Literature DB >> 31038687

Data Resource Profile: The National Cancer Institute's Health Information National Trends Survey (HINTS).

Lila J Finney Rutten1, Kelly D Blake2, Victoria G Skolnick1, Terisa Davis3, Richard P Moser2, Bradford W Hesse2.   

Abstract

Entities:  

Mesh:

Year:  2020        PMID: 31038687      PMCID: PMC7124481          DOI: 10.1093/ije/dyz083

Source DB:  PubMed          Journal:  Int J Epidemiol        ISSN: 0300-5771            Impact factor:   7.196


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Data resource basics

The National Cancer Institute’s (NCI) Health Information National Trends Survey (HINTS) was conceived in 1997 during a multidisciplinary conference focused on risk communication with attenders representing the fields of psychology, health behaviour and education, public health, clinical medicine and health journalism. The key recommendation born of this conference encouraged NCI to develop a communication-specific population survey to track trends in US adults' access to, need for and use of health and cancer information. Heeding the call for development of a national communication survey, NCI developed a nationally representative survey to assess trends in cancer-related communication, health information-seeking and cancer-related knowledge, attitudes and behaviour. HINTS is a cross-sectional, nationally representative survey of the US non-institutionalized adult population (aged 18 years and older) which collects data on health-related information and health-related knowledge, attitudes and behaviour., HINTS was first fielded in 2002–03 and the general population survey has been administered five times over a 15-year period, with HINTS 4 and 5 including multiple annual cross-sectional data collection cycles. The resulting data (n = 37 365) can be tracked for trends over time or, if there are no trends anticipated a priori, can be aggregated into a larger sample for further analysis. Table 1 summarizes survey design and implementation details for each completed survey administration, including survey field period, survey mode, total sample size, response rate, and number of cancer patients and survivors.
Table 1.

Health Information National Trends Survey (HINTS) survey design and implementation characteristics (2003–17)

HINTS 1HINTS 2HINTS 3HINTS 4
HINTS 5
Cycle 1Cycle 2Cycle 3Cycle 4Cycle 1
Field period initiated20022005200820112012201320142017
ModeRDDRDDMail & RDDMailMailMailMailMail
Total no. of respondents63695586Mail: 3582 RDD: 409239593630318536773285
Response rate33.0%24.0%Mail: 40.0% RDD: 24.2%36.7%40.0%35.2%34.4%32.4%
No. cancer patients/survivors7638731001563464459542504
Health Information National Trends Survey (HINTS) survey design and implementation characteristics (2003–17)

Data collected

HINTS 1 was administered in 2002–03 as a random digit dial (RDD) computer-assisted telephone interview to a representative sample of US households drawn from all telephone exchanges in the US. One adult aged 18 years or older within each household was selected for the extended interview during a household screening. Interviews were conducted in English or Spanish, depending on respondent preference. Further details about the sample and sampling design are published elsewhere. HINTS 2 was administered in 2005 as an RDD computer-assisted telephone interview to a representative sample of U.S. households drawn from all telephone exchanges in the U.S. One adult from each household was selected for interview, which was conducted in English or Spanish according to respondent preference. Further details about sampling design are published elsewhere. HINTS 3 was fielded in 2008 using a mixed-mode, dual-frame design. One sample frame was a list-assisted RDD computer-assisted telephone interview, wherein one adult from each household was selected for an interview. Interviews were conducted in English or Spanish, depending on respondent preference. The second sample frame was a comprehensive national listing of addresses available from the United States Postal Service. These households were administered a mailed survey. In the mail sample, all adults in the household at each sampled address were asked to complete a questionnaire. Thus, the mail sample was a stratified cluster sample, in which the household was the cluster. Further details on the HINTS 3 survey design and operations are published elsewhere. The HINTS 4 administration included four cross-sectional mail-mode data collection cycles over 4 years starting in 2011 and concluding in 2014 (Table 1). HINTS 4 Cycles 1–4 were administered as mailed questionnaires using a sampling frame of addresses provided by Marketing Systems Group (MSG). The protocol for mailing the questionnaires involved an initial mailing of the questionnaire, followed by a reminder postcard, and up to two additional mailings of the questionnaire as needed for non-responding households. Most households received one survey per mailing (in English), whereas households that were potentially Spanish-speaking received two surveys per mailing (one in English and one in Spanish). In the second stage of sampling, one adult from each sampled household was selected for participation. Further details on the survey design and operations for the HINTS 4 data collection cycles have been previously described. HINTS 5 includes four cross-sectional data collection cycles over 4 years, starting in 2017 and scheduled to end in 2020. The first of the HINTS 5 data collection cycles (HINTS 5, Cycle 1) was conducted in 2017. HINTS 5, Cycle 1 was administered as a single-mode mailed survey using a sampling frame of addresses provided by MSG, following the same protocol as HINTS 4. Further details on the HINTS 5, Cycle 1 data collection have been previously published. Three additional topic-specific HINTS modules, not described in this data resource profile, were fielded in 2009 (HINTS Puerto Rico), 2015 (HINTS-FDA Cycle 1) and 2017 (HINTS-FDA Cycle 2).

