Warning: fopen(/home/virtual/kjan/journal/upload/ip_log/ip_log_2025-07.txt): failed to open stream: Permission denied in /home/virtual/lib/view_data.php on line 83

Warning: fwrite() expects parameter 1 to be resource, boolean given in /home/virtual/lib/view_data.php on line 84
Comparison of the Reliability and Validity of Fall Risk Assessment Tools in Patients with Acute Neurological Disorders
  • KSAN
  • Contact us
  • E-Submission
ABOUT
BROWSE ARTICLES
EDITORIAL POLICY
FOR CONTRIBUTORS

Articles

Original Article

Comparison of the Reliability and Validity of Fall Risk Assessment Tools in Patients with Acute Neurological Disorders

Korean Journal of Adult Nursing 2013;25(1):24-32.
Published online: February 28, 2013

1College of Nursing, Chonbuk National University, Cheonju, Korea.

2College of Nursing, Chonnam National University, Gwangju, Korea.

3Department of Nursing, Changwon National University, Changwon, Korea.

4Department of Nursing, Asan Medical Center, Seoul, Korea.JFIFddDuckydqhttp://ns.adobe.com/xap/1.0/ Adobed     ! 1AQa"q 2#w8B36v7XRr$9bCt%u&Ws'(xy4T5fH  !1AQaq"2B Rbr#u67Ѳ3sTt5v8Sc$4ĂCÔ%UӅFV ?_Aנj- H>>,m*>fzp"TrKkr^r.|_&]|*vPuܶvoQ1mwVJUhu-I"=LniAƕ8"۲ k*ҿ[yu:.vUQ+)%F DHyVBk>Hy8jݹ q~9D4KRmzQ)^ʔ.J%k_tVi5NTjg!'ky|5asOȻ)R۸ߩFMԿ3L4j6dڜ#NIwUF]JqB/(FafJRzq3\G՛ ?~\ 6)6W4m[O^L0E&rRMض*C .]Unl-1 1r#Rj/&QɈ׉˩s6Rj=5Tg.y.·Pӡ:JJS:C8-2u]d&vUz;7p9 5VnL֢"y)">iי(IDDd| Yj0; LRfS:ktYK%*N2^m|&dğth":ey)uPQZW)gcC3Pv&MMWd&Ŵ۲mvTRoժM03*F3Yd6\8,\hݻ kߔi<k NTwSԪmljj[>->ptU%'LR>&EBH$MQAUx[$Z6vi&_a.KIQ{hyƒ j"JOC9eFҝfj;˚Ω<[3_m% lQ@4g=5$(J]Yc-OMq<Ǎ wSzڗ)k$7VIP붾ͯnV+卵*t]iЎD31~SA1éC2u)ʼnQn-Uoi3:grI8ؓWm*G zܕ)ZקJ}Y YlGeJ6cB2I NS3Q>k=KTBT]W6+SOXQgGR? telˊ%-Re\hѯ2TF"C/OJΩ6r[N.0{SpljjX1“jOsӥ;ҭhe}xu`Ք&.)yO̒ Fߑ.$Qw;9Iw2o+RVJMSOj[SoҌZ%;`d$blQ{Ro{Imڌ>3egf\O֝Uzx"䢸g+mv%Gʆ:|V[N'&ס-ޝ'kfE|K,G&˳98Juin/\\Qݿ̋v~Ǩ!rtWU d|E߫R4d}.qPw*Ӭv5YEcn~f5c%MTMkb-F>5JT,})QHg%{("ӔȸWMsYyWNRrkkJr0XドnͫT}r-jj,Ŕʍ\Q2Ri>v$5!]"JB2WɅ)]VԜUc8i|.jeRO6^V.¸ Q&#|ܶ-*uOG%JAtRZRr]FFG\۩w+?'zչSѧt jz>KW&ot{7P&2D;&\\>Q2JzܗAKSfeNn[jRrԕf6,q,F1tRfԗ>vֶևj-&R'Zi2=xv~Elbsvm8=ӛ"ū񕜈BȩlWau[]ٷBߨF~J!|Ipr3R̴#Yp)={7:G{+:\W}n|Q#%)7^-h"Ƒq:M*%J&$T軨I333׎g_- ucBwwjp[6i25$̏bU’ٱRv?G\~#Iͪb7<<}Ezt" q_Inw,7-d,G÷%T* Wg1"䥱kq/A.,_KhqŒxwvo u2ۥۧ.bQ}XκA$֣ +K״ZUNmڸII{.v{5z5ѮRme[moyƾd~cRݾK'j.\i&/S6f|b=5: p!6i_ 4j6=.si˧eƾtS^c.Y^RJVS-Vi3,esi08?H$GvZgg?gi䤟2adw릿:"۪lkSN>q-4kI܋ێe̊qۅgDoѨ9; #T.Q;7#~_Ufstb_'w~Xw1Xk,vcOt._}v}8"(4Z\ۘgk?J?bm_c!g{HZV]Fkk%~gEt)b秴vΰB|꽸}mp~E6ݹv;7P٤v+ri*3Ԣ|'O14_~7nP{7ZU\Vű[ +7󖱅o#:ǥŬ\|3r%TJX]V7ez¨Y]lc|O3V! R zbJ'PnGqVJ"19WVeOF埜EaEJωqCN5Z g-9[S<$sUK5b|7sn\7x qmv##FF\ w[=-43$^ooVSiXօv7iB۴yg>]Vf"r$J3""32!Zh[K%7GvNLs+4nB/B{vlsobJaҺJR:0g%&zR\ S3T[&ִor*ⷳc3ʊO[iozW٨%$gn:ܶWwFBԹjHP&z u&F2\f;ipW73 [; '_̽b;vib!oec dC-tS__$Xs]l9&z$2/N>%'[}b{h/{`{Ji׉׏ YJB/X%}.|+{(S:qz]4_Kѵo`^tY_4S#* ^zvݾMr+TrkQ g.8Ͽ^i>ӈǙvix>$o( ^qt*&t1oJVu-ql5U6jCЉmĻ*"?JT=K'O/|=Vo}l0b}}f?X[?/\JSBe,kP8ETJ==?.p5ފgbU9}ǶdNKk—_$8̸͓ۍ8Di\BԿ-1v{FF]|.^ۅ{vl12׏z7-R7wE?\nh\jN/Kձr_oBw"N QMBZqe-m:ӨSn6j4%!hQ;sv'm4kcM=!8\m[M4{SMliۇ%eֽR&N:{2A8)THLK3Zj[jPBx#BگMf:G1\`edcʮ?|w(-̮vXt,bW2;.ιNHRR#YwTM"<;mk\.foIDjmlJ;vxy7o7i\,KQŊ9d^Mmgc L*.T6tLeIuOH3SJQ3=F/ʿ<9\JM6mN6=<{xkP!F1QR[I$6ُimXu2An2yԒMU q f[IB-'䤯jYm52&JG\zд\~vdg QtHGXw&1Lw+nDEdC1w|YJmvP)HZ>i0BPβә?R:QO["]I_Jʏۍ>QKyu^bycBq4lXF~l [\*N>-J6,Gq(Zr5h]CwYӤU~ʶߑ u*SIv%ZfJ7)! FS*s_\|IŸZ)J ]ܜi4"z[+Z,MOZ))}|Ʀ(RUNIII.S'ˍO~˨rn}M)xxӕ0 eyҵ7YMAB]ӣU:/ѭ*6bcwP͵ "+qēVjŹO|GtY4V j[mLV M -m>",B$ GD1~j6O4|LxnNmqATNR3ε|DŽa[fmn-ڭ+FiK7Pcm;r5 l8r{#-]'nrFh2ruycb;pW=njRqRJ(d mnpckNnʹ+6]tz~E=ʕ l ZZ5jSi3#47.Lcfe`9؏v囜.F\-UZ:*0_<Νu9Lӵm&)_3\^ҹ3"1n1v_|uRʞͫr'iȧN_kH׺8xXrj=\МH)V\ˬ.Xʸ oVRC}ySU9/OBY먌5 ٿwޞ)rw8Ӫi5*5ZΗcGƱ !ZۄlmpjJ -l <R̵/JAպZuq\IdUS 48wXJJtcg4cI~aqߓwŷrm-v)G7yS^7H^-\mŌAq|"m9IBnF㏉9[N+mmy/!KKۉ%n +BdddfFF6FQRN-U5;Sv'm4kcM=Mn)\qιqUd9F%",6MGdT%-+~ f%+y֛^3SrF>6lc(֪vۊN;g._0Sѧ]ETWرkQKzGe9ʨsKA"yC y2\[5 rԭ7Gk5Mzw_4sM3hxЊ'oÍ5jsub )ͪ~tR2H]R͍>̋m6=%(˿(Wrr-܅y5(ܔJ޺YunW̹븹NsqK ]/QR#"ZMDfD|43Qw|._ԡSqTZBg??O Ϥ)/E_U|i}2 9Z?¹0:x'3,whǣ?C y-A~=daJј&M?D1_PS+Oi&;a @;Dž7[ zZC"bv:jjMQk$M RԸ3uA\=wI.AwC"^.{?-\NSiˏ"b}T/}q/ o.1M}R%:-ZniʒL$SgrBW*,Mw'N\ɇ{s\j]VryG'8f`}'N<*/`U숻z CwHq18J+vԕKss4R53/&XTt1bZƟo\=%nO)h$rBi-nKĪ^ ջڜlwkYm[̑+/QrZo%TQ;TLs($2C:s.