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The number of adults entering higher-risk age groups for receiving a cancer diagnosis is rising, with predicted numbers of cancer cases expected to increase by nearly 50% by 2050. Living with cancer puts exceptional burdens on individuals and families during treatment and survivorship, including how they navigate their relationships with one another. One role that a member of a support network may enact is that of a surrogate seeker, who seeks information in an informal capacity on behalf of others. Individuals with cancer and surrogate seekers often use the internet to learn about cancer, but differences in their skills and strategies have received little empirical attention.
This study aimed to examine the eHealth literacy of individuals with cancer and surrogate information seekers, including an investigation of how each group evaluates the credibility of web-based cancer information. As a secondary aim, we sought to explore the differences that exist between individuals with cancer and surrogate seekers pertaining to eHealth literacies and sociodemographic contexts.
Between October 2019 and January 2020, we conducted a web-based survey of 282 individuals with cancer (n=185) and surrogate seekers (n=97). We used hierarchical linear regression analyses to explore differences in functional, communicative, critical, and translational eHealth literacy between individuals with cancer and surrogate seekers using the Transactional eHealth Literacy Instrument. Using a convergent, parallel mixed methods design, we also conducted a thematic content analysis of an open-ended survey response to qualitatively examine how each group evaluates web-based cancer information.
eHealth literacy scores did not differ between individuals with cancer and surrogate seekers, even after adjusting for sociodemographic variables. Individuals with cancer and surrogate seekers consider the credibility of web-based cancer information based on its channel (eg, National Institutes of Health). However, in evaluating web-based information, surrogate seekers were more likely than individuals with cancer to consider the presence and quality of scientific references supporting the information. Individuals with cancer were more likely than surrogate seekers to cross-reference other websites and web-based sources to establish consensus.
Web-based cancer information accessibility and evaluation procedures differ among individuals with cancer and surrogate seekers and should be considered in future efforts to design web-based cancer education interventions. Future studies may also benefit from more stratified recruitment approaches and account for additional contextual factors to better understand the unique circumstances experienced within this population.
The number of adults entering higher-risk age groups for receiving a cancer diagnosis is rising, with predicted numbers of cancer cases expected to increase by nearly 50% by 2050 [
Active participation in health care decision-making leads to better outcomes and increased quality of life and helps patients receive appropriate and cost-effective treatments [
One way in which individuals with cancer and support networks serve active roles in health care experiences is web-based health information seeking [
eHealth literacy is a dynamic, intrapersonal skill set that is shaped by the experiences, technologies, and opportunities available to an individual at a given time [
Sillence et al [
Critical eHealth literacy is defined as the knowledge and ability of a person to evaluate the credibility, relevance, and risk of exchanging web-based health information [
This study aimed to evaluate the eHealth literacy of individuals with cancer and surrogate seekers. Given that perceived skills to evaluate web-based health information do not always translate into proficient performance behaviors [
Hypothesis 1: compared with individuals with cancer, surrogate seekers will have a higher self-reported ability related to functional, communicative, critical, and translational eHealth literacy.
Research question 1: What differences exist between individuals with cancer and surrogate seekers pertaining to eHealth literacy and sociodemographic contexts?
Research question 2: What processes do individuals with cancer and surrogate seekers use to evaluate the credibility of web-based cancer information?
Between October 2019 and January 2020, we conducted a 20-minute web-based survey with adults registered with the broad consent research registry of a large southeastern medical university. The broad consent research registry is a database of individuals with cancer who volunteered to be contacted about research opportunities. We were provided with contact information for individuals with cancer who had consented to be contacted for research and who also had an International Classification of Diseases-10 code identifying cancer. Identified individuals with cancer (N=6847) were sent an email invitation, receiving up to 1 reminder. All identified individuals with cancer received a follow-up email because of our not distributing individualized survey links. This allowed potential participants to forward the email to other eligible individuals. The eligibility criteria included being an English-speaking adult (aged ≥18 years) and having used the internet to look for advice or information about (1) their own cancer or (2) a family member or friend’s cancer in the past 6 months. Surrogate seekers were identified through a snowball sampling technique. We sent an email invitation to the identified individuals with cancer:
If you have not searched for cancer information in the past six months but have a family member or friend that searches online cancer information for you, we would like to hear from them. Please consider forwarding them this email.