Data quality

To ensure data quality before data collection, each HINTS administration has included cognitive testing for each HINTS instrument, with testing particularly focused on new questions. The goal of cognitive testing is to provide valid measures of the constructs of interest with a minimum of response error. Testing was conducted on both paper and RDD surveys. After data collection, data quality efforts for the RDD surveys include direct data entry. The computer-assisted telephone interview (CATI) program ensures that proper skip patterns are followed and constrains data entry to valid values for each survey item. The CATI program also allows for range and edit checks on the entry of numerical responses to questions such as age, length of time since last search for health information, servings of fruits or vegetables consumed daily, height and weight and other numerical response questions. For mailed surveys, post-data collection quality control checks are conducted on the scanned data and electronic images of the survey. Quality assurance staff compare the hard-copy questionnaire with the data captured in the database item-for-item and the images stored in the repository page-for-page, to ensure that all items are correctly captured. Scanned data are validated according to HINTS specifications. Violations of validation rules (such as marking more than one choice box in a mark-only-one question) are flagged and reviewed. Additionally, quality assurance staff closely review frequencies and cross tabulations of the HINTS raw data to identify outliers and to verify open-ended items.

Survey constructs and measures

Each HINTS administration includes a core set of items. Table 2 summarizes the key constructs represented in the survey core of HINTS and describes the nature of the associated survey items. Core constructs include health information-seeking, cancer prevention and screening, cancer-related knowledge and behaviour; cancer risk perceptions; health care use and access; and technology utilization and access. Additional constructs or items have been included in specific HINTS administrations to capture timely or emerging phenomena or to glean greater detail on core constructs. Table 3 summarizes the sociodemographic characteristics of the total sample and weighted estimates for each of the survey administrations. Estimates are weighted to correct for non-response bias and to be representative of the US population; population distributions therefore reflect those of the US population with regard to age, sex, race and ethnicity.
Table 2.

Core constructs measured in the Health Information National Trends Survey (HINTS)

ConstructMeasures
SociodemographicsAge, sex, race, ethnicity, income, home ownership status, financial strain, health insurance coverage, education, marital status, employment status, country of origin (US vs other), health status, cancer history
Health information-seekingEver sought health information, health information sources, trust in health information sources, confidence in health information-seeking, information-seeking experiences, internet use for health information
Cancer prevention and screening knowledge and behaviourColorectal, breast, and cervical cancer screening, HPV vaccination
Cancer-related behaviourTobacco use, sun safety, physical activity, diet
Cancer risk perceptionsConfusion, fatalism, health beliefs, perceived risk of developing cancer
Health care use and accessUsual source of care, cost barrier to care, patient-provider communication
Technology use and accessInternet access through dial-up, broadband, cellular network, wireless network; use of internet for health-related reasons; ownership of tablet computers, smartphones, basic cellphones; use of health-related apps; use of social media for health-related reasons
Table 3.

