J. Med. Internet Res. - User-generated online health content: a survey of Internet users in the United Kingdom.

Tópicos

{ health(1844) social(1437) communiti(874) }
{ inform(2794) health(2639) internet(1427) }
{ age(1611) year(1155) adult(843) }
{ group(2977) signific(1463) compar(1072) }
{ high(1669) rate(1365) level(1280) }
{ result(1111) use(1088) new(759) }
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{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
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{ measur(2081) correl(1212) valu(896) }
{ method(1219) similar(1157) match(930) }
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{ data(1714) softwar(1251) tool(1186) }
{ method(984) reconstruct(947) comput(926) }
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{ state(1844) use(1261) util(961) }
{ signal(2180) analysi(812) frequenc(800) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ cancer(2502) breast(956) screen(824) }
{ survey(1388) particip(1329) question(1065) }
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{ bind(1733) structur(1185) ligand(1036) }
{ sequenc(1873) structur(1644) protein(1328) }
{ featur(3375) classif(2383) classifi(1994) }
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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) }
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{ motion(1329) object(1292) video(1091) }
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{ record(1888) medic(1808) patient(1693) }
{ monitor(1329) mobil(1314) devic(1160) }
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{ medic(1828) order(1363) alert(1069) }
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{ can(981) present(881) function(850) }
{ analysi(2126) use(1163) compon(1037) }
{ structur(1116) can(940) graph(676) }
{ use(1733) differ(960) four(931) }
{ drug(1928) target(777) effect(648) }
{ implement(1333) system(1263) develop(1122) }
{ 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) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

CKGROUND: The production of health information has begun to shift from commercial organizations to health care users themselves. People increasingly go online to share their own health and illness experiences and to access information others have posted, but this behavior has not been investigated at a population level in the United Kingdom.OBJECTIVE: This study aims to explore access and production of user-generated health content among UK Internet users and to investigate relationships between frequency of use and other variables.METHODS: We undertook an online survey of 1000 UK Internet users. Descriptive and multivariate statistical analyses were used to interpret the data.RESULTS: Nearly one-quarter of respondents (23.7%, 237/1000) reported accessing and sharing user-generated health content online, whereas more than 20% (22.2%, 222/1000) were unaware that it was possible to do this. Respondents could be divided into 3 groups based on frequency of use: rare users (78.7%, 612/778) who accessed and shared content less than weekly, users (13.9%, 108/778) who did so weekly, and superusers (7.5%, 58/778) who did so on a daily basis. Superusers were more likely to be male (P<.001) and to be employed (P<.001), but there were no differences between the groups with respect to educational level (P=.99) or health status (P=.63). They were more likely to use the Internet for varied purposes such as banking and shopping (P<.001).CONCLUSIONS: Although this study found reasonably widespread access of user-generated online health content, only a minority of respondents reported doing so frequently. As this type of content proliferates, superusers are likely to shape the health information that others access. Further research should assess the effect of user-generated online content on health outcomes and use of health services by Internet users.

Resumo Limpo

ckground product health inform begun shift commerci organ health care user peopl increas go onlin share health ill experi access inform other post behavior investig popul level unit kingdomobject studi aim explor access product usergener health content among uk internet user investig relationship frequenc use variablesmethod undertook onlin survey uk internet user descript multivari statist analys use interpret dataresult near onequart respond report access share usergener health content onlin wherea unawar possibl respond divid group base frequenc use rare user access share content less week user week superus daili basi superus like male p employ p differ group respect educ level p health status p like use internet vari purpos bank shop pconclus although studi found reason widespread access usergener onlin health content minor respond report frequent type content prolifer superus like shape health inform other access research assess effect usergener onlin content health outcom use health servic internet user

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