DQ: When reviewing the literature for your evaluation plan and different types of evidence for your project, what gaps in the findings did you encounter?

DQ: When reviewing the literature for your evaluation plan and different types of evidence for your project, what gaps in the findings did you encounter?

Research showed gaps between hand-washing knowledge and practice when reviewing the literature towards the evaluation plan compared to different types of evidence found for the project. In initial, midpoint, and end-line data, a disparity between hygienic hand washing knowledge and self-reported behaviors was discovered. In many hospital settings, hand washing is regarded as one of the most effective hygiene promotion actions for public health (Kuehn, 2020). In hand washing, there is still a disconnect between knowledge and practice. People can be educated about the need for hand washing through long-term and broad campaigns. Tradition, customs, and obsolete information are frequently used in practice, and there is commonly a gap between theoretical aspects and its use in existence. To enhance hand washing practice with soap, there is a persistent gap between knowledge and practice, and long-term motivational activities are required (Rabbi & Dey, 2017). To effectively integrate new techniques, healthcare practitioners must believe that they are desirable and relevant to their work. Therefore, presenting a new notion known as the theory-practice-ethics gap. When looking at some of the persistently bad outcomes in healthcare, this theory-practice-ethics imbalance must be considered.

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This is an exceptional post, Sahida. Indeed, successful searching for relevant evidence is important. Clinicians must choose appropriate databases, using appropriate search strategies, to successfully navigate the databases they are searching. Conducting research must comply with particular rules and guidelines to ensure accuracy by evading sampling errors. Sampling errors can greatly affect the accuracy and interpretation of outcomes, which can cause harm to the population under study (Flinton, 2020). In this case, the issue of a small population sample may deter the findings from extrapolation. Sample sizes are always essential in research. Small sample size can affect the reliability of a study because it can result in higher variability, which may cause bias (Hennink & Kaiser, 2022). While smaller sample sizes can give quick results, they do not always produce reliable or accurate estimates. As such, it is not advisable to make a strong conclusion about the topic under study, whether the outcomes are positive or not.

References

Flinton, D. M. (2020). Sampling errors, bias, and objectivity. Medical imaging and radiotherapy Research: Skills and strategies, 149-165. DOI: 10.1007/978-3-030-37944-5_10

Hennink, M., & Kaiser, B. N. (2022). Sample sizes for saturation in qualitative research: A systematic review of empirical tests. Social Science & Medicine, 292, 11452