We did not identify dyads of patients and their support networks to examine similarities, differences, or trends. This study recruited surrogate seeker participants through referrals from individuals with cancer who completed the survey, but we did not establish any dyadic connections between patients and the surrogate seekers they recommended to complete the survey.
The participants who completed the survey were remunerated with a US $25 e–gift card for their time. The study data were collected and managed using REDCap (Research Electronic Data Capture; Vanderbilt University) tools hosted at the University of Florida [
The sociodemographic characteristics for this study, including age, sex, race, and socioeconomic status, were measured using items adopted from the Health Information National Trends Survey and the US Census Bureau (
We measured eHealth literacy using the Transactional eHealth Literacy Instrument (TeHLI) of Paige et al [
The multidimensional TeHLI includes 18 items anchored on a 5-point Likert-type scale, ranging from 1 (strongly disagree) to 5 (strongly agree). The instrument measures four competencies: (1) functional (eg, “I can summarize basic health information from the internet in my own words”); (2) communicative (eg, “I have the skills I need to talk about health topics on the internet with multiple users at the same time”); (3) critical (eg, I can tell when health information on the internet is fake”); and (4) translational (eg, “I can use the internet as a tool to improve my health”). The internal consistency of data from each dimension was sufficient for patients (Cronbach α=.85-.87) and surrogate seekers (Cronbach α=.83-.91). We also sought to understand how patients and surrogate seekers appraise web-based health information. A single, open-ended item was included in the survey asking, “When you found information online, how did you decide if the information was credible?”
This mixed methods study used a convergent parallel design, in which the quantitative and qualitative data collection occurred concurrently [
As part of the survey, an open-ended question (When you found information online, how did you decide if the information was credible?) was included to investigate how participants determine whether the health information found on the web was credible. Using a content analysis method, we first completed an inductive open-coding process to determine common themes among both respondent populations [
As a final step, integration of the data occurred by merging the quantitative results with the qualitative results [
Codes, operational definitions, and examples to guide open-ended responses.
Code | Definition | Respondent quotes |
Determined channel credibility | This code should be used when the respondent answers the question by saying they looked for credible websites and paid attention to where the information was coming from such as Mayo Clinic or a .gov or .edu website. If the respondent double-checked information, read reviews, or trusted the website, these answers could fall under this category as well. |
Published in a reputable peer-reviewed journal It came from a credible source like a journal or medical center Study was done by a credible medical institution Research or credible sample size or investigators By whom it was provided I made sure the website is accredited |
Determined source credibility | This code should be used when the respondent answers the question by saying they looked up to see who the author was and if they were credible. |
I noted the author and the credibility of the institution which it represented I had to x-ref dates and study authors to see what was most current, who was still strong in the field, etc. I looked at the credentials of the author |
Checked citations for scientific support | This code should be used when the respondent answers the question by saying they checked the resources of the information to see if it was coming from a credible source. An example of this could be if the respondent looks at the resource the information was taken from, checked the sources at the bottom of the website, age of the article, etc. |
I looked at the resources the information came from I checked the sources at the bottom of the website Age of article references Researched the sources listed Looked for citations from doctors at the bottom Source references |
Cross-referenced content with other web-based sources | This code should be used when the respondent answers the question by saying they looked at or researched several different sources or web pages to determine if the web-based health information was consistent with each other. |
