Sage Journals: Discover world-class research

Abstract

Purpose

American Indian and Alaska Native (AI/AN) peoples face disproportionate health risks. Understanding how AI/ANs seek out information can inform effective campaigns design that can help address these risks. We investigate preferred communication sources, health information seeking behavior (HISB), self-efficacy, perceived importance of health information, and prevention orientation of American Indians and Alaska Natives (AI/ANs).

Design

We administered a survey at 3 cultural events.

Setting

The National Tribal Health Conference in Bellevue, the University of Washington Winter and Spring Powwows in Seattle.

Subjects

Participants (N = 344) of the survey included people from tribes throughout the US, particularly from northwestern tribes.

Analysis

Independent samples t-tests and ANOVAs examined differences in HISB. Frequency analyses identified preferred health information. PROCESS tested the relationship between perceived importance and HISB, and moderation from prevention orientation and self-efficacy.

Results

Preferred health information source were doctor (M = 3.5), the internet (M = 3.32) and friends/relatives (M = 3.11). Females demonstrated more HISB than males (P < .01). Individuals with a college degree or higher showed greater HISB (P < .001). AI/ANs living on reservations (M = 2.34, SD = 1.53) preferred newspapers for health information more than those in metropolitan (M = 1.64, SD = .13) or rural areas (M = 1.45, SD = .16, P < .05). Perceived importance is a robust positive factor that predicts HISB (b = .48, t(315) = 9.67, P < .001).

Conclusion

This study offers advice for scholars and practitioners to design messages to increase accessibility of health information.

Keywords

health communication indigenous risk communication health disparities

American Indian and Alaska Native (AI/AN) peoples face disproportionate health risks, including a heightened susceptibility to cardiovascular disease,^1,2 Alzheimer’s disease,^3,4 and cancer.⁵ Effective health communication acts as a critical determinant to enhance well-being and reduce health disparities among AI/ANs. Health campaigns achieve greater success when communicators account for individual and population-specific characteristics, such as health information seeking.^6,7 Understanding how AI/ANs seek out information can inform effective campaigns design, especially in the current media environment in which people have access to an unprecedented amount of information.⁸

Health information seeking behavior (HISB) can be defined as a purposeful and goal-oriented pursuit of specific health information related to both reactive and preventative behaviors.^9,10 This pursuit can include several activities, including searching for information on the Internet, consulting friends and family, and proactively speaking with a healthcare provider.¹¹ HISB is a crucial aspect of shared decision-making among patients and healthcare providers that can empower patient agencies in a healthcare setting.¹² HISB can have mental and physical health outcomes because health seekers gain a better understanding and greater knowledge about health problems they encounter.^13,14 HISB also helps manage uncertainty about health problems; past studies have indicated that seeking health information can have health outcomes by giving participants more certainty about how these actions can benefit their health.^15–17 HISB can help reduce healthcare inequality as patients can act as active information seekers to learn more health information themselves instead of relying on information conveyed from systemically discriminatory sources.⁹ This is especially important for priority populations who historically have faced discrimination from the US healthcare system that has caused distrust within Native communities.¹⁸

Purpose

To better tailor health communication campaigns to the intended audience, it is important to understand how both the sources consulted and the level of HISB might differ based on group-level differences. HISB among AI/ANs could be related to demographic differences such as age,¹⁹ gender,²⁰ and education.^9,21 Additionally, residence of AI/ANs in metropolitan, rural, or reservation areas could be related to HISB,²² especially considering access to health services and the Internet varies widely based on residence.^23–25 Health information sources require an evaluation of how media receivers perceive credibility, trust, and importance. However, little is known about how, why, and from what sources AI/ANs seek health information. To help communicators and practitioners develop health messaging that is effective and culturally appropriate for this priority population, it is critical to examine health information preferences among AI/ANs.

One concept that could impact health preferences among AI/ANs is perceived health importance. Perceived importance refers to the level at which people believe having health information is related to staying healthy in general. For example, even if a person agrees that being healthy is important, someone who has a low level of perceived importance of health information might not believe that knowing health information would help them keep themselves or their families healthy.²⁶ This concept could be related to HISB, as individuals who recognize the importance of health information for their well-being are likely to seek out that information more actively than those who do not see it as important.^27,28 However, the relationship between the perceived importance of health information and HISB is unclear due to factors such as lack of time,^29,30 low trust in healthcare providers,^8,31 and information overload,³² which may lead to undesired behaviors such as information avoidance.³³ Due to these mixed findings, we propose a research question to examine whether perceived importance of health information is related to HISB among participants.

