Nurses' perceptions of shortage effects
Nursing stats
Statistical methods were not always explained or even mentioned in the methods section of the articles, but were often buried in the text of the results section or listed only as footnotes to tables. In several instances, no statistical procedure was specified, but the presence of a p value indicated that a test had been performed.
Hellems, Gurka and Hayden (2007),
Buerhaus, DesRoches, Donelan, Dittus and Ulrich (2007) report a six-year survey of U.S. nurses performed over 2002-2006 and compares mean responses for a sample they allege is large enough to represent the current U.S. nurse population. They report and discuss changes in nurse perceptions of conditions and health care outcomes derived from national, regional and local nurse shortages over the survey years and indicate where changes are statistically significant, presenting 'p-values' to indicate effect strength of the change over various years. As Hellems, Gurka and Hayden (2007) indicate above, however, peer-reviewed academic studies increasingly fail to fully explain the statistics they base their assertions on (1085). The 2007 Buerhaus, DesRoches, Donelan, Dittus and Ulrich study is one such paper, presenting conclusions supported by p-values for change over time, supporting the random survey methodology and generalizeable sample size, but nowhere explaining how they achieved statistical significance for these claims.
Nonetheless the study presents interesting findings, using nonparametric, descriptive statistics to compare respondent perceptions of effects deriving from nurse shortages. Smith (1985) explains nonparametric statistics are appropriate whether distributions are normal or not (596). These results come from methodically controlled random samples that the authors allege are large enough to generalize to the wider population (Buerhaus, DesRoches, Donelan, Dittus and Ulrich, 2007, p. 70), although they do not show the calculations used to estimate that precise cutoff...
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