How frequently it was repeated in both articles and university-based publications Cross-referencing multiple sites I checked additional websites to compare information as accurate |
Cross-referenced content with recommendations from health care | This code should be used when the respondent answers the question by saying they researched health information on the web to confirm that it aligned with what their clinician recommended. This code can also be used when a patient or caregiver confirms information found on the web between 2 websites. |
Compared information with what I had gotten from my medical source Seemed like it was in line with what my health care clinician told me Compared with information I received from my physician and medical team |
Discussed content with a health care clinician | This code should be used when the respondent answers the question by saying they discussed the information they found on the web with their health care clinician to check its credibility. |
I reviewed my symptoms with the information provided, then discussed the symptoms and information with my physician I asked my doctor about it |
Miscellaneous | This code should be used when the respondent answers the question with a response that does not fit into any other predefined reason or cannot be explicitly categorized. |
Yes it seemed helpful and made me make a doctor appointment Asked a family member It sounded reasonable with what I knew already I trust hospital information |
Uncodeable | This code should be used when the respondent answers the question with a response that does not pertain to the information asked. An example of this could be they did not answer the question correctly or provided information that is not relevant to this data. |
Not sure Yes I did Yes Had way to know just had to trust reparation Looks real if all of them about what I think |
This study received institutional review board approval from the University of Florida (IRB#201802322). Each participant completed a waiver of informed consent providing them with clear expectations of what the study entailed and provided their consent before participating. Any identifiable respondent information was anonymized according to ethical privacy standards.
A total of 303 participants responded to the survey. A small proportion (n=21, 6.9%) of the participants reported not searching for web-based cancer information in the past 6 months and were excluded from the analyses. The final sample consisted of 282 participants, which included individuals with cancer (n=185, 65.6%) and surrogate seekers (n=97, 34.4%).
Sociodemographic characteristics (patient sample, N=185).
Variables | Values | |
Age, mean (SD) | 57.44 (14.29) | |
|
||
|
Male | 50 (27) |
|
Female | 105 (56.8) |
|
Intersex | 1 (0.5) |
|
Missing | 29 (15.7) |
|
||
|
White | 142 (76.8) |
|
Hispanic or Latino | 4 (2.2) |
|
Black or African American | 8 (4.3) |
|
Other | 2 (1.1) |
|
Missing | 29 (15.7) |
|
||
|
Less than high school | 2 (1.1) |
|
High school or General Education Development | 15 (8.1) |
|
Some college | 32 (17.3) |
|
Completed college | 45 (24.3) |
|
Completed some postgraduate | 10 (5.4) |
|
Master’s degree | 31 (16.8) |
|
Other advanced degree beyond master’s | 14 (7.6) |
|
Missing | 36 (19.5) |
|
||
|
Single | 43 (23.2) |
|
Partnered | 9 (4.9) |
|
Married | 105 (56.8) |
|
Missing | 67 (36.2) |
|
||
|
Midwest | 0 (0) |
|
Northeast | 7 (3.8) |
|
Southeast | 143 (77.3) |
|
Southwest | 6 (3.2) |
|
West | 0 (0) |
|
Missing | 29 (15.7) |
|
||
|
Breast | 39 (26.4) |
|
Skin (squamous cell carcinoma, basal cell carcinoma, melanoma, and Merkel cell) | 26 (17.6) |
|
Blood (leukemia, lymphoma, and myeloma) | 12 (6.6) |
|
Lung | 10 (6.8) |
|
Thyroid | 8 (5.4) |
|
Prostate | 6 (4.1) |
|
Colon and rectal | 5 (3.4) |
|
Non-Hodgkin lymphoma | 4 (2.7) |
|
Ovarian | 4 (2.7) |
|
Pancreatic | 4 (2.7) |
|
Endometrial | 2 (1.4) |
|
Esophageal | 2 (1.3) |
|
Head and neck | 2 (1.4) |
|
Kidney | 2 (1.3) |
|
Mesothelioma | 2 (1.4) |
|
Parotid gland | 2 (1.3) |
|
Throat | 2 (1.4) |
|
Bladder | 1 (0.7) |
|
Bone | 1 (0.7) |
|
Brain | 1 (0.7) |
|
Fallopian tube | 1 (0.7) |
|
Lymphedema | 1 (0.7) |
|
Mesenteric | 1 (0.7) |
|
Sarcoma | 1 (0.7) |
|
Synovial | 1 (0.7) |
|
Testicular | 1 (0.7) |
|
Uterine | 1 (0.7) |
|
Miscellaneous or other | 6 (4.1) |
aTypes of cancers (n=148). Individuals with cancer may have reported >1 cancer type. Segments of both patients and surrogate seekers did not provide cancer type.