We also consider two attitudinal concepts that could moderate the relationship between perceived importance of health information and HISB: prevention orientation and perceived self-efficacy. Prevention orientation is an individual difference where those who possess a prevention orientation show a higher focus on maintaining good health, living a long life, and exerting control over healthy practices such as eating fruits and vegetables.⁸ Prevention orientation could moderate the relationship between perceived issue importance and HISB because it involves self-efficacy around caring for health, which has been shown in past research to be as important to behavioral intentions as acknowledging the importance of a behavior.³⁴ That is, those with more prevention orientation will tend to seek health information at a higher rate than those without, even if they have the same level of issue importance. Perceived self-efficacy for health information, which refers to the belief that a person could successfully find health information on their own,^8,35 could influence HISB. Without self-efficacy for health information, participants might be less likely to seek out health information even if they think it is important as they do not believe they could be successful in gathering it. Put another way, prevention orientation and perceived self-efficacy for health information could moderate the potential relationship between perceived importance and HISB among AI/ANs.

Research Questions

RQ1

Does participants’ HISB differ by age, gender, education, and/or residence (ie, rural, urban, or reservation)?

RQ2a

What are participants’ preferred sources for gaining health information?

RQ2b

Do participants’ preferred sources of health information differ by age, gender, education, and/or residence (ie, rural, urban, or reservation)?

RQ3a

Is there a relationship between perceived importance of health information and HISB among AI/AN participants?

RQ3b

Is the relationship in RQ3a moderated by prevention orientation and/or perceived self-efficacy?

Methods

Design

We administered surveys at three cultural events in Washington state during 2017. Events include the National Tribal Health Conference in Bellevue, the University of Washington Winter Powwow in Seattle, and the University of Washington Spring Powwow in Seattle. An Indigenous-led research institute at a university located in the Pacific Northwest guided this study. A large research and education unit hosted a booth at the 3 events to administer a survey to identify AI/AN health needs and to disseminate health information on various health conditions that affect AI/AN people. Potential participants could approach the booth and learn about the survey. If they were interested in participating, they were asked 2 screening questions to determine eligibility to complete the study: (1) “Do you identify as American Indian or Alaska Native” and (2) “Are you at least 18 years of older? Respondents who answered the survey were provided with a $5 gift certificate as a thank you for their time. All data was collected anonymously, and no identifying information was associated with the questionnaires. The study was determined to be exempt from review from the [Washington State University] Institutional Review Board (#19570-005).

Sample

Attendees at these events include people from tribes throughout the US, but particularly from northwestern tribes, eg, Tulalip, Yakima, and Skokomish. The National Tribal Health Conference was held in Bellevue, Washington, and included workshops, exhibitions, and presentations from health service providers and community members. Attendees at these three events included health officials, tribal leaders, the lay public, and students.

Measures

Questions on the survey included items to assess their HISB, dependence on health information sources, perceived importance of health information, prevention orientation, perceived self-efficacy for health information, as well as demographic questions. The questions and scales are detailed below.

HISB

We use six items from a scale developed by Maibach et al. (2006) to evaluate AI/ANs’ HISB. Items include (1) “I don’t have time to bother learning a lot of health information”; (2) “I make a point to read/watch stories about health”; (3) “When sick, I try to get information about my disease”; (4) “I like to get health information from a variety of sources”; (5) “When I take medicine, I try to get as much information about benefits and side effects”; and (6) “Before making a decision about my health, I find out everything I can about this issue”. A 5-point Likert scale (anchors: 1 “Strongly disagree” to 5 “Strongly agree”) is used.

Preferred Sources

To examine dependence on health information sources and frequency in obtaining health information among AI/ANs s, respondents were asked, “How often do you use the following sources to get information about health and well-being?” Response options for the type of source include newspaper; television; radio; your doctor; health professionals including your doctor; friends and relatives; internet sources other than social media; and internet sources including social media. The frequency scale included: never, very rarely, rarely occasionally, frequently, and very frequently.

