AMIA Annu Symp Proc - What do patients search for when seeking clinical trial information online?

Tópicos

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

Resumo

The Internet has become a common source for consumers to seek health information across a wide range of topics including searching for clinical trials. However, not much is known about what consumers search for in relation to clinical trials and how they formulate their search queries. In this study, we use log file data from TrialX.com, a consumer-centric website that provides clinical trial information to ascertain patterns in consumer queries. We analyzed semantic patterns in the queries by mapping query keywords to the UMLS Semantic Types and performed a manual evaluation of user paths. We found that the queries can be grouped into combinations of information needs related to condition, location and treatment. The results also suggested that the consumers using longer search queries with multiple Semantic Types are more likely to take action to participate in clinical trials. The study provides early insights that can be used to inform changes in website content and information display to improve clinical trials information seeking.

Resumo Limpo

internet becom common sourc consum seek health inform across wide rang topic includ search clinic trial howev much known consum search relat clinic trial formul search queri studi use log file data trialxcom consumercentr websit provid clinic trial inform ascertain pattern consum queri analyz semant pattern queri map queri keyword uml semant type perform manual evalu user path found queri can group combin inform need relat condit locat treatment result also suggest consum use longer search queri multipl semant type like take action particip clinic trial studi provid earli insight can use inform chang websit content inform display improv clinic trial inform seek

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