J. Med. Internet Res. - eHealth literacy: extending the digital divide to the realm of health information.

Tópicos

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

Resumo

CKGROUND: eHealth literacy is defined as the ability of people to use emerging information and communications technologies to improve or enable health and health care.OBJECTIVE: The goal of this study was to explore whether literacy disparities are diminished or enhanced in the search for health information on the Internet. The study focused on (1) traditional digital divide variables, such as sociodemographic characteristics, digital access, and digital literacy, (2) information search processes, and (3) the outcomes of Internet use for health information purposes.METHODS: We used a countrywide representative random-digital-dial telephone household survey of the Israeli adult population (18 years and older, N = 4286). We measured eHealth literacy; Internet access; digital literacy; sociodemographic factors; perceived health; presence of chronic diseases; as well as health information sources, content, search strategies, and evaluation criteria used by consumers.RESULTS: Respondents who were highly eHealth literate tended to be younger and more educated than their less eHealth-literate counterparts. They were also more active consumers of all types of information on the Internet, used more search strategies, and scrutinized information more carefully than did the less eHealth-literate respondents. Finally, respondents who were highly eHealth literate gained more positive outcomes from the information search in terms of cognitive, instrumental (self-management of health care needs, health behaviors, and better use of health insurance), and interpersonal (interacting with their physician) gains.CONCLUSIONS: The present study documented differences between respondents high and low in eHealth literacy in terms of background attributes, information consumption, and outcomes of the information search. The association of eHealth literacy with background attributes indicates that the Internet reinforces existing social differences. The more comprehensive and sophisticated use of the Internet and the subsequent increased gains among the high eHealth literate create new inequalities in the domain of digital health information. There is a need to educate at-risk and needy groups (eg, chronically ill) and to design technology in a mode befitting more consumers.

Resumo Limpo

ckground ehealth literaci defin abil peopl use emerg inform communic technolog improv enabl health health careobject goal studi explor whether literaci dispar diminish enhanc search health inform internet studi focus tradit digit divid variabl sociodemograph characterist digit access digit literaci inform search process outcom internet use health inform purposesmethod use countrywid repres randomdigitaldi telephon household survey isra adult popul year older n measur ehealth literaci internet access digit literaci sociodemograph factor perceiv health presenc chronic diseas well health inform sourc content search strategi evalu criteria use consumersresult respond high ehealth liter tend younger educ less ehealthliter counterpart also activ consum type inform internet use search strategi scrutin inform care less ehealthliter respond final respond high ehealth liter gain posit outcom inform search term cognit instrument selfmanag health care need health behavior better use health insur interperson interact physician gainsconclus present studi document differ respond high low ehealth literaci term background attribut inform consumpt outcom inform search associ ehealth literaci background attribut indic internet reinforc exist social differ comprehens sophist use internet subsequ increas gain among high ehealth liter creat new inequ domain digit health inform need educ atrisk needi group eg chronic ill design technolog mode befit consum

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