Perceived Importance

This concept was measured using seven items.⁸ These seven items are commonly adopted in health communication research.²⁶ A 5-point Likert scale (anchors: 1 “Strongly disagree” to 5 “Strongly agree”) is used. Items include: (1) “I would like more TV shows to use health issues in their storylines”; (2) “It is important to be informed about health issues”; (3) “Media spends too much time on coverage of health issues”; (4) “To be and stay healthy, it’s critical to be informed about health issues”; (5) “I feel better if I can confirm a health recommendation from several sources”; (6) “The amount of health information available today makes it easier to take care of my health”; and (7) “I need to know about health issues so I can keep myself and my family healthy”.

Prevention Orientation

To examine the degree of effort invested in disease prevention, we use seven items.⁸ On a 5-point Likert scale (anchors: 1 “Strongly disagree” to 5 “Strongly agree”), respondents were asked to indicate their level of agreement on each of the following statements: (1) “Living life in best possible health is important to me”; (2) “Eating right, exercising, and preventive measures will keep me healthy”; (3) “Living a long life is very important to me”; (4) “My health depends on how well I take care of myself”; (5) “I try to understand my personal health risks”; (6) “I actively try to prevent disease and illness”; and (7) “I wish I had more control over my health”.^8,36

Perceived Self-Efficacy

This concept was measured using six items.⁸ Respondents were asked to indicate their agreement from 1 “Strongly disagree” to 5 “Strongly agree” with each statement: (1) “I am able to find good health information”; (2) “I never find good answers to my health questions”; (3) “I enjoy learning about health issues”; (4) “Most health issues are too complicated for me to understand”; (5) “I am overwhelmed by the amount of health information available to me”; and (6) “I have difficulty understanding health information that I read”.

In addition to the variables above, we ask 5 demographic questions including: “What is your age (in years)?”; “What is your gender?”; “Are you American Indian/Alaska Native?”; “What is the highest grade of school that you completed?”; and “Where do you live most of the year?”.

Analysis

This cross-sectional survey data was analyzed using means, standard deviations, and ranges (the difference between the lowest and highest values) for continuous variables, and frequencies or percentages for categorical variables, to depict the overall descriptive analysis of the sample. To address RQ1, we use t-tests and one-way ANOVA to explore how HISB may differ by age, gender, education, and residence. For the evaluation of RQ2a and RQ2b, we apply three statistical techniques: frequency analysis, independent sample t-tests, and one-way ANOVA, to understand preferred sources of health information and determine differences by demographic characteristics. For RQ3a and RQ3b, we examine the association between the perceived importance of health information and HISB using regression analysis. To explore the moderating effects of prevention orientation and perceived self-efficacy on the relationship between the perceived importance of health information and HISB, we apply PROCESS analysis (Hayes, 2022). All statistical analyses were performed using SPSS version 24.

Results

Descriptive Analysis

344 participants completed the survey. The average age of the respondents was 42.9 (SD = 15.04), ranging from 18–77 years old. 67.9% identified as female. 71.8% reported having completed either some college or a graduate degree, while 28.2% had either a high school diploma, GED, vocational training, or less. About half (49.6%) of the respondents live in a large metropolitan area, followed by reservations (25.5%) and rural areas (24.9%) (Table 1).

Table 1.

Demographic Descriptive Statistics by Event and Overall, N = 344

	2017 National tribal health conference	UW 2017 winter pow wow	UW 2017 spring pow wow	Overall
	n = 81	n = 100	n = 163	N = 344
Age in years, M (SD)	46.48 (12.11)	40.14 (17.32)	42.69 (14.59)	42.86 (15.04)
Gender, n (%)
Man	16 (19.8%)	38 (38.0%)	52 (32.1%)	106 (30.9%)
Woman	64 (79.0%)	60 (60.0%)	109 (67.3%)	233 (67.9%)
Other	1 (1.2%)	2 (2.0%)	1 (.6%)	4 (1.2%)
Highest level of education, n (%)
High school/GED/vocational or less	9 (11.4%)	35 (35.7%)	51 (31.9%)	95 (28.2%)
Some college/college grad	70 (88.6%)	63 (64.3%)	109 (68.1%)	242 (71.8%)
Residence, n (%)
Reservation	39 (48.1%)	17 (17.5%)	30 (18.9%)	86 (25.5%)
Rural area or town, but not on a reservation	21 (25.9%)	24 (24.7%)	39 (24.5%)	84 (24.9%)
Large metropolitan area	21 (25.9%)	56 (57.7%)	90 (56.6%)	167 (49.6%)

Note. The number of percentages is presented as valid percentages; Some column percentages may not sum to one due to rounding.

