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      Translation, cross-cultural adaptation, and validation of the Chinese version of self-efficacy and attitudes for providing Mouth Care scale

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          Abstract

          Background

          In recent years, oral care for older people has received extensive attention in long-term care facilities. The Self-Efficacy for Providing Mouth Care (SE-PMC) and Attitudes for Providing Mouth Care (A-PMC) scale evaluated the self-efficacy and attitude of nursing staff while providing oral care. However, whether this scale is valid and reliable for Chinese nursing staff in China remains unverified. This study aims to translate the English version of SE-PMC and A-PMC into Chinese and determine their reliability and validity.

          Methods

          After obtaining the author’s consent, the procedure for a double-back translation and cross-cultural adaptation was conducted to develop the Chinese version of SE-PMC and A-PMC. The validity and reliability of the Chinese version of SE-PMC and A-PMC were evaluated in a cross-sectional observational study with 852 nurses from 42 Geriatric Care Facilities (GCFs). Exploratory factor analysis (EFA) (n = 427) and confirmatory factor analysis (CFA) (n = 425) were conducted to test the construct validity and quality of the factor structures. We applied the item discrimination test and homogeneity test for item analysis. Cronbach’s alpha coefficient and split-half coefficient were adopted to evaluate internal consistency.

          Results

          The Chinese version of SE-PMC (11 items, 3 factors) and A-PMC (11 items, 2 factors) included 22 items, reflecting adequate construct validity and reliability. In addition, test-retest reliability was 0.809 for SE-PMC and 0.811 for A-PMC, evincing good stability. The Cronbach’s α coefficient of SE-PMC was 0.831, with each factor ranging from 0.793~0.906. The Cronbach’s α coefficient of the A-PMC was 0.768, with each factor ranging from 0.814~0.824. Item-Content Validity Index (I-CVI) of SE-PMC and A-PMC ranged from 0.84 ~1.00 and 0.82~1.00, respectively.

          Conclusion

          The Chinese version of SE-PMC and A-PMC was validated as a reliable assessment tool to evaluate the self-efficacy and attitude of nursing staff in GCFs for providing oral care in China.

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          Most cited references34

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          The impact of changing attitudes, norms, and self-efficacy on health-related intentions and behavior: A meta-analysis.

          Paschal Sheeran, William Klein, Eleanor Miles … (2016)
          Several health behavior theories converge on the hypothesis that attitudes, norms, and self-efficacy are important determinants of intentions and behavior. However, inferences regarding the relation between these cognitions and intention or behavior rest largely on correlational data that preclude causal inferences. To determine whether changing attitudes, norms, or self-efficacy leads to changes in intentions and behavior, investigators need to randomly assign participants to a treatment that significantly increases the respective cognition relative to a control condition, and test for differences in subsequent intentions or behavior. The present review analyzed findings from 204 experimental tests that met these criteria.
          Article 0 comments Cited 221 times – based on 0 reviews     Review now
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            Assessing the Quality and Appropriateness of Factor Solutions and Factor Score Estimates in Exploratory Item Factor Analysis

            Pere Ferrando, Urbano Lorenzo-Seva (2017)
            This article proposes a comprehensive approach for assessing the quality and appropriateness of exploratory factor analysis solutions intended for item calibration and individual scoring. Three groups of properties are assessed: (a) strength and replicability of the factorial solution, (b) determinacy and accuracy of the individual score estimates, and (c) closeness to unidimensionality in the case of multidimensional solutions. Within each group, indices are considered for two types of factor-analytic models: the linear model for continuous responses and the categorical-variable-methodology model that treats the item scores as ordered-categorical. All the indices proposed have been implemented in a noncommercial and widely known program for exploratory factor analysis. The usefulness of the proposal is illustrated with a real data example in the personality domain.
            Article 0 comments Cited 96 times – based on 0 reviews     Review now
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              Old and New Ideas for Data Screening and Assumption Testing for Exploratory and Confirmatory Factor Analysis