Sociodemographic characteristics (surrogate seeker sample, N=97).
Variables | Values | ||
Age (years), mean (SD) | 51.72 (19.99) | ||
|
|||
|
Male | 17 (18) | |
|
Female | 65 (67) | |
|
Missing | 15 (15) | |
|
|||
|
White | 69 (71) | |
|
Hispanic or Latino | 3 (3) | |
|
Black or African American | 4 (4) | |
|
Native American or American Indian | 1 (1) | |
|
Asian or Pacific Islander | 1 (1) | |
|
Other | 4 (4) | |
|
Missing | 15 (15) | |
|
|||
|
Less than high school | 1 (1) | |
|
High school or General Education Development | 6 (76) | |
|
Some college | 13 (13) | |
|
Completed college | 41 (42) | |
|
Completed some postgraduate | 2 (2) | |
|
Master’s degree | 12 (12) | |
|
Other advanced degree beyond master’s | 3 (3) | |
|
Missing | 19 (20) | |
|
|||
|
Single | 31 (32) | |
|
Partnered | 4 (4) | |
|
Married | 47 (48) | |
|
Missing | 15 (15) | |
|
|||
|
Midwest | 0 (0) | |
|
Northeast | 1 (1) | |
|
Southeast | 77 (79) | |
|
Southwest | 3 (3) | |
|
West | 0 (0) | |
|
Missing | 16 (16) | |
|
|||
|
Breast | 15 (18) | |
|
Skin (squamous cell carcinoma, basal cell carcinoma, melanoma, and Merkel cell) | 9 (11) | |
|
Colon and rectal | 9 (11) | |
|
Brain | 7 (8) | |
|
Prostate | 6 (7) | |
|
Blood (leukemia, lymphoma, and myeloma) | 4 (3) | |
|
Lung | 4 (3) | |
|
Ovarian | 4 (3) | |
|
Pancreatic | 4 (3) | |
|
Bladder | 3 (4) | |
|
Liver | 2 (2) | |
|
Kidney | 2 (2) | |
|
Oral | 2 (2) | |
|
Uterine | 2 (2) | |
|
Stomach | 2 (2) | |
|
Head and neck | 1 (1) | |
|
Endometrial | 1 (1) | |
|
Esophageal | 1 (1) | |
|
Appendix | 1 (1) | |
|
Bone | 1 (1) | |
|
Unknown (cannot remember, not sure yet, and unknown) | 3 (4) |
aTypes of cancers (n=83). Surrogate seekers may have reported >1 cancer type. Segments of both patients and surrogate seekers did not provide the cancer type.
eHealth literacy competency scores.
Competency | Values, n | Values, mean (SD) | Values, median (range) |
Functional eHealth literacy | 244 | 4.06 (0.76) | 4.00 (1-5) |
Communicative eHealth literacy | 239 | 3.29 (0.91) | 3.20 (1-5) |
Critical eHealth literacy | 238 | 3.49 (0.75) | 3.60 (1.60-5) |
Translational eHealth literacy | 239 | 3.98 (0.65) | 4.00 (2-5) |
Functional (
We also found statistically significant associations between sociodemographic variables and eHealth literacy competencies in step 1 of the hierarchical linear regression models, whether the participant was an individual with cancer or a surrogate seeker. Identifying as a female and reporting a college education resulted in a positive association with functional eHealth literacy (
Regression of surrogate seeker versus patient status on eHealth literacy.