%+eoNttq۰kK7O0m_t_pZ1SsSM7"mevFZ[w -FJ*T*jФQRg BSu|]g:ɵzjqwmltL.e3sRMچkSmjkmWœިm++¦'tILk*բQ D,PB\lI[9{%Gb R6öۍmX-MaʉA931cs..G4CujQտ[9 }G-xwl)IQz j Ó"rqe&=]꾧֎c)<kӳ+0JrRR3'TnXi^xMF Bު*tIL.[h"2"nKzZe'ZV/RrNYz]8죝n]Ķܩ>^Ժ]u-7^\mZjܣ9+Rmn ߑv?oꋘ?&ƪy^N4o=3-ؔ̿*`}V݁ ƒPu8%$ ݗ]wt;\y\>='OjPIp/nJU8{϶FNMsf"ίNqƹ(+ ݮF2Km |jܴZs%zf*eȫ?]4)I۵nR&FX + [jDh(#哑9q9Eծj8noǕZf\J-l&Z˫}`ӎhyrΉn\űn]9pʌӣ"׮Wt?N4_I_~54#/my1Xr*척aS#DT >q ssΛW;3oUaJSRMDgQnt:Ql,/ ܷfRqiM Ȼ>Cob;A>ڦWقM9X~/!'MW.}Vrߔꔵ!5|iB(0-zF=}okڢE$^wW~nokY߮\6՜̌{i-AF*9)\t9IV6۸5ZUF6R$ŨQIq砳YUZ]eyv >hI櫥N )&l JulwE1GDOuFN2| }馥uC1rޫV+^gdb&W[4<^e4YW,d|htͮsUM)۸8:{3d{AѢ)~ \#J=NdƮꮓ90 |1K$v*?мS ]i$J,C,SG?/_՜pMSƯM|mG1V1$~K>CSvkuj=&) -,yLjuFHK{c駗.SOua;BrSqj-ۍZ#'Jys7[g2z/.u4+XV2VQ.ޕ)$"(%)#Z7suZ%j }BǬݕe)Jvz8zJf:hIN|svO1O#IEcۍjݽ:SdὮvu^@:o^5cs>i/VqmVm]ؔܢn6'vޑ̗J4Wn@OlKbX ;n:hgJ9ŻyǑz8f܌q&Y fN0N;[69 rbׅC2/#kE l&2~èMR.*%g=Ft.%؝e8<.e=Uv{~㻏"EˑnvDѭ͜Lu3u0:U֝$[M5<:oi+V4V9 6nXvx&_ q Qqw3W:uϔ2yb/(ɳ|5zQiJ#r|Hw#.W?4aDŲ\ugWG;Cw鐢K|xg)##=O.dF˟jMUvWĻsr.z]kPc9"]R)mkfOd*uYf١RsB Aîh=k]ʳUrrZsq`d#r$/Ը3o^&lRWȍyuW̦Y4QDUMJ65ƒ[+ygk XK_±k#y:8(TJOSQhJt2.DR}"5[) r)6V6u5k:eXZmv𭤔!푊Q[qQ}ҹLE- 8qIZG|UM4j}Mܕ[Vwm{} Naqµ"ԈM zOpKѰ?IAD3Ir0'/q1itoB5{%wkOBn-ۜduqIzYK60{+DʕܞqIt";r1mG/\/ym[6JƫR \L=S=OT@Ix[TMm{>ݾտ֒ݸӉLYIx>+"JVNzx||5rI?C{oz8۹e\R-^\A2F R+N9 vlT]"ۭ d)t֞i #E2jB@׵=#/N+!ĕhx}I!cM`ąZ*ŻɄҒ߮Y.Z}='/oۙ3IpW̮hT7cTSuz9>B}΄&h!>lӵn~j˅IvU.'v'CSZw8QK3G> ,J59ٷ+HSg䧎hJdzvwv-cvxS5[̊n~ؿ%ַX?O0\6ne 6kn9.ϯ} *h 8_QhLݣ7q +=XBҲ5?[[)+F`=4 }B,sNg==u*Nj9k_GJ)+R~GSPBȒZ:(K]heL=vKPӢwq(NrG^ثϣ?#tC?.ͼ[ۅo؞y#%ǛjVyLSw%T*s92JTM%"YkQО.q)gCͲn8cgi6j1MѾ[{9h^vƘǚםidfi.^RHmg&rׇz:}݃}xT$ضk'5s-狶,\vpbPD،=Okf.c#cdz2FK5T!&)|ntD<+OŹU i-G[EE*FDfeaf2QƤM\UG_{ǹm%\yrGy:.\4wjPGUJޕUV7Do\7Vy_13w;[?c]H\$IJ,*L]3b%L{y.JRKG2sq,B6T}(#nW|km+q5] r㪍bJ@y{byz,b踊3ϻJ,'^xd،)JVw#.Vټc''ÝպWtbRؒJz۠8!o9IۄS95E9ؔ-e9JR{dmnッ<[~n${~Њ$W?&ՐY_? #a.ߑv?oꋘ?&ơ|y^N4o=3t=~7!/M3>n8W홎2M`Qx+ z qy8%]7_~540ۦ彷]Wq CѡwkďyF5Dum_}~P(5.(X,K9vᯐ?leB9;Jhm#3{CxGE-S{;@Fz˙]=O'!ɿ]' r`:7'2bЖ>Iy,/eTy/V<.H?UYY{\^#ѣr9^7?xoRȆ7EoS_&??zϾM?(~Q-K&>"~aߨ t7Emsϛ+?;fCr)fY+>z$tIkjn_>vnrֳki-˹l= t;'EyC¥|/BLwBJdgjۛ$s S1|ɍV%JI6KvəhzIlBYɒ|0"Sy0F>eo5W)O+X˻u';v)2vVq۳kۮws?UʑBǴYO漪e2MIjPAک\b1)DDؚKm6ZWΨgȕ۶yjڳ 2ضN[C[|r@9Jfo<_eI7q.|cÊV߷:i.:$ȋ)1%%)ADZCEBxJ0MJۥy(bNsKM9k43IwNt.\%N簤I'.j|ƃ2$grBEٌ\}9:v*!n7M(ɽ]7c@XxƱԨ37īf62cTTfFK]9wntQHͮvٱI/f|j=7}\_V5U^+:uljSȃY(XI.ȱmo1甅jڎIZ2>#\*:gY|4k\8ZwSqtyA!+];бޞKծË¥e)#5ap.QK^8VdU{*ѽL\=qmjnB5>{ Ӟ`v±5 ^k&O~Oshɷ,;6nOW>u6{RqS`)S%jp\ipdEBLfTWy$GIYw~䲭J.1vSY5z.V>^+Ǎvc.I[R{QsNR3ӎfhd>y?UJ*}~[e\i5U^͛E]G_FS(Iɿ]i8:4zj~շsW,ˆsy:%O}iur]iF5~3M:Ӟ#N06)4ߧgdawIotiz:1r5YDZLHBSi;NQc44la=Y kQIT*ըl:tq2(է9VO4뒳܂~2rq'nrVZŦ[t7\oլfb/mlpc.I8콚q^1iE~䰳mi[dۧw֤ICfdFeCsg:i| 6擣׋* 96lust^{%99UNRvaMܽo ammi$em4D6DD\nA%$$#}۷/ݕr99JMն[oT޲E"KTaP+HGkŴj5TM5xƱOS-k`ۛkٝWz;{kS}F;~q|~^_|euwnE'pSupUP)V]vE+t =ZRaVdG6= *.ϼnj9:UɷbېmF_tޫgHjVS'śǕًdkkѻ_]Kv?nT>)^e=Ar1'3ԔILyD?:-^in):{7.؂\.:V }#뺾.3r̸*xbFM aȵz 6SQ:ײj[ 8nn iFMw rR"5M5I旘35f^j='j:nNW.ʭocZvZKV^ɚJ.cM1ZI7E'6rg탸5oZ=[m Z`\hbMUR١Ȗĉ):Jin!_7Dй+f̷eKҷvͨBPR(V`y6tw*MRΝcB.ڭTnc;P$8nFvm4(D(R#R-L -2:FP lxZKQc6I("Km%$E, 78uXIFA$RQI$JbInG]c[ֹ:ZM+n^')JmJMJRu{e)7jQDw~%yQl}BZujSSf۩QZ+Dzhd5o%BIc'GZ?}΍:>Ɵivז-%݌J5MqGWTVʦh݇ܟ~Օ_6 n'{3~mϬj'J11OȻn߃r Qr\3y٘+WӍ'WxEs^O3 o~[|7>]]H9݇ZomT@]?5B:Z߂'`V_+/MSKX߆ޠk3?o7y:4R/7þ] iG߬aBRU&?r&/} cQߥGj2?C5Yśe7hU=?+ x龳f-܈czW^7p%-(\D4h{UK&ӡn^m]Fݢ:`δvj俜F+) y[{{ 7 tu>gvrěOj'5 iRg[ͶFjGe n~qT$ci ۚ0oԹc*jL[sVWqj\ݻ&6"WoK:cnWmrv)o>66(F>=W^bf#c zzʞtپy%mՉPël e}J.\Zk4ttt>oEM=q)hJjI=ͥ(%]脼_88ф;͛gWG;Cw~˘$4=uWdĜTثNDkiQL9U*O"4XP`02,Ge-k5$h>ܼ]3vr6!9RQPIVSnM(ۓ{>;/Qͱv{3&-[rc)ܚI$n{Sv3[j00)-D3z}MRzVQпj,T[uVs0\}Sid;r(ݝJ>æʺL&c[jPK0~d(FKÝW\m]GTcF|Iׁ)I3~#oX%vҦEݑؼ5Żv2qAZTE^..M{ʐfȏ2##.R}*KʛZz^ӞN*lPťLf\G6[WVQquV]XAi)5J!,$iJ6o$tPZc;Kjx_n3`qIelV~vLy{fn匋Ѿn%;zV.n'-ұdd2߽1bZksPe3TI9)$ԩIN9Vơ\=2885N\ p)/a柛w9g_lױo8ݷ iixJV& ғRi{N^_oAŮE6Y7I$Nk$|Q)-*4Z)^¸%4Qm [I%.c-OV+C֧R#%ѨCe3i;w$G+_dy| Fzj$DI(=OA gj%v/]8qԯNIS*֩',Q%\44ZZ%D|Ǧʴ6&vֵI$%8(ԬƾS&#Z. }6z?b/|Jl{ץv&mpx4Z$”ڝ4-H%dGKfM:sKSRWeJAn]>s6应-W9'H]'uȫYvgK^\czp|My\鏩w/ËQ.)]\QiS`8uL뚛̸=J"ܻi\å'-)54Ue]:K\퓡vK xwBqrH\*֕TnzC.mT=t-H]SČ~Nu╏NÅ3f|͡G~B+Xm[Q7U{9"~jgK Zoʰ7"qJ,ekSeNGgϳ] ^.6:s}_,%eRg<5⿨z{ZPun#jRІ.6g T.!]xa c#jN$Zpl̋H WZu8WmMRýsĮ?Mco~sx TU҆Q :KDG4n42.<3/'^?6/ܠڒ^yrrÿr2\D}}B]^E~^T cɛ7϶Y[<֞[7d}2%QPqOLEQR\CIsj1?