Evidence map›Paper›PMID 36901236›Full record

ArticleInternational journal of environmental research and public health2023

Chinese Translation and Cross-Cultural Adaptation of the Return-to-Work Self-Efficacy Scale among Chinese Female Breast Cancer Survivors.

Andy S K Cheng, Suki Lee, Nadia Li, Sammi Tsang, Yingchun Zeng

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Article in International journal of environmental research and public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
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  4. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Andy S K ChengDepartment of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China.ORCID 0000-0001-7503-5273
Suki LeeYang Memorial Methodist Social Service, Hong Kong, China.
Nadia LiHong Kong Lutheran Social Service, Hong Kong, China.
Sammi TsangHeep Hong Society, Hong Kong, China.
Yingchun ZengSchool of Medicine, Zhejiang University City College, Hangzhou 242332, China.ORCID 0000-0001-9250-4086

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer is the leading cancer type among women globally. Since breast cancer has a high survival rate, most survivors are likely to return to work (RTW). In recent years, breast cancer cases have risen significantly in younger age groups. As self-efficacy is an important factor in the success of RTW, this study performed a translation and cross-cultural adaptation of the Chinese version of the Return-To-Work Self-Efficacy Scale (CRTWSE-19) and examined its psychometric properties in patients with breast cancer. This validation study followed standard guidelines, including forward translation, back translation, cross-cultural adaptation, and psychometric testing. The results of this study show that the CRTWSE-19 met reliability standards, including high internal reliability for the total scores and subscales. An exploratory factor analysis of 19 items extracted 3 factors showing consistency with the original version of the RTWSE-19. Criterion validity was demonstrated by comparing subdomains with the Fear of Cancer Recurrence Inventory. Furthermore, the known-group validity was studied by comparing mean scores among the unemployed group and the employed group. We conclude that the CRTWSE-19 has very good screening accuracy and is able to discriminate between working and unemployed populations. It can facilitate health care professionals in triaging, planning, and evaluating interventions in clinical practice.

Indexed as

Breast NeoplasmsCancer SurvivorsCross-Cultural ComparisonFemaleHumansNeoplasm Recurrence, LocalPsychometricsReproducibility of ResultsReturn to WorkSelf EfficacySurveys and QuestionnairesSurvivorsbreast cancerreturn-to-workself-efficacy

Identifiers

PMID36901236
PMCPMC10001523

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Read underepoch 390

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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.