Variable | Functional, β (SE; 95% CI) | Communicative, β (SE; 95% CI) | Critical, β (SE; 95% CI) | Translational, β (SE; 95% CI) | |
|
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|
Age (years) | −0.01 (0.01; −0.01 to 0.01) | −0.01 (0.01a; −0.02 to −0.01) | −0.01 (0.01a; −0.02 to −0.01) | .00 (0.00; −0.01 to 0.00) |
|
Sexb | −0.34 (0.11c; −0.55 to −0.13) | −0.19 (0.13; −0.45 to 0.07) | −0.25 (0.11d; −0.46 to −0.04) | −0.10 (0.10; −0.29 to 0.09) |
|
Racee | .05 (0.15; −0.25 to 0.35) | −0.11 (0.19; −0.48 to 0.25) | −0.11 (0.15; −0.40 to 0.19) | .19 (0.14; −0.07 to 0.46) |
|
Educationf | .41 (0.10 g; 0.21 to 0.61) | .34 (0.13g; 0.10 to 0.59) | .27 (0.10g; 0.07 to 0.47) | .30 (0.10g; 0.12 to 0.48) |
|
Marital statush | .17 (.10; −0.03 to 0.36) | −0.04 (0.12; −0.28 to 0.20) | .08 (0.10; −0.12 to 0.28) | −0.06 (0.09; −0.24 to 0.12) |
|
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|
Respondenti | .07 (0.10; −0.13 to 0.26) | .13 (0.12; −0.12 to 0.37) | −0.05 (0.10; −0.24 to 0.15) | −0.15 (0.09f; −0.33 to 0.03) |
a
bSex (1=male; 0=female).
c
d
eRace (1=White; 0=people of color).
fEducation (1=college educated; 0=less than college educated).
g
hMarital status (1=married; 0=not married).
iRespondent (1=caregiver; 0=patient).
Frequencies of codes reported by individuals with cancer (n=169) and surrogate seekers (n=89).
Code | Individual with cancer, n (%) | Surrogate seeker, n (%) |
Determined channel credibility | 70 (41.4) | 37 (41.6) |
Determined source credibility | 8 (4.7) | 3 (3.4) |
Checked citations for scientific support | 5 (2.9) | 16 (18)a |
Cross-referenced content with other web-based sources | 52 (30.8)b | 18 (20.2) |
Cross-referenced content with recommendations from clinicians | 6 (3.6) | 3 (3.4) |
Discussed content with clinician | 11 (6.5) | 5 (5.6) |
Miscellaneous | 13 (7.7) | 6 (6.7) |
Not coded | 4 (2.4) | 1 (1.1) |
a
b
One code that reflected a considerable difference between individuals with cancer and surrogate seekers was the mode of appraising credibility by
I checked the sources at the bottom of the website. If no sources (scholarly websites or government/organization website hosts) were provided, then I did not deem it credible.
Other surrogate seekers said, “I decided if it was credible if I had ample sources and clear answers.” (surrogate seeker ID 275; Hispanic female, 21 years old, completed some college); “There were credible references that were less than five years old.” (surrogate seeker ID 344; Black female, 56 years old, college graduate).
The second most used strategy was
The action words
Frequencies of action words reported by individuals with cancer (n=123) and surrogate seekers (n=57).
