I was once told that a good sample is not good in terms of size or generalizability. A good sample requires an understanding of purposeful sample strategies. Ineffectiveness in data saturation is the failure to reach saturation point that can hampers content and research validity (Fusch & Ness, 2015). Additionally, data saturation is reached when there is enough information to reproduce similar study; and when the capability to obtain extra new information has been reached, or when further coding is no longer practicable.
A major strategy of improving data saturation is making sure the recruited units for sampling have achieved saturation point (Patton, 2015). Likewise, this process means reaching a point in which all the relevant data of the research analysis have been obtained. For example, the recruited sample of patients with Alzheimer dementia have reached a basis for concluding or finalizing the research explanation that could lead to consequent data-wide. Additionally, it is important to note the limitations that determine enough
