J. Med. Internet Res. - Who uses physician-rating websites? Differences in sociodemographic variables, psychographic variables, and health status of users and nonusers of physician-rating websites.

Tópicos

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Resumo

CKGROUND: The number of physician-rating websites (PRWs) is rising rapidly, but usage is still poor. So far, there has been little discussion about what kind of variables influence usage of PRWs.OBJECTIVE: We focused on sociodemographic variables, psychographic variables, and health status of PRW users and nonusers.METHODS: An online survey of 1006 randomly selected German patients was conducted in September 2012. We analyzed the patients' knowledge and use of online PRWs. We also analyzed the impact of sociodemographic variables (gender, age, and education), psychographic variables (eg, feelings toward the Internet, digital literacy), and health status on use or nonuse as well as the judgment of and behavior intentions toward PRWs. The survey instrument was based on existing literature and was guided by several research questions.RESULTS: A total of 29.3% (289/986) of the sample knew of a PRW and 26.1% (257/986) had already used a PRW. Younger people were more prone than older ones to use PRWs (t967=2.27, P=.02). Women used them more than men ((2) 1=9.4, P=.002), the more highly educated more than less educated people ((2) 4=19.7, P=.001), and people with chronic diseases more than people without ((2) 1=5.6, P=.02). No differences were found between users and nonusers in their daily private Internet use and in their use of the Internet for health-related information. Users had more positive feelings about the Internet and other Web-based applications in general (t489=3.07, P=.002) than nonusers, and they had higher digital literacy (t520=4.20, P<.001). Users ascribed higher usefulness to PRWs than nonusers (t612=11.61, P<.001) and users trusted information on PRWs to a greater degree than nonusers (t559=11.48, P<.001). Users were also more likely to rate a physician on a PRW in the future (t367=7.63, P<.001) and to use a PRW in the future (t619=15.01, P<.001). The results of 2 binary logistic regression analyses demonstrated that sociodemographic variables (gender, age, education) and health status alone did not predict whether persons were prone to use PRWs or not. Adding psychographic variables and information-seeking behavior variables to the binary logistic regression analyses led to a satisfying fit of the model and revealed that higher education, poorer health status, higher digital literacy (at the 10% level of significance), lower importance of family and pharmacist for health-related information, higher trust in information on PRWs, and higher appraisal of usefulness of PRWs served as significant predictors for usage of PRWs.CONCLUSIONS: Sociodemographic variables alone do not sufficiently predict use or nonuse of PRWs; specific psychographic variables and health status need to be taken into account. The results can help designers of PRWs to better tailor their product to specific target groups, which may increase use of PRWs in the future.

Resumo Limpo

ckground number physicianr websit prws rise rapid usag still poor far littl discuss kind variabl influenc usag prwsobject focus sociodemograph variabl psychograph variabl health status prw user nonusersmethod onlin survey random select german patient conduct septemb analyz patient knowledg use onlin prws also analyz impact sociodemograph variabl gender age educ psychograph variabl eg feel toward internet digit literaci health status use nonus well judgment behavior intent toward prws survey instrument base exist literatur guid sever research questionsresult total sampl knew prw alreadi use prw younger peopl prone older one use prws t p women use men p high educ less educ peopl p peopl chronic diseas peopl without p differ found user nonus daili privat internet use use internet healthrel inform user posit feel internet webbas applic general t p nonus higher digit literaci t p user ascrib higher use prws nonus t p user trust inform prws greater degre nonus t p user also like rate physician prw futur t p use prw futur t p result binari logist regress analys demonstr sociodemograph variabl gender age educ health status alon predict whether person prone use prws ad psychograph variabl informationseek behavior variabl binari logist regress analys led satisfi fit model reveal higher educ poorer health status higher digit literaci level signific lower import famili pharmacist healthrel inform higher trust inform prws higher apprais use prws serv signific predictor usag prwsconclus sociodemograph variabl alon suffici predict use nonus prws specif psychograph variabl health status need taken account result can help design prws better tailor product specif target group may increas use prws futur

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