Action words | Patients, n (%) | Surrogate seekers, n (%) | |
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Looked | 22 (17.9) | 17 (29.8) |
|
Reviewed | 3 (2.4) | 0 (0) |
|
Read or reading | 16 (13) | 7 (12.3) |
|
Gathered | 1 (0.8) | 1 (1.8) |
|
Texted | 1 (0.8) | 0 (0) |
|
Searched or researched or tried to find | 11 (8.9) | 7 (12.3) |
|
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|
Spoke or speaking or discussed | 5 (4.1) | 1 (1.8) |
|
Asked | 7 (5.7) | 4 (7) |
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|
Checked or double-checked | 9 (7.3) | 4 (7) |
|
Cross-referenced | 5 (4.1) | 2 (3.5) |
|
Considered or thinking | 6 (4.9) | 0 (0) |
|
Compared | 17 (13.8) | 8 (14) |
|
Evaluated or screened | 2 (1.6) | 0 (0) |
|
Confirmed or made sure or verified | 4 (3.3) | 1 (1.8) |
|
Decided or deemed or noted | 4 (3.3) | 3 (5.3) |
|
Assumed | 2 (1.6) | 0 (0) |
|
|||
|
Used or using | 6 (4.9) | 2 (3.5) |
|
Tried | 2 (1.6) | 0 (0) |
The purpose of this study was to evaluate the eHealth literacy of individuals with cancer and surrogate seekers and explore the unique processes each group uses to evaluate web-based cancer information. Functional, communicative, critical, and translational eHealth literacy scores did not statistically significantly differ between individuals with cancer and surrogate seekers; however, we found differences in how individuals with cancer and surrogate seekers determine whether web-based cancer information is credible. This brings into question the validity of the web-based content retrieved from each group and how it influences health decisions, behaviors, and outcomes. The results demonstrate the value of understanding both the skill set and the process by which web-based content is accessed and evaluated before its exchange with others.
We did not find any statistically significant differences between individuals with cancer and surrogate seekers’ confidence in their abilities to access, exchange, evaluate, and act on web-based health information for the purposes of maintaining or improving health. Individuals with cancer and surrogate seekers reported a high degree of confidence in their eHealth literacy across all competencies; however, functional and translational eHealth literacy had a slightly higher average score than critical and communicative eHealth literacy scores.
The findings from this study align with previous literature that showed younger, more educated populations having higher eHealth literacy scores and an increased ease of accessing web-based content, often influenced by the level of use [
Heiman et al [
Regardless of their eHealth literacy skill sets, individuals with cancer and surrogate seekers most often determine credibility according to the channel of the web-based cancer information. This suggests that those seeking cancer information do not see a significant need for corroboration of web-based information if the site publishing it is perceived as credible. Several respondents noted that they determined whether web-based health information was credible based on whether they had visited a website in the past and were already familiar with it. Others determined that the information was credible if the website provided the information that the patient or surrogate seeker was searching for. Similar findings have been discussed in the scoping review by Verm et al [
Confirmation bias, or the phenomena of “seeking or interpreting evidence in ways that are partial to existing beliefs, expectations, or a hypothesis in hand” has the potential to greatly influence the subconscious motivations for seeking web-based health information in patients and supporting network roles [
More surrogate seekers than individuals with cancer reviewed the references, citations, and links provided with web-based health information to determine whether the content was credible. Conversely, more individuals with cancer than surrogate seekers cross-referenced content with other web-based sources to determine its credibility. Individuals with cancer may determine the credibility of information through sheer quantity (ie, how often it is repeated across multiple sources), whereas surrogate seekers may determine its credibility based on scientific support and quality of citations. This distinction in information-seeking behaviors and preferred evaluation methods between individuals with cancer and surrogate seekers is important to examine, as individuals with cancer are prone to misinformation and to consensus effects of information [
Identifying the diverse and unique ways in which individuals with cancer and surrogate seekers access, appraise, and evaluate the credibility of web-based cancer information could provide a deeper, more tailored design and evaluation of patient education resources. These resources are developed with the intention of being perceived as credible by each recipient, so having distinctive information on how different groups retrieve this web-based content could help us better appeal to the established behaviors that individuals with cancer and surrogate seekers use to enhance their appraisal and evaluation of the credibility of web-based information. Understanding the process by which individuals with cancer and their surrogate seekers access and evaluate web-based information credibility will further inform how to deliver educational content from varying web-based sources, hopefully increasing both patient and surrogate seekers’ autonomy and self-efficacy throughout their cancer care. While identifying the dynamic ways in which individuals with cancer and surrogate seekers access and appraise web-based cancer information yields important insights into future message design and implementation, understanding the interpersonal contexts of this population is imperative for a more refined understanding of why they execute such skills. Researchers should consider nuances related to psychological and relational factors that affect these appraisal and evaluation skills more deeply, including the level of perceived importance that the patient or surrogate seeker has for receiving credible web-based information, how their personal relationships impact their appraisal and evaluation skills, and how stress levels impact the appraisal and evaluation process.
