1. Abstract
The abstract does not provide an accurate summary of the study since it does not include the limitations of the study and implications for nursing care in relation to falls. While the study states that its outcomes agree with ambulant assessment of patient’s daily conduct and its contribution to how falls among the elderly can be identified, it does not offer the effects of these outcomes on nursing care.
2. Statement of the Problem
Through an in-depth introduction, the authors detail the problem of falls among the elderly with data and figures based on research studies. However, the authors do not explicitly introduce the statement of the problem of falls in the study. In its abstract, the study attempts to determine the problem of the relationship between the probability of falls and a patient’s daily-life activities or conduct. Imperatively, they should have created a statement of the problem after their introduction.
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3. Purpose
The researchers make the purpose of their study clear to their audience. They posit that their study is meant to determine the link between fall incidents and a patient’s daily activities. As such, they use wearable sensors to evaluate habit forming activities and daily-life gait quality.
4. Methods
The study uses an appropriate design by selecting 319 older people in Amsterdam (Holland) and its environs between March 2011 and January 2014. The sample is fit for the research design since those sampled were aged between 65 and 99 years and were exposed to a mini mental state examination to determine their mental fitness for the study. Further, the participants put on a trunk accelerometer for a week. They also completed questionnaires besides performing strength and trail making tests to determine the risk factors for falls (Van Schooten et al., 2016). The study also identifies inclusion and exclusion criteria clearly. For example, older persons below 65 years and those above 99 years were not included in the study. Furthermore, those included had to pass the mini mental test within the range of 19 and 30. Participants were also expected to walk for at least 20 meters daily with the help of an assistive tool if required. In addition, a data collection tool or instrument was necessary for the study since the researcher needed to collect the information concerning fall incidents among the participants. For instance, they use questionnaires apart from the accelerometer readings to collect data from the older people. However, the authors do not include a discussion of reliability and validity of testing but linked the efficacy of their testing method to available literature from previous studies in Japan (Van Schooten et al., 2016).
5. Results
The authors used numerical variables that were changed to z-scores while the dichotomous variables were changed to coding. The study determined Pearson’s correlation among the 39 estimated gait quality features in the participants. The authors also used accelerated failure time (IAFT) framework to determine the univariate links between each gait quality features and time for the first fall and time for the second fall. Before using the multivariate frameworks, the researchers carried out a principal analysis of the components as a way of reducing their data. Therefore, the data and statistical analysis models used in the study are appropriate. Further, the authors explain clearly how the statistics were used and present the results clearly in the article. They use graphs, tables, and figures to present the outcomes of their study. The number of people who participated in the study is 319 with 51% being female and over ninety percent in living in communities. The participants’ average age was 75.5 years old and had a mean MMSE score of 27 (Van Schooten et al., 2016). In their results, the authors assert that some factors related to fall history, consumption of alcohol and gait quality influenced when first falls can occur in participants with good accuracy.
6. Limitations
The researchers present the limitations of the study and comprehensively discuss their implications. For instance, they state that the extensive use of a certain set of gait quality features can be changed by adding other gait characteristics for effective results. They also note that the random dropout of participants was also another limitation of their study, though they doubt if it affected the outcomes.
7. Conclusion
The researchers state that their study is the first one to describe the correlations between gait quality and fall prediction among older people. Therefore, nurse practitioners, future research studies and policymakers can use their findings to carry out more research on the topic and find alternative ways to predict falls among older people with good accuracy (Van Schooten et al., 2016). The authors emphasize that future studies on the relationship between falls and daily-life conditions and activities among the older people will offer more understanding on how nurses can predict falls and prevent them in ambulatory settings.
8. Implications
The study’s findings have several implications for nursing care, especially in ambulant situations where they need to prevent falls by predicting their first and second occurrence. These findings will be use useful for me as a nurse since they will enable me to predict chances of falls occurring among the older patients in my care. It is an evidence-based study that demonstrates how nurses can predict with accuracy fall incidences among their elderly patients. For instance, I can incorporate gait quality features in a patient’s history of falls to determine with accuracy when they may have their first fall.
Reference
Van Schooten, K.S. Pijnappels, M. Rispens, S.M. Elders, P.J.M., Lips, P., Daffertshofer, A.,
Beek, P.J., & van Dieen. (2016) Daily-Life Gait Quality as Predictor of Falls in Older People: A 1-Year Prospective Cohort. PLoS ONE , vol.11, no.7.