Sample size and weighted estimates for HINTS respondents by sociodemographic characteristics

HINTS 1HINTS 2HINTS 3HINTS 4
HINTS 5Combined
2003
2005
2008
Cycle 1 (2011)
Cycle 2 (2012)
Cycle 3 (2013)
Cycle 4 (2014)
Cycle 1 (2017)
Total
N % N % N % N % N % N % N % N % N %
Total636911.4558611.7767412.2395912.7363012.9318512.7367712.9328513.437 365100.0
Sex
 Female384851.9365751.9469651.4230451.5217251.4190651.6218451.7191451.122 68151.6
 Male252148.1192948.1296948.6155248.5139048.6119748.4142448.3130348.914 28548.4
Age
 18-34165631.2103731.0111330.858230.352930.542627.246730.836721.9617729.1
 35-49196131.1149430.1183129.693227.384526.471230.574326.765528.7917328.8
 50-64149221.5152222.8245123.1133925.2116825.6107025.1122025.1106330.111 32524.9
 65-746949.78129.311898.45839.25559.45149.46379.667611.156609.5
>=755486.67076.710108.14558.04148.03607.94287.93858.243077.7
Race/ethnicity
 Hispanic76411.749613.062212.846114.551115.051115.454015.142715.7433214.2
 NH White427671.8410369.9544569.3243166.8204367.1158466.9196066.6186865.723 71067.9
 NH Black71610.543810.068711.557611.449610.942110.553411.340910.3427710.8
 NH Other3126.02997.14246.42717.42087.12097.22396.92498.322117.1
Education
 Less than high school74716.968714.568313.939112.832913.52979.730811.62178.7365912.6
 High school graduate182832.0144729.9180426.678523.177520.369924.467018.261622.9862424.5
 Some college163726.8154532.2219234.8116731.1105737.693332.7109030.094232.810 56332.3
 College graduate192724.3169623.5263724.7153132.9138028.6116733.2145840.1140635.613 20230.6
Income
 <$20, 0001 11119.289917.7114219.882924.374021.968020.277419.455917.4673420.0
 $20, 000 to <$35, 000129522.586817.7105616.758417.250114.941814.548912.742312.2563415.9
 $35, 000 to <$50, 00095817.665214.287314.052012.645915.539414.748214.838614.9472414.7
 $50, 000 to <$75, 00095517.792422.0120319.159416.952416.844617.755017.253019.1572618.2
 $75, 000+121423.1115028.4204130.4103129.092631.080133.097935.9106436.3920631.1
Metro/non-metro county
 Metro517480.9435280.0619282.2332184.2308783.7270982.1315783.6281284.430 80482.7
 Non-metro119519.1123420.0148217.863815.854316.347617.952016.447315.6656117.3
Core constructs measured in the Health Information National Trends Survey (HINTS) Sample size and weighted estimates for HINTS respondents by sociodemographic characteristics

Regulatory and ethical considerations

Each HINTS administration has been approved through expedited review by the Westat Institutional Review Board, and subsequently deemed exempt by the U.S. National Institutes of Health Office of Human Subjects Research Protections.