The limitations of this study include addressing the longitudinal effects of eHealth literacy, assessing contextual factors related to individuals with blood cancer, and examining dyadic groups of individuals with cancer and surrogate seekers. First, this was a cross-sectional study, which poses a challenge given that eHealth literacy is a dynamic skill set that evolves over time, making it difficult to determine large effects from 1 period. Future surveillance research is needed to explore how eHealth literacy in individuals with cancer and surrogate seeker groups changes over time. This study explored eHealth literacy in 2 independent groups of individuals with cancer and surrogate seekers. The TeHLI is a relatively new eHealth literacy measure. Similar to the eHEALS, we recognize that more advanced statistical analyses must be conducted to strengthen evidence for its use (eg, measurement invariance and item response theory). Examining measurement invariance in future studies is particularly important as this statistical test is the only way to confirm whether a latent variable can be truly compared across 2 or more groups. Given the exploratory nature of this study, such tests were not conducted.
This study did not take possible contextual factors for individuals with cancer and surrogate seekers into account, such as date of diagnosis, how recently they received their diagnosis compared with when they searched for web-based health information, or the varying levels of stress experienced when participating in this web-based health information seeking and credibility appraisal process. Assessing these factors in future studies could assist in better understanding the unique circumstances experienced within the population and how these interpersonal factors possibly influence eHealth literacy over the course of their cancer journey.
Most respondents in this study were diagnosed with or had cared for someone with breast, skin, or some type of blood cancer. Although not consistent with national estimates of cancer incidence and prevalence [
Using the TMeHL as a theoretical foundation [
Seeing the variance between individuals with cancer and surrogate seekers in what they deem most important when evaluating the credibility of web-based health information offers several avenues for future research, including exploring the potential barriers each group encounters when searching for and appraising web-based information. According to the TMeHL [
When viewed practically, strategic messages that are targeted to a group’s preferred source or channel of information will increase the likelihood of its seeing the information as relevant and credible and have greater potential to better initiate patient and surrogate seeker engagement over the course of one’s own or a loved one’s health care management. The continual advances in computer-assisted technologies make tailoring messages to these variables an important next step, as this level of personalization can not only help enhance the individuals with cancer and surrogate seekers’ web-based health information acquisition experience, but also hold considerable potential to provide pertinent information to these populations. Our study included patients and surrogate seekers, but we did not examine the eHealth literacy skills or information-seeking behaviors of individuals with cancer with their own surrogate seekers. Future research with dyads of individuals with cancer and health care clinicians is needed to determine the value of tailored messages within this context.
Individuals with cancer and surrogate seekers report similar eHealth literacy levels, but there is evidence that these groups apply unique approaches to evaluating the credibility of web-based health information. The results of this study have important theoretical and practical implications for expanding the understanding and applicability of the TMeHL to inform future message design interventions. Future research is needed to examine how dyads of individuals with cancer and surrogate seekers evaluate web-based health information and the acceptability of collaborative patient with cancer support network dyadic eHealth literacy interventions.
Sociodemographic questions from Health Information National Trends Survey and US Census Bureau.
Surrogate seeker types.
eHealth Literacy Scale
Research Electronic Data Capture
Transactional eHealth Literacy Instrument
Transactional Model of eHealth Literacy
This work was supported by the University of Florida Clinical and Translational Science Institute grant support (National Institutes of Health National Center for Advancing Translational Sciences under grant UL1 TR000064) and the University of Florida College of Journalