J. Med. Internet Res. - Mapping mHealth research: a decade of evolution.

Tópicos

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

Resumo

CKGROUND: For the last decade, mHealth has constantly expanded as a part of eHealth. Mobile applications for health have the potential to target heterogeneous audiences and address specific needs in different situations, with diverse outcomes, and to complement highly developed health care technologies. The market is rapidly evolving, making countless new mobile technologies potentially available to the health care system; however, systematic research on the impact of these technologies on health outcomes remains scarce.OBJECTIVE: To provide a comprehensive view of the field of mHealth research to date and to understand whether and how the new generation of smartphones has triggered research, since their introduction 5 years ago. Specifically, we focused on studies aiming to evaluate the impact of mobile phones on health, and we sought to identify the main areas of health care delivery where mobile technologies can have an impact.METHODS: A systematic literature review was conducted on the impact of mobile phones and smartphones in health care. Abstracts and articles were categorized using typologies that were partly adapted from existing literature and partly created inductively from publications included in the review.RESULTS: The final sample consisted of 117 articles published between 2002 and 2012. The majority of them were published in the second half of our observation period, with a clear upsurge between 2007 and 2008, when the number of articles almost doubled. The articles were published in 77 different journals, mostly from the field of medicine or technology and medicine. Although the range of health conditions addressed was very wide, a clear focus on chronic conditions was noted. The research methodology of these studies was mostly clinical trials and pilot studies, but new designs were introduced in the second half of our observation period. The size of the samples drawn to test mobile health applications also increased over time. The majority of the studies tested basic mobile phone features (eg, text messaging), while only a few assessed the impact of smartphone apps. Regarding the investigated outcomes, we observed a shift from assessment of the technology itself to assessment of its impact. The outcome measures used in the studies were mostly clinical, including both self-reported and objective measures.CONCLUSIONS: Research interest in mHealth is growing, together with an increasing complexity in research designs and aim specifications, as well as a diversification of the impact areas. However, new opportunities offered by new mobile technologies do not seem to have been explored thus far. Mapping the evolution of the field allows a better understanding of its strengths and weaknesses and can inform future developments.

Resumo Limpo

ckground last decad mhealth constant expand part ehealth mobil applic health potenti target heterogen audienc address specif need differ situat divers outcom complement high develop health care technolog market rapid evolv make countless new mobil technolog potenti avail health care system howev systemat research impact technolog health outcom remain scarceobject provid comprehens view field mhealth research date understand whether new generat smartphon trigger research sinc introduct year ago specif focus studi aim evalu impact mobil phone health sought identifi main area health care deliveri mobil technolog can impactmethod systemat literatur review conduct impact mobil phone smartphon health care abstract articl categor use typolog part adapt exist literatur part creat induct public includ reviewresult final sampl consist articl publish major publish second half observ period clear upsurg number articl almost doubl articl publish differ journal most field medicin technolog medicin although rang health condit address wide clear focus chronic condit note research methodolog studi most clinic trial pilot studi new design introduc second half observ period size sampl drawn test mobil health applic also increas time major studi test basic mobil phone featur eg text messag assess impact smartphon app regard investig outcom observ shift assess technolog assess impact outcom measur use studi most clinic includ selfreport object measuresconclus research interest mhealth grow togeth increas complex research design aim specif well diversif impact area howev new opportun offer new mobil technolog seem explor thus far map evolut field allow better understand strength weak can inform futur develop

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