Data resource use

HINTS data are used by researchers to explore use of different communication channels to obtain health information among the US adult population; these data are also used to assess public knowledge and attitudes about health-relevant topics. HINTS data are used by programme planners to identify health information and communication facilitators and barriers within and across populations, and to inform the development of effective health communication strategies. Social scientists use HINTS data to test and refine their theories of health communication in the information age and to guide recommendations for theory-driven interventions aimed at improving population health. HINTS data have been used to pursue a wide variety of research questions. To date, there have been more than 400 peer-reviewed articles, published in more than 160 journals, which have used HINTS data, and an edited dedicated book comprising the HINTS knowledge base. As an illustrative example, two special issues of the Journal of Health Communication have featured HINTS articles, following from HINTS research presented at the national HINTS Data Users Conferences. The first special issue, The Health Information National Trends Survey (HINTS): Research from the Baseline, was published in 2006, featuring data from the inaugural HINTS data collection. Studies published in this special issue covered a range of topics including cancer knowledge,, cancer cognition and risk perceptions, and cancer information-seeking and communication. The second special issue, Partners in Progress: Informing the Practice of Health Communication through National Surveillance, was published in 2010. This special issue featured analysis of data from the first three administrations of HINTS and included studies on the following topics: health communication surveillance methodology,, health communication and information-related disparities, patient-provider communication, and use of the internet and health communication technology., Highly cited articles from these special issues offer examples of the specific research topics pursued through use of HINTS data. Viswanath and colleagues examined the relationship between publicity and knowledge gaps using two cancer topics with varied levels of publicity: knowledge about tobacco and sun exposure. Results indicated that education and income were associated with awareness of the smoking and cancer link despite heavy media attention, and having at least a high school education was associated with knowledge of the sun exposure and cancer link. Dillard and colleagues assessed whether perceived risk of developing lung cancer was associated with acceptance of smoking-related myths and beliefs. Those whose perceived that risk was less than their objective risk (unrealistic optimists) were more likely to report: that there is no risk of developing lung cancer among those who smoke only a few years; and that developing lung cancer is determined by genetic factors. Unrealistic optimists were less likely to report an intention to quit smoking. Koch-Weser and colleagues examined sociodemographic factors associated with use of the internet for health information-seeking and found that those who used the internet to seek health information were younger, had higher education and income, preferred numbers to words to describe risk and were more likely to indicate that it is important to get personal medical information electronically. A complete bibliography of HINTS publications is maintained on the HINTS website: [https://hints.cancer.gov/publications-reports/hints-publications.aspx]. A variety of other HINTS reports are also available: [https://hints.cancer.gov/publications-reports/nci-reports.aspx]. A series of HINTS Briefs have been developed to provide population-level estimates for specific survey questions and to summarize noteworthy research findings by demographic characteristics: [https://hints.cancer.gov/publications-reports/hints-briefs.aspx]. HINTS Briefs are targeted toward results users who want to use HINTS data to inform their applied work. Many HINTS Briefs also summarize research findings from recent peer-reviewed journal articles using HINTS data. The following are some of the topics summarized in HINTS Briefs: Considerations for Developing Effective Health Communication Strategies; Preventing Cancer through Increased Human Papillomavirus (HPV) Vaccine Uptake; and Developing an Electronic Health Information System for High-Quality Cancer Care.

Cancer patients and survivors

HINTS data have been extensively used to characterize the experiences of cancer patients and survivors. We conducted a review of the literature to identify published studies using HINTS data focused on cancer patients and survivors. We searched MEDLINE and EMBASE from 1 January 2003 to 15 May 15 2018, using the following search terms: health information national trend* or HINTS as text phrases, AND survivor* or cancer* OR explode neoplasms [MeSH]. This search returned 229 abstracts. All abstracts were reviewed to identify those meeting the following conditions: (i) the study used data from U.S. national collection of the Health Information National Trends Survey (HINTS); and (ii) the study focused on cancer survivors/patients or compared cancer survivors or patients with other populations. Studies that used HINTS items or a HINTS instrument to collect data in a special (non-national) population were excluded, and studies that used cancer history as a control variable (i.e. not a variable of specific interest) were also excluded. A total of 35 articles met the inclusion criteria and were reviewed. The following themes emerged in the focus of the articles reviewed: information seeking trends, experiences and sources; patient-centred communication and clinical care; use of internet and mobile technology in health; health-related behaviour; cancer cognition; and health status and health outcomes. Table 4 summarizes the sociodemographic, cancer diagnosis and treatment status characteristics of the cross-sectional cohorts of cancer patients and survivors for each relevant HINTS administration. The table summarizes the total number of cancer patients per each survey administration, describes the sociodemographic characteristics thereof and indicates counts and percentages for specific cancer types. Across the survey years, the most frequent cancer types were breast, colon, cervical, skin, prostate, melanoma and endometrial cancer. In each survey year, most cancer patients reported receiving treatment for their cancer (range: 81.5–91.8%), with the majority of respondents reporting at least 2 years since diagnosis. These data offer a rich resource for examination of cancer patients’ and survivors’ cancer-related knowledge, attitudes and behaviours, as well as their information-seeking experiences and needs.
Table 4.