\}%tJ0e~ *sk"*)&ۓEi#{1J8Hrt|'ܝRr8)=ƔN'RVz:cf]F7bZyZUȘ4x8,#JG̒?.W9XnO]KO]%]ƻ O5Γ/3qÓj؍/r̺rƵ 5\&m6h.xoeX[=<3%< lZ"2h\Z[&jW3ejm?k&[]ųj+{N{66leu_+lj]q* 7g*knأYv= q ەdxЬZ|%GUrQ3jLŒqET]1% qkXYūYc[7Ś]QY\jko\</Lc7+'hMSUc6qXyؙ~6#ѯv.0$BQi5YyIhɍiy=KD!n3Vm[V%W-B%swa97ajۗ m+9~]fKq|Ddaˑ0A]_v޺mM5* F-BYHJ5}q>ʉ.6hyDmpD׬'-_v5;5[8K[viJ.3dR:oYHHh9I7:۽fi+wm^ [)odPѱ52CZUJicSw\&_s0uBȍh32džzQflcd^m|7GѹE!fO5]]H9݇ZomT@]?5B:Z߂'`V_+/MSKX߆ޠk3?o7y:4R/7þ] iG߬aBRU&?r&/} cQߥGj2?C5Yśe7hU=?+ x龳f-܈czW^7p%5|Y:SJE\U-(a_cƣUǽXXKiȞNlmۊڭڄR!**ܤMeȽ$|X5(Ź\rJ~ܮ]>'HB0cp XFr_c?f?7<ukSgov¥iG>>䙗i.+t+bOjIܶ . i^:nm}s}(3>NZ$2Qg([".>i.ƾ)B̋M8+"- >eE6DݥJnJˣt׻ 5.˅nJGwZD~!i۶a,Db3ZQ3O#KO5/֍ozuK'GbRi᝘NV_ҝcvם ZoX}F6z 7e5_e:ۓj=AB+iܔERadMBq*ԯ DwI/Gy*mĥiRKg6skY/#SN4e$-yXM YL?^ĸNNӪ{$r1JJRSLO]Aqm>V/s[~i/j+m>z}eI"Qvp]{ZԼ:{vPAG2=T͡@ڐ#u"E*>C;o$~C#_d/HBq^YRٽzIKbOm\~żjFFGdiQ(*/i*#.FF]©m=BmpQQQSP&Ҫ!T&^>:y)$ˑÐFčI Bӡ-t!bM WҦŶ'UZ=}zvn~oT/\ǒ'nr8 AJIӆz<^uߖ4eFC1i+v!3qNyߕni?4JZlmYFXFۼO0B\m[ tʄU3s"Sr(NJ;SKW72L4̏BVdf^Ҹj\]ȱ۪(ӷm?J-KEmWڽ^4<8qu%9pŹW~877ܾeVгS(յe^C]yX͹! םm4FGȋ\y'Z FX7e)|Gjt߹#gb\ŧq_([R8[qU$Z (ʻezV2V!iQ,i$JE˂٩ a(GK'O{vnBvryRd-RK4=qxZJMl_CuuIz @Rt㮽޳!|68\-l[џ84-2Pu" RJ_^OL>G1~XnBŬw6J0*Uvlږ1N G1q9IUm*'oWu][&UyYZbBZRZNfEJf"+2nF~Eû7n1xv.RUM$6 lAxSQJ&n5ܞwlEói"#>4׿Q.nEq7Oko[1wg8ZQwZYiqtm&~">Bo?w͡ni2峋NCEy Ҕ+%ZJ ʩq*fpˤl,~^Mχk1+:ݕ z&Y`KLӪУDr3[*Z :(SL&ݻ۬Vqsyԭs x|iI߽zZrg.:mp%6ԜvgmpIUt;QbS.Է) ǨKSV,*lڌ|5Jt3#NP.=+OZ~/G سIgbꥹJnl_DUM\iM!֔wVZuԺ,yV.Q>f v:݇WiaŸN5Ҕ[M7SsrvǣrMW= \8ZW-jsnڕ.ZnF2qt ً[ٻޘY۷Zm"Jxr&NAfA-݌to9s359݆mZ+N1-qS$D=17 x׵+%_ ve4ir6Z$FDڗnFtOr'7'{9C˨ꤡaYoace{Refnft RR"4%ʌm:Sj3)OdInTO>X'vxV#jܮw9Fog;5.~Y5\~18YQܹvj4+~t7S ﬕs %^۵ڴDZV69R^Y+rj$ԇoJKR5wB9C>Y:l+EǎS{ʲ{T6Wi* ^^9k/y/Cs\g*qڵgn4T8mERr|Ti+iPe;;.i\EBEJ 丬i9ɧM-ԼsGDrZ>r#R>~X9y4b棇9JwV۔%m(b[Tjvl}۩~nDԺ{Zo-YuK1vx.nWuO+jN [ٮ0%"΢CdTJK-RަH"$I(*ve &҉FzB,_Vpqp9m8werv')E;o&QE׵^d9˦j\_,ڵugZȻ̧8k+jK{wmr@3ӭ2 wFkzFVqs1؛.v'I%$[iT]D5Dl2 nk7qUxԫLS+sا3/ΖeZYK<["%-g/kRs:f3;*E ت wJ%)5&+&rw*霣i|sMҴ|;R+fm䡩.!**dӶ-6s6,]zAXMWjmnz%SJߴm2UXw7MQ%<!tKys#P,W>s;3IYwx<+i_\\\U6 u7P|xbn_k&ӓVOe䦒 VUr,-㘘"-LZeOSҠթrEvq8Kf%5%&K"#%vD/.ZYYŏ+p$nZkvއuW9㓱Z G wYIFyf)?ƎUm5ԉ/'k84{KO:rQI}XRuԪ|*lu)3qZ[mSm5R3".Xcَ5c®ࢫI*۳~wRϿQWޝ(EJrri&ۥ^ʶ齲Im|[yb;mnm֩uiܘq>E+Ikx߄3r33-5𹻖09ϖ9[Tz~mr5NsWl$oPusޛ^{Z;);sڹf\3oٹZmԉ/'k84{NO:rQIBø8Bݱ3n֤DiK4u& ofSȒܩx<˘|N0Fչ]qsp"}! QWw@t4ӭ+cO5%]'*{eM߲DRO1y*q8w++e!c߶ܪlZWّM欼 CQ̼빶lX{vib/V/ ai;x6~]+z]MWB>re-:lgk}պ!#9?%܋V-c[z!W?c7YNm/jRr[HOzԻefճ0q15Zp#rkQQ0tU-AmڵP/cȕ?0cZYj;:0ZM=D6g ?'UN+ձ[K ܖB2'xq9{|۫N0ku 7xaj;n\ 2[VznMlWiKbSk))f..)Km)&bGZ=>OR܍W:j'rM'wYz&/鶧{Sʵb"vջq[I-ՌZH._x*BagC'T(Q:$ͳQcMCKy?3g'ߝqnT);qs #ؤZ}OOI:cfnc8W~qy.;^pVl]Hԓ>^H^@7-AA܃nmL(uWܻS߿ Td95Bdh4t6*dDh!EhI[iŨ\L.&Nc ܮf^;$R)\rip9I|ٺ?#R.ZDZ;/]nݻqs\QE9M&Bd ]N mN*D>tgbK>+ˏ.!23]BȔR1ɝ^j'k2ƮqBQq[$di]icV/e`޵B.FIIJqbi>Ӥ|p; 6${)RU>_e}^dzdfzi %ekRVUS?6'hׂ)5.\+qUgzE2C˷ecŏ^֔ibk shesFWJ#~> Wk~ݨ}ڶ>ơǚ)׽ZƉo~B-ڼrvoE:Ʃ3ۣK7+Y`WirS):{>ڛ}:wԨ(J_";6R%[u&ƫdZ_\'np| RJwNeTW,=rrbnkڄ[M3ܴz)3- R.?:okۼ0TU'w{6&w7j1z3ON'fGoO?)S_bQ_¿R(^ԴԴG.EtMڇ&RUiW uQjU> Kiu1d<ѥIQ'RQ1:O/lŗᏩiʂv&Jc{D5 Tt)1.n[n۶X}RjqnOʽ(~[Ns{ސ⛌uO,kgo֢dRNQȄ .'6W!׌P朼tdZjFGE"]K@'i۪N;sI[{SOzk>`rRR+!σj8&TjlvA̷Q?HyjyLHNտJMjܶT۽lG?SnKN%<‘ nq[N0Sq[Ta(&t(|HGO~gvkݻTR4&Z$#ViOY1r$6YF?e4U/Mvxų:zbU^gQQ+NW_'4jfz^c'#`rvrڡ(IJ/J ݦ6 ]-CW |_{v*_q3^DZ}Ic6Uڌ8p7{crZq5ki`)mU6|-Z5^iEz3P=:Cu7DF'k%}<C-޹ֲ̱#\,(f88%X-N(ck0VLR~} G"-8ӏ/ϰKq?(#nrVTmZ;zióM4 m |UT'C^_1X.gXM{%ʤd 4\ovN":"y-,T)fLQgۢr=/CƹǨJVr[a+!rT|%Y\ٱzsS>jͱ.oOc6f$q% ǒGo;n[];ߎjrk{~\VۓNIGn:iqxo |~t5)Rxעri{Vi&NUOl_ѮMfsޕkЄay.0P{7N((BaIP$ K"U6Gl ݙqJRu+qN$ m#*p<|{:>-Ev=86N*MM긭U*uѾ?/^o7;'u,h4݌xښRM:5.(/ \իU.{F^rmF-Jɷ.>Q"[4xT^OZ~mK}T0ݛ^SAo9u?lX(' qj%=X}"^e4wˠ|rܫ 6I\Ķ;Ӻw!'ڍWg{ i U_9Avhۣƾ+:vs/MK[ɭīe{`Zgb}r[i'GE2J7Nez579wRq+Un ]J.cJ4M:h箽Wxxm^ pc\wcN%'My $$| :$Fqɏ¾^қP9J6Wxvu}ݵP>Z'FFdg"-; [¢cmWkÎT8nG%ݣ7*\խCLRYZͤiD&J#'ehbSyXK|y*ӞpS̍R`[pTr/Eg)K+92{_ n3zwz'oŸۤ+sOj J:`T>Cf*lwd\fYOP"R E֢̔L4ɥ :;.b(B02rJ蠟9>V'9M%)IqnhP<%,r'P/vNSwr#w"ݨaqc(|{kd=^0jTMR2ULNz|.<|^PfY22##!,K~E BEJۜ&jRNsHަޛg\r,v؜.jK3)[EJ2ii{KEiHP^&]Gn8x=K}Wx/KI9-ϵwQ%spܾ[^R}S3$qvq8M[ ozKxcqmJ/ӿ{_}7&ݨ\f6ZSyQz& 7ۉ[8~UNn|nkiTB+4RI8'Nc%tn{!]Ȋo.nEmʱn𵵥J A+wy#+ikǒڂ;՛s85'KmE:Ђu""Iģ5p=БbTY-ͽڔ詻ngL2Q}$de# fs^o{DUUsfwӶ;s1T,ǤtޒQ\෼J=.tKU,7čJ5 N$y3kdSMQU~mO[03 $zAڟsF5^뜞"Կ QHmrR"ӳηer+ҔZ]hE-6Jmt'ޒ=O[sQj)6K}?e4v_KfZheޓ=BV[bY}lݒTTЬ{ȫvO_qpRApVŗ 6ju=*BR)g "O1yhb=tqJ gtm\b3RY+JQ^Ō֍\յ\>+uSi{=x ^w;uӘ#ĸzLn*$anok߷CBӷ}5Yqvdž<( "_OWit5:EZj2 B ρ1̊fi[n!HQF82q1牙nqnEpT(2RMoM4ϳOu ':֧_Xjsg jP^(ڙ{2%E͖j^}ZU[Q$'U) <܂%!s"m R'G5M0<+zM6qYm$ڕ$3ǧH]?o2N<8F1̻r_my[Rf59NjpzBnl7*{.QP 3N&^BLJPjAHCK2Q}$#~YMq8 k(MFMU)8MEqTy+Tʞ-ar5yܕOXw!e;q-Jqܶ䓊Y:LC UE{/t>r"lI9)3KJjϤA 6SEE$d߇3KG*En|P\ԭTn6I-ƍKTj<1H_zwGr19wF N8ݝ+a9ɫM6mhePi%mmD! """"""*1bRKrD"vnrM۫mmĽm]ӡiG~e"˩ lhRTMk^MX["Jݱk7_ޕ*DqĒ&flՒ}`W}~SմZ{ĕ~wm*/{{ѹ_-0ط#P]xlڱ~Tn5wi*lڪ (JxioϏbqKYR|!