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. 2019 Jul 23:33:73.
doi: 10.34171/mjiri.33.73. eCollection 2019.

Psychometric properties of the Persian version of the Patient Measure of Safety (PMOS)

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Psychometric properties of the Persian version of the Patient Measure of Safety (PMOS)

Fatemeh Sarvi et al. Med J Islam Repub Iran. .

Abstract

Background: Patient safety practice reduces the adverse events that may occur in the health care system during procedures, diseases, and diagnoses. Failure and negligence in identifying and resolving health care system errors may result in financial and physical harm. Thus, this study aimed to investigate the psychometric properties of the Patient Measure of Safety in Hospitals (PMOS). Methods: This study was conducted on 264 patients in 4 hospitals. The patient measure of safety questionnaire has 44 items and 9 domains. To translate the PMOS questionnaire, standardized forward-backward procedure was used, and a panel of experts assessed the face and content validity of the Persian version. Internal consistency, confirmatory factor analysis (CFA), and test-retest method were used to test the validity and reliability of the instrument. Also, AMOS (version 23) and SPSS (version 16) software were used for data analysis and modeling. Results: The average CVI score was 0.85, indicating well results in the Persian context. CVR score was 0.65. The indices of goodness of fit were acceptable for Iranian sample (CFI=0.91, TLI=0.89, RMSEA=0.063, relative/normal Chi-Square Statistic (X2/df)=2.85). All items were significantly loaded on the domains, except the 33rd and 38th items that were related to the eighth domain. Thus, the final Persian version was developed with 8 domains and 42 items. Internal consistency was acceptable for these domains, and test-retest method showed a good reliability (r=0.984). Conclusions: The Persian version of PMOS is an appropriate instrument to assess the safety of patients in Persian language communities. Also, PMOS is an optimal tool to identify and avoid preventable errors.

Keywords: Hospital; Patient; Reliability; Safety; Statistical model; Validity.

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