Analysis

RQ1 asks whether HISB differs by demographic attributes, including age, gender, education, and residence. Independent samples t-test and one-way ANOVA analysis were used to analyze differences in HISB between gender, different age groups, educational levels, and residence. Results showed that female had more HISB (M = 4.05, SD = .04) than male (M = 3.88, SD = .59), t(320) = 2.64, P < .01. A significant difference was also found among different educational groups. Respondents with college or graduate degree (M = 4.08, SD = .53) had greater HISB than those who did not (M = 3.78, SD = .58), t(318) = -4.35, P < .001. There was no significant effect for different age groups, t(325) = -1.71, P = .09, nor among residence, F(2, 317) = 2.32, P = .10.

RQ2 aims to discover AI/ANs preferred sources for health information. Figure 1 showed that the most popular health information source among AI/AN peoples is their doctor (M = 3.5), followed by internet sources other than social media (M = 3.32), friends and relatives (M = 3.11), health professionals other than your doctor (M = 3.02), television (M = 2.54), social media (M = 2.31), radio (M = 2.27), and newspaper (M = 1.9).

Figure 1.

Preferred Sources About Health Information. Note. Participants Were Asked “How Often do You Use The Following Sources to Get Information About Health and Well-Being?” The Average Mean Scores Ranged From “Never” = 0 to “Very Frequently” = 5.

To further examine the preferred sources about health information by demographics, results of independent sample t-test showed that older groups tended to seek out health information through newspaper, t(334 = -3.06, P < .01, and their doctors, t(324) = 2.38, P < .05, more than younger groups. A significant difference was also found in gender. Females (M = 3.68, SD = 1.13) more often get information from their doctors than males (M = 3.11, SD = 1.38), t(319) = 3.91, P < .001. There were significant effects for education on the use of TV, t(327) = 2.73, P < .01, health professionals, t(322) = -2.84, P < .01, and internet sources, t(323) = -3.24, P = .001. Respondents with either college or graduate degrees tended to obtain health information from health professionals and internet sources while those with less years in education more often received their health information from television. Moreover, one-way ANOVA analysis showed that the use of newspaper to get health information differs by residence, F(2, 327) = 4.94, P < .01. Results of multiple comparisons using Bonferroni demonstrated that respondents who live on reservations (M = 2.34, SD = 1.53) tended to rely on newspapers to obtain health information more than those living on large metropolitan areas (M = 1.64, SD = .13, P < .05) or rural areas (M = 1.45, SD = .16), P < .05.

RQ3a evaluates the relationship between perceived importance of health information and HISB, as well as the moderating roles of prevention orientation and perceived self-efficacy. Perceived importance of health information significantly predicted HISB, b = .48, t(315) = 9.67, P < .001, indicating that a one-unit increase in perceived importance of health information corresponds to a .48 predicted increase in HISB. Perceived importance of health information also explained a significant 23% of variance in HISB, R2 = .23, F(1, 315) = 91.55, P < .001. To test RQ3b, Model 2 in the PROCESS macro for SPSS version 4.0 (Hayes, 2022) with 5000 bootstrap samples and 95% confidence intervals was applied. The results show that no significant moderating effects of prevention orientation (b = .06, SE = .08, P = .485) or perceived self-efficacy (b = .07, SE = .08, P = .374) were found on HISB.

Discussion

The main objective of this study was to explore whether health information-seeking behaviors among AI/ANs differ by demographic factors. We also aimed to provide insight into preferred health communication channels for AI/ANs based on individual differences. Through surveys conducted at 3 cultural events in Washington state, we found that HISB differs due to gender and education. Females search for health information more often than males. Moreover, AI/ANs with college or graduate degree are more likely to actively search for health information. This echoes previous findings that show having a high school diploma³⁷ and identifying as a woman^20,38 are related to increased HISB. For practitioners, this could mean that more attention should be paid to encouraging HISB among men and those with fewer years of education. Future research should qualitatively explore potential reasons for these gender and education differences to better tailor health campaigns to diverse demographic groups.

