Telemed J E Health - Understanding the online health information user profiles in Korea: from a psychological perspective.

Tópicos

{ inform(2794) health(2639) internet(1427) }
{ use(1733) differ(960) four(931) }
{ use(2086) technolog(871) perceiv(783) }
{ visual(1396) interact(850) tool(830) }
{ studi(1119) effect(1106) posit(819) }
{ high(1669) rate(1365) level(1280) }
{ data(1737) use(1416) pattern(1282) }
{ health(1844) social(1437) communiti(874) }
{ system(1976) rule(880) can(841) }
{ state(1844) use(1261) util(961) }
{ gene(2352) biolog(1181) express(1162) }
{ method(1969) cluster(1462) data(1082) }
{ clinic(1479) use(1117) guidelin(835) }
{ method(1557) propos(1049) approach(1037) }
{ data(1714) softwar(1251) tool(1186) }
{ group(2977) signific(1463) compar(1072) }
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{ patient(2315) diseas(1263) diabet(1191) }
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{ design(1359) user(1324) use(1319) }
{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ care(1570) inform(1187) nurs(1089) }
{ general(901) number(790) one(736) }
{ method(984) reconstruct(947) comput(926) }
{ search(2224) databas(1162) retriev(909) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
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{ perform(1367) use(1326) method(1137) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
{ model(3480) simul(1196) paramet(876) }
{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
{ patient(2837) hospit(1953) medic(668) }
{ model(2656) set(1616) predict(1553) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ cost(1906) reduc(1198) effect(832) }
{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ can(981) present(881) function(850) }
{ structur(1116) can(940) graph(676) }
{ use(976) code(926) identifi(902) }
{ drug(1928) target(777) effect(648) }
{ result(1111) use(1088) new(759) }
{ implement(1333) system(1263) develop(1122) }
{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ process(1125) use(805) approach(778) }
{ activ(1452) weight(1219) physic(1104) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

This study was conducted to explore the profiles of online health information users in terms of certain psychological characteristics and to suggest guidelines for the provision of better user-oriented health information service. The cross-sectional study design was used with convenient sampling by Web-based questionnaire survey in Korea. To analyze health information user profiles on the Internet, a two-step cluster analysis was conducted. The results reveal that online health information users can be classified into four groups according to their level of subjective knowledge and health concern. The findings also suggest that four clusters that exhibit distinct profile patterns exist. The findings of this study would be useful for health portal developers who would like to understand users' characteristics and behaviors and to provide more user-oriented service in a satisfactory manner. It is suggested that to develop a full understanding of users' behaviors regarding Internet health information service, further research would be needed to explore users' various needs, their preferences, and relevant factors among users across a variety of health problem-addressing Web sites at different professional levels.

Resumo Limpo

studi conduct explor profil onlin health inform user term certain psycholog characterist suggest guidelin provis better userori health inform servic crosssect studi design use conveni sampl webbas questionnair survey korea analyz health inform user profil internet twostep cluster analysi conduct result reveal onlin health inform user can classifi four group accord level subject knowledg health concern find also suggest four cluster exhibit distinct profil pattern exist find studi use health portal develop like understand user characterist behavior provid userori servic satisfactori manner suggest develop full understand user behavior regard internet health inform servic research need explor user various need prefer relev factor among user across varieti health problemaddress web site differ profession level

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