Sample size and weighted estimates for HINTS respondents with a personal history of cancer by sociodemographic characteristics and cancer-related characteristics

HINTS 1HINTS 2HINTS 3HINTS 4
HINTS 5Combined
2003
2005
2008
Cycle 1 (2011)
Cycle 2 (2012)
Cycle 3 (2013)
Cycle 4 (2014)
Cycle 1 (2017)
Total
N % N % N % N % N % N % N % N % N %
Have you ever been diagnosed as having cancer?
 Yes76310.7787311.311, 0017.255638.534648.194598.085428.525048.645, 1698.88
Sex
 Female53264.5759656.0959056.6531757.8325854.7728059.9631962.4130359.68319559.08
 Male23135.4327743.9141143.3522942.1720045.2316840.0420537.5918740.32190840.92
Age
 18-34578.78295.09182.54143.08155.80124.6693.7841.711584.56
 35-4913919.7111717.5510114.894610.084511.784015.374815.073010.5056614.53
 50-6422930.4424632.1832334.1020235.0013831.9513729.6416434.8217137.16161033.10
 65-7416421.2923322.7827822.3614424.9812624.5914125.8514622.3015324.95138523.59
 >=7517319.7824622.4027026.1214526.8613525.8712024.4914624.0312525.67136024.21
Race/ethnicity
 Hispanic384.69335.12404.96274.72428.92375.775111.24368.513046.67
 NH White61382.7073084.5884484.3741182.6132080.4228584.4333780.3834076.18388081.93
 NH Black517.51375.03548.18516.36396.52367.08506.235111.363697.24
 NH Other315.09385.27352.50326.30184.13162.72222.15223.942144.15
Education
 Less than high school8617.0710514.1910015.975613.814216.114611.544815.70306.8651313.86
 High school graduate24637.0223331.4824226.7014026.3810619.0210625.129416.0011727.53128426.51
 Some college18522.8526630.7326828.7716126.9015139.7513230.2416431.9514734.72147430.66
 College graduate22823.0623923.6038428.5519332.9116025.1216233.1020936.3619330.89176828.97
Income
<$20, 00015022.1217222.0216021.1112824.538418.849617.5511418.529018.4099420.42
 $20, 000 to <$35, 00017725.6314320.5816118.618816.916415.504611.827913.957413.2483217.14
 $35, 000 to <$50, 00010618.789514.2913417.318118.005915.676114.227014.98519.7565715.28
 $50, 000 to <$75, 00010014.3912719.8914616.617414.696418.467320.797313.688222.2173917.61
 $75, 000+11719.0714123.2224126.3612125.8711131.5410935.6313738.8815436.40113129.54
Metro/non-metro county
 Metro61379.5467678.3079879.3345982.2337674.0338983.7546180.1642681.99419879.89
 Non-metro15020.4619721.7020320.6710417.778825.977016.258119.847818.0197120.11
Derived variable to categorize responses on cancer typea
 Bladder cancer only101.38131.78171.5440.7481.4661.52111.3050.76741.31
 Bone cancer only10.2320.1950.7910.090.0.20.1210.01120.16
 Breast cancer only10813.1116414.2513913.027710.936512.547217.138715.368314.7279513.89
 Cervical cancer only9011.32607.74668.98377.46338.39305.46307.10298.673758.18
 Colon cancer only415.54374.44505.02305.10152.61173.42203.31235.082334.35
 Endometrial cancer only364.88352.79312.64133.26102.87111.92154.11101.581613.04
 Head/neck cancer only80.8150.7750.7571.3530.7240.92101.8561.47481.08
 Hodgkins only61.0340.3440.5784.1720.4271.1343.16351.36
 Renal cancer only111.69121.29100.7150.7851.21102.0392.1340.51661.30
 Leukaemia only40.5130.49131.3681.2330.5950.7272.4971.44501.08
 Liver cancer only20.2210.3020.080.0.30.7810.4990.23
 Lung cancer only131.9291.77161.8561.15102.6661.7481.1082.07761.78
 Melanoma only527.66688.78677.75265.21194.39205.97274.99234.583026.22
 Non-Hodgkin only91.4281.0761.2271.3061.9540.3592.08491.17
 Oral cancer only60.8820.2530.2030.7040.9510.1310.170.200.42
 Ovarian cancer only212.69213.46161.46132.6460.6340.6040.5220.05871.59
 Pancreatic cancer only20.2310.0730.240.10.0430.170.20.35120.14
 Pharyngeal cancer only50.6061.6061.3510.0510.0910.1120.670.220.57
 Prostate cancer only619.62719.72878.48539.975110.76549.47598.33426.204789.08
 Rectal cancer only20.1320.0920.1530.180.0.20.2140.78150.20
 Skin cancer only13816.3016217.8823922.4411623.089220.0510725.4011725.0212424.95109521.67
 Stomach cancer only51.4591.6530.350.30.5020.1710.0120.71250.66
 More than one cancer checked607.5411511.3214014.2010718.448218.216614.176513.937013.6370513.72
 Other cancer only628.71577.01504.99325.76265.86246.57285.01346.723136.42
 Lymphoma only (HINTS 1)192.81190.39
Did you ever receive any treatment for your cancer?
 Yes72181.4586286.9241791.0147789.1345791.76293487.83
 No15118.5512013.08448.995510.87408.2441012.17
How long ago were you diagnosed with cancer? (derived)
Less than 1 year since diagnosis11516.6211915.959910.90589.885610.005814.495712.436115.2262313.43
 2-5 years17120.3223131.1124126.6112723.4211128.4211731.1011319.929617.66120724.82
 6-10 years16423.4316016.0618417.9510120.248420.318817.739421.149520.7397019.71
 11+ years30539.6435136.8844244.5424746.4619041.2717036.6922146.5121246.39213842.04