From our data, we found HISB did not differ by age. Age is often discussed as a major factor of HISB, with some studies indicating that older adults may not seek out health information as often due to lack of familiarity with or trust in health information sources.^19,39 Although our study did not reflect these previous findings, a potential explanation for this null finding is that seeking out health information on the Internet was not the most utilized source for health information seeking in this study. The use of conversations with doctors and other non-Internet sources could mitigate the effect of age on HISB as there is less of a technology divide involved with these sources. Future research should investigate this lack of relationship among this priority population further, however, and also investigate the influence of digital divide among the Native communities.⁴⁰

The urban-rural divide in HISB has also been widely discussed in the literature.^41–43 Health disparities among AI/ANs living on reservations indicates that there may be a lack of HISB occurring in these historically underserved places.^44,45 However, we found no significant differences in residence. Health communicators may consider working with local community-oriented services to better evaluate the needs of specific areas rather than relying on strategies based on more broad geography (Figure 2).

Figure 2.

The Moderating Model of RQ3a and RQ3b

We sought to understand the preferred sources for health information among AI/ANs. Our results demonstrate that doctors are the most utilized source to obtain health information, followed by internet sources other than social media and conversations with friends and relatives. In the age of social media abundance where people rely on the Internet more than ever before,⁷ the continuing reliance on conversations with trusted sources such as doctors and friends are an important insight. The interpersonal nature of this HISB echoes previous findings that argue for narrowly tailored and community-oriented approaches to health information for AI/ANs.⁴⁶ Practitioners should consider partnering with community leaders and local organizations in the development and rollout of health communication campaigns as national social media campaigns may not be as effective for AI/AN communities.

We found a significant relationship between perceived importance and HISB. This indicates that as AI/ANs perceive having health information as more crucial to staying healthy, they seek out that information more. Our finding is consistent with past research related to uses and gratifications, where people have agency in the information they consider in an overwhelming media environment.^47,48

Our results showed no significant moderating effect of either prevention orientation or self-efficacy on the relationship between perceived importance and HISB. This indicates that these 2 individual differences related to efficacy are not as crucial as found in past research on other populations such as social media users in China⁴⁹ and more general samples,⁵⁰ but does mirror some studies that indicate HISB can be more social and relational than a simple individual transaction,^12,51 which underscores the need to examine HISB from a more community-oriented perspective where people consult each other and work together to seek health information among AI/ANs. This community-oriented conceptualization could potentially explain the lack of moderation from these individual-level differences. Our earlier findings that conversations with doctors, as well as friends and family, being more prevalent than Internet searching could also support this conceptualization.

We acknowledge that this study has several limitations. First, surveying people attending AI/AN events represents a convenience sample. However, through surveying at AI/AN events we were able to access a non-clinical population that can be difficult to reach. Second, our results may not be generalizable to other AI/AN populations throughout the US. While attendees of the events include people from tribes throughout the US, it was likely that a majority were from northwestern tribes. Therefore, our results may not be generalizable to those living outside the Pacific Northwest. Future studies could examine HISB among other regions and with additional AI/AN populations in the US. In addition, almost 3 quarters of respondents reported having completed either some college or a graduate degree, indicating that our sample was more educated than the overall AI/AN population (approximately 22% had a bachelor’s degree).⁵² Nonetheless, as the first study of HISB among AI/ANs, this work can help guide the development of culturally tailored communication materials and health promotion strategies.

So What?

What Is Already Known on This Topic?

Health information seeking behaviors have been shown to contribute to positive health outcomes.^13,14 However, more research is needed into how American Indians and Alaska Natives (AI/ANs), a priority population, seek out health information.

What Does This Article Add?

This study offers practical applications for health communication scholars and practitioners because it provides actionable suggestions to (1) design tailored messages based on health information seeking styles and preferences on heath information sources among AI/ANs; (2) determine effective strategies to disseminate health information; and (3) increase the accessibility of health information which can ultimately reduce health disparities.

What Are the Implications for Health Promotion Practice or Research?

Findings of this study imply a need for health research with direct partnerships with priority communities. The strong reliance on doctors for health information highlights the need for collaboration with local communities.

