The traditional method of presenting quantitative research findings based on the statistical results of null hypothesis testing can limit the ability of clinicians and consumers to translate research findings into meaningful information for treatment planning and evaluation. In this article, the authors compare results from an illustrative study based on traditional statistical methods, including a t test and p values, to a more clinically useful approach using confidence levels. The process of calculating confidence levels using the basic quantitative information included in most clinical research articles is described. The argument is made that confidence levels do not replace traditional (null) hypothesis testing. Rather, they facilitate the interpretation of statistical findings, improve clinical decision making, and support the development of evidence-based occupational therapy practice.
AtkinsD. C.BedicsJ. D.McGlincheyJ. B.BeauchaineT. P. (2005). Assessing clinical significance: Does it matter which method we use?Journal of Consulting & Clinical Psychology, 73, 982–989.
3.
BeninatoM.Gill-BodyK. M.SallesS.StarkP. C.Black-SchafferR. M.SteinJ. (2006). Determination of the minimal clinically important difference in the FIM instrument in patients with stroke. Archives of Physical Medicine & Rehabilitation, 87, 32–39.
4.
BraitmanL. E. (1991). Confidence intervals assess both clinical significance and statistical significance. Annals of Internal Medicine, 114, 515–517.
5.
Canadian Association of Occupational Therapists. (2009). Joint Position Statement on Evidence-based Occupational Therapy (1999). Available at: http://www.caot.ca/default.asp?pageid=156.
6.
CarverR. P. (1978). The case against statistical significance testing. Harvard Educational Review, 48, 378–399.
7.
ClelandJ. A.ChildsJ. D.WhitmanJ. M. (2008). Psychometric properties of the Neck Disability Index and Numeric Pain Rating Scale in patients with mechanical neck pain. Archives of Physical Medicine & Rehabilitation, 89, 69–74.
8.
DysartA. M.TomlinG. S. (2002). Factors related to evidence-based practice among U.S. occupational therapy clinicians. American Journal of Occupational Therapy, 56, 275–284.
9.
FroehlichG. W. (1999). What is the chance that this study is clinically significant? A proposal for Q values. Effective Clinical Practice, 2, 234–239.
10.
GrangerC. V. (1998). The emerging science of functional assessment: Our tool for outcomes analysis. Archives of Physical Medicine & Rehabilitation, 79, 235–240.
11.
HebertR.SpiegelhalterD. J.BrayneC. (1997). Setting the minimal metrically detectable change on disability rating scales. Archives of Physical Medicine and Rehabilitation, 78, 1305–1308.
12.
JacobsonN. S.TruaxP. (1991). Clinical significance: A statistical approach to defining meaningful change in psychotherapy research. Journal of Consulting & Clinical Psychology, 59, 12–19.
13.
JohnstonM. V.Case-SmithJ. (2009). Development and testing of interventions in occupational therapy: Toward a new generation of research in occupational therapy. OTJR: Occupation, Participation & Health, 29, 4–13.
14.
KovacsF. M.AbrairaV.RoyuelaA.CorcollJ.AlegreL.CanoA.. (2007). Minimal clinically important change for pain intensity and disability in patients with nonspecific low back pain. Spine, 32, 2915–2920.
15.
LawM. C.MacDermidJ. (2008). Evidence-based rehabilitation: A guide to practice (2nd ed.). Thorofare, NJ: SLACK Incorporated.
OglesB. M.LunnenK. M.BonesteelK. (2001). Clinical significance: History, application, and current practice. Clinical Psychology Review, 21, 421–446.
18.
OttenbacherK. J.JohnsonM. B.HojemM. (1988). The significance of clinical change and clinical change of significance: Issues and methods. American Journal of Occupational Therapy, 42, 156–163.
19.
OttenbacherK. J.MaasF. (1999). How to detect effects: Statistical power and evidence-based practice in occupational therapy research. American Journal of Occupational Therapy, 53, 181–188.
20.
PooleC. (2001). Low P-values or narrow confidence intervals: Which are more durable?Epidemiology, 12, 291–294.
21.
RothmanK. J. (1998). Writing for epidemiology. Epidemiology, 9, 333–337.
22.
ShakespeareT. P.GebskiV.TangJ.LimK.LuJ. J.ZhangX.. (2008). Influence of the way results are presented on research interpretation and medical decision making: The PRIMER collaboration randomized studies. Medical Decision Making, 28, 127–137.
23.
ShakespeareT. P.GebskiV. J.VenessM. J.SimesJ. (2001). Improving interpretation of clinical studies by use of confidence levels, clinical significance curves, and risk-benefit contours. Lancet, 357, 1349–1353.
24.
SudsawadP. (2005). A conceptual framework to increase usability of outcome research for evidence-based practice. American Journal of Occupational Therapy, 59, 351–355.
YostK. J.SorensenM. V.HahnE. A.GlendenningG. A.GnanasakthyA.CellaD. (2005). Using multiple anchor- and distribution-based estimates to evaluate clinically meaningful change on the Functional Assessment of Cancer Therapy-Biologic Response Modifiers (FACT-BRM) instrument. Value in Health, 8, 117–127.