|KN53 OS222$jzww%i}>N)E+rۥ7c$Ofl/LNث\6H9: FY󡈾I)fB֔JI_ ֣^: 9mY{66㒢7Uj]:.-os[R&gMF3˸#໹kmjq^8W"PΦURjʄWa˧T!͋ lW48JB2ko+ /Nw QwQzQ ے%$ޓ7^YL|r7!v%Trܥ &|M8~ybrn[RV gSn{{*#2#ԽᢏӴHak" ӌcwҜw&RJ07ױ>Ļ =^ BɆ)v32.M1=#6%̠tҤnzqMwԣ~s*%-j|_m*.Yx9Sz=)qE4 3pk+,`=kNRڥ=B=nŔNAx)Q$ԩȧ4z3t#Z2lҮYn$S%y- JzGpu|LBV7ZW#;Wwipܷ%(6jFG5#{$D"uۭ~]֫SrD܃fҎӾ+Tu>-ZTQ& N|$沸ii>eRWݳu'[O̻j8JۻEѩ[]vni= ڒ,[_%kC7I3Nv$4ɎЈeٸoUu:[}Do5|zNq=Tre%ɧ6&~DȍF]ƞG5q m]/w/ \ʲr8=oʔe9U(W"|S]uZd#?Se[W"ֿh][-7Nu:T=)R}.;ml*5Dlf $fF(̏T hiIUU4Szɕ t(%_|2 ~6eM;TƗK[f&]LK^CE2[ȏBOd;Mi|cx,^6;sیGpQ\NuJIFTJ~đArh* B"$H쉩eXPRj?sl"ԥ)su]xpԴY%VESH"ЋJǰ K&5^Ukzׄ8kEgS2h&Se\ Yl]WҶp-ZUvi7QS:4byqOo+[̺腋[6-_Fo.6[7$p&^ _GZԸߍkc.qqoI[9m߸YxOZЦ1uoiSH)P9Uʄjcq= S>֙NeR><;+ڌk%_qT].srNO?s[=vH[]RZHRMtᩗVؾ:/~u)ԍdg%=edVrISb{6vSu=(ܥ)mTv/J}̇8 S3ad:^hBSf؉OɔLhI_1d8,L><_A0y3rXq"'(۱;mFNII.v5_(^q~X>y{3צ I*Vܛv/jW' T'NR'j%ꔩ:mJ3SB}΋!-H-RJBТQoedi9tjENenPpke.%4]#{:>mkEɱdYWl\\\'nRM4&U>?Ќˉk÷!𴪛]]5}UqG~ݏI"O~s6(Ļ)qO~h}uԕd}Q~G,oE!&G&/]_H-O=o{k\̭bkv.Ô܈+;arZx)m?M\3lU$mk-CFXjTv6u' g:Vn_*qk:VC A%'4JV%EY)#BғO4<e׿jQQ]yUr4=wm[K1r׵%Iũ-O}|kC;/VcݩWZ)EHdžTru]8hgĵ-;=>U_ InvTm_jBM+QiF"9*{DI/iuo(=TzϖmPQl_v4z>T*ȴ>YF;ε\t]EH4ꌇ[VrLzef 2T^V>g2~kg5~Nק;{~Z~W}&ŒBӿS2$J?~(Yœ"˲ߩ\O]: J׉ښT{mmIѩn3˧)4LdFZ/zUG>U> n 5& ϴ-KJi2o]uKljvK3$bԔҚV旧iY5.ίfi96v7!v))FJM4{jG~Jt/lUE%pTAFe4qQk\ve۽/u/Im+W')v{\-E|Pms7߮DZRr۞/mu*1ՙaB܆ -xg3#6ۥtRogʌU)׎]ZҞNnŞr}F1Nnޞ;cZ{N}ۿMiuxʉ*3qi'9KHQ$WJxXyرŔe~[v5~/jN9Q4o6rJv FrdxM*iRjMzUinHdн7ᾞS=S'7 } ̽zt7K|_g J=Lq+/Bw_\ۧx\HJUPzQ<hqF[V0x==CsU7q|^ {)Iq38$_A(VgcKu06Ƅ"%i~_ˉk QCܣB8Ku/񋇵u([w}$F|8TՠI.E !;RJ^}MɒD_q2];Ɖ{5}*n7nEInO{Mwv}&q+v [V}Ĝ@%>#dXQ$f;iep.GquixVt x6bj͵mlKقQ[T]zs/&yەnM'W}!Fp_d^Tu N{ɻ'l{խ2.sTu{W^H&;1s)Pӛ6>$mě;Łnj= fLT)>׸+qReɴ[UR\L*P/!$Ӊ3Q 'K=m~6XqW3^W+ųO_[F$rR*u"T%@O +%# ]˽!aܽz{ͷvQh쩎]hGތ5ɇ*DzJDRNLi 4:{~2FmXY-zzĽ^f=]uū{/+&c:Ma{ĝDp2m܍kHș/(--m_vݮK(V{R}.k&yƴ7i^4@3f sK3^Ř˸B=]?gt5KbZB<e;kQLpxuWC}n 5ҴepB##~q= `x]KWF {GfŲ}?G.I9pjWkU]>={7q{kO/^I3==f1ɏ%nnʫ/Zu_yXN<57ۍ'vy/"8넭M2eԷ&Y,в33%IkjMr7xf nmQkX4踼>a-GcIeތw&U=-:qnW)z¥j :WqSZvԒ#j"KrIU)%qrmRoDGQ~SYRsu*V)  ,/x)MFD6O#]z 96[Ui(JRfw'y$GeUީkdMF-ݻ98F2d[o{Rn0n-xsV6Dh|Eb2E:KCOӪv4SJCr"J!!m,hRLD| ZYFm/X~ΧfrN&4Ƒ=Z9Mh.Mܵw/BdrܥniŪ8ɧ|y%œ[M=_tj?F!z5\evM:\ ~F-sg钬OWq“iiȍ<Gi%%n2rqͻllƑ)okw7}\Uk-:&fj솘XerV9yZuʼşdFC=rmo%~ZN78X(N)_7.Εn1MpJ}62jjJdI";R5&iLԸc:jmqiQj$ujp\{;v5B񥍪Xn Ą4qOERjzN(Ga٠䌡)p*v(J7#ZۻZ8O W uONb+^Qipv9GvֽƼϯrYƖKGJQDNPhRJjᡧC"21"9ѓS1;R_O7/WGz)8fE%F2ukmvSov/iZ&/]~KmI[:^~ͤ\kMi稜\ywJt3W7 8Ʒ~ݥeFgѼw"8VVSج\뻆}ݭ/J6Q)d|)zU3>k\L=;ow֯gN3pKѫ|wmkZ$z^2R:E)f>ς нd|#׆?\ǔpV{;\$ƵE%-ͪm0S6[n< kE[}mvE4DDZ^$OZ0*$~XUv҅B@^?]so#%ojw;Y#SxxueBگy v^i-)s)zV jC{7Gt.w3v,ygg8s]aE_,*E tY5k٨h=o"m泏:\6w噓aiL׎n^c\75AGkЯ0Lf46َ`egZ˓p/k;̛]kq!ݸzpԭG"}R9Ve>ˏHUjJ-&7nrnwG*Xv\˱/vN}O)ʼn&CV͍f̵]r\PMB-6Du-#RͰtRN^)mT _}nSȕC*_xBuTkJW[`ɩ`ejvsngP ڻ.-WUtܑqԹQj)t;vN&RNũT+8%IXӃ5fK՛-d9 ]CƑm|nZ-6=Hz,*aEm W3VzRšdY~Xf׀Xx"]s;)5u*ُHB BRGS6bݶؿ 9j[1*jױga7oX CUI%0v#~\-O-Ꙛuɷ쏪&5mY٦M`LJ2qK~HZbr =N'YobI. (^ ׾{_ ?OJ`S`3BN[}5w6:ǵ/iSlt=4F*d&T4y/#. ɵim5Uֲf 眕6Y7 fơ=3dϕq뚩$qTM-%r!$@A? ޾V0c~{[{;򥧅a~ڵ»&ڄv1ek=wb MLkNAԬw-x>~/r=e73VeVN)K%Sښe"+3uXuچrn ֺVzscJ峻m}vb㶓n\YbIUBT%*,0nov=;z꣓S/nSXSpl##k9mXGrZv^Gde!ŷRԠzQyjC]`gToPov{j~KRBMY}i[߶9KL2ԉO0K#m>wB[ٍ+n[[b٦DX ݲpo] [\m5qdT()mo4Oy9Ie b][wղmM~vmi۱~t \}$яimRk(L c Cvk7r9_r1 ;zv|F@KyZ[&jEji/"6$69ml#e]9s\{ScL}Ȣؿ0q/nZ*t,CLoD߉Njǚy=Pgmu6^]l-["çUʖMlʍp-"qmU>۷uFOJ%Ǔkx 'g=睋k[3u,{³WɘݪF]ՍeFX"Oy\,cچ=w/gn Ļ]#2? vqy-gXnR.^}ݺFs{ŝG]}e|#0mjx"ƬWكm?rgU^xVB":Dt>@LRbun~ݭ,w+v⪕;\U(RYa61>#Jm˞Μ9g9XKaG='u8gf}'qy#ɉw J]We.ʲ-<+&q%s?2dњztҼn`cΤmmqMdz O[-ߩӲ&;[tmܝVnr">{x<8U+p:Ig]zjGkt,uzf}dؠoJaکqEq -(:d<պ=eKy[˗^%ZXkX[C2߱\ITTLGzANM￵i]K>UsOGDDD.ZF6* ҃V Zhz{'xp^`wo8r0h ZmJ5"jb[l=yUu7-;7IT%:jFjߖm0tzU'K)څNۧYJ)4IQ}^KWm7kSP>q;ނ#)'n7&׊r?óM{IwR\j2Qn[v pe#/tAF\ϵ225q֒om6z})6҅*oqDsMf CNIN=T S2t,_ѧ}kveMF0J\Rnnݙܹy[rUc-j{yGtkQ%s]5qB.Nw.JN1LvR Ui5J ZESQԙr):MJ+g}χ!2;q([jAud][ljVK3$ײSJI=/|&tl'*n۽f.frܥ jQO8>&Z];.|7T/C}$ڋUmP2Reҭ8hFF\L 3~e v\۫]ݝNmrnB%*]Z«hKc=BTLG :V74$=Ǘy+EX'4tn(I:Ѝ;Df8c,k1%dJ6.j6ź{N~l6&*fœI7 WAlGOu-ҢH,,(ǔe뿋쩨kM܍ZſgRvQ' 9)?n|er˭|I|-fGK.rΛp8XV1%K6mvG+tc+qE&ǸC_Nm:l=_/m5^[dߌڇ.c<%:)tQ$Ow~-aY;UJ>=F)2[nk؆?훐M=l6[4(O.]2#-H^n#->&mp5~Fӛ+|| S,xag%qkEUzUgæBhߕP(7]kFnq?֖CpruZ6*rEڊtS|*tI*E}7R<,nUU֫^I7Q*mSly%rdȓd8hE<9oHhMfNSRj[i7D[Rj݊+kდq{"$$H?p\̅S?㭻;t~R߁)^/>Qj`yt[w ԛ;²~+ߔ_ YW~|o]?x^ᯛ `ʼn;g)T@vWn]>&4lp+$D̢1l|ȨF%-}.9[}w~ ԠLM9hСablfe&QoW!s?wjLK?s7yO>(=C~_nyǜu?v3vyo oI@qV-jeES^[9WoSܝh"l2C1a͔CiJ@3:Pճw=/7ovuk+\V;lDgն<[A+rX~d;m!_s8ݖ׷;;.0llUC+?i#_crʙ1~C.\–q ul8Hܶ2m`ܻM3Tov|Bs rɵ"oLS- DКw=Tv@f'6|YlD͓Y%׵-#Ѯo%:&!3o%\J<02;K87>^vgƓ# ;ݝmz^Y6=PS39U%~ &f# }o!muH;ʲŇ˷yvP+&.7e[3'vR4Yj̗IZ`e˽3o[WU{ m[sUbۋZǾۆl6~9'V*.\S2<Sd*zY[aŶ`]C$n.v^Ʌ dng>ەZ,Mmϑ :n6nϦezWqUJ4! ۇ4R! =>>Fn|Q[{pRO17ƕ~._I''00k=b՛o}Osðc2'o\3}ݭQ^2 . R1yKȣtAݿ-uܾw!`?1Whn|gzUo[ECWwjUIן)^h#1ɭ!/Z np;o;ΗŻkXs."6E`Z1 עӐ9Kl8qd q} 2Stt;#j>;խabONŗ=fwP1j)l6J̶|gV2`y/0E˛6+ԫ1? 6}KW c\KoKͨ2ۅFw–s*TԞLיuDx .kCzWXhy۶gLu|%TnupǺl-S* PRaLnT+c+*xl.v!.U=|; !_L̎뱚U=4hm:ٯ"y)$:>%(n}X'p[ȴ ^˒4kƓmzDx \ 'NqamP7nyN݅=j7%McSڵj%STy qXymvCg{w/w=wSW5r̹u erծˊsOm=DhEҚRb#n)QOxtվQwe]I}wCa'"[ۂ-z}2UuKP$㜉ԧ:mc<Ý>RoL?wu|%ҷ&K y_!y9 ??:tq3(UU-lkS'ɸ@jdzQˬR] EVPW1DJq2n:,c|ǻ̑;y{X,ۂ.u.b˕u.tKBjQ"[S園S`ٮdNبeJ&9Ơ ~0a(Vm٘L+Jr*vڑE( x0+tp˕ n';wm-ޜMOxX>{#2%jgb2M[`K*\5@8l'e=0u+w ֘鳾{y܀:R*Ya]"Ӧ%ktynlۣ65,3gU}{GYrb;ge'TKwǘ.,rpܚV]Tr,!dp /ԺU,xՉ>s׽~W5oTh yx?xrrx?)?ilbT׬,z$Ԏ.UH٠\U1pU:]JwSrGZq8àd驐,N67QYBӢD㏙W!Q25ϸo9ms-7-%3CihO.J鯽-;MZM8ku-7k9S$8]q2E(}bۏI[DKOK}3KUB^u %Y,u.-&f#]'܆o$x`Yu,dzwM;#oKxn;\[d7}Rb+*Y䛂ZuBӱl{j0O̓}LhK;[aֶaGL{Cb#S.T[>߃F]NK"u^LUʐ_ykW?!GRj29͖qa'0[npcDvV)qz9R)PۨM^aJx W] r>];eN3vxdmĘ(5W2K1䪖weF{mE/QP6\u54x5[hۮ-Nk”i[lUgL]J}5 S:EhiUrgHl!ŒJ$pe=q^b͵Q' ?6|R\,JA ڵ"TDꈭ:ymg`B5t%M] <N_zv2_Ortٵ/i/ReӮ*7[qүqEG* m"[I:6e^p"I$jԴęh!m)]GZkcjS!{e^z}+Cѥ9;R|/ֱeiUԏCNu2Zhcٗg$ݭwvr P8*7/Lk~I'Km1+MW%Bk|oOm>-#qj*|Dbѱkn|n{v#jĮqNpMIUm(7Liz;{ҜݞڝVƚVϬ+sO!OstGvxӉ']uӎ4g_ 1^-8ۦ k!)Ύ5O;YSB#2Zzχ;<.ֵOtge~.(RC#wFZeGZٸ6FFJ4e2ˇpJT$[wgV)q6muDGJ56q\I!̗ y/I~RtJ9kJ]Iy*'FN0s.[l!fw'y(7$œ WƫgyΙdMEU JQJv̋vmrۖ.jWR_M֨djYgSj0^\y'EoECjm$ IƩK>Z28J2TiJ2N#}.s cArl嫶nB.FIJ.)۔\ZiM>/hLĸ=C1s[?YMqp|94- 鮝𦔽/k^#NT(Y LS$6˩}{;5 )B۷W$qpN)qqoot}ZDVә;7TiK|6f3h$dԄ}fqݡ>Nb򗉉+ͶO]>ߡ_VtYf79ڰիF sq~prս|QM)g%l0ocJȨHz V;Bb/kLAcfPJ,ԭ{ƍgpjNR6VSI*$!yV足jᇑ.](EܣqM\qJ2eZT).<9UB/(B0j)mtKEj#׿fDI-=rZړj|'Nڤ]k*i$5qt"ݙPM6E4ke^Z8ۏhz$Q(R Ay2zfRñnpnkbkI:=j &ΝșW?׵d{+ύM'??XqeeĽ.[o=UxFS=ӷdZwenՄ]_X=ĭVa* pKs0ބۍfJ3 gz̚i|wnxtjc¼5${(1fXQ65ȼb̶Zkn>%FQMJXӡ{TZEVNᖣimT/37cNJUPnP҂ZOE~"-Rc4^b- FEͧtf5[)S!OZIښݲ͑;tvܡ+N)AR=hCNn;wL16-:特7M$=Tҕ-.R[HٷnXk sn[ҞD-0WS9p9:-Ϸ-jѬNu{ҹfv)[Ľvwfg(ٷfe+0mYj8Q1\ݧg]Eǎvڿc!4#j5̋C2"}BRriFp7=ô\TZ:\BLfj#I22װ<;صZl j 6:l"6]۸ K'6RTѯ^ئOԓV\?$x7s#r:Oh{ց=MmuHԷd{pN /܅:UE#Yy+(SgQ(Щ)RHzw>^Ѿݻ>mK&^ '$Jۻ&w%F|xfz%˳ L~3N?Cy9 v w/{ƿ kz3x> sXv}vP"@WyC z`'톽Dw%-tt yVY\wmuPYQA0iG-2JP,6/gˢ]u.-n!Zw.N7Q]Df}Q0({a\@=i_X7gFǘ8^⻲}G MZ1)WEfO12G+=-B@z\`||w6ċj߬m}UwRox֢I &c~XGP6Qndpvܻul'V7^FJt^{b^B(L~sѣ6@߿^xqU!ڙ5|Vpvef-uӥ^3  FSDɯKD%0r}FF穛r7 +o"V8tv̖NQU!5uFd"bCr^bJ=֤fM#ʳԷP0O-9xRBm\=`r-:;~3Tl(nXtXi%2Vٛ#vwqƴ`L@"H‹qW.j,JM5B[)WܺUeZFqc'V˷1W7V̾-MHФwn8N;HPSdݷC7&2j.W\τGŎ'Vb]c.x+Rx1%C2T{myg[qU|+m:M:շ8҉yWd)ՋWS%%:iqlʹmGwݹ WnNŤѩ5(9hTٵDdGUi-)vSs2 2{OnT$Xck n:¶(lASLeȔBjμPpTb2~N2~%^k[ܗ[Jzs0ӓHBKq[}JَA-$dFQgjxxFv4r/x*Rm% `4J(&iv7SkԲmSH1YWmx 8n.k']:Z˭_W >ڃXЩ. jTq%Aā[E}amc]D:rmHRiu:uӚӢ\p(5-q%e)(۬ҖȽIf<߽pr&ݫVfY91q2ĭEQgYbTGQ&,yL+N$[q*RVۉQ=FuTܻ>f>f㋳8N6$܌n)9&»iˤsX,݅܍ȩv+sRTpO}d?Wn/Inpȸ%O]StQO|v5\}7Zwb.AIVK^:wb{[uݯcytO߶S<{8KSRׁH̏N7ۚ[xkwYy_'ZӵF+>쌛ZUĦreE9F[24De{}@:ExWs-\ǻ7K-\JNvEk%:s˙#κ].oͳ;լ7wB6nwu:$L; DkI#Wz.:Xp(˅v$Sq,wn\qIN-e<5Oe+vuYTpcojUI_ާP8 O 7&VL8z$_B-H-[uh]T{|8=qVRN-:Ij:7PUtXϷmy鉿:RIM~33ӸS2#׳GdŲ5+/Bx{(WzȨ5Y㞎#|˖+ ط.|e<o/rߔX>7s}VE.OVti׽ .5nNJO"95{#q}Ay9do]R"M6z\tnNS-D!@3N_jicWsy*5uٮRcWv/.,j}=S)j5C^> Ie =gu9ӛqjtz]۪TMoߧI!Ǧ¶m:,"[L!{qAv-o 3{"KʼnrIkfٶj2ƙ؄S`7` k6jzޞ?e5G&6uʷ2%ԒRKE*G\Npom F/V |C0.q_eenƣ<5Oh'67ɪn[SĽ{ڔjǘzs;~׌(ۂ`ܢ1ƣ` _l9Va6%UQWh~P~\F^ZHR@:ۧCJ{ôGeBh;~ۧnU J\O+n2 RҠ)ng}Kh{5+S×ܛ.1ZjG)iRȤIN 4%{oΜ/eO[Nffd ĹK?nnԼMqX'܌nZvq<ķbFnͪaQ`5 s,M_լ?-@_{w{ӺձJ}GF[%v\5[ŒGkOw/ΜM9rjË%2+rd~+󲕛C9U۳r[aJǭm|˒LAʨSCq[XMۺoubfp:t+ΤĻo ][ zt-*67kvS7D·MMCQXm;)܎n_h%]4ܙnRk!]ڵsDUF"`R, &#R_*[z*ZqFXɻ]7|۵w+'pFDەs=r./ᐚm3Hשy yD"jHCr':sA65نѮ^o1V/ f;nFr3VM)e*- s D'H݅fӧ\*޷[k<7u<-]֍Q8R h|p=WlW3s%Q %3l}@U-K6f-NϿu|ڴmWN׮[׸F*mW\%r! C78:޳vBG7ŵ.JթԚ2x)ST!