an objective manner on a broad range of topics and circumstances, there are limitations and potential negative consequences with its utilization. Firstly, it makes the assumption that an assessment can be able to quantify domains such as physical, emotional, social, well-being, etc. with a single quantitative score. Furthermore, how are these domains weighted? Will they be measured the same or equally for each person? Or will it take into account how important these specific domains are for each person when creating the final score? Each person has their own specific set of experiences and values and a point of argument is that this needs to be taken into account. However, this would be a difficult task for the person to rank these quality of life domains. Another point to keep in mind is that people's values and experiences change over time and their quality of life domain rankings may differ. This caveat must be added or the dynamics of this could be taken into account when interpreting and understanding the results from a quality of life measuring tool. Quality of life measuring tools can also promote a negative and pessimistic view for clinicians, patients, and families, especially when used at baseline per say during the time of diagnosis. Quality of life measuring tools can fail to account for effective therapeutic strategies that can alleviate health burdens, and thus can promote a self-fulfilling prophecy for patients. On a societal level, the concept of low quality of life can also perpetuate negative prejudices experienced by people per say with disabilities or chronic illnesses. Analysis Statistical biases It is not considered uncommon for there to be some statistical anomalies during data analysis. Some of the more frequently seen in health-related quality of life analysis are the ceiling effect, the floor effect, and response shift bias. The ceiling effect refers to how patients who start with a higher quality of life than the average patient do not have much room for improvement when treated. The opposite of this is the floor effect, where patients with a lower quality of life average have much more room for improvement. Consequentially, if the spectrum of quality of life before treatment is too unbalanced, there is a greater potential for skewing the end results, creating the possibility for incorrectly portraying a treatment's effectiveness or lack thereof. Response shift bias Response shift bias is an increasing problem within longitudinal