Skip to content

Advertisement

  • Research article
  • Open Access
  • Open Peer Review

Odds of talking to healthcare providers as the initial source of healthcare information: updated cross-sectional results from the Health Information National Trends Survey (HINTS)

  • 1,
  • 1,
  • 2 and
  • 3Email author
BMC Family Practice201819:146

https://doi.org/10.1186/s12875-018-0805-7

  • Received: 21 July 2017
  • Accepted: 26 June 2018
  • Published:
Open Peer Review reports

Abstract

Background

People use a variety of means to find health information, including searching the Internet, seeking print sources, and talking to healthcare providers, family members, and friends. Doctors are considered the most trusted source of health information, but people may be underutilizing them in favor of searching the Internet.

Methods

A multinomial logistic regression of cross-sectional data from Cycle 4 of the Health Information National Trends Survey (HINTS) was conducted. Independent variables included gender, age, rurality, cancer history, general health, income, race, education level, insurance status, veteran status, Internet use, and data year; the dependent variable was the first chosen source of health information.

Results

The most frequent initial source of health information was the Internet, and the second most frequent was healthcare providers. There were significant differences in odds of using healthcare providers as the first source of health information. Those likely to use doctors as their initial source of health information were older adults, black adults, adults with health insurance, those who do not use the Internet, and adults who do not have a college degree.

Conclusions

People who use healthcare providers as the first source of health information may have better access to health care and be those less likely to use the Internet. Doctors may have to provide more information to those who do not use the internet and spend time verifying information for those who do use health information from the internet.

Keywords

  • Health information sources
  • Information seeking behavior
  • Health communication
  • Healthcare providers
  • Cross-sectional

Background

Individuals want information to manage and improve their health. While the most trusted source of health information is healthcare providers [1], individuals draw on a number of resources for health information. Prior research has found that the Internet is the fastest growing source of health information [2], and is used more among younger adults, people with chronic conditions, the uninsured, and people who live far from their doctor [3, 4].

Despite its widespread use, individuals also frequently distrust information they find on the Internet, seeking to verify the information obtained with a doctor, through other websites, print sources, or with friends and family [5]. This distrust is well warranted - researchers have shown that the quality of information provided on the Internet varies widely by website, and that there is potential for harm due to inaccurate information [6]. As a result, individuals rely on a diversity of resources to help address their health information needs.

Physicians have a vested interest in being a primary and trusted source of health information. Discussing health information strengthens the patient-provider relationship; research indicates that patients appreciate when physicians help them evaluate health information they received from other sources [7]. Further, research has confirmed the importance of timely access to health information to allow patients to make informed treatment decisions at their medical appointments [8] and treatment satisfaction helps encourage adherence and positive health outcomes [9]. Patients prefer to be involved in their own medical decision-making, and the more informed they feel, the more involved they prefer to be in decision-making [10] and the more satisfied they feel with treatment decisions [11, 12]. Further, healthcare providers are often in the only position to know whether the information that individuals receive are appropriate for their conditions, ensuring patients are informed and are using accurate information when making decisions.

Given the diversity of sources of information and its widely varied quality, it is critical that we keep up on trends associated with changes in how individuals source their health information. This analysis updates prior work conducted by Volkman, Luger, Harvey, Hogan, Shimada, Amante, McInnes, Feng, and Houston in 2014 concerning the most frequently used first sources of health information, and characteristics of patients that seek health information from doctors first [13]. The demographic trends among those who seek doctors as the first source of health information are analyzed using expanded data to identify substantive changes in practice.

Methods

Data collection

This study used data obtained through the Health Information National Trends Survey (HINTS 4) [14], an annual survey fielded to a representative sample of United States (U.S.) adults over 18 years of age, sponsored by the National Cancer Institute (NCI), which explores the public’s use of cancer-related information. The fourth version of HINTS, used in this study, was administered by mail to a sample of U.S. civilian, non-institutionalized adults in four separate cycles: 2011, 2012, 2013, and 2014. HINTS had a response rate of 37% in HINTS 4 Cycle 1, 40% in Cycle 2, 35% in Cycle 3, and 34% in Cycle 4. [15, 16] Non-response was systematically more likely for respondents who were male, minority, younger, less educated, or Hispanic. The survey uses a stratified postal address frame to randomly sample residential addresses. Weighting is provided to allow interested researchers to develop population estimates.