řn~9 W:Wpܢ件{xf8ٳwKE ҰWxVB\qBZ 2wMb[lGSnyԚ~z9ZmያvoN2Afnݽjf>)j3 !;gOYʹK" Wftڎ+׭b*2ϻK>ۢӱeyԪXISUm[z+ugX%0lϏnvg!;t{BqPj>PyvR7Cj]O%+ݲ :qiMj6W}3vC/R=4Som]ŗ=ю, TF6U_-\6MyskwMr&Q\wjKܩyMϣUj0*}RZܷSdY3>Zjqj6TgzpA/M`/Cmл,޻feE[/+uk^Vs1W$G(JsW2ٰu*߻q*Y޵.Wi:ur5T),=0uRmho.twܖiYwrWHntvEj8qhf`Ͻpf(R&>Ki%I7$QӖm-2 ~yߗQ-앑/ x[k8nw.c㩵k}]FkbJl:{.(˩n0Hqvαp7 귎.Gupx[N`Yq'+ruU7[ү+>!xrȫoSo]OC# d^Q]\>!ƛGw^Mx"-+%vdX-:M2UR%d>%l ioSu6lsj7D P>XxHz Ukà(n^Q V>5cVtWj SEiJdznyej[lE' 3kuٌNn4JW)gB {4 j6&]' m-(ZMEz8cz>WZ6#7+[,MR-Z!4ܓtCyE|umj1ƽvƷV\;%>Q :#Le(iVz5 4ũۤUWxX ^(ҔsլB2w-V ^R+; ˂M\z+Uwr+RWY⺧~ Q*JcYSNSλUd8in=v K낫k\IRרSUaCFmϿ5̗P|u ZTԕ}>oYѲ1sfP+sQkX8Gb~6r,s>^\,mGL+7[n-E\.Fqḕcl*Jmjb5 ,m]c}NXfeVlǸJ5eˡ$4%g~N p4Y*WwW٧<8v#;qԩTut,m"#Y D\5V`\\Lȋ];LȇiS6ϝZ l>LruR\v=ǘϔDg=ԈdFZ+M{=|,[;0>RiSi4,S5}yxw&(E7&fݙ4UՕ! ~'Id)]ǽu2K-fޭ \08Vڅ쓬=Vy^^ IhyKR-B#Ըr=]mܻӾ'*Umkoy rTqT_i,/8Q^<ݤ|4ԻO(܄"'5N~#m.(Ҿ2i6Uev&I*<}҄$eNtÛzyWJubW^iBW.܅Wڮg]irO6Ve90sgv.+sV޿aޔ[p?3q*FutUo*eL\KM'EG*ZcAFfG5J 5jj=MJ3OK:k˝'NMB7m3uFҕ\-Ywg%PRqMIyZGY9|μvn߻5cWݷa^+X֥vnݘ\v7m>Fgzv"-;Ew֝}1|RjN𿊀7g#֟*GQQ|#/bo]p$>_Un9гUbn9׃ErQBU-^vDmVh'<R[fdHT]*~}3j;nvjc7s-rӳ Y8[n[1pJx kX[Jk9Mn!_Nю6x:iZ˦U |߉^Ԛ݃hYxk &U^bwKk.[jE+P(˞=9j@snCv7%c_7=xǁ<l {t'酚+1F‹l׭:ݻILruǶkL-L(K0L1&>wXB(pm;1fpnlp֓%Skidkt(U +xulo'/ڕeN r=^pZZ:Pnj8Hf"48ijY[ N[yZٻ+=  ø:3 ?^ܷ^Sr#YK[UF?CuhC b]GM')mڏsNrܗI]ljq6VB. W,UK"YX5{c >Iqā> T:n!,5l2VzCl|+I[*SrjnS6٨y+x,@>П.g+!rn9>N|W>OZT_ut Y""v7|sfި;Pclm EùN,{'fNT%U&LfH8~1v>Il}统u6P˗c(WV~H^bMU.o*oOF0N:_:6Smr_.b+|ݶYY غF,mwjv>f*>QM뭱Sd:`N{l/⎱;n-z~"Gze퇎J5S KG9!Gn;N1 ݎ h6m|S?ɂ5'WOÞ 7|7^ao @mxGmi^jϽ>01Mf0լD3-2T. VXR"ɥV Kl J O7|u?bvа;6.eߓ|[1bmRr,eRz`z 6܎-ͨku͹Fː dPhYgZUj}nvX;z=gVեTv_J }\1n7w2J?ޘγc\E 1Aޑzq;\r]]\Y&[nsNei\uURje*Qk2CSl*xJz-xٶlm+|UjUؓ`Ladqiĩ!Gd\W~fz;Tn*PdRM&T4`չSWq5k훶(N"Ӎ% V]֦wb.nUO!u*J&Oӕ2e|Z=eV쫚΅g#+/RW:طnbi*Wyo)p{:ETKؚR(RY+r웓r(IF) VmȵNB:h Q1ғ|u8E]{,'$-TR[j49l*3"I鯴zhd>Q+\BkNF=.$ZR4Nwհ(IpNi.(Gi33#33e$FXK*NdWrud[r{xnk$v2ıh+J1TQ[#JQl[tRO]LHKٮ NӍnF񨔤֞Em'MILB"ԋ%dBŋ+p̿_17jzT~4pc Vo\ƹb9Rq-'1j;8ܗ)hE%DZKS<璸Bu*%*Yw5ڻ9ۣ^z4U; Ñk\U(o~G?VUĎ:?P?_F_Kߤ~ᓾI |pr.Ok\SklRhҪz{­P .}SktZ7UQ4ڌIM8̈eaӊJZ%FFZu,KZvln廐SNFIVtuNi?CM5]+Ph,{jN JSR$IS^tSUVrORYu.9WyP6 [Kiu m!X|]Y79ӄ)\ģ)pbڳr%*&ꑶ_-H*dzk)1 V3')UAϹٶWRxe'պn۫h7AR9 EAJeGLms!%D| A 5]/Q3eb̄vnVn%za\m kZnv([emqrIҕij|""><hjJשvvǕ|Pޟs}V~2&Z?+2N&Z4w@)4iSڪ_>/JN9Hiۏuf8'It[ȲR.hZ$ȋ_Y ~U<UUO*6b)Ovzڜj\R̋.$FsQuҊj^נ䈈y<zZIuP[}Qm=C?zN(Exqu/kn S-FzKZzOסӽjJ\)F3b!r5ٝ|;6 o=-3*λ]αb\abqRi-w޵⦪~b8Kpo)Z=>)ғ"5/GTZLE-輵f7ݘ۹~+&+w/7GFI:l33fg.N~۲\2|*cnermnnM+Fq"ѪIz%j =YW8@~gc/~?N'?)«qȸs➟n=k" X“m֮VreMh2[uݖ] *FܖN)MȐ`f0 g,C9̑o;ddudJ=In13:ݒvvdMUEJLp^,6t-@͐9'{7m{-3,>hnF;ѰM)->>+Ěz!R* :`e--m7nB\u{b U>[8֪]6^ߤLʦ\DFNo$$dͶlgno8OrsQ\l̯hRo8tuNo+ CTxu!2[>ctFpeޓƻֶR"3QrQuOѳgwQr;S~)6HhZw/GgVTmUf_yt7%$];zLWF̰xy2Ʉu!MCmš_0[W6jf#a-KLi+3Q7c^qg%s<1aYIQeZf+}>;S6L0]Yu_h9߻<ƅpmiM$AVvŚ,*#t2.8Y)-Zhshü97/#Oro"u^/uFgWɺ,p:6a,^x%$Yve^3PƗMnTP&yS}OJ '덫MH^:rXԴJۋ/rI;S*,+yz1hv)Qw^ڍJ2oL׊q(\fDj:^T%vOadɂnS}ZO)N*λdaȜkG_PIEO}нa(^iQX᯦-7^)%g'SJx(.S9zVɴZ{E ))ۅi/s7 VIV-|sj0*UBTHIqRf>FP$KqN0 R̻8j\GcC}IUz\i 6F)Q{Gҧ3qSzKj-Az VЛS-zy:8*mNk|D鿓ND2u+0Yŝ7kqm·?8Ib]u>˗^_>(]vӋzv+ݩ){vZrJ2RQ몋C$z [,pp,8mڊbR]Il .f~d/ݓs㓓mͶ{mgjQwn=Oic9ܚm4Q/6ݨ[TƧ?nԶoytf{@AzT{e{[O'ZRZt~AGD?s3􌿂ՉIw'|~U\ w~di:Kޱ)U/sU%njѩ&GSP^ǝd)..!^U` 1wX[aԇSxoFV6_扐)T 2Mfd=ۖͭiZ7KK Bi9%7@<3<ճԻU,},a}FRqɛr i@ONJvK KLN M, ʖv0n-]DwlI-X6ܶ$Jʴh5O+mOI+Ra瞠\ MG7BفjYo1#͖0V`Ѱ2M?c8>-Crt*JkIGS:e#hPKx[鱼>{5m;wcն&>j-M֥^َ) 6yȜl_w{-ō̱r> U=]iw3)r*]:K]6BdCTZ|>gf}LW}[$'Y5 &c -j.z6R 67MԷFMnÌwI7w5E}o޽+K ֵy4܌ȥW"COyR[q5Ӱ͙f[v"_#q{MV6܍3"u9BK(41ӯqˇc${ߝCi6I(OmθzҜ5k^:>Jzw.>qV8{vU[ڶEm|DžBz].KHjI]x;Mɗ{m,qZXr忇2u^RO2Z}ZێS[2Jen!*NDcrBUً4<ǼMҲs1Zw57c3&ĖڻzmP*FuJG1-dN:|OU}ҵgi2t~F^^Z.VxjvŧnNNh<:]^~NN+ge^g.SԔGFe߯'[vn'(ScJ]kܗ7eJOlRrfziݮq̋S"\*U<*W]k$FջV}? 7g#֟*GQQ|#/bo]p$>_Un9;l S VvQU%OLU{οmU6bZ1MTx%!֙Q7, J=!3 ;Q,ڌ;6ͱ݅q^&ߔ·n #WbwӖX.HtG)N&d̵zpI,n cu ޖUj+VXUp[w]N o.J6Z8Ts&utxln;~HPHS/xw`G\ʡ¿rj Z^vt"[L:SD\h0sUwR,}[x^X,R2Vn< ]2YDr[SRKs8tXb̷G?Ps Tv 3be,zVz D[/I.KOEQrm'$7|[J>r S`5յwT#\w1FTz\Ԛ &"ׅhSHrD\'r]~/>p;:Piuu:"9ő=tTaS7V2rӷk7mb[^WmPp*[y.Þ6f]cizJCgRR@UVl큝.WJP1N{/\whZ ػϧӱE7|E֫Sί.x-Y&pi%v''-x6r'Ws*6=DwwUu]=C?MK [yrtܒG$!WGqJ*%SAz ED[^)/tė/g=#Omd.|^n/sl׉g DZqemqowݮRzUܜ=ڽ-o/Iۖ;qVʘgPp|mm;6zGl9.8pwWgsJ2qPbe}}UpNjٯ}7TMQKrؽtEx%v w߾8%|j;~|}pK]ơ/ w߾8%|j;~|}pK]ơ/ w&~e_H 8PL7:%ʭ5Kw&U2vwR_+rm'}C7#rWoO&HoG?M$UR7{FU]u ;# !Wk`|W>׹潇9Vn)6)*ҹ{%qV4q>W1vi#T"Qk&GwxcJBJ- Ϸ^ˁxkU}ԣ/3.;]J=<*)cS)ROK9H=,r zX @)cS)Da^ԽQ gxJI=w֣gf*TRj

