Int J Med Inform - Factors that influence public engagement with eHealth: A literature review.

Tópicos

{ inform(2794) health(2639) internet(1427) }
{ health(1844) social(1437) communiti(874) }
{ studi(2440) review(1878) systemat(933) }
{ system(1050) medic(1026) inform(1018) }
{ search(2224) databas(1162) retriev(909) }
{ studi(1119) effect(1106) posit(819) }
{ implement(1333) system(1263) develop(1122) }
{ extract(1171) text(1153) clinic(932) }
{ research(1218) medic(880) student(794) }
{ use(976) code(926) identifi(902) }
{ featur(1941) imag(1645) propos(1176) }
{ howev(809) still(633) remain(590) }
{ import(1318) role(1303) understand(862) }
{ health(3367) inform(1360) care(1135) }
{ use(2086) technolog(871) perceiv(783) }
{ can(981) present(881) function(850) }
{ imag(1947) propos(1133) code(1026) }
{ imag(1057) registr(996) error(939) }
{ algorithm(1844) comput(1787) effici(935) }
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{ care(1570) inform(1187) nurs(1089) }
{ studi(1410) differ(1259) use(1210) }
{ risk(3053) factor(974) diseas(938) }
{ research(1085) discuss(1038) issu(1018) }
{ compound(1573) activ(1297) structur(1058) }
{ gene(2352) biolog(1181) express(1162) }
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{ bind(1733) structur(1185) ligand(1036) }
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{ network(2748) neural(1063) input(814) }
{ imag(2675) segment(2577) method(1081) }
{ patient(2315) diseas(1263) diabet(1191) }
{ take(945) account(800) differ(722) }
{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
{ treatment(1704) effect(941) patient(846) }
{ surgeri(1148) surgic(1085) robot(1054) }
{ framework(1458) process(801) describ(734) }
{ problem(2511) optim(1539) algorithm(950) }
{ error(1145) method(1030) estim(1020) }
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{ design(1359) user(1324) use(1319) }
{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ general(901) number(790) one(736) }
{ method(984) reconstruct(947) comput(926) }
{ case(1353) use(1143) diagnosi(1136) }
{ data(3963) clinic(1234) research(1004) }
{ perform(999) metric(946) measur(919) }
{ model(2341) predict(2261) use(1141) }
{ visual(1396) interact(850) tool(830) }
{ perform(1367) use(1326) method(1137) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ record(1888) medic(1808) patient(1693) }
{ model(3480) simul(1196) paramet(876) }
{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
{ state(1844) use(1261) util(961) }
{ 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) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
{ data(3008) multipl(1320) sourc(1022) }
{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ 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) }
{ survey(1388) particip(1329) question(1065) }
{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ process(1125) use(805) approach(778) }
{ activ(1452) weight(1219) physic(1104) }
{ method(1969) cluster(1462) data(1082) }
{ method(2212) result(1239) propos(1039) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

RPOSE: Public engagement with eHealth is generally viewed as beneficial. However, despite the potential benefits, public engagement with eHealth services remains variable. This article explores reasons for this variability through a review of published international literature.METHODS: A focused search, conducted in January 2009, of three bibliographic databases, MEDLINE, CINAHL and EMBASE, returned 2622 unique abstracts.RESULTS: Fifty articles met the inclusion criteria for the review. Four main types of eHealth service were identified: health information on the Internet; custom-made online health information; online support; and telehealth. Public engagement with these services appears to depend on a number of factors: characteristics of users; technological issues; characteristics of eHealth services; social aspects of use; and eHealth services in use.CONCLUSIONS: Recommendations for policy makers, developers, users and health professionals, include: targeting efforts towards those underserved by eHealth; improving access; tailoring services to meet the needs of a broader range of users; exploiting opportunities for social computing; and clarifying of the role of health professionals in endorsement, promotion and facilitation.

Resumo Limpo

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