Participants

A population sample was obtained from the combined 2011–2014 HINTS data. Of the total 14,451 participants, 10,024 were included in this study. The exclusion criteria, mirrored from Volkman et al. 2014, allow for comparison and extension on prior research and were based on responses to the survey question: “The most recent time you looked for information about health or medical topics, where did you go first?” Participants were excluded if they had a missing response (n = 112), a response error (e.g., multiple responses) (n = 1848), or if they never sought health or medical topic information (i.e., question inapplicable) (n = 2467).

Measures

To quantify the first source used for seeking health information, participants were asked: “The most recent time you looked for information about health or medical topics, where did you go first?” Potential responses to this question included: Internet, doctor/healthcare provider, publications, family/friends/co-workers, telephone service, cancer organization, library, complementary, alternative, or unconventional medicine practitioner, and other. A derived variable was created by dichotomizing the responses as “doctor/healthcare provider” and “other” (i.e., Internet, publications, family/friends/co-workers, other, telephone service, cancer organization, library, and complementary or alternative medicine practitioner).

Sociodemographic characteristics used in this analysis included gender (male/female), age (18–45/ 46–64/65–75/ 76≤), income (<$20,000 / $20,000–$49,999 / $50,000≤), race/ethnicity (non-Hispanic White/non-Hispanic Black/Hispanic/Other), education (<high school/high school graduate/some college/college graduate≤), rurality, and veteran status. Rurality (yes/no) was determined by the 2003 USDA rural/urban designation assigned to the respondent’s mailing address [17]. Veteran status (yes/no) was determined by responses to the following question: “Have you ever served on active duty in the U.S. Armed Forces, military Reserves, or National Guard? Active duty does not include training in the Reserves, or National Guard, but DOES include activation, for example, for the Persian Gulf War.”

Cancer history, general health, and health insurance were included in the analysis as important clinical characteristics. Cancer history (yes/no) was assessed by the question: “Have you ever been diagnosed with cancer?” The question: “In general, would you say your health is? [excellent/very good/good/fair/poor]” was used to assess general health (excellent/very good/good/fair/poor). In 2011 and 2013 participants were categorized as possessing insurance if they had: “Insurance through a current or former employer or union,” “Insurance purchased directly from an insurance company,” “Medicare, Medicaid, Medical Assistance, or any kind of government-assistance plan for those with low incomes or a disability,” “TRICARE or other military health care,” “VA health care,” or “Indian Health Service.” In survey years 2012 and 2014 possession of health insurance was determined by the question: “Do you have any kind of health care coverage, including health insurance, prepaid plans such as HMOs, or government plans such as Medicare?” A variable for health insurance (yes/no) was derived from the combined response data of 2011–2014.

Other sample characteristics included in the analysis were Internet use and Internet access. To determine Internet use (yes/no) participants were asked: “Do you ever go online to access the Internet or World Wide Web, or to send and receive e-mail?” Internet access (dial-up, broadband, cellular, or wireless networks) was assessed by a follow-up question: “When you use the Internet, do you access it through [dial-up, broadband, cellular, or wireless networks]?”

Analytic methods

All analyses were conducted in STATA 14 using survey weighting and jackknife variance estimations provided by HINTS [15]. Analyses were first performed using the combined data from 2011 and 2012 to replicate the findings from Volkman et al. 2014 and ensure model fidelity. These analyses were then extended across 2011–2014, thereby including all currently available data.

Maintaining fidelity to the original paper [13], the data was analyzed describing the first source chosen by participants for health information (Table 1). Weighted descriptive statistics were analyzed for participants who reported a doctor/healthcare provider as their first source of health information (Table 2). Individual logistic regression models were created to explore the association between first source of health information and demographic characteristics as in Volkman et al. 2014. A weighted multivariable logistic regression model was created to explore the adjusted association between first source of health information and demographic characteristics (Table 3). A category for missing data was included in the analysis of the descriptive statistics but was excluded from the logistic model.
Table 1

First Health Information Source

 

Data Years 2011–2012 (N = 5307)

Data Years 2011–2014 (N = 10,024)

