In view of the Covid-19 pandemic, the data collection strategy took the form of an online survey via a form compiled in REDCap and using the HSOPSC version 2.0, translated and adapted based on the pre-test results. The survey was published on the hospital intranet and a link was provided for data collection via the web.
Overall, the findings from examining the psychometric properties of the Brazilian version of the HSOPSC 2.0 were positive, displaying good internal consistency and construct validity, as expressed in the reliability estimates and model fit indices. However, the low factor loadings present in 10 items would entail removing these items to explore a factor model that best fits the data collected in the sample of this study. For several reasons, we chose not to go this way. The theoretical basis underlying the AHRQ SOPS survey is recognised as applicable to the reality of Brazilian health services [29, 30]. Brazil's National Patient Safety Programme highlights the importance of building a strengthened patient safety culture and encourages its measurement to monitor advances and weaknesses in this area. Furthermore, the programme encourages sharing a fair culture of reporting, accountability and learning in health services. Also, all stages of the translation and cross-cultural adaptation were carried out with methodological rigor, which included a scrutiny of translation possibilities and alternatives, and was supported by an expert panel. Lastly, data collection for validation of version 2.0 took place in a single hospital during the Covid-19 pandemic period, which may have affected the fit of the data to the ten-factor model.
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A combination of quantitative and qualitative methods was used, to add breadth and scope to the findings (Creswell, 1994). Quantitative data techniques included confirmatory factor analysis (CFA, Kline, 1998) to examine the psychometric properties of the LSSS survey, and discriminant function analysis to examine group differences among normal-, low-, high-achieving students and students with LD regarding the use of SRL strategies and compensation strategies (i.e., mean scale scores on the LSSS survey) (Tabachnick & Fidell, 2001). Qualitative data analyses were conducted for both open-ended questions using the coding paradigm suggested by Strauss and Corbin (1990), which included open coding, axial coding, and selective coding, and interrater agreement for coding both questions was fairly high (88% and 80%, respectively). Highlights of the major findings from this study is presented below.
After the screenings, all three raters answered the survey about the softwares performances (Table 2). The highest ranked software was Rayyan, with a mean score of 35 out of 40 points, followed by Abstrackr and Colandr which scored 33.75 and 16.25 points, respectively. Even though it took over an hour for raters to learn how to use Colandr, which was the least intuitive one, all softwares provided faster semi-automatic screening processes when compared to manual screening. 589ccfa754
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