Michael Glick|Barbara Greenberg
A march toward scientific literacy
research studies produce results necessarily answers importance research especially biomedical discipline dentistry cannot emphasized enough everything dentistry stems discoveries vetted validated sometimes even vaunted explain understand research outcomes use statistical methods interpret produced data well provide measure certainty proposed associations unfortunately many health care professionals poor understanding health statistics often able apply research results gleaned scientific literature inform clinical practice1wegwarth schwartz lm woloshin gaissmaier w gigerenzer g physicians understand cancer screening statistics national survey primary care physicians united statesarch intern med 2012 156 340349google scholar 2gigerenzer g gaissmaier w kurzmilcke e schwartz lm woloshin helping doctors patients make sense health statisticspsychol sci public interest 2007 8 5396crossref pubmed scopus 815 google scholar healthrelated data abound readily available health care professionals patients see interpret yet scientific training held different norms patients supposed comprehend apply published research promulgated within professional domain simply put supposed understand scientific language conventions used make inferences research results need understand basic statistical relevant concepts however enough able translate research results making clinical decisions also need able communicate information patients public inundated countless professional social sources healthrelated information unless understand effectively translate language biomedical science practical purposes scientifically illiterateunless understand effectively translate language biomedical science practical purposes scientifically illiterate unless understand effectively translate language biomedical science practical purposes scientifically illiterate would impractical assess dental implant failures studying every patient entire population patients ever received dental implant instead sample subset population randomly selected representative entire population interest patients studied outcome investigation use statistical methods infer samples implant failure rate true would see entire population knowing dental implant failure rate among population whole could help us estimate failure rate might among patients statistical methods help us summarize data interpret understand study results help concepts measures effect size example standardized mean difference odds ratio relative risk accuracy precision clinical relevancy however importantly reader scientific literature also needs understand limitation statistical testing possibility drawing incorrect conclusions critical questions ask unfortunately scientific illiteracy may serious health consequences one misunderstood misinterpreted statistical concepts biomedical literature pervasive p value3best 3rd greenberg bl glick tea tasting test p value aint think isjada 2016 147 527529abstract full text full text pdf pubmed scopus 8 google scholar want know treatment confers better outcome treatment b p value measure probability observed result study extreme result would expected assumption difference awkward counterintuitive measure difficult understand assess probability finding real effect rather probability would expect given assumption real effect calculated p value certain predetermined threshold value example 05 call finding statistically significant couple important caveats keep mind calculated p value refers particular studied patient sample cannot applied similar patient samples clinical significance inferred mathematically calculated p value clinical perspective p value little real usefulness producers clinicians scientific literature overly concerned significant findings demonstrated p values yet confidence intervals ci effect size probably important statistical concepts making clinical decisions p value test statistic point estimate ci provide range point estimate effect size magnitude difference given level certainty ci tell us significance point estimate well indication range true population value could lie given degree certainty4greenberg bl kantor ml clinicians guide literature interpreting resultsjada 2009 140 4854abstract full text full text pdf pubmed scopus 4 google scholar help clinician determine clinical relevance research data boxboxconfidence interval statistical significance clinical significance relevancea study regarding placement implant brand versus placement implant brand b resulted treatment effect 2 implants 40 millimeters marginal bone loss favor implant b calculated 95 confidence interval ci around treatment effect 40 mm 20 mm 60 mm expressed treatment effect 40 95 ci 20 60 means study would performed 100 times would expect treatment effect target population true difference would lie 20 mm 60 mm 95 studies 95 ci treatment effect marginal bone loss would included 00 result would interpreted statistically significant p 05 based convention 05 threshold value significance example 00 difference treatment effect outside calculated range 95 ci 20 60 researchers claim found statistically significant result p 05 ci provides degree certainty finding may clinically significant clinician determined clinically meaningful treatment effect example clinician determined treatment effect 30 mm clinically significant study result would considered clinically relevant clinically meaningful clinician must assess clinical relevance entire range upper lower values confidence interval open table new tab boxconfidence interval statistical significance clinical significance relevancea study regarding placement implant brand versus placement implant brand b resulted treatment effect 2 implants 40 millimeters marginal bone loss favor implant b calculated 95 confidence interval ci around treatment effect 40 mm 20 mm 60 mm expressed treatment effect 40 95 ci 20 60 means study would performed 100 times would expect treatment effect target population true difference would lie 20 mm 60 mm 95 studies 95 ci treatment effect marginal bone loss would included 00 result would interpreted statistically significant p 05 based convention 05 threshold value significance example 00 difference treatment effect outside calculated range 95 ci 20 60 researchers claim found statistically significant result p 05 ci provides degree certainty finding may clinically significant clinician determined clinically meaningful treatment effect example clinician determined treatment effect 30 mm clinically significant study result would considered clinically relevant clinically meaningful clinician must assess clinical relevance entire range upper lower values confidence interval open table new tab accessing assessing applying scientific findings dental students taught practice dental school beyond differentiate us technicians unless resign rely solely others tell us inform clinical decisions need basic skills evaluate new scientific information understanding p values cis measures effect size inform clinical practice minimum requirement clinicians making decisions practices based biomedical literature understanding concepts also necessary conduct proper risk communicationsomething every time give patient treatment plan knowledge understanding basic statistical clinically relevant concepts 2 essential elements effectively assessing credibility clinical relevance study results conclusions incorporating novel innovations practices understanding new research findings alter clinical guidelines work flow enhance patient care knowing apply new information provide better oral health care essentialour profession demands patients deserve dr glick professor william feagans chair school dental medicine university buffalo state university new york buffalo ny also editor journal american dental association dr greenberg professor chair department epidemiology community health school health sciences practice new york medical college valhalla ny also statistical editor journal american dental association p values confidence intervalsthe journal american dental associationvol 148issue 11previewdrs glick greenbergs august jada editorial titled march toward scientific literacy glick greenberg bl jada 20171488543545 regarding statistical literacy especially relates p values mean mean fine far went however like calls attention benefits confidence intervals ci authors gently downplayed typically insightfree reliance investigators journal editors common statistical convention namely p value 05 fulltext pdf