Source

N

Weighted %

95% CI

N

Weighted %

95% CI

Internet

3315

67.63

65.89–69.33

6353

68.72

67.35–70.05

Doctor/healthcare provider

937

15.66

14.17–17.27

1798

15.26

14.21–16.37

Publications

652

9.39

8.38–10.52

1138

8.89

8.12–9.72

Family/friends/co-workers

235

4.95

4.17–5.87

444

4.97

4.32–5.72

Other

72

0.99

0.66–1.47

108

0.85

0.63–1.15

Telephone service

40

0.61

0.40–0.94

73

0.55

0.39–0.76

Cancer organization

17

0.26

0.14–0.49

30

0.24

0.14–0.43

Library

21

0.23

0.14–0.39

45

0.30

0.21–0.42

Complementary or alternative medicine practitioner

18

0.28

0.15–0.50

35

0.23

0.14–0.36

CI Confidence Interval

Table 2

Characteristics of Respondents Choosing Doctor/Healthcare Provider as First Source of Health Information

 

Data Years 2011–2012 (n = 937)

Data Years 2011–2014 (n = 1789)

 

N

Weighted %

95% CI

N

Weighted %

95% CI

Gender

 Male

385

43.16

38.56–47.88

742

45.42

41.98–48.91

 Female

531

53.81

48.90–58.64

1014

51.95

48.36–55.53

 Missing

21

3.03

1.26–7.13

42

2.63

1.48–4.63

Age

 18–45

150

28.62

24.00–33.74

271

29.20

25.50–33.21

 46–64

347

34.66

30.46–39.11

675

34.03

31.09–37.11

 65–75

241

18.14

15.47–21.16

441

16.49

14.69–18.47

 76–99

179

14.71

12.44–17.30

345

15.08

13.26–17.09

 Missing

20

3.87

1.30–10.92

66

5.19

3.18–8.36

Rurality

 Yes

21

2.32

1.37–3.91

39

2.34

1.47–3.69

 No

916

97.68

96.09–98.63

1759

97.66

96.31–98.53

 Missing

Cancer history

 Yes

186

13.50

11.36–15.96

364

13.45

11.87–15.20

 No

746

86.12

83.67–88.25

1413

84.98

83.01–86.75

 Missing

5

0.39

0.14–1.05

21

1.58

0.78–3.15

General health

 Excellent

71

8.71

6.00–12.46

131

8.52

6.62–10.90

 Very good

302

31.08

26.58–35.96

578

32.06

28.84–35.46

 Good

347

34.63

30.25–39.27

655

36.73

33.29–40.32

 Fair

141

16.47

12.83–20.90

279

14.78

12.29–17.66

 Poor

52

6.48

3.58–11.45

98

5.04

3.34–7.53

 Missing

24

2.64

1.60–4.33

57

2.88

2.02–4.08

Income

 Less than $20,000

234

26.40

21.31–32.21

466

25.56

22.13–29.32

 $20,000 to $49,999

258

27.10

22.54–32.21

485

26.57

23.31–30.11

 $50 k or above

311

34.14

29.91–38.65

577

34.25

31.15–37.49

 Missing

134

12.35

9.31–16.21

270

13.63

11.46–16.13

Race/Ethnicity

 White, NH

532

58.93

53.77–63.90

912

56.04

52.30–59.71

 Black, NH

143

9.18

7.13–11.73

290

10.64

8.58–13.14

 Hispanic

111

16.36

12.42–21.25

245

15.31

12.56–18.53

 Other, NH

63

6.74

4.44–10.10

111

5.63

4.12–7.63

 Missing

88

8.80

6.48–11.83

240

12.39

10.14–15.05

Education

 Less than high school

118

23.11

17.99–29.16

239

20.42

17.14–24.15

 High school graduate

240

23.01

19.23–27.27

431

21.77

19.07–24.73

 Some college

292

31.83

27.26–36.79

570

31.00

27.57–34.65

 College or above

266

20.39

17.46–23.66

494

23.23

20.61–26.08

 Missing

21

1.67

0.97–2.86

64

3.57

2.52–5.04

Health insurance

 Yes

855

86.04