HINTS 1 had different response options that did not have liver, Hodgkin and non-Hodgkin cancers. Hodgkin and non-Hodgkin cancers were probably combined under lymphoma.

Sample size and weighted estimates for HINTS respondents with a personal history of cancer by sociodemographic characteristics and cancer-related characteristics HINTS 1 had different response options that did not have liver, Hodgkin and non-Hodgkin cancers. Hodgkin and non-Hodgkin cancers were probably combined under lymphoma.

Strengths and weaknesses

HINTS is unique among national data resources in its focus on health communication and health information. The HINTS programme offers a resource for investigators from diverse disciplines and gives access to data that speak to population use of information and communication resources during a time of unprecedented change in the information and communication landscape. As described above and in Table 4, HINTS also provides a rich cohort of cancer patient and survivor data for secondary analysis. Since its inception, the HINTS programme has invested heavily in efforts to ensure that the data are readily and easily accessible and usable for data users and results users. The HINTS website is rich with tools to enable data access and to support data use (see Data resource access section). A variety of materials have also been developed for results users, including an online data display tool, and HINTS Briefs, which summarize key results from HINTS publications and offer insights into potential applications in public health and clinical practice. HINTS data are cross-sectional; as such, inferences about causality are generally not appropriate. Similar to other national health surveys, response rates for HINTS have declined over time., Lower response rates may introduce bias in the data, but efforts were made in each HINTS administration to reduce potential for bias through sampling and weighting procedures. Additionally, methodological research suggests that the negative impact of declining response rates on data quality may not be as dramatic as previously assumed.,, The HINTS programme team recently conducted a rigorous non-response bias analysis of data from HINTS 4 (Cycles 1 and 3) to characterize the potential impact of non-response. Findings from this study revealed that many of the demographic influences on non-response (e.g. age, socioeconomic status) can be compensated for through application of standard weighting procedures. More specific results of this non-response analysis involving comparison of response rates among population subgroups, comparison with national benchmarks, and level-of-effort analysis have been previously published. National surveys are usually constrained to measuring constructs with only one or two survey items, to reduce respondent burden. Therefore, the number of items available for measuring complex attitudinal and behavioural constructs is often limited. Although use of single items for measurement of social and behavioural constructs is not ideal, this approach is common in large-scale and national survey research., When compared with validated multi-item scales, single-item measures can have similar test–retest reliability and construct validity,; however, single items are less reliable than scales and may attenuate observed associations. Constraints on survey length may also lead to changes in the survey content over time, thereby limiting the temporal trends and comparisons that may be tracked over time. While the relatively small sample size for HINTS does not support the calculation of reliable estimates at the state level, innovative geographical information system strategies have been employed to calculate regional geographical estimates, and supplemental funding has been granted to certain NCI-designated comprehensive cancer centres to support collection of HINTS data at the local level.