Corresponding author: Yoo, Sung-Hee. College of Nursing, Chonnam National University, Hak 1-dong, Dong-gu, Gwangju 501-746, Korea. Tel: +82-62-530-4941, Fax: +82-62-220-4544, shyoo@chonnam.ac.kr
• Received: October 9, 2012   • Revised: February 5, 2013   • Accepted: February 17, 2013

© 2013 Korean Society of Adult Nursing

  • 184 Views
  • 1 Download
  • 15 Crossref
  • 11 Scopus
prev next
  • Purpose
    The aim of the study was to identify the most appropriate fall-risk assessment tool for neurological patients in an acute care setting.
  • Methods
    This descriptive study compared the reliability and validity of three fall-risk assessment tools (Morse Fall Scale, MFS; St Thomas's Risk Assessment Tool in Falling Elderly Inpatients, STRATIFY; Hendrich II Fall Risk Model, HFRM II). We assessed patients who were admitted to the Department of Neurology, Neurosurgery, and Rehabilitation at Asan Medical Center between July 1 and October 31, 2011, using a constructive questionnaire including general and clinical characteristics, and each item from the three tools. We analyzed inter-rater reliability with the kappa value, and the sensitivity, specificity, predictive value, and the area under the curve (AUC) of the three tools.
  • Results
    The analysis included 1,026 patients, and 32 falls occurred during this study. Inter-rater reliability was above 80% in all three tools. and the sensitivity was 50.0% (MFS), 84.4%(STRATIFY), and 59.4%(HFRM II). The AUC of the STRATIFY was 82.8. However, when the cutoff point was regulated as not 50 but 40 points, the AUC of the MFS was higher at 83.7.
  • Conclusion
    These results suggest that the STRATIFY may be the best tool for predicting falls for acute neurological patients.
  • 1. Advanced Analytics. Inter-rater reliability discussion corner by Kilem L. Gwet-sample size determination 2010;Retrieved May 1, 2011. Web site: http://agreestat.com/blog_irr/sample_size_determination.html.
  • 2. Australian Council for Safety and Quality in Health Care. Preventing falls and harm from falls in older people: Best practice guidelines for Australian hospitals and residential aged care facilities. Safety and Quality Council, Canberra, Australia: Author; 2005.
  • 3. Barker A, Kamar J, Graco M, Lawlor V, Hill K. Adding value to the STRATIFY falls risk assessment in acute hospitals. Journal of Advanced Nursing. 2011;67:450-457.
  • 4. Chapman J, Bachand D, Hyrkas T. Testing of the sensitivity, specificity and feasibility of four falls risk assessment tools in a clinical setting. Journal of Nursing Management. 2011;19:133-142.
  • 5. Eagle DJ, Salama S, Whitman D, Evans LA, Ho E, Olde J. Comparison of three instruments in predicting accidental falls in selected inpatients in a general teaching hospital. Journal of Gerontological Nursing. 1999;25(7):40-45. PMID:10476130
  • 6. Evans D, Hodgkinson B, Lambert L, Wood J, Kowanko I. Falls in acute hospitals: A systematic review. The Joanna Briggs Institute for evidence based nursing and midwifery; 1998. in conjunction with the royal adelaide hospital, adelaide, South Australia. National Library of Australia Cataloguing-in-publication data ISBN Number: 0-9586131-2-5.
  • 7. Friedman SM, Munoz B, West SK, Rubin GS, Fried LP. Falls and fear of falling: Which comes first? A longitudinal prediction model suggests strategies for primary and secondary prevention. Journal of American Geriatric Society. 2002;50:1329-1335.
  • 8. Gu MO, Jeon MY, Eun Y. The development and effect of an tailored falls prevention exercise for older adults. Journal of Korean Academy of Nursing. 2006;36:341-352.
  • 9. Harlein J, Halfens RJ, Dassen T, Lahmann NA. Falls in older hospital inpatients and the effect of cognitive impairment: A secondary analysis of prevalence studies. Journal of Clinical Nursing. 2011;20:175-183.
  • 10. Heinze C, Halfens RJ, Roll S, Dassen T. Psychometric evaluation of the Hendrich Fall Risk Model. Journal of Advanced Nursing. 2006;53:327-332.
  • 11. Hendrich AL, Bender PS, Nyhuis A. Validation of the Hendrich II Fall Risk Model: A large concurrent case/control study of hospitalized patients. Applied Nursing Research. 2003;16:9-21.
  • 12. Hur JY, Kim HJ. Relationship of risk factors, knowledge and attitude to falls in elderly in patients. Journal of Korean Gerontological Nursing. 2009;11:38-50.
  • 13. Jang IS, Kim DJ. Home safety assessment for fall prevention in elderly people in a rural community. Journal of Korean Gerontological Nursing. 2002;4:176-186.
  • 14. Kim EA, Mordiffi SZ, Bee WH, Devi K, Evans D. Evaluation of three fall-risk assessment tools in an acute care setting. Journal of Advanced Nursing. 2007;60:427-435.
  • 15. Lovallo C, Rolandi S, Rossetti AM, Lusignani M. Accidental falls in hospital inpatients: Evaluation of sensitivity and specificity of two risk assessment tools. Journal of Advanced Nursing. 2010;66:690-696.
  • 16. Milisen K, Staelens N, Schwendimann R, Paepe LD, Verhaeghe J, Braes T, et al. Fall prediction in inpatients by bedside nurses using the St. Thomas's Risk Assessment Tool in Falling Elderly Inpatients (STRATIFY) instrument: A multicenter study. Journal of the American Geriatrics Society. 2007;55:725-733.
  • 17. Morse JM, Morse RM, Tylko SJ. Development of a scale to identify the fall-prone patient. Canadian Journal on Aging. 1989;8:366-371.
  • 18. Myers H. Hospital fall risk assessment tools: A critique of the literature. International Journal of Nursing Practice. 2003;9:223-235.
  • 19. Myers H, Nikoletti S. Fall risk assessment: A prospective investigation of nurses' clinical judgement and risk assessment tools in predicting patient falls. International Journal of Nursing Practice. 2003;9:158-165.
  • 20. O'Connell B, Myers H. The sensitivity and specificity of the Morse Fall Scale in an acute care setting. Journal of Clinical Nursing. 2002;11:134-136.
  • 21. Oliver D, Britton M, Seed P, Martin FC, Hopper AH. Development and evaluation of evidence based risk assessment tool (STRATIFY) to predict which elderly inpatients will fall: Case-control and cohort studies. British Medical Journal. 1997;315:1049-1053.
  • 22. Oliver D, Papaioannou A, Giangregorio L, Thabane L, Reizgys K, Foster G. A systematic review and meta-analysis of studies using the STRATIFY tool for prediction of falls in hospital patients: How well does it work? Age and Ageing. 2008;37:621-627.
  • 23. Papaioannou A, Parkinson W, Cook R, Ferko N, Coker E, Adachi JD. Prediction of falls using a risk assessment tool in the acute care setting. BMC Medicine. 2004;2:1.
  • 24. Perell KL, Nelson A, Goldman RL, Luther SL, Prieto-Lewis N, Rubenstein LZ. Fall risk assessment measures: An analytic review. Journal of Gerontology Series A: Biological Sciences and Medical Scienc. s. 2001;56:M761-M766. PMID: 11723150
  • 25. Petitpierre NJ, Trombetti A, Carroll I, Michel JP, Herrmann FR. The FIM instrument to identify patients at risk of falling in geriatric wards: A 10-year retrospective study. Age and Ageing. 2010;39:326-331.
  • 26. Ryu YM, Roche JP, Brunton M. Patient and family education for fall prevention involving patients and families in a fall prevention program on a neuroscience unit. Journal of Nursing Care Quality. 2009;24:243-249.
  • 27. Shin KR, Shin SJ, Kim JS, Kim JY. The effects of fall prevention program on knowledge, self-efficacy, and preventive activity related to fall, and depression of low-income elderly women. Journal of Korean Academy of Nursing. 2005;35:104-112.
Figure 1

