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      Validation of a new tool for evaluating subjects’ satisfaction with medicine package leaflets: a cross-sectional descriptive study

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          ABSTRACT

          BACKGROUND:

          Package leaflets of medicines need to be intelligible, but tools for their evaluation are scarce.

          OBJECTIVE:

          To validate a new tool for assessing subjects’ satisfaction with medicine package leaflets (LiS-RPL).

          DESIGN AND SETTING:

          Cross-sectional descriptive study conducted in two regions of Portugal (Lisbon and Centre).

          METHODS:

          503 participants (53.1% male) were selected according to convenience and homogenously distributed into three groups: 1 to 6; 7 to 12; and > 12 years of schooling. LiS-RPL was developed based on international regulation guidelines and was initially composed of 14 items. Twelve package leaflets were tested. Dimensionality calculations included: exploratory factor analysis and minimum rank factor analysis; Kaiser-Meyer-Olkin index and Bartlett’s sphericity test to assess matrix adequacy for exploratory factor analysis; exploratory bifactor analysis with Schmid-Leiman solution to detect possible existence of a broad second-order factor; and Bentler’s Simplicity Index and Loading Simplicity Index to assess factor simplicity. Diverse coefficients were calculated to assess reliability.

          RESULTS:

          Minimum rank factor analysis detected a two-factor or single-factor structure. Exploratory factor analysis with 12 items showed a two-factor structure, explaining 69.11% of the variance. These items were strongly correlated with each other (r = 0.80). Schmid-Leiman: all items seemed to represent the general factor (loadings above 0.50), which was 76.4% of the extracted variance. Simplicity indices were good (percentile 99): Bentler’s Simplicity Index of 0.99 and Loading Simplicity Index of 0.48. Internal consistency indexes indicated good reliability. LiS-RPL was shown to be homogenous.

          CONCLUSION:

          LiS-RPL is a validated tool for evaluating subjects’ satisfaction with medicine package leaflets.

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          Most cited references39

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          SPSS and SAS programs for determining the number of components using parallel analysis and Velicer’s MAP test

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            Analyzing and interpreting data from likert-type scales.

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              Dimensionality assessment of ordered polytomous items with parallel analysis.

              Parallel analysis (PA) is an often-recommended approach for assessment of the dimensionality of a variable set. PA is known in different variants, which may yield different dimensionality indications. In this article, the authors considered the most appropriate PA procedure to assess the number of common factors underlying ordered polytomously scored variables. They proposed minimum rank factor analysis (MRFA) as an extraction method, rather than the currently applied principal component analysis (PCA) and principal axes factoring. A simulation study, based on data with major and minor factors, showed that all procedures consistently point at the number of major common factors. A polychoric-based PA slightly outperformed a Pearson-based PA, but convergence problems may hamper its empirical application. In empirical practice, PA-MRFA with a 95% threshold based on polychoric correlations or, in case of nonconvergence, Pearson correlations with mean thresholds appear to be a good choice for identification of the number of common factors. PA-MRFA is a common-factor-based method and performed best in the simulation experiment. PA based on PCA with a 95% threshold is second best, as this method showed good performances in the empirically relevant conditions of the simulation experiment. © 2011 American Psychological Association
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                Author and article information

                Journal
                Sao Paulo Med J
                Sao Paulo Med J
                Sao Paulo Med J
                São Paulo Medical Journal
                Associação Paulista de Medicina - APM
                1516-3180
                1806-9460
                13 January 2020
                2019
                : 137
                : 5
                : 454-462
                Affiliations
                [I ] originalPhD. Pharmacist and Invited Professor, Department of Pharmacotherapy, Research Center for Biosciences and Health Technologies (CBIOS), Universidade Lusófona, Campo Grande, Lisbon, Portugal.
                [II ] originalPhD. Psychologist, Statistician and Assistant Professor, Psychology Department, School of Psychology and Life Sciences, Lusophone University of Humanities and Technologies (ULHT), Lisbon, Portugal; Human Environment Interaction Lab (HEI-lab), ULHT, Lisbon, Portugal; Instituto Universitário de Lisboa (ISCTE-IUL), Cis-IUL, Lisbon, Portugal.
                [III ] originalPhD. Linguist and Associate Professor, Department of General and Romance Linguistics, School of Arts and Humanities & Centre of Linguistics, University of Lisbon, Lisbon, Portugal.
                [IV ] originalPhD. Pharmacist and Associate Professor, Department of Social Pharmacy, School of Pharmacy, Research Institute for Medicines and Pharmaceutical Sciences, University of Lisbon, Lisbon, Portugal.
                Author notes
                Address for correspondence: Carla Pires. Research Center for Biosciences and Health Technologies (CBIOS), Universidade Lusófona, Campo Grande 376, 1749-024 Lisbon, Portugal. Tel. +351 217 515 500. E-mail: p5558@ 123456ulusofona.pt

                Conflict of interest: The authors declare that there were no conflicts of interest

                Article
                10.1590/1516-3180.2019.0123160919
                9745827
                31939571
                b5d24ecb-f37e-447a-baf8-40da2aaf214a
                © 2022 by Associação Paulista de Medicina

                This is an open access article distributed under the terms of the Creative Commons license.

                History
                : 21 June 2019
                : 21 June 2019
                : 16 September 2019
                Page count
                Figures: 0, Tables: 7, Equations: 0, References: 36, Pages: 09
                Categories
                Original Article

                product labelling,psychometrics,legislation, pharmacy,pharmaceutical preparations,patient satisfaction,package leaflets,package inserts,medicines,validation,likert scale,regulation

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