Int J Med Inform - Market segmentation of health information use on the Internet in Korea.

Tópicos

{ inform(2794) health(2639) internet(1427) }
{ age(1611) year(1155) adult(843) }
{ search(2224) databas(1162) retriev(909) }
{ state(1844) use(1261) util(961) }
{ general(901) number(790) one(736) }
{ spatial(1525) area(1432) region(1030) }
{ risk(3053) factor(974) diseas(938) }
{ activ(1452) weight(1219) physic(1104) }
{ high(1669) rate(1365) level(1280) }
{ time(1939) patient(1703) rate(768) }
{ model(2341) predict(2261) use(1141) }
{ care(1570) inform(1187) nurs(1089) }
{ control(1307) perform(991) simul(935) }
{ use(976) code(926) identifi(902) }
{ ehr(2073) health(1662) electron(1139) }
{ howev(809) still(633) remain(590) }
{ data(1714) softwar(1251) tool(1186) }
{ can(774) often(719) complex(702) }
{ survey(1388) particip(1329) question(1065) }
{ studi(1119) effect(1106) posit(819) }
{ import(1318) role(1303) understand(862) }
{ take(945) account(800) differ(722) }
{ detect(2391) sensit(1101) algorithm(908) }
{ result(1111) use(1088) new(759) }
{ cancer(2502) breast(956) screen(824) }
{ structur(1116) can(940) graph(676) }
{ health(1844) social(1437) communiti(874) }
{ patient(1821) servic(1111) care(1106) }
{ activ(1138) subject(705) human(624) }
{ sampl(1606) size(1419) use(1276) }
{ monitor(1329) mobil(1314) devic(1160) }
{ blood(1257) pressur(1144) flow(957) }
{ perform(999) metric(946) measur(919) }
{ clinic(1479) use(1117) guidelin(835) }
{ error(1145) method(1030) estim(1020) }
{ studi(2440) review(1878) systemat(933) }
{ imag(2675) segment(2577) method(1081) }
{ network(2748) neural(1063) input(814) }
{ featur(3375) classif(2383) classifi(1994) }
{ sequenc(1873) structur(1644) protein(1328) }
{ model(3404) distribut(989) bayesian(671) }
{ method(2212) result(1239) propos(1039) }
{ method(1969) cluster(1462) data(1082) }
{ process(1125) use(805) approach(778) }
{ decis(3086) make(1611) patient(1517) }
{ estim(2440) model(1874) function(577) }
{ implement(1333) system(1263) develop(1122) }
{ drug(1928) target(777) effect(648) }
{ use(1733) differ(960) four(931) }
{ analysi(2126) use(1163) compon(1037) }
{ can(981) present(881) function(850) }
{ use(2086) technolog(871) perceiv(783) }
{ intervent(3218) particip(2042) group(1664) }
{ first(2504) two(1366) second(1323) }
{ data(3008) multipl(1320) sourc(1022) }
{ gene(2352) biolog(1181) express(1162) }
{ group(2977) signific(1463) compar(1072) }
{ cost(1906) reduc(1198) effect(832) }
{ signal(2180) analysi(812) frequenc(800) }
{ medic(1828) order(1363) alert(1069) }
{ data(2317) use(1299) case(1017) }
{ model(2656) set(1616) predict(1553) }
{ patient(2837) hospit(1953) medic(668) }
{ research(1218) medic(880) student(794) }
{ model(3480) simul(1196) paramet(876) }
{ health(3367) inform(1360) care(1135) }
{ record(1888) medic(1808) patient(1693) }
{ perform(1367) use(1326) method(1137) }
{ compound(1573) activ(1297) structur(1058) }
{ visual(1396) interact(850) tool(830) }
{ system(1050) medic(1026) inform(1018) }
{ research(1085) discuss(1038) issu(1018) }
{ studi(1410) differ(1259) use(1210) }
{ data(3963) clinic(1234) research(1004) }
{ case(1353) use(1143) diagnosi(1136) }
{ featur(1941) imag(1645) propos(1176) }
{ method(984) reconstruct(947) comput(926) }
{ model(2220) cell(1177) simul(1124) }
{ design(1359) user(1324) use(1319) }
{ method(1557) propos(1049) approach(1037) }
{ extract(1171) text(1153) clinic(932) }
{ algorithm(1844) comput(1787) effici(935) }
{ concept(1167) ontolog(924) domain(897) }
{ learn(2355) train(1041) set(1003) }
{ chang(1828) time(1643) increas(1301) }
{ problem(2511) optim(1539) algorithm(950) }
{ framework(1458) process(801) describ(734) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ treatment(1704) effect(941) patient(846) }
{ assess(1506) score(1403) qualiti(1306) }
{ motion(1329) object(1292) video(1091) }
{ patient(2315) diseas(1263) diabet(1191) }
{ imag(2830) propos(1344) filter(1198) }
{ method(1219) similar(1157) match(930) }
{ bind(1733) structur(1185) ligand(1036) }
{ imag(1057) registr(996) error(939) }
{ measur(2081) correl(1212) valu(896) }
{ system(1976) rule(880) can(841) }
{ data(1737) use(1416) pattern(1282) }
{ imag(1947) propos(1133) code(1026) }