              David B. Flora, Cathy LaBrish, R. Chalmers (2012)
              We provide a basic review of the data screening and assumption testing issues relevant to exploratory and confirmatory factor analysis along with practical advice for conducting analyses that are sensitive to these concerns. Historically, factor analysis was developed for explaining the relationships among many continuous test scores, which led to the expression of the common factor model as a multivariate linear regression model with observed, continuous variables serving as dependent variables, and unobserved factors as the independent, explanatory variables. Thus, we begin our paper with a review of the assumptions for the common factor model and data screening issues as they pertain to the factor analysis of continuous observed variables. In particular, we describe how principles from regression diagnostics also apply to factor analysis. Next, because modern applications of factor analysis frequently involve the analysis of the individual items from a single test or questionnaire, an important focus of this paper is the factor analysis of items. Although the traditional linear factor model is well-suited to the analysis of continuously distributed variables, commonly used item types, including Likert-type items, almost always produce dichotomous or ordered categorical variables. We describe how relationships among such items are often not well described by product-moment correlations, which has clear ramifications for the traditional linear factor analysis. An alternative, non-linear factor analysis using polychoric correlations has become more readily available to applied researchers and thus more popular. Consequently, we also review the assumptions and data-screening issues involved in this method. Throughout the paper, we demonstrate these procedures using an historic data set of nine cognitive ability variables.
              Article 0 comments Cited 47 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Lan Chen: Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: InvestigationRole: Writing – review & editing
                Liyan Gu:
                ORCID: https://orcid.org/0000-0002-9955-3937
                Role: MethodologyRole: SupervisionRole: ValidationRole: Writing – original draft
                Xianchen Li: Role: SoftwareRole: Validation
                Wenyao Chen: Role: InvestigationRole: Project administration
                Lingjuan Zhang: Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: Writing – review & editing
                Tanay Chaubal: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (iso-abbrev): PLoS One
                Journal ID (publisher-id): plos
                Title: PLoS ONE
                Publisher: Public Library of Science (San Francisco, CA USA )
                ISSN (Electronic): 1932-6203
                Publication date (Electronic): 22 July 2022
                Publication date Collection: 2022
                Volume: 17
                Issue: 7
                Electronic Location Identifier: e0271800
                Affiliations
                [1 ] Nursing Department, Shanghai General Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
                [2 ] Education and Scientific Research Department of Clinical Nursing, Changhai Hospital Affiliated to Naval Medical University, Shanghai, China
                [3 ] Department of Neurology, NO. 905 Hospital of PLA Navy, Shanghai, China
                [4 ] Clinical Research Center, Shanghai General Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
                [5 ] Shanghai Quality Control Center of Geriatric Care, Shanghai, China
                International Medical University, MALAYSIA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-9955-3937
                Article
                Publisher ID: PONE-D-22-06893
                DOI: 10.1371/journal.pone.0271800
                PMC ID: 9307152
                PubMed ID: 35867694
                SO-VID: 7345a4af-515e-4c6d-83f3-1c059ce8533c
                Copyright © © 2022 Chen et al
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 26 March 2022
                Date accepted : 8 July 2022
                Page count
                Figures: 2, Tables: 4, Pages: 12
                Funding
                Funded by: the Standardization Pilot Program of Shanghai Quality and Technical Supervision Bureau
                Award ID: S18-04-017
                Award Recipient :
                Funded by: Science and Technology Research Project of Health and Health Committee of Songjiang District
                Award ID: 316
                Award Recipient :
                This study was funded by a grant from the Standardization Pilot Program of Shanghai Quality and Technical Supervision Bureau (S18-04-017) and Science and Technology Research Project of Health and Health Committee of Songjiang District (Oral health promotion strategies for the elderly population in long-term care institutions in Songjiang District-316).
                Categories
                Subject: Research Article
                Subject: Medicine and Health Sciences
                Subject: Oral Medicine
                Subject: Oral Health
                Subject: Biology and Life Sciences
                Subject: Anatomy
                Subject: Digestive System
                Subject: Teeth
                Subject: Medicine and Health Sciences
                Subject: Anatomy
                Subject: Digestive System
                Subject: Teeth
                Subject: Biology and Life Sciences
                Subject: Anatomy
                Subject: Head
                Subject: Jaw
                Subject: Teeth
                Subject: Medicine and Health Sciences
                Subject: Anatomy
                Subject: Head
                Subject: Jaw
                Subject: Teeth
                Subject: People and Places
                Subject: Population Groupings
                Subject: Professions
                Subject: Medical Personnel
                Subject: Nurses
                Subject: Medicine and Health Sciences
                Subject: Health Care
                Subject: Health Care Providers
                Subject: Nurses
                Subject: Research and Analysis Methods
                Subject: Mathematical and Statistical Techniques
                Subject: Statistical Methods
                Subject: Factor Analysis
                Subject: Physical Sciences
                Subject: Mathematics
                Subject: Statistics
                Subject: Statistical Methods
                Subject: Factor Analysis
                Subject: Biology and Life Sciences
                Subject: Psychology
                Subject: Psychological Attitudes
                Subject: Social Sciences
                Subject: Psychology
                Subject: Psychological Attitudes
                Subject: Medicine and Health Sciences
                Subject: Oral Medicine
                Subject: Medicine and Health Sciences
                Subject: Health Care
                Subject: Caregivers
                Subject: Medicine and Health Sciences
                Subject: Health Care
                Subject: Geriatric Care
                Custom metadata
                Data Availability All relevant data are within the paper and its Supporting Information files.

                ScienceOpen disciplines: Uncategorized
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                ScienceOpen disciplines: Uncategorized

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