J. Med. Internet Res. - Website quality, expectation, confirmation, and end user satisfaction: the knowledge-intensive website of the Korean National Cancer Information Center.

Tópicos

{ use(2086) technolog(871) perceiv(783) }
{ decis(3086) make(1611) patient(1517) }
{ care(1570) inform(1187) nurs(1089) }
{ method(1557) propos(1049) approach(1037) }
{ intervent(3218) particip(2042) group(1664) }
{ inform(2794) health(2639) internet(1427) }
{ studi(2440) review(1878) systemat(933) }
{ structur(1116) can(940) graph(676) }
{ design(1359) user(1324) use(1319) }
{ model(3404) distribut(989) bayesian(671) }
{ control(1307) perform(991) simul(935) }
{ can(981) present(881) function(850) }
{ error(1145) method(1030) estim(1020) }
{ chang(1828) time(1643) increas(1301) }
{ clinic(1479) use(1117) guidelin(835) }
{ system(1050) medic(1026) inform(1018) }
{ health(3367) inform(1360) care(1135) }
{ model(3480) simul(1196) paramet(876) }
{ activ(1138) subject(705) human(624) }
{ survey(1388) particip(1329) question(1065) }
{ process(1125) use(805) approach(778) }
{ data(1737) use(1416) pattern(1282) }
{ measur(2081) correl(1212) valu(896) }
{ imag(2830) propos(1344) filter(1198) }
{ take(945) account(800) differ(722) }
{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
{ concept(1167) ontolog(924) domain(897) }
{ algorithm(1844) comput(1787) effici(935) }
{ perform(999) metric(946) measur(919) }
{ studi(1119) effect(1106) posit(819) }
{ spatial(1525) area(1432) region(1030) }
{ research(1218) medic(880) student(794) }
{ signal(2180) analysi(812) frequenc(800) }
{ cost(1906) reduc(1198) effect(832) }
{ health(1844) social(1437) communiti(874) }
{ cancer(2502) breast(956) screen(824) }
{ result(1111) use(1088) new(759) }
{ implement(1333) system(1263) develop(1122) }
{ detect(2391) sensit(1101) algorithm(908) }
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{ imag(1057) registr(996) error(939) }
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{ featur(3375) classif(2383) classifi(1994) }
{ network(2748) neural(1063) input(814) }
{ imag(2675) segment(2577) method(1081) }
{ patient(2315) diseas(1263) diabet(1191) }
{ treatment(1704) effect(941) patient(846) }
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{ extract(1171) text(1153) clinic(932) }
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{ visual(1396) interact(850) tool(830) }
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{ perform(1367) use(1326) method(1137) }
{ blood(1257) pressur(1144) flow(957) }
{ record(1888) medic(1808) patient(1693) }
{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
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{ patient(2837) hospit(1953) medic(668) }
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{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
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{ first(2504) two(1366) second(1323) }
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{ high(1669) rate(1365) level(1280) }
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{ use(1733) differ(960) four(931) }
{ drug(1928) target(777) effect(648) }
{ estim(2440) model(1874) function(577) }
{ activ(1452) weight(1219) physic(1104) }
{ method(1969) cluster(1462) data(1082) }
{ method(2212) result(1239) propos(1039) }

Resumo

CKGROUND: The fact that patient satisfaction with primary care clinical practices and physician-patient communications has decreased gradually has brought a new opportunity to the online channel as a supplementary service to provide additional information.OBJECTIVE: In this study, our objectives were to examine the process of cognitive knowledge expectation-confirmation from eHealth users and to recommend the attributes of a "knowledge-intensive website.". Knowledge expectation can be defined as users' existing attitudes or beliefs regarding expected levels of knowledge they may gain by accessing the website. Knowledge confirmation is the extent to which user's knowledge expectation of information systems use is realized during actual use. In our hypothesized research model, perceived information quality, presentation and attractiveness as well as knowledge expectation influence knowledge confirmation, which in turn influences perceived usefulness and end user satisfaction, which feeds back to knowledge expectation.METHODS: An empirical study was conducted at the National Cancer Center (NCC), Republic of Korea (South Korea), by evaluating its official website. A user survey was administered containing items to measure subjectively perceived website quality and expectation-confirmation attributes. A study sample of 198 usable responses was used for further analysis. We used the structural equation model to test the proposed research model.RESULTS: Knowledge expectation exhibited a positive effect on knowledge confirmation (beta = .27, P < .001). The paths from information quality, information presentation, and website attractiveness to knowledge confirmation were also positive and significant (beta = .24, P < .001; beta = .29, P < .001; beta = .18, P < .001, respectively). Moreover, the effect of knowledge confirmation on perceived usefulness was also positively significant (beta = .64, P < .001). Knowledge expectation together with knowledge confirmation and perceived usefulness also significantly affected end user satisfaction (beta = .22 P < .001; beta = .39, P < .001; beta = .25, P < .001, respectively).CONCLUSIONS: Theoretically, this study has (1) identified knowledge-intensive website attributes, (2) enhanced the theoretical foundation of eHealth from the information systems (IS) perspective by adopting the expectation-confirmation theory (ECT), and (3) examined the importance of information and knowledge attributes and explained their impact on user satisfaction. Practically, our empirical results suggest that perceived website quality (ie, information quality, information presentation, and website attractiveness) is a core requirement for knowledge building. In addition, our study has also shown that knowledge confirmation has a greater effect on satisfaction than both knowledge expectation and perceived usefulness.

Resumo Limpo

ckground fact patient satisfact primari care clinic practic physicianpati communic decreas gradual brought new opportun onlin channel supplementari servic provid addit informationobject studi object examin process cognit knowledg expectationconfirm ehealth user recommend attribut knowledgeintens websit knowledg expect can defin user exist attitud belief regard expect level knowledg may gain access websit knowledg confirm extent user knowledg expect inform system use realiz actual use hypothes research model perceiv inform qualiti present attract well knowledg expect influenc knowledg confirm turn influenc perceiv use end user satisfact feed back knowledg expectationmethod empir studi conduct nation cancer center ncc republ korea south korea evalu offici websit user survey administ contain item measur subject perceiv websit qualiti expectationconfirm attribut studi sampl usabl respons use analysi use structur equat model test propos research modelresult knowledg expect exhibit posit effect knowledg confirm beta p path inform qualiti inform present websit attract knowledg confirm also posit signific beta p beta p beta p respect moreov effect knowledg confirm perceiv use also posit signific beta p knowledg expect togeth knowledg confirm perceiv use also signific affect end user satisfact beta p beta p beta p respectivelyconclus theoret studi identifi knowledgeintens websit attribut enhanc theoret foundat ehealth inform system perspect adopt expectationconfirm theori ect examin import inform knowledg attribut explain impact user satisfact practic empir result suggest perceiv websit qualiti ie inform qualiti inform present websit attract core requir knowledg build addit studi also shown knowledg confirm greater effect satisfact knowledg expect perceiv use

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