Footnotes

Acknowledgements

Studies such as ours could not be done without the participants, and we are grateful to them for sharing their time and perspectives. Research reported in this publication was supported by the National Institutes of Health under award numbers K01AG066063, R01AG093837 and P60AA026112. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

ORCID iD

Kathryn Robinson-Tay

Ethical Considerations

This study was certified exempt by the Washington State University Institutional Review Board (#19570-005).

Consent to Participate

Informed consent was obtained by all participants prior to their participation.

Author Contributions

We confirm that all 3 authors contributed to the research, analysis, and development of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Research reported in this publication was supported by the National Institutes of Health under award numbers K01AG066063, R01AG093837 and P60AA026112.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

References

Breathett

Sims

Gross

, et al. Cardiovascular health in American Indians and Alaska natives: a scientific statement from the American heart association. Circulation. 2020;141(25):e948-e959. doi:10.1161/CIR.0000000000000773

Hutchinson

Shin

. Systematic review of health disparities for cardiovascular diseases and associated factors among American Indian and Alaska native populations. PLoS One. 2014;9(1):e80973. doi:10.1371/journal.pone.0080973. Baradaran HR, ed.

Olson

Albensi

. Race- and sex-based disparities in Alzheimer’s disease clinical trial enrollment in the United States and Canada: an indigenous perspective. J Alzheimers Dis Rep. 2020;4(1):325-344. doi:10.3233/ADR-200214

Sehar

Kopel

Reddy

. Alzheimer’s disease and its related dementias in US native Americans: a major public health concern. Ageing Res Rev. 2023;90:102027. doi:10.1016/j.arr.2023.102027

Kratzer

Jemal

Miller

, et al. Cancer statistics for American Indian and Alaska native individuals, 2022: including increasing disparities in early onset colorectal cancer. CA Cancer J Clin. 2023;73(2):120-146. doi:10.3322/caac.21757

Boyd

Furgal

. Communicating environmental health risks with Indigenous populations: a systematic literature review of current research and recommendations for future studies. Health Commun. 2019;34(13):1564-1574. doi:10.1080/10410236.2018.1507658

Jia

Pang

Liu

. Online health information seeking behavior: a systematic review. Healthcare. 2021;9(12):1740. doi:10.3390/healthcare9121740

Maibach

Weber

Massett

Hancock

Price

. Understanding consumers’ health information preferences development and validation of a brief screening instrument. J Health Commun. 2006;11(8):717-736. doi:10.1080/10810730600934633

Jacobs

Amuta

Jeon

. Health information seeking in the digital age: an analysis of health information seeking behavior among US adults. Cogent Soc Sci. 2017;3(1):1302785. doi:10.1080/23311886.2017.1302785. Alvares C, ed.

10.

Niederdeppe

Hornik

Kelly

, et al. Examining the dimensions of cancer-related information seeking and scanning behavior. Health Commun. 2007;22(2):153-167. doi:10.1080/10410230701454189

11.

Lambert

Loiselle

. Health information—seeking behavior. Qual Health Res. 2007;17(8):1006-1019. doi:10.1177/1049732307305199

12.

Anker

Reinhart

Feeley

. Health information seeking: a review of measures and methods. Patient Educ Couns. 2011;82(3):346-354. doi:10.1016/j.pec.2010.12.008

13.

Johnson

Meischke

. Women’s preferences for cancer information from specific communication channels. Am Behav Sci. 1991;34(6):742-755. doi:10.1177/0002764291034006010

14.

Mitchell Turner

Rimal

Morrison

Kim

. The role of anxiety in seeking and retaining risk information: testing the risk perception attitude framework in two studies. Hum Commun Res. 2006;32(2):130-156. doi:10.1111/j.1468-2958.2006.00006.x

15.

Lewis

Martinez

Freres

, et al. Seeking cancer-related information from media and family/friends increases fruit and vegetable consumption among cancer patients. Health Commun. 2012;27(4):380-388. doi:10.1080/10410236.2011.586990

16.

Rains

. Health information seeking and the world wide web: an uncertainty management perspective. J Health Commun. 2014;19:1-12. doi:10.1080/10810730.2013.872731

17.

Tan

ASL

Mello

Hornik

. A longitudinal study on engagement with dieting information as a predictor of dieting behavior among adults diagnosed with cancer. Patient Educ Couns. 2012;88(2):305-310. doi:10.1016/j.pec.2012.02.008

18.

