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      Measuring moral distress in nurses during a pandemic: Development and validation of the COVID‐MDS

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          Abstract

          The COVID‐19 pandemic created novel patient care circumstances that may have increased nurses' moral distress, including COVID‐19 transmission risk and end‐of‐life care without family present. Well‐established moral distress instruments do not capture these novel aspects of pandemic nursing care. The purpose of this study was to develop and evaluate the psychometric properties of the COVID‐19 Moral Distress Scale (COVID‐MDS), which was designed to provide a short MDS that includes both general and COVID‐19‐specific content. Researcher‐developed COVID‐19 items were evaluated for content validity by six nurse ethicist experts. This study comprised a pilot phase and a validation phase. The pilot sample comprised 329 respondents from inpatient practice settings and the emergency department in two academic medical centers. Exploratory factor analysis (EFA) was conducted with the pilot data. The EFA results were tested in a confirmatory factor analysis (CFA) using the validation data. The validation sample comprised 5042 nurses in 107 hospitals throughout the United States. Construct validity was evaluated through CFA and known groups comparisons. Reliability was assessed by the omega coefficient from the CFA and Cronbach's alpha. A two‐factor CFA model had good model fit and strong loadings, providing evidence of a COVID‐19‐specific dimension of moral distress. Reliability for both the general and COVID‐19‐specific moral distress subscales was satisfactory. Known groups comparisons identified statistically significant correlations as theorized. The COVID‐MDS is a valid and reliable short tool for measuring moral distress in nurses including both broad systemic sources and COVID‐19 specific sources.

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          Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives

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            Comparative fit indexes in structural models.

            Normed and nonnormed fit indexes are frequently used as adjuncts to chi-square statistics for evaluating the fit of a structural model. A drawback of existing indexes is that they estimate no known population parameters. A new coefficient is proposed to summarize the relative reduction in the noncentrality parameters of two nested models. Two estimators of the coefficient yield new normed (CFI) and nonnormed (FI) fit indexes. CFI avoids the underestimation of fit often noted in small samples for Bentler and Bonett's (1980) normed fit index (NFI). FI is a linear function of Bentler and Bonett's non-normed fit index (NNFI) that avoids the extreme underestimation and overestimation often found in NNFI. Asymptotically, CFI, FI, NFI, and a new index developed by Bollen are equivalent measures of comparative fit, whereas NNFI measures relative fit by comparing noncentrality per degree of freedom. All of the indexes are generalized to permit use of Wald and Lagrange multiplier statistics. An example illustrates the behavior of these indexes under conditions of correct specification and misspecification. The new fit indexes perform very well at all sample sizes.
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              Intraclass correlations: Uses in assessing rater reliability.

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                Author and article information

                Contributors
                ecramer2@kumc.edu
                Journal
                Res Nurs Health
                Res Nurs Health
                10.1002/(ISSN)1098-240X
                NUR
                Research in Nursing & Health
                John Wiley and Sons Inc. (Hoboken )
                0160-6891
                1098-240X
                23 July 2022
                23 July 2022
                : 10.1002/nur.22254
                Affiliations
                [ 1 ] Health Services and Outcomes Research Children's Mercy Research Institute Kansas City Missouri USA
                [ 2 ] College of Nursing and Health Innovation Department of Undergraduate Nursing University of Texas at Arlington Arlington Texas USA
                [ 3 ] Department of Health Policy and Administration Pennsylvania State University State College Pennsylvania USA
                [ 4 ] Center for Health Outcomes and Policy Research, School of Nursing, Leonard Davis Institute of Health Economics University of Pennsylvania Philadelphia Pennsylvania USA
                Author notes
                [*] [* ] Correspondence Emily Cramer, Children's Mercy Research Institute, 2401 Gillham Road, Kansas City, MO 64108, USA.

                Email: ecramer@ 123456cmh.edu

                Author information
                http://orcid.org/0000-0001-7969-7522
                http://orcid.org/0000-0002-8823-3436
                Article
                NUR22254
                10.1002/nur.22254
                9349918
                35869944
                19778892-6712-4450-8281-dca40c2f152f
                © 2022 Wiley Periodicals LLC.

                This article is being made freely available through PubMed Central as part of the COVID-19 public health emergency response. It can be used for unrestricted research re-use and analysis in any form or by any means with acknowledgement of the original source, for the duration of the public health emergency.

                History
                : 21 June 2022
                : 17 July 2021
                : 27 June 2022
                Page count
                Figures: 0, Tables: 3, Pages: 10, Words: 7183
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                corrected-proof
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.1.7 mode:remove_FC converted:04.08.2022

                environment and health,ethical issues,infectious diseases,instrument development and validation,methodological research,organizational structure,professional issues,systems research/multi‐system issues,systems research

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