Data resource access

The HINTS programme has striven from the beginning to enable users to use the HINTS data as easily as possible. HINTS data are in the public domain, and public use datasets are available for download as SAS, STATA and SPSS files from [https://hints.cancer.gov]. Each dataset is bundled with supporting documents including analytics recommendations (including example statistical software code), history document, codebook, methodology report (including details about sampling and the creation of survey weights) and annotated survey instruments. Codebooks for each dataset are also available online, and all of the instruments included in the data download bundle are annotated with variable names and allowable codes. Additionally, several resources been published describing how to use HINTS data: [https://hints.cancer.gov/meetings-trainings/how-to-hints-webinar.aspx]. Where possible, HINTS adheres to the F.A.I.R. (Findable, Accessible, Interoperable, and Reusable) principles. HINTS is as a cross-sectional national survey of non-institutionalized adults, developed to track trends in cancer-related communication, health information-seeking and cancer-related knowledge, attitudes and behaviour in the US population. It is the only national population-based survey that collects information on the US public’s need for, access to and experience with cancer-related information. HINTS was first fielded in 2002–03, and has been administered five times over approximately a 15-year period, with HINTS 4 and 5 including multiple data collection cycles (n = 37 365). HINTS was initially administered as a random digit dial (RDD) computer-assisted telephone interview to a representative sample of households drawn from all telephone exchanges in the US. In 2008, HINTS was fielded using a mixed-mode (RDD telephone interview and mailed questionnaire), dual-frame (all telephone exchanges in the US and a comprehensive national listing of United States Postal Service addresses) format. Each HINTS administration since 2008 has been conducted as a mailed survey using an address-based sampling frame. Each HINTS instrument includes a core set of items to assess: communication technology access and use, health and cancer information-seeking, cancer-related knowledge and behaviour, cancer risk perceptions and health care access. HINTS public use datasets are available for download: [https://hints.cancer.gov].

Funding

This work was supported by the National Cancer Institute via HHSN261201800002B. Conflict of interest: None declared.
  71 in total

1.  Cancer information seeking preferences and experiences: disparities between Asian Americans and Whites in the Health Information National Trends Survey (HINTS).

Authors:  Giang T Nguyen; Scarlett L Bellamy
Journal:  J Health Commun       Date:  2006

2.  Predictors of perceived risk for colon cancer in a national probability sample in the United States.

Authors:  Jennifer Hay; Elliot Coups; Jennifer Ford
Journal:  J Health Commun       Date:  2006

3.  Factors associated with patients' perceptions of health care providers' communication behavior.

Authors:  Lila J Finney Rutten; Erik Augustson; Kay Wanke
Journal:  J Health Commun       Date:  2006

4.  A Nonresponse Bias Analysis of the Health Information National Trends Survey (HINTS).

Authors:  Aaron Maitland; Amy Lin; David Cantor; Mike Jones; Richard P Moser; Bradford W Hesse; Terisa Davis; Kelly D Blake
Journal:  J Health Commun       Date:  2017-05-30

5.  Cancer risk perceptions, beliefs, and physician avoidance in Appalachia: results from the 2008 HINTS Survey.

Authors:  Robin C Vanderpool; Bin Huang
Journal:  J Health Commun       Date:  2010

6.  Providing health messages to Hispanics/Latinos: understanding the importance of language, trust in health information sources, and media use.

Authors:  Marla L Clayman; Jennifer A Manganello; K Viswanath; Bradford W Hesse; Neeraj K Arora
Journal:  J Health Commun       Date:  2010

7.  Health and cancer information seeking practices and preferences in Puerto Rico: creating an evidence base for cancer communication efforts.

Authors:  Guillermo Tortolero-Luna; Lila J Finney Rutten; Bradford W Hesse; Terisa Davis; Julie Kornfeld; Marta Sanchez; Richard P Moser; Ana Patricia Ortiz; Ruby A Serrano-Rodriguez; Kia Davis
Journal:  J Health Commun       Date:  2010

8.  HealthyME HealthyU(©2010UCPGB): a collaborative project to enhance access to health information and services for individuals with disabilities.

Authors:  Brian F Geiger; Marcia R O'Neal; Stephen L Firsing; Kay Hogan Smith; Priya Chandan; Anne Schmidt; Jeri B Jackson
Journal:  J Health Commun       Date:  2010

9.  Health behaviors in cancer survivors.

Authors:  Deborah K Mayer; Norma C Terrin; Usha Menon; Gary L Kreps; Kathy McCance; Susan K Parsons; Kathleen H Mooney
Journal:  Oncol Nurs Forum       Date:  2007-05       Impact factor: 2.172

10.  Differences in cancer information-seeking behavior, preferences, and awareness between cancer survivors and healthy controls: a national, population-based survey.

