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Validation of the MISSCARE-BRASIL survey - A tool to assess missed nursing care 1 1 Paper extracted from Doctoral Dissertation “Validation of the MISSCARE-BRASIL - Instrument to evaluate missed nursing care”, presented to Escola de Enfermagem de Ribeirão Preto, Universidade de São Paulo, PAHO/WHO Collaborating Centre for Nursing Research Development, Ribeirão Preto, SP, Brazil.

ABSTRACT

Objective:

to analyze the metric validity and reliability properties of the MISSCARE-BRASIL survey.

Method:

methodological research conducted by assessing construct validity and reliability via confirmatory factor analysis, known-groups validation, convergent construct validation, analysis of internal consistency and test-retest reliability. The sample consisted of 330 nursing professionals, of whom 86 participated in the retest phase.

Results:

of the 330 participants, 39.7% were aides, 33% technicians, 20.9% nurses, and 6.4% nurses with administrative roles. Confirmatory factorial analysis demonstrated that the Brazilian Portuguese version of the instrument is adequately adjusted to the dimensional structure the scale authors originally proposed. The correlation between “satisfaction with position/role” and “satisfaction with teamwork” and the survey’s missed care variables was moderate (Spearman’s coefficient =0.35; p<0.001). The results of the Student’s t-test indicated known-group validity. Professionals from closed units reported lower levels of missed care in comparison with the other units. The reliability showed a strong correlation, with the exception of “institutional management/leadership style” (intraclass correlation coefficient (ICC)=0.15; p=0.04). The internal consistency was adequate (Cronbach’s alpha was greater than 0.70).

Conclusion:

the MISSCARE-BRASIL was valid and reliable in the group studied. The application of the MISSCARE-BRASIL can contribute to identifying solutions for missed nursing care.

Descriptors:
Validation Studies; Nursing Care; Nursing Methodology Research; Patient Safety; Nursing; Factor Analysis, Statistical

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