Although there is still uncertainty about the best way to measure PSF, this study generated new knowledge about which patients experienced fatigue 4–6 weeks after a stroke, and may therefore help to identify which patients may be at risk of impaired quality of life after a stroke (6, 9, 10).
The span of the reported confidence intervals (95% CI) from the logistic regression analysis (Table 3) is relatively broad. This is probably due to the fact that a small sample gives greater variation around the true estimate. This means that even if the results are statistically significant, the estimated odds ratio for each of the variables should be interpreted with caution.
Representativeness of the sample
Following the recruitment protocol at each hospital presented a number of challenges. This may have meant that some patients who met the inclusion criteria were not asked to participate, which in turn may have led to unintentional bias in the sample. Some patients did not want to participate in the study, partly because they were too ill. The patients who had more severe outcomes and more pronounced fatigue may have chosen not to participate in the study because they thought it was too demanding.
Another reason why patients did not want to participate in this study was that they felt too healthy. When patients feel too ill to participate in a study, it can lead to bias in the sample, or mean that only the healthiest patients are represented in the study. Compared to the population registered in the stroke register (29), the participants in our study are 10 years younger on average. The proportion of women is 5 per cent lower, and the proportion who had a minor stroke (NIHSS <6) is 5 per cent higher.
Data collection by means of a structured questionnaire in individual interviews can lower the patient’s threshold for completing the questionnaire, resulting in a higher completion rate. This type of approach helps to gather more complete data and prevents data omissions. It also reduces the possibility of misunderstanding the questionnaire.
One of the strengths of this study is that it uses data from a multi-centre study that has recruited patients from several different hospitals in the country. Furthermore, we include a large number of participants in the study. These elements increase the generalisability of the results to other stroke patients.
In our study, the prevalence of fatigue in patients 4–6 weeks after a stroke was 43.6 per cent. The following factors increased the risk of PSF in the sample: health problems before the stroke, depression after the stroke, care responsibilities for someone close and higher severity of stroke (measured by NIHSS).
Nurses and healthcare personnel need to know who is particularly at risk of PSF so that these patients can be given the appropriate follow-up at the right time. It is therefore important to know the prevalence of PSF and the factors associated with PSF. However, more research is needed on PSF.
Thank you to Manuela Zucknick, a statistician in the Department of Biostatistics, University of Oslo, for helping with the quality assurance of statistical analyses and interpretations.
Our study was funded with support from South-Eastern Norway Regional Health Authority (project number 2013086) and the European Commission’s seventh framework programme (FP7-PEOPLE-2013-COFUND) (agreement number 609020 – Scientia Fellows). The University of Oslo and Oslo University Hospital, Ullevål, have contributed research time and administrative support to the study.
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