Receiver operating characteristic curve for the fall risk assessment tool.

kjan-25-24-g001.jpg
Table 1

General and Clinical Characteristics (N=1,026)

kjan-25-24-i001.jpg

CNS=central nervous system.

Table 2

Inter-rater Reliability of the Fall Risk Assessment Tool

kjan-25-24-i002.jpg

MFS=morse fall scale; STRATIFY=St Thomas's risk assessment tool in falling elderly inpatients; HFRM II=Hendrich II fall risk model.

Table 3

Sensitivity, Specificity, and Predictive Value for the Fall Risk Assessment Tool (N=1,026)

kjan-25-24-i003.jpg

MFS=morse fall scale; STRATIFY=St Thomas's risk assessment tool in falling elderly inpatients; HFRM??Hendrich II fall risk model.

Table 4

AUC and Optimal Cutoff Point for the Fall Risk Assessment Tool

kjan-25-24-i004.jpg

AUC=area under ROC curve; MFS=morse fall scale; STRATIFY=St Thomas's risk assessment tool in falling elderly inpatients; HFRM II=Hendrich II fall risk model.

Figure & Data

References

    Citations

    Citations to this article as recorded by  
    • Effects of Forest Environment on Peak Cough Flow and Dyspnea in Patients with Neurological Disorders
      Jung Woo Shin, Jong Hwan Choi
      Journal of People, Plants, and Environment.2025; 28(2): 209.     CrossRef
    • Changes in Health Risks, Daily Activities and Antipsychotic Use After Humanitude Care for People With Dementia: A Retrospective Study
      Sungjun Kim, Jiyoung Kim, SungWoo Chung, Ju Young Sim
      Journal of Clinical Nursing.2025;[Epub]     CrossRef
    • Sensitivity of Fall Risk Perception and Associated Factors in Hospitalized Patients with Mental Disorders
      Ji Young Kim, Sung Reul Kim, Yusun Park, Jin Kyeong Ko, Eunmi Ra
      Asian Nursing Research.2024; 18(5): 443.     CrossRef
    • Congruency and its related factors between patients' fall risk perception and nurses' fall risk assessment in acute care hospitals
      Jieun Choi, Sujin Lee, Eunjin Park, Sangha Ku, Sunhwa Kim, Wonhye Yu, Eunmi Jeong, Sookhee Park, Yusun Park, Sung Reul Kim
      Journal of Nursing Scholarship.2024; 56(4): 507.     CrossRef
    • Falls in Patients of Medical Institutions in South Korea: A Literature Review
      Jongwon Choi, Woochol Joseph Choi
      Physical Therapy Korea.2023; 30(1): 1.     CrossRef
    • Development and validation of interpretable machine learning models for inpatient fall events and electronic medical record integration
      Soyun Shim, Jae Yong Yu, Seyong Jekal, Yee Jun Song, Ki Tae Moon, Ju Hee Lee, Kyung Mi Yeom, Sook Hyun Park, In Sook Cho, Mi Ra Song, Sejin Heo, Jeong Hee Hong
      Clinical and Experimental Emergency Medicine.2022; 9(4): 345.     CrossRef
    • Factors included in adult fall risk assessment tools (FRATs): a systematic review
      Hendrika de Clercq, Alida Naudé, Juan Bornman
      Ageing and Society.2021; 41(11): 2558.     CrossRef
    • Factors Influencing Falls in High- and Low-Risk Patients in a Tertiary Hospital in Korea
      Young-Shin Lee, Eun-Ju Choi, Yeon-Hee Kim, Hyeoun-Ae Park
      Journal of Patient Safety.2020; 16(4): e376.     CrossRef
    • Predictors of Health-related Quality of Life among Spouses of Older Adults with Dementia in the Community-dwelling
      Hye-Young Jang, Song Yi Han
      Journal of Korean Academy of Community Health Nursing.2019; 30(4): 518.     CrossRef
    • Effects of Fall Prevention Education Program on Attitudes, Prevention Behaviors, and Satisfaction among Elderly Inpatients
      Young Ok Kang, Rhayun Song
      Korean Journal of Adult Nursing.2018; 30(1): 49.     CrossRef
    • Risk factors of falling in patients with neurological diseases
      Michaela Miertová, Ivana Bóriková, Martina Tomagová, Katarína Žiaková
      Kontakt.2018; 20(3): e217.     CrossRef
    • Characteristics and Risk Factors for Falls in Tertiary Hospital Inpatients
      Eun-Ju Choi, Young-Shin Lee, Eun-Jung Yang, Ji-Hui Kim, Yeon-Hee Kim, Hyeoun-Ae Park
      Journal of Korean Academy of Nursing.2017; 47(3): 420.     CrossRef
    • A prediction model of falls for patients with neurological disorder in acute care hospital
      Sung-Hee Yoo, Sung Reul Kim, Yong Soon Shin
      Journal of the Neurological Sciences.2015; 356(1-2): 113.     CrossRef
    • Validation of Fall Risk Assessment Scales among Hospitalized Patients in South Korea using Retrospective Data Analysis
      Young Ok Kang, Rhayun Song
      Korean Journal of Adult Nursing.2015; 27(1): 29.     CrossRef
    • Evaluation of Clinical Usefulness of Delirium Assessment Tools for Elderly Patients after Neurosurgery
      Su-Jung Kim, Jun-Ah Song
      Journal of Korean Gerontological Nursing.2015; 17(1): 38.     CrossRef

    Download Citation

    Download a citation file in RIS format that can be imported by all major citation management software, including EndNote, ProCite, RefWorks, and Reference Manager.

    Format:

    Include:

    Comparison of the Reliability and Validity of Fall Risk Assessment Tools in Patients with Acute Neurological Disorders
    Korean J Adult Nurs. 2013;25(1):24-32.   Published online February 28, 2013
    Download Citation
    Download a citation file in RIS format that can be imported by all major citation management software, including EndNote, ProCite, RefWorks, and Reference Manager.

    Format:
    • RIS — For EndNote, ProCite, RefWorks, and most other reference management software
    • BibTeX — For JabRef, BibDesk, and other BibTeX-specific software
    Include:
    • Citation for the content below
    Comparison of the Reliability and Validity of Fall Risk Assessment Tools in Patients with Acute Neurological Disorders
    Korean J Adult Nurs. 2013;25(1):24-32.   Published online February 28, 2013
    Close

    Figure

    • 0
    Comparison of the Reliability and Validity of Fall Risk Assessment Tools in Patients with Acute Neurological Disorders
    Image
    Figure 1 Receiver operating characteristic curve for the fall risk assessment tool.
    Comparison of the Reliability and Validity of Fall Risk Assessment Tools in Patients with Acute Neurological Disorders

    General and Clinical Characteristics (N=1,026)

    CNS=central nervous system.

    Inter-rater Reliability of the Fall Risk Assessment Tool

    MFS=morse fall scale; STRATIFY=St Thomas's risk assessment tool in falling elderly inpatients; HFRM II=Hendrich II fall risk model.

    Sensitivity, Specificity, and Predictive Value for the Fall Risk Assessment Tool (N=1,026)

    MFS=morse fall scale; STRATIFY=St Thomas's risk assessment tool in falling elderly inpatients; HFRM??Hendrich II fall risk model.

    AUC and Optimal Cutoff Point for the Fall Risk Assessment Tool

    AUC=area under ROC curve; MFS=morse fall scale; STRATIFY=St Thomas's risk assessment tool in falling elderly inpatients; HFRM II=Hendrich II fall risk model.

    Table 1 General and Clinical Characteristics (N=1,026)

    CNS=central nervous system.

    Table 2 Inter-rater Reliability of the Fall Risk Assessment Tool

    MFS=morse fall scale; STRATIFY=St Thomas's risk assessment tool in falling elderly inpatients; HFRM II=Hendrich II fall risk model.

    Table 3 Sensitivity, Specificity, and Predictive Value for the Fall Risk Assessment Tool (N=1,026)

    MFS=morse fall scale; STRATIFY=St Thomas's risk assessment tool in falling elderly inpatients; HFRM??Hendrich II fall risk model.

    Table 4 AUC and Optimal Cutoff Point for the Fall Risk Assessment Tool

    AUC=area under ROC curve; MFS=morse fall scale; STRATIFY=St Thomas's risk assessment tool in falling elderly inpatients; HFRM II=Hendrich II fall risk model.

    TOP