80.79–90.02

1638

87.10

83.88–89.76

 No

65

10.74

7.54–15.08

122

9.76

7.53–12.57

 Missing

17

3.22

1.10–9.11

38

3.13

1.68–5.77

Veteran status

 Veteran

139

11.45

9.04–14.39

264

11.52

9.68–13.67

 Non-veteran

735

80.64

76.31–84.34

1391

80.30

77.24–83.03

 Missing

63

7.91

5.27–11.72

143

8.18

6.24–10.64

Internet use

 Yes

550

61.81

56.45–66.90

1042

61.36

57.74–64.85

 No

386

38.17

33.07–43.53

744

37.97

34.54–41.52

 Missing

1

0.03

0.00–0.19

12

0.67

0.24–1.91

Access to Internet

 Telephone line

52

5.10

3.15–8.14

93

4.70

3.40–6.46

 Broadband

359

37.47

32.29–42.96

645

38.52

34.84–42.34

 Cellular network

166

22.29

17.49–27.95

370

25.37

21.81–29.29

 Wireless network

274

31.30

26.59–36.43

565

35.61

31.90–39.49

 Missing

12

5.12

1.58–15.31

27

3.77

1.62–8.50

Data Year

 2011

436

42.15

37.45–47.01

436

21.91

19.36–24.68

 2012

501

57.85

52.99–62.55

501

30.06

26.64–33.72

 2013

408

23.11

20.15–26.35

 2014

453

24.92

21.87–28.25

CI Confidence Interval, NH Non-Hispanic

Table 3

Model of Seekers Choosing Doctor/Healthcare Provider First For 2011–2014

 

Healthcare Provider N (weighted %)

Other Sources N (weighted %)

Unadjusted OR (95% CI), p-value

Adjusted OR (95% CI), p-value

Gender

 Male

742 (15.25)

3005 (84.75)

 Female

1014 (14.98)

5080 (85.02)

0.98 (0.83–1.16), 0.803

0.85 (0.67–1.07), 0.156

Age

 18–45

271 (9.33)

2766 (90.67)

 46–64

675 (15.28)

3471 (84.72)

1.75 (1.42–2.17), 0.000c

1.62 (1.26–2.07), 0.000 c

 65–75

441 (25.50)

1260 (74.50)

3.33 (2.65–4.17), 0.000c

2.15 (1.55–3.00), 0.000 c

 76–99

345 (38.87)

525 (61.13)

6.18 (4.81–7.94), 0.000c

2.94 (2.08–4.17), 0.000 c

Rurality

 No

1759 (15.17)

8099 (84.83)

 Yes

39 (20.18)

127 (79.82)

1.41 (0.79–2.53), 0.243

1.31 (0.65–2.64), 0.440

Cancer history

 No

1413 (14.23)

7104 (85.77)

 Yes

364 (24.64)

1076 (75.36)

1.97 (1.66–2.34), 0.000c

1.19 (0.94–1.51), 0.149

General health

 Excellent

131 (10.74)

1006 (89.26)

 Very good

578 (13.07)

3031 (86.93)

1.25 (0.90–1.73), 0.177

1.04 (0.71–1.52), 0.851

 Good

655 (15.76)

2912 (84.24)

1.56 (1.13–2.14), 0.007b

0.95 (0.65–1.39), 0.794

 Fair

279 (20.65)

932 (79.35)

2.16 (1.50–3.13), 0.000c

0.96 (0.59–1.54), 0.854

 Poor

98 (35.98)

184 (64.02)

4.67 (2.55–8.55), 0.000c

2.22 (0.77–6.43), 0.141

Income

 Less than $20,000

466 (23.06)

1305 (76.94)

 $20,000 to $49,999

485 (16.21)

2122 (83.79)

0.65 (0.50–0.84), 0.001b

0.87 (0.62–1.22), 0.427

 $50 k or above

577 (10.68)

4019 (89.32)

0.40 (0.32–0.50), 0.000c

0.72 (0.51–1.02), 0.062

Race/Ethnicity

 White, NH

912 (13.02)

5112 (86.98)

 Black, NH

290 (17.14)

1066 (82.86)

1.38 (1.03–1.85), 0.029a

1.46 (1.01–2.11), 0.043a

 Hispanic

245 (19.97)

946 (80.03)

1.67 (1.28–2.18), 0.000c

1.26 (0.90–1.75), 0.178

 Other, NH

111 (13.49)

519 (86.51)

1.04 (0.71–1.52), 0.833

1.24 (0.76–2.02), 0.380

Education

 Less than high school

239 (35.60)

