clinical research nurses. We received 102 valid responses from clinical nurses. Based on the bias of the boxplot distribution and the ceiling and floor effects for the items analysis of the 26-item draft scale, 17 items remained. Exploratory factor analysis (EFA) revealed that the scale consisted of three subscales and 17 items. Regarding fit indices of the model, the goodness-of-fit index (GFI), adjusted GFI (AGFI), comparative fit index (CFI), and root mean square error of application (RMSEA) were 0.775, 0.704, 0.477, and 0.081, respectively. The Cronbach's alpha coefficient for the overall scale was 0.951, with subscales ranging from 0.820 to 0.942. The validity and reliability of this scale were acceptable. This scale may be helpful to evaluate the usefulness of learning programs, i.e., the practice level of NSPDM.

Indexed as

Decision MakingNeoplasmsClinical Trials as TopicHumansJapanPilot ProjectsPsychometricsReproducibility of ResultsSurveys and Questionnaires

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.