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      Development and psychometric evaluation of the Emotional Intelligence Test (EMI‐T) for social care and healthcare student selection

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Aim

          To develop an emotional intelligence (EI) test and evaluate its psychometrics for social and healthcare student selection.

          Design

          A cross‐sectional methodological design.

          Methods

          The test was developed based on a systematic review and focus group interviews. Content validity was evaluated with expert panels, and preliminary psychometrics with two pilot studies. Descriptive statistics, correlations and item response theory were used.

          Data Sources

          Search was conducted in six databases 2018. Focus group interviews were conducted with educators and professionals in 2019. Expert panels with doctoral students, researchers and educators were conducted in 2020. Pilot tests with students were conducted 2020–2021. The developed test was administered to 4808 applicants 2021.

          Results

          The test included four subscales. Correlations support the test's theoretical structure. The items were mainly easy.

          Conclusion

          The test assesses EI objectively and comprehensively. The item‐level distractor analysis can be used for further test development.

          Impacts

          Social care and healthcare students engage in clinical practice early in their studies, and these environments can be emotionally challenging. Assessing EI in student selection with adequate test can help the institutions of higher education to select the students with required abilities to succeed in the studies. The assessment of EI during student selection also provides information higher education institutions could use to develop and provide support interventions. The results may also encourage practice placements to include EI elements as learning objective. The results of this study and especially the use of IRT and detailed distractor analysis to evaluate the psychometric properties of EMI‐T can benefit researchers and educators that develop or evaluate objective assessment tools with multiple choice questions.

          Implications for the profession and/or patient care

          Emotional intelligence is important for students to enable professional interaction.

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          Most cited references34

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          Correlation Coefficients

          Patrick Schober, Christa Boer, Lothar A Schwarte (2018)
          Correlation in the broadest sense is a measure of an association between variables. In correlated data, the change in the magnitude of 1 variable is associated with a change in the magnitude of another variable, either in the same (positive correlation) or in the opposite (negative correlation) direction. Most often, the term correlation is used in the context of a linear relationship between 2 continuous variables and expressed as Pearson product-moment correlation. The Pearson correlation coefficient is typically used for jointly normally distributed data (data that follow a bivariate normal distribution). For nonnormally distributed continuous data, for ordinal data, or for data with relevant outliers, a Spearman rank correlation can be used as a measure of a monotonic association. Both correlation coefficients are scaled such that they range from -1 to +1, where 0 indicates that there is no linear or monotonic association, and the relationship gets stronger and ultimately approaches a straight line (Pearson correlation) or a constantly increasing or decreasing curve (Spearman correlation) as the coefficient approaches an absolute value of 1. Hypothesis tests and confidence intervals can be used to address the statistical significance of the results and to estimate the strength of the relationship in the population from which the data were sampled. The aim of this tutorial is to guide researchers and clinicians in the appropriate use and interpretation of correlation coefficients.
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            The content validity index: are you sure you know what's being reported? Critique and recommendations.

            Denise Polit, Cheryl Beck (2006)
            Scale developers often provide evidence of content validity by computing a content validity index (CVI), using ratings of item relevance by content experts. We analyzed how nurse researchers have defined and calculated the CVI, and found considerable consistency for item-level CVIs (I-CVIs). However, there are two alternative, but unacknowledged, methods of computing the scale-level index (S-CVI). One method requires universal agreement among experts, but a less conservative method averages the item-level CVIs. Using backward inference with a purposive sample of scale development studies, we found that both methods are being used by nurse researchers, although it was not always possible to infer the calculation method. The two approaches can lead to different values, making it risky to draw conclusions about content validity. Scale developers should indicate which method was used to provide readers with interpretable content validity information. (c) 2006 Wiley Periodicals, Inc.
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              The Ability Model of Emotional Intelligence: Principles and Updates

              John Mayer, David Caruso, Peter Salovey (2016)
              Article 0 comments Cited 167 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Anne Pienimaa:
                ORCID: https://orcid.org/0000-0003-0857-5776
                anne.m.pienimaa@utu.fi
                Journal
                Journal ID (nlm-ta): J Adv Nurs
                Journal ID (iso-abbrev): J Adv Nurs
                Journal ID (doi): 10.1111/(ISSN)1365-2648
                Journal ID (publisher-id): JAN
                Title: Journal of Advanced Nursing
                Publisher: John Wiley and Sons Inc. (Hoboken )
                ISSN (Print): 0309-2402
                ISSN (Electronic): 1365-2648
                Publication date (Electronic): 27 December 2022
                Publication date (Print): February 2023
                Volume: 79
                Issue: 2 ( doiID: 10.1111/jan.v79.2 )
                Pages: 850-863
                Affiliations
                [ 1 ] Department of Nursing Science 20014 University of Turku Turku Finland
                [ 2 ] Metropolia University of Applied Sciences Helsinki Finland
                [ 3 ] UAS Student Selection Consortium Laurea University of Applied Sciences Vantaa Finland
                [ 4 ] Department of Teacher Education University of Turku Turku Finland
                [ 5 ] Department of Health Sciences Tampere University, Tampere University Hospital Tampere Finland
                Author notes
                [*] [* ] Correspondence

                Anne Pienimaa, Department of Nursing Science, 20014 University of Turku, Turku, Finland.

                Email: anne.m.pienimaa@ 123456utu.fi

                Author information
                https://orcid.org/0000-0003-0857-5776
                https://orcid.org/0000-0002-7538-9837
                Article
                Publisher ID: JAN15557 Other ID: JAN-2022-0636.R2
                DOI: 10.1111/jan.15557
                PMC ID: 10107289
                PubMed ID: 36575904
                SO-VID: b6f253a7-c74d-463d-b4e3-a0b63edc3d24
                Copyright © © 2022 The Authors. Journal of Advanced Nursing published by John Wiley & Sons Ltd.
                License:

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                Date revision received : 07 November 2022
                Date received : 10 April 2022
                Date accepted : 19 December 2022
                Page count
                Figures: 3, Tables: 4, Pages: 14, Words: 9570
                Funding
                Funded by: Development Project for Student Selection in Finnish Universities of Applied Sciences (UAS) 2017‐2020. , doi 10.13039/501100016234;
                Award ID: OKM/200/523/2016
                Categories
                Subject: Research Methodology: Instrument Development
                Subject: Research Papers
                Subject: Research Methodology: Instrument Development
                Custom metadata
                source-schema-version-number 2.0
                cover-date February 2023
                details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:6.2.7 mode:remove_FC converted:17.04.2023

                ScienceOpen disciplines: Nursing
                Keywords: emotional intelligence,instrument development,nursing education,psychometric evaluation,social care and healthcare education,student selection
                Data availability:
                ScienceOpen disciplines: Nursing
                Keywords: emotional intelligence, instrument development, nursing education, psychometric evaluation, social care and healthcare education, student selection

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