Last data update: May 13, 2024. (Total: 46773 publications since 2009)
Records 1-4 (of 4 Records) |
Query Trace: Weaver JB[original query] |
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Health information-seeking behaviors, health indicators, and health risks
Weaver JB , Mays D , Weaver SS , Hopkins GL , Eroglu D , Bernhardt JM . Am J Public Health 2010 100 (8) 1520-5 OBJECTIVES: We examined how different types of health information-seeking behaviors (HISBs)-no use, illness information only, wellness information only, and illness and wellness information combined-are associated with health risk factors and health indicators to determine possible motives for health information seeking. METHODS: A sample of 559 Seattle-Tacoma area adults completed an Internet-based survey in summer 2006. The survey assessed types of HISB, physical and mental health indicators, health risks, and several covariates. Covariate-adjusted linear and logistic regression models were computed. RESULTS: Almost half (49.4%) of the sample reported HISBs. Most HISBs (40.6%) involved seeking a combination of illness and wellness information, but both illness-only (28.6%) and wellness-only (30.8%) HISBs were also widespread. Wellness-only information seekers reported the most positive health assessments and the lowest occurrence of health risk factors. An opposite pattern emerged for illness-only information seekers. CONCLUSIONS: Our findings reveal a unique pattern of linkages between the type of health information sought (wellness, illness, and so on) and health self-assessment among adult Internet users in western Washington State. These associations suggest that distinct health motives may underlie HISB, a phenomenon frequently overlooked in previous research. |
Healthcare non-adherence decisions and internet health information
Weaver JB , Thompson NJ , Weaver SS , Hopkins GL . Comput Human Behav 2009 25 (6) 1373-1380 While the internet is emerging as an important transforming mechanism for health care and public health, questions remain about its limitations. Growing evidence indicates that a significant proportion of internet health information consumers is engaging treatment strategies inconsistent with professional recommendations. This study aimed to distinguish internet users who report non-adherence behavior from their counterparts based on several personal and environmental determinants. Using information obtained via the internet to refuse or discontinue treatment recommended by a doctor or dentist proved to be a widespread (11.2%) behavior. Internet health information bolstered non-adherence appears strongly linked with personal determinants such as anxiety, diminishing health, and gender--a pattern consistent with prior adherence research--and with environmental determinants including the perceived importance of both internet health information and internet-facilitated interpersonal interactions as well as using the internet as a social support vehicle. (PsycINFO Database Record (c) 2009 APA, all rights reserved) (journal abstract). |
Profiling characteristics of internet medical information users
Weaver JB 3rd , Mays D , Lindner G , Eroglu D , Fridinger F , Bernhardt JM . J Am Med Inform Assoc 2009 16 (5) 714-22 OBJECTIVE: The Internet's potential to bolster health promotion and disease prevention efforts has attracted considerable attention. Existing research leaves two things unclear, however: the prevalence of online health and medical information seeking and the distinguishing characteristics of individuals who seek that information. DESIGN: This study seeks to clarify and extend the knowledge base concerning health and medical information use online by profiling adults using Internet medical information (IMI). Secondary analysis of survey data from a large sample (n = 6,119) representative of the Atlanta, GA, area informed this investigation. MEASUREMENTS: Five survey questions were used to assess IMI use and general computer and Internet use during the 30 days before the survey was administered. Five questions were also used to assess respondents' health care system use. Several demographic characteristics were measured. RESULTS: Contrary to most prior research, this study found relatively low prevalence of IMI-seeking behavior. Specifically, IMI use was reported by 13.2% of all respondents (n = 6,119) and by 21.1% of respondents with Internet access (n = 3,829). Logistic regression models conducted among respondents accessing the Internet in the previous 30 days revealed that, when controlling for several sociodemographic characteristics, home computer ownership, online time per week, and health care system use are all positively linked with IMI-seeking behavior. CONCLUSIONS: The data suggest it may be premature to embrace unilaterally the Internet as an effective asset for health promotion and disease prevention efforts that target the public. |
Health-risk correlates of video-game playing among adults
Weaver JB 3rd , Mays D , Sargent Weaver S , Kannenberg W , Hopkins GL , Eroglu D , Bernhardt JM . Am J Prev Med 2009 37 (4) 299-305 BACKGROUND: Although considerable research suggests that health-risk factors vary as a function of video-game playing among young people, direct evidence of such linkages among adults is lacking. PURPOSE: The goal of this study was to distinguish adult video-game players from nonplayers on the basis of personal and environmental factors. It was hypothesized that adults who play video games, compared to nonplayers, would evidence poorer perceptions of their health, greater reliance on Internet-facilitated social support, more extensive media use, and higher BMI. It was further hypothesized that different patterns of linkages between video-game playing and health-risk factors would emerge by gender. METHODS: A cross-sectional, Internet-based survey was conducted in 2006 with a sample of adults from the Seattle-Tacoma area (n=562), examining health risks; media use behaviors and perceptions, including those related to video-game playing; and demographics. Statistical analyses conducted in 2008 to compare video-game players and nonplayers included bivariate descriptive statistics, stepwise discriminant analysis, and ANOVA. RESULTS: A total of 45.1% of respondents reported playing video games. Female video-game players reported greater depression (M=1.57) and poorer health status (M=3.90) than female nonplayers (depression, M=1.13; health status, M=3.57). Male video-game players reported higher BMI (M=5.31) and more Internet use time (M=2.55) than male nonplayers (BMI, M=5.19; Internet use, M=2.36). The only determinant common to female and male video-game players was greater reliance on the Internet for social support. CONCLUSIONS: A number of determinants distinguished video-game players from nonplayers, and these factors differed substantially between men and women. The data illustrate the need for further research among adults to clarify how to use digital opportunities more effectively to promote health and prevent disease. |
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