Findling

Casey

Fryberg

, et al. Discrimination in the United States: experiences of Native Americans. Health Serv Res. 2019;54(S2):1431-1441. doi:10.1111/1475-6773.13224

19.

Agree

King

Castro

Wiley

Borzekowski

. “It’s got to be on this page”: age and cognitive style in a study of online health information seeking. J Med Internet Res. 2015;17(3):e79. doi:10.2196/jmir.3352

20.

Manierre

. Gaps in knowledge: tracking and explaining gender differences in health information seeking. Soc Sci Med. 2015;128:151-158. doi:10.1016/j.socscimed.2015.01.028

21.

Myrick

Willoughby

. Educated but anxious: how emotional states and education levels combine to influence online health information seeking. Health Informatics J. 2019;25(3):649-660. doi:10.1177/1460458217719561

22.

Bhaskar

O’Hara

. Indian health service coverage among American Indians and Alaska natives in federal tribal areas. J Health Care Poor Underserved. 2017;28(4):1361-1375. doi:10.1353/hpu.2017.0120

23.

Duran

Oetzel

Lucero

, et al. Obstacles for rural American Indians seeking alcohol, drug, or mental health treatment. J Consult Clin Psychol. 2005;73(5):819-829. doi:10.1037/0022-006X.73.5.819

24.

Holm

Vogeltanz-Holm

Poltavski

McDonald

. Assessing health status, behavioral risks, and health disparities in American Indians living on the northern plains of the U.S. Public Health Rep. 2010;125(1):68-78. doi:10.1177/003335491012500110

25.

Towne

Smith

Ory

. Geographic variations in access and utilization of cancer screening services: examining disparities among American Indian and Alaska native elders. Int J Health Geogr. 2014;13(1):18. doi:10.1186/1476-072X-13-18

26.

Williams-Piehota

McCormack

Treiman

Bann

. Health information styles among participants in a prostate cancer screening informed decision-making intervention. Health Educ Res. 2008;23(3):440-453. doi:10.1093/her/cyn011

27.

Huurne

Gutteling

. Information needs and risk perception as predictors of risk information seeking. J Risk Res. 2008;11(7):847-862. doi:10.1080/13669870701875750

28.

Werk

Hill

Graber

. Impact of knowledge, self-efficacy, and perceived importance on steps taken toward cancer prevention among college men and women. J Cancer Educ. 2017;32(1):148-154. doi:10.1007/s13187-016-0996-3

29.

Ghiasi

. Health information needs, sources of information, and barriers to accessing health information among pregnant women: a systematic review of research. J Matern Fetal Neonatal Med. 2021;34(8):1320-1330. doi:10.1080/14767058.2019.1634685

30.

Scantlebury

Booth

Hanley

. Experiences, practices and barriers to accessing health information: a qualitative study. Int J Med Inf. 2017;103:103-108. doi:10.1016/j.ijmedinf.2017.04.018

31.

Hou

Shim

. The role of provider–patient communication and trust in online sources in internet use for health-related activities. J Health Commun. 2010;15(sup3):186-199. doi:10.1080/10810730.2010.522691

32.

Soroya

Farooq

Mahmood

Isoaho

Zara

S-e

. From information seeking to information avoidance: understanding the health information behavior during a global health crisis. Inf Process Manag. 2021;58(2):102440. doi:10.1016/j.ipm.2020.102440

33.

Barbour

Rintamaki

Ramsey

Brashers

. Avoiding health information. J Health Commun. 2012;17(2):212-229. doi:10.1080/10810730.2011.585691

34.

Strecher

McEvoy DeVellis

Becker

Rosenstock

. The role of self-efficacy in achieving health behavior change. Health Educ Q. 1986;13(1):73-92. doi:10.1177/109019818601300108

35.

Brown

Ganesan

Challagalla

. Self-efficacy as a moderator of information-seeking effectiveness. J Appl Psychol. 2001;86(5):1043-1051. doi:10.1037/0021-9010.86.5.1043

36.

Wolff

Massett

Maibach

Weber

Hassmiller

Mockenhaupt

. Validating a health consumer segmentation model: behavioral and attitudinal differences in disease prevention-related practices. J Health Commun. 2010;15(2):167-188. doi:10.1080/10810730903528041

37.