409 (64.40)

 High school graduate

431 (18.73)

1289 (81.27)

0.42 (0.30–0.57), 0.000c

0.68 (0.42–1.11), 0.123

 Some college

570 (13.85)

2465 (86.15)

0.29 (0.22–0.39), 0.000c

0.67 (0.41–1.10), 0.115

 College or above

494 (9.48)

3895 (90.52)

0.19 (0.14–0.25), 0.000c

0.50 (0.29–0.865, 0.011a

Health insurance

 No

122 (10.39)

945 (89.61)

 Yes

1638 (15.76)

7179 (84.24)

1.61 (1.17–2.21), 0.003b

1.97 (1.28–3.04), 0.002b

Veteran status

 Non-veteran

1391 (14.03)

7079 (85.97)

 Veteran

264 (19.05)

866 (80.95)

1.44 (1.15–1.82), 0.002 b

1.05 (0.77–1.44), 0.742

Internet use

 No

744 (43.71)

974 (56.29)

 Yes

1042 (10.83)

7214 (89.17)

0.16 (0.13–0.19), 0.000c

0.34 (0.25–0.46), 0.000c

Data Year

 2011

436 (13.62)

2263 (86.38)

 2012

501 (17.58)

2107 (82.42)

1.35 (1.08–1.70), 0.010a

1.22 (0.92–1.62), 0.157

 2013

408 (14.84)

1738 (85.16)

1.11 (0.88–1.38), 0.383

0.95 (0.69–1.31), 0.737

 2014

453 (14.86)

2118 (85.14)

1.11 (0.89–1.38), 0.368

1.14 (0.86–1.52), 0.358

a= significant at the 0.05 level; b = significant at the 0.01 level, c = significant at the 0.001 level

OR Odds Ratio, CI Confidence Interval, NH Non-Hispanic

Results

Our analysis describing the first source of health information showed that the majority of survey respondents continue to report using the Internet as a first source of health information (n = 6353, 68.72%) followed by doctor/healthcare provider (n = 1798, 15.26), publications (n = 1138, 8.89%), and family/friends/co-workers (n = 444, 4.97%).

The respondents who more frequently selected doctor/healthcare provider as a first source the most recent time they looked for health information were female (n = 1014, 51.95%), ages 46–64 (n = 675, 34.03%), non-rural (n = 1795, 97.66%), had an income of $50,000 or above (n = 577, 34.25%), non-Hispanic white (n = 912, 56.04%), had some college education (n = 570, 31.00%), and were non-veterans (n = 1391, 80.30%). These respondents also had no history of cancer (n = 1413, 84.98%), reported very good (n = 578, 32.06) or good health (n = 655, 36.73), and had health insurance (n = 1638, 87.10%). These respondents used the Internet (n = 1042, 61.36%) and accessed the internet through broadband (n = 645, 38.52%) or wireless networks (n = 565, 35.61%). (n = 1042, 61.36%).

An adjusted logistic regression showed significant differences in the likelihood of a respondent reporting doctors as first sources of health information on the basis of age, race, education, health insurance, and Internet use. Individuals who chose doctor/healthcare provider as a first source were more likely to be aged 46–64 [OR = 1.62, p = 0.000], 65–75 [OR = 2.15, p = 0.000], or 76–99 [OR = 2.94, p = 0.000] than to be in the 18–45 year age group. Those who chose a doctor as the first source of health information were more likely to be non-Hispanic black [OR = 1.46, p = 0.043], more likely to have health insurance [OR = 1.97, p = 0.002], less likely to have college education or more [OR = 0.50, p = 0.011], and less likely to use the Internet [OR = 0.34, p = 0.000]. Significant differences in the unadjusted logistic regression models for cancer history, general health, income, race (Hispanic), education (high school and some college), veteran status, and data year were attenuated when the logistic regression model was adjusted, similar to the prior analysis.

Discussion

Adults of all age groups older than 18–45 had higher odds of listing their doctor as their first source of health information, and these odds increased with successive age groups. This finding contrasts with prior research in which the OR for the age group 46–64 was not significant [13]. Trust may play a role, as prior research revealed that older adults are less likely to trust information from the Internet, television, magazines, and newspapers than young adults, while trusting doctors the most of any source [18]. Young adults may be less likely to go to physicians as a source of health information as this age group is historically less likely to use primary care services or have insurance coverage [19], although the uninsured rate has decreased since open enrollment for the Affordable Care Act began [20]. Young adults are also more likely to be Internet users, and use the Internet as an initial source of health information [21].

