J. Med. Internet Res. - Single-case experimental designs to evaluate novel technology-based health interventions.

Tópicos

{ research(1085) discuss(1038) issu(1018) }
{ treatment(1704) effect(941) patient(846) }
{ method(1557) propos(1049) approach(1037) }
{ clinic(1479) use(1117) guidelin(835) }
{ model(2220) cell(1177) simul(1124) }
{ howev(809) still(633) remain(590) }
{ intervent(3218) particip(2042) group(1664) }
{ cancer(2502) breast(956) screen(824) }
{ method(2212) result(1239) propos(1039) }
{ data(1737) use(1416) pattern(1282) }
{ imag(1057) registr(996) error(939) }
{ patient(2315) diseas(1263) diabet(1191) }
{ assess(1506) score(1403) qualiti(1306) }
{ algorithm(1844) comput(1787) effici(935) }
{ general(901) number(790) one(736) }
{ data(3963) clinic(1234) research(1004) }
{ gene(2352) biolog(1181) express(1162) }
{ use(2086) technolog(871) perceiv(783) }
{ activ(1452) weight(1219) physic(1104) }
{ detect(2391) sensit(1101) algorithm(908) }
{ measur(2081) correl(1212) valu(896) }
{ problem(2511) optim(1539) algorithm(950) }
{ error(1145) method(1030) estim(1020) }
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{ studi(1410) differ(1259) use(1210) }
{ system(1050) medic(1026) inform(1018) }
{ model(2341) predict(2261) use(1141) }
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{ imag(2675) segment(2577) method(1081) }
{ take(945) account(800) differ(722) }
{ studi(2440) review(1878) systemat(933) }
{ motion(1329) object(1292) video(1091) }
{ surgeri(1148) surgic(1085) robot(1054) }
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{ featur(1941) imag(1645) propos(1176) }
{ risk(3053) factor(974) diseas(938) }
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{ studi(1119) effect(1106) posit(819) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ model(3480) simul(1196) paramet(876) }
{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
{ state(1844) use(1261) util(961) }
{ 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) }
{ data(3008) multipl(1320) sourc(1022) }
{ first(2504) two(1366) second(1323) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ can(981) present(881) function(850) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ high(1669) rate(1365) level(1280) }
{ use(1733) differ(960) four(931) }
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{ method(1969) cluster(1462) data(1082) }

Resumo

Technology-based interventions to promote health are expanding rapidly. Assessing the preliminary efficacy of these interventions can be achieved by employing single-case experiments (sometimes referred to as n-of-1 studies). Although single-case experiments are often misunderstood, they offer excellent solutions to address the challenges associated with testing new technology-based interventions. This paper provides an introduction to single-case techniques and highlights advances in developing and evaluating single-case experiments, which help ensure that treatment outcomes are reliable, replicable, and generalizable. These advances include quality control standards, heuristics to guide visual analysis of time-series data, effect size calculations, and statistical analyses. They also include experimental designs to isolate the active elements in a treatment package and to assess the mechanisms of behavior change. The paper concludes with a discussion of issues related to the generality of findings derived from single-case research and how generality can be established through replication and through analysis of behavioral mechanisms.

Resumo Limpo

technologybas intervent promot health expand rapid assess preliminari efficaci intervent can achiev employ singlecas experi sometim refer nof studi although singlecas experi often misunderstood offer excel solut address challeng associ test new technologybas intervent paper provid introduct singlecas techniqu highlight advanc develop evalu singlecas experi help ensur treatment outcom reliabl replic generaliz advanc includ qualiti control standard heurist guid visual analysi timeseri data effect size calcul statist analys also includ experiment design isol activ element treatment packag assess mechan behavior chang paper conclud discuss issu relat general find deriv singlecas research general can establish replic analysi behavior mechan

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