Authors:  Abbey R Roach; Emily L B Lykins; Celestine G Gochett; Emily H Brechting; Lili O Graue; Michael A Andrykowski
Journal:  J Cancer Educ       Date:  2009       Impact factor: 2.037

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  24 in total

1.  Adult Cancer Survivors' Engagement and Interest in Patient-Centered Research.

Authors:  Margaret M Lubas; Yan Lu; Aaron W Gehr; Bassam Ghabach; Bhavna Tanna; Kalyani Narra; Tara M Brinkman; Rohit P Ojha
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2019-11-18       Impact factor: 4.254

2.  Factors Associated with Reducing Disparities in Electronic Personal Heath Records Use Among Non-Hispanic White and Hispanic Adults.

Authors:  Hao Wang; Sydney E Manning; Amy F Ho; Usha Sambamoorthi
Journal:  J Racial Ethn Health Disparities       Date:  2022-04-27

3.  A multilevel, low literacy dual language intervention to promote colorectal cancer screening in community clinics in Florida: A randomized controlled trial.

Authors:  Shannon M Christy; Steven K Sutton; Rania Abdulla; Carol Boxtha; Paola Gonzalez; Lakeshia Cousin; Aldenise Ewing; Samantha Montoya; Diana Lopez; Tina Beehler; Julian Sanchez; Rodrigo Carvajal; Cathy D Meade; Clement K Gwede
Journal:  Prev Med       Date:  2022-03-17       Impact factor: 4.637

4.  State and regional estimates using seven cycles of pooled nationally representative HINTS data.

Authors:  Lee Harding; Ronaldo Iachan; Kelly Martin; Yangyang Deng; Deirdre Middleton; Richard Moser; Kelly Blake
Journal:  Soc Sci Med       Date:  2022-01-17       Impact factor: 5.379

5.  Examining Rural-Urban Differences in Fatalism and Information Overload: Data from 12 NCI-Designated Cancer Centers.

Authors:  Jakob D Jensen; Jackilen Shannon; Ronaldo Iachan; Yangyang Deng; Sunny Jung Kim; Wendy Demark-Wahnefried; Babalola Faseru; Electra D Paskett; Jinxiang Hu; Robin C Vanderpool; DeAnn Lazovich; Jason A Mendoza; Sanjay Shete; Linda B Robertson; Rajesh Balkrishnan; Katherine J Briant; Benjamin Haaland; David A Haggstrom; Bernard F Fuemmeler
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2022-01-28       Impact factor: 4.090

6.  Revisiting nutrition backlash: Psychometric properties and discriminant validity of the nutrition backlash scale.

Authors:  Jakob D Jensen; Elizabeth A Giorgi; Jennifer R Jackson; Julia Berger; Rachael A Katz; Amy R Mobley
Journal:  Nutrition       Date:  2020-07-31       Impact factor: 4.008

7.  Racial disparities in routine health checkup and adherence to cancer screening guidelines among women in the United States of America.

Authors:  Amarachukwu F Orji; Takashi Yamashita
Journal:  Cancer Causes Control       Date:  2021-07-03       Impact factor: 2.506

8.  U.S. public opinion toward policy restrictions to limit tobacco product placement and advertising at point-of-sale and on social media.

Authors:  Kelly D Blake; Anna Gaysynsky; Rachel Grana Mayne; Andrew B Seidenberg; Annette Kaufman; Heather D'Angelo; Maria Roditis; Robert E Vollinger
Journal:  Prev Med       Date:  2021-12-24       Impact factor: 4.018

9.  Relationship Between Individual Health Beliefs and Fruit and Vegetable Intake and Physical Activity Among Cancer Survivors: Results from the Health Information National Trends Survey.

Authors:  Meghan B Skiba; Elizabeth T Jacobs; Tracy E Crane; Lisa M Kopp; Cynthia A Thomson
Journal:  J Adolesc Young Adult Oncol       Date:  2021-08-05       Impact factor: 1.757

10.  Race, Educational Attainment, and E-Cigarette Use.

Authors:  Shervin Assari; Ritesh Mistry; Mohsen Bazargan
Journal:  J Med Res Innov       Date:  2019-09-14
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