In our updated analyses but not in the original research [13], respondents who were black had higher odds of noting that a doctor was their first source of health information. This finding is in contrast with the results of prior research reporting that black patients do not trust doctors as much as white patients [22]. Since the Affordable Care Act was implemented, there has been a significant reduction in racial disparities in health care access, utilization, and rates of being uninsured [23]. This reduction in access disparities may have played a role in the increase in black patients choosing doctors as a first source of medical information, as they were more readily able to see doctors. The attitudes of black patients toward doctors may be improved by this increased access to health care and communication with doctors [24].

Our results also show that respondents with more education had lower odds of using their doctor as a first source of health information, even though prior research demonstrates that college-educated adults are more likely to have a usual place of health care [25]. Prior research has shown that those with higher levels of education were more trusting of the Internet, magazines, and newspapers as sources of health information than those with lower levels [18]. These respondents may choose the internet first, similar to research corroborating that those with higher education levels more frequently seek health information on the Internet [26]. In our analyses, those who use the Internet have lower odds of seeking a doctor as the first source of health information. Using the Internet for information may lead to self-diagnosis, encouraging misdiagnosis and inappropriate medical advice [27]. HINTS does not ask questions regarding the specific internet sources used and trusted; future research could elaborate on the legitimacy of trusted internet health information sources.

In the original analysis [13], people who rated their general health as good had lower odds of choosing a doctor and those who rated their health as poor had higher odds of choosing a doctor as their first health information source than those with excellent health, however, the impact of health status on choice of health information source was no longer significant with the addition of 2 years of data. This could be due to an increase in those with poor health using the internet or other sources or people with good health seeking information from doctors more. Healthy people may be seeking information from doctors first more than in previous years due to increased access to care as the uninsured rate has decreased [20]. Other prior research provides evidence that people with poor health are more likely to seek health information on the Internet than those with good health, and the internet may be displacing doctors as a primary source in this group [28]. People with poor health may have chronic conditions that require more health information or more frequent information than regular patients, and may use multiple information sources [29]. Doctors can assist these patients by helping verify information and guiding them on where to find credible sources [30].

This analysis was strengthened by the addition of an extra 2 years of data, doubling the sample size and allowing for analysis of changes in significance. However, a limitation that persists is the cross-sectional nature of the data because within-person trends over time cannot be assessed. A second limitation is the fact that these are self-reported data, as people may not accurately recall whether they used certain information sources. HINTS only surveys U.S. households, so these findings may not be generalizable to populations outside the United States; there may be differences in trust and use of internet health sources in other countries. Further, the specific publications or Internet sources of health information were not assessed, so the credibility of the sources remains unknown. Finally, we did not know whether the doctors mentioned were primary care or specialty doctors, and this information may add depth to the analysis. Future research could elaborate on both the use and trust of more specific sources of information.

Conclusion

Doctors are the most trusted sources of health information yet the results of a recent survey of health information sources show that 69% of adults in the U.S. reportedly chose the Internet and 15% chose healthcare providers as their first source of health information when they had a medical problem. Those more likely to choose doctors as an initial source of health information were older than age 45, more likely to have health insurance, more likely to be black, less likely to be college educated, and less likely to use the Internet. Doctors may need to provide more information to these patients than those who use the Internet, however, they may need to spend more time verifying the accuracy of information provided to those who choose the Internet first.

Abbreviations

HINTS: 

Health Information National Trends Survey

HMO: 

Health maintenance organization

NCI: 

National cancer institute

OR: 

Odds ratio

US: 

United States

VA: 

Veteran’s affairs

Declarations

Acknowledgements

This is the result of work supported by the Department of Family Medicine at The Ohio State University. We would like to acknowledge Bradford Hesse of the National Cancer Institute and thank him for his review of this work.

Availability of data and materials

The datasets analyzed during the current study are available in the HINTS repository at https://hints.cancer.gov.

Authors’ contributions

CMS analyzed and reviewed the results, drafted, and finalized the manuscript. JVH analyzed the results and participated in the draft of the manuscript. ASM contributed to the draft of the manuscript, edited and revised the manuscript, and assisted with interpretation of study analyses. TRH contributed to the conception and design of the analyses and contributed to the draft and revisions of the manuscript. All authors have read and approved the final manuscript and agree to be accountable for all aspects of the work.

Ethics approval and consent to participate

Not applicable. We did not collect data, but are reporting previously collected national cross-sectional data.

Consent for publication

Not applicable. Individual patient data not reported.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Family Medicine, The Ohio State University, Room 502, 460 Medical Center Drive, Columbus, OH 43210, USA
(2)
Department of Family Medicine, The Ohio State University, Room 530, 460 Medical Center Drive, Columbus, OH 43210, USA
(3)
Departments of Family Medicine and Biomedical Informatics, The Ohio State University, Room 532, 460 Medical Center Drive, Columbus, OH 43210, USA

References

  1. Cutilli CC. Seeking health information: what sources do your patients use? Orthop Nurs. 2010;29(3):214–9.PubMedGoogle Scholar
  2. Fox S. Health topics: 80% of internet users look for health information online. Pew Research Center 2011. http://pewinternet.org/Reports/2011/HealthTopics.aspx. Accessed 7 Apr 2017.
  3. Bundorf MK, Wagner TH, Singer SJ, Baker LC. Who searches the internet for health information? Health Serv Res. 2006;41(3 Pt 1):819–36.View ArticlePubMedPubMed CentralGoogle Scholar
  4. Tu HT, Cohen GR. Striking jump in consumers seeking health care information. Track Rep. 2008;20:1–8.Google Scholar
  5. Schwartz KL, Roe T, Northrup J, Meza J, Seifeldin R, Neale AV. Family medicine patients’ use of the internet for health information: a MetroNet study. J Am Board Fam Med. 2006;19(1):39–45.View ArticlePubMedGoogle Scholar
  6. Benigeri M, Pluye P. Shortcomings of health information on the internet. Health Promot Int. 2003;18(4):381–6.View ArticlePubMedGoogle Scholar
  7. Tan SS, Goonawardene N. Internet health information seeking and the patient-physician relationship: a systematic review. J Med Internet Res. 2017;19(1):e9.View ArticlePubMedPubMed CentralGoogle Scholar
  8. Hibbard JH, Peters E. Supporting informed consumer health care decisions: data presentation approaches that facilitate the use of information in choice. Annu Rev Public Health. 2003;24:413–33.View ArticlePubMedGoogle Scholar
  9. Joosten EA, DeFuentes-Merillas L, de Weert GH, Sensky T, van der Staak CP, de Jong CA. Systematic review of the effects of shared decision-making on patient satisfaction, treatment adherence and health status. Psychother Psychosom. 2008;77(4):219–26.View ArticlePubMedGoogle Scholar
  10. Say R, Murtagh M, Thomson R. Patients’ preference for involvement in medical decision making: a narrative review. Patient Educ Couns. 2006;60(2):102–14.View ArticlePubMedGoogle Scholar
  11. Whelan T, Levine M, Willan A, Gafni A, Sanders K, Mirsky D, Chambers S, O'Brien MA, Reid S, Dubois S. Effect of a decision aid on knowledge and treatment decision making for breast cancer surgery: a randomized trial. JAMA. 2004;292(4):435–41.View ArticlePubMedGoogle Scholar
  12. Stacey D, Légaré F, Col NF, Bennett CL, Barry MJ, Eden KB, Holmes-Rovner M, Llewellyn-Thomas H, Lyddiatt A, Thomson R et al. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev. 2014;(1):CD001431. https://doi.org/10.1002/14651858.CD001431.pub4.
  13. Volkman JE, Luger TM, Harvey KL, Hogan TP, Shimada SL, Amante D, McInnes DK, Feng H, Houston TK. The National Cancer Institute’s Health Information National Trends Survey [HINTS]: a national cross-sectional analysis of talking to your doctor and other healthcare providers for health information. BMC Fam Pract. 2014;15:111.View ArticlePubMedPubMed CentralGoogle Scholar
  14. National Cancer Institute. HINTS Survey Instruments. 2016. https://hints.cancer.gov/data/survey-instruments.aspx. Accessed 13 Feb 2017.
  15. National Cancer Institute. Frequently Asked Questions about HINTS. 2016. https://hints.cancer.gov/about-hints/frequently-asked-questions.aspx. Accessed 13 Feb 2017.
  16. Westat. Health Information National Trends Survey 4 (HINTS 4) Cycle 4 Methodology Report. 2015. https://hints.cancer.gov/docs/HINTS_4_Cycle_4_Methodology_Report.pdf. Accessed 1 Nov 2017.
  17. United States Department of Agriculture Economic Research Service. 2013 Rural-Urban Continuum Codes--Data Set. United States Department of Agriculture. 2016. http://www.ers.usda.gov/data-products/rural-urban-continuum-codes.aspx. Accessed 7 Apr 2017.
  18. Hesse BW, Nelson DE, Kreps GL, Croyle RT, Arora NK, Rimer BK, Viswanath K. Trust and sources of health information: the impact of the internet and its implications for health care providers: findings from the first Health Information National Trends Survey. Arch Intern Med. 2005;165(22):2618–24.View ArticlePubMedGoogle Scholar
  19. Cohen RA, Bloom B. Access to and utilization of medical care for young adults ages 20-29 years: United States. 2008 NCHS Data Brief. 2010;29:1–8.Google Scholar
  20. Sommers BD, Musco T, Finegold K, Gunja MZ, Burke A, McDowell AM. Health reform and changes in health insurance coverage in 2014. N Engl J Med. 2014;371(9):867–74.View ArticlePubMedGoogle Scholar
  21. Kontos E, Blake KD, Chou WY, Prestin A. Predictors of eHealth usage: insights on the digital divide from the Health Information National Trends Survey 2012. J Med Internet Res. 2014;16(7):e172.View ArticlePubMedPubMed CentralGoogle Scholar
  22. Richardson A, Allen JA, Xiao H, Vallone D. Effects of race/ethnicity and socioeconomic status on health information-seeking, confidence, and trust. J Health Care Poor Underserved. 2012;23(4):1477–93.View ArticlePubMedGoogle Scholar
  23. Chen J, Vargas-Bustamante A, Mortensen K, Ortega AN. Racial and ethnic disparities in health care access and utilization under the affordable care act. Med Care. 2016;54(2):140–6.View ArticlePubMedPubMed CentralGoogle Scholar
  24. Martin KD, Roter DL, Beach MC, Carson KA, Cooper LA. Physician communication behaviors and trust among black and white patients with hypertension. Med Care. 2013;51(2):151–7.View ArticlePubMedPubMed CentralGoogle Scholar
  25. Blackwell DL, Villaroel MA. Tables of summary health statistics for U.S. adults: 2015 National Health Interview Survey. National Center for Health Statistics 2016. http://www.cdc.gov/nchs/nhis/SHS/tables.htm. Accessed 7 Apr 2017.
  26. Lorence DP, Park H, Fox S. Assessing health consumerism on the web: a demographic profile of information-seeking behaviors. J Med Syst. 2006;30(4):251–8.View ArticlePubMedGoogle Scholar
  27. Semigran HL, Linder JA, Gidengil C, Mehrotra A. Evaluation of symptom checkers for self diagnosis and triage: audit study. BMJ. 2015;351:h3480.View ArticlePubMedPubMed CentralGoogle Scholar
  28. Lee YJ, Boden-Albala B, Larson E, Wilcox A, Bakken S. Online health information seeking behaviors of Hispanics in new York City: a community-based cross-sectional study. J Med Internet Res. 2014;16(7):e176.View ArticlePubMedPubMed CentralGoogle Scholar
  29. Zulman DM, Jenchura EC, Cohen DM, Lewis ET, Houston TK, Asch SM. How can eHealth technology address challenges related to multimorbidity? Perspectives from patients with multiple chronic conditions. J Gen Intern Med. 2015;30(8):1063–70.View ArticlePubMedPubMed CentralGoogle Scholar
  30. Sommerhalder K, Abraham A, Zufferey MC, Barth J, Abel T. Internet information and medical consultations: experiences from patients’ and physicians’ perspectives. Patient Educ Couns. 2009;77(2):266–71.View ArticlePubMedGoogle Scholar

Copyright

© The Author(s). 2018

Advertisement