Resumo

CKGROUND: Internet is the common way to access all kind of information, thus it becomes to have highly influential place on the range of health care as well. More and more people have been using Internet to get the latest information on the health-related matters. However, it is very important but not easy to find the correct data and select it efficiently among the enormous amount of information. To identify the information seekers and understand their needs or purposes, they would be very effective for the providers to give high-quality health information for the Internet users.OBJECTIVES: The purpose of this study is to reveal the patterns of utilization of health information on the Internet. The subjects of the survey were randomly selected among the local residents by their age and gender. It was conducted in Gangwon, the province and Incheon, the metropolitan city at the same time. To investigate the similar amount of population, 0.5% of Gangwon and 0.3% of Incheon dwellers were chosen.METHODS: 10,325 people were responded to the telephone poll and the investigation had been conducted from July to October 2006. 8656 from 10,325 completed the survey and 1665 (19.2%) of them had used Internet to get health information in last 1-year. The use of health information on the Internet was classified into four categories as follows: general health tips, disease specific information, shopping for health commodities, and selection of hospitals. The questionnaire included articles regarding socio-demographic characteristics such as age, gender, income, education, dwelling area, health status and behaviors such as cigarette smoking and alcohol consumption.RESULTS: Of all 1665 respondents, 726 (17.2%) men (total 4210) and 939 (21.1%) women (total 4446) had used Internet for health information in last 1-year. The health information that people wanted from Internet was as follows: general health tips (64.2%), disease specific information (32.0%), shopping for health commodities (23.7%), and selection of hospitals (19.3%). The people of higher education and higher income level tended to use Internet more often for health information. Metropolitan city dwellers used health information on the Internet more than people from province did. Personal health status appeared to be the most important factor to search the information about general health tips from the Internet. Healthy people (68.3%) used the Internet more than people with diseases (44.4%) who used Internet most frequently for disease specific information (62.6%). Residence area was the most important factor of online shopping for health commodities. While 31.8% of city dwellers used the Internet, only 19.0% of metropolitan or county dwellers used it for the same purpose. Determinant factors for the utilization of the Internet for hospital selection were residence area, age, and health examination.CONCLUSIONS: We found that each section of health information has its own clients concerning their personal interests and status of health and life style. That is why customized market segmentation is strongly recommended for their loyal customers. Depends on the information seekers' health status, it should be decided which information would be more useful for them between general health tips and specific disease. On the other hand, the area where the information seekers live can be more influential on terms of shopping for health commodities. These results will be a great help to start to understand the closer atmosphere of the ideal health information market to provide more valuable services in more various use.

Resumo Limpo

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