NR 505 Statistical and Clinical Significance

NR 505 Statistical and Clinical Significance

NR 505 Statistical and Clinical Significance

Statistical and clinical significance of research are both very important within the medical community and both are only productive when they bring change or influence on the patient population. According to El-Masri (2016) a statistically significant result shows the observed effect is not likely due to chance. For example, the values assigned to rule out the null hypothesis are based on pre-determined criteria. Statistical significance allows the researcher to make determinations based on the study findings and data as to the true value this research will have on the patient population. Clinical significance measures the magnitude of the relationship between the independent variable and the outcome variable (El-Masri, 2016). Clinical significance is measured by the value it brings to quality of life, patient outcomes, and cost. Healthcare professionals must be careful to ensure the results of the study are credible and they can be transferred to positively impact a patient population.

In my opinion, I believe you can accept the null hypothesis and still demonstrate clinical significance. My understanding of clinical significance is the impact it brings to the patient population from the research data available whether the results show productive change or harmful change. “Was the treatment plan effective?” and “Does it have significance within the clinical practice?” are questions that help determine clinical significance. For example, a hypothetical research study on a group of clinically depressed patients utilizing cognitive behavior therapy as the independent variable showed no statistically significant difference between the control group and the independent group than the null hypothesis is accepted. However, the clinical results of the data showed many participants responded well to cognitive behavior therapy and verbalized improved mood, outlook, and quality of life. The researcher could look at confidence intervals to determine if cognitive behavior therapy had clinical significance on the depressed patient population and could produce change within the clinical setting such as improved quality care outcomes, patient satisfaction, or a reduction in hospital stays. Clinical significance refers to the real-life impact of research findings (El-Masri, 2016).

According to Connelly (2014) the clinical significance of a study must be determined by the clinician because

NR 505 Statistical and Clinical Significance
NR 505 Statistical and Clinical Significance

they know the needs of their patient population and the practice setting in which they operate. In my opinion, if I questioned the credibility of the qualitative study I could still potentially find clinical significance in my practice area. For example, a hypothetical study on veterans’ suicide risk post deployment with in-depth interviews on a sample size of approximately 20 veterans to discuss their experience with re-integration into society and the effects on their mental health needs. The credibility of the data could be in question simply because the saturation of the data did not occur. However, as a clinician working in a rural setting with a large veteran population, I see how certain questions regarding post deployment and mental health needs could improve the quality of life and possibly reduce the suicide risk within my patient population then I have discovered clinical significance while questioning the credibility of the study.

Connelly, L.M. (2014). Statistical and clinical significance. Medsurg Nursing: Official Journal of the Academy of Medical-Surgical Nurses, 23(2), 118-9.

El-Masri, M. M. (2016). Statistical versus clinical significance in nursing research. The Canadian Journal of Nursing Research = Revue Canadienne De Recherche en Sciences Infirmieres48(2), 31-32. doi:10.1177/0844562116677895

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The question I chose this week discusses how my research on veterans could be transferred to a different population group. I found this question fascinating and I feel I have two distinct population groups that could fall into a similar situation as veterans returning from combat and reintegrating back into a civilian lifestyle. The first group would be police officers who are accustomed to putting their life on the line every day in the line of duty. I can see where police officers see many fellow officers wounded or killed because of protecting others. Meffert (2014) discussed the similarities between a combat veteran and a police officer and the level of stress endured and the high rate of post traumatic stress disorder (PTSD) as a result of their career choice. Police officers are often the first line of defense and first responder in a life-threatening situation, emergency scenario, or domestic abuse where women and children are being assaulted.

The qualitative research on post war veterans could easily relate to police officers as they try to have normal lives and when they are off duty. The common thread with these two disciplines is the PTSD from work related violence that permeates their existence on and off duty. Meffert (2014) discusses how PTSD can impact work and personal relationships and effect overall mental health and the individual’s ability to relate to others. The second group I feel could relate to the qualitative study would be victims of domestic violence. In this population group there is a combat zone within the home setting thus increasing the risks for victims to experience PTSD. Victims of domestic abuse can have a difficult time relating to other individuals within the community and can feel isolated and alone and live in a constant posture of defense and fear for their personal safety. This posture of defense can impact mental well-being and a sense of belonginess similar to that of the post war veteran. All three situations could benefit from qualitative research on reintegration into community following life outside of their previous combat zone.


Meffert, S. M., Henn-Haase, C., Metzler, T. J., Qian, M., Best, S., Hirschfeld, A., & Marmar, C. R. (2014). Prospective study of police officer spouse/partners: a new pathway to secondary trauma and relationship violence. Plos One9(7), e100663. doi:10.1371/journal.pone.0100663

This weeks discussion is regarding statistical and clinical significance.  We are asked to review these two ideas and differentiate between the two.  Statistics has never been my strong point but it is important to know especially when reviewing and understanding research.  I found a great piece of literature that was printed by American Nurse Today explaining the importance of both ideas.  Both concepts are related but it is vital to know their differences and how they can be applied to practice.  A statistically significant difference
means an association or difference exists between the variables that wasn’t caused solely by normal variation or chance. A clinically significant difference means the researchers found a statistically significant
difference that experts in the field believe is substantial enough to be clinically important and thus should direct the course of patient care.  Statistical significance must always be established before clinical significance can be determined.  Clinical significance is a subjective judgment that can’t be determined by a
single test. (Heavy, 2015. p.1-2.).  If the results from a qualitative study is regarded as questionable, I believe it may still be clinically significant.  Qualitative design deals with perceptions and opinions and may not be applicable to one’s area of care but can still be applied to another situation.  A study may not be transferable to one situation but can still be transferable to another.  A hypothetical example could be one where the environment could influence a participants perception of the issue.  A qualitative study regarding the quality of care for mental health patients in an indoor ER safe room with no windows or sunlight may be different than an institution with outdoor privileges and comfortable surroundings.  If a persons environment is on the same level as the participants in the study, the results may have clinical significance, if it is drastically different for better or worse, it may not be significant.  I had trouble knowing how to answer the middle question above but I think the answer is yes.  It could be possible for a study to support the null hypothesis and demonstrate clinical significance.  An example could be that a study supports the idea that certain patients are not at higher risk for falls and that could direct caretakers to not have to implement extra safety measures as they would higher fall risk patients.  I look forward to reading everyone’s reply’s to further my understanding of this weeks lesson.


Heavey, E. (2015). Differentiating statistical significance and clinical significance. American Nurse Today10(5), 26-28