Feinberg

Frijters

Johnson-Lawrence

Greenberg

Nightingale

Moodie

. Examining associations between health information seeking behavior and adult education status in the U.S.: an analysis of the 2012 PIAAC data. PLoS One. 2016;11(2):e0148751. doi:10.1371/journal.pone.0148751. Zeeb H, ed.

38.

Rowley

Johnson

Sbaffi

. Gender as an influencer of online health information-seeking and evaluation behavior. J Assoc Inf Sci Technol. 2017;68(1):36-47. doi:10.1002/asi.23597

39.

Miller

LMS

Bell

. Online health information seeking: the influence of age, information trustworthiness, and search challenges. J Aging Health. 2012;24(3):525-541. doi:10.1177/0898264311428167

40.

Bissell

. The digital divide dilemma: preserving native American culture while increasing access to information technology on reservations. J Law Technol Policy. 2004. Published online.

41.

Greenberg

Haney

Blake

Moser

Hesse

. Differences in access to and use of electronic personal health information between rural and urban residents in the United States. J Rural Health. 2018;34(S1):s30-s38. doi:10.1111/jrh.12228

42.

Hale

Cotten

Drentea

Goldner

. Rural-urban differences in general and health-related internet use. Am Behav Sci. 2010;53(9):1304-1325. doi:10.1177/0002764210361685

43.

Lee

Kanthawala

Choi

Kim

. Rural and non-rural digital divide persists in older adults: internet access, usage, and attitudes toward technology. Gerontechnology. 2021;20(2):1-9. doi:10.4017/gt.2021.20.2.32-472.12

44.

Filippi

Pacheco

McCloskey

, et al. Internet use for health information among American Indians: facilitators and inhibitors. J Health Dispar Res Pract. 2014;7(3):4.

45.

Indian health service. Disparities. Published online October 2019. https://www.ihs.gov/newsroom/factsheets/disparities/

46.

Geana

Greiner

Cully

Talawyma

Daley

. Improving health promotion to American Indians in the Midwest United States: preferred sources of health information and its use for the medical encounter. J Community Health. 2012;37(6):1253-1263. doi:10.1007/s10900-012-9564-x

47.

Park

Goering

. The health-related uses and gratifications of YouTube: motive, cognitive involvement, online activity, and sense of empowerment. J Consum Health Internet. 2016;20(1-2):52-70. doi:10.1080/15398285.2016.1167580

48.

Xiao

Lee

Zeng

. Internet uses for general, health-related, and smoking cessation information seeking from gender and uses and gratifications frameworks. Int J Commun. 2022;16:789-813. Published online January 14, 2022. https://ijoc.org/index.php/ijoc/article/view/17735

49.

Niu

Willoughby

Zhou

. Associations of health literacy, social media use, and self-efficacy with health information–seeking intentions among social media users in China: cross-sectional survey. J Med Internet Res. 2021;23(2):e19134. doi:10.2196/19134

50.

Zeng

. The relationship between self-efficacy and online health information seeking: a meta-analysis. Adv Psychol Sci. 2023;31(4):535. doi:10.3724/SP.J.1042.2023.00535

51.

Kivits

. Everyday health and the internet: a mediated health perspective on health information seeking. Sociol Health Illn. 2009;31(5):673-687. doi:10.1111/j.1467-9566.2008.01153.x

52.

US Census Bureau . Census Bureau releases new American community survey selected population tables and American Indian and Alaska Native Tables. Census.gov. https://www.census.gov/newsroom/press-releases/2023/acs-selected-population-aian-tables.html. Accessed June 23, 2025.

Health Information Seeking Behavior Among American Indian and Alaska Native Peoples

Abstract

Purpose

Design

Setting

Subjects

Analysis

Results

Conclusion

Keywords

Purpose

Research Questions

Methods

Design

Sample

Measures

HISB

Preferred Sources

Perceived Importance

Prevention Orientation

Perceived Self-Efficacy

Analysis

Results

Descriptive Analysis

Analysis

Discussion

So What?

What Is Already Known on This Topic?

What Does This Article Add?

What Are the Implications for Health Promotion Practice or Research?

Footnotes

Acknowledgements

ORCID iD

Ethical Considerations

Consent to Participate

Author Contributions

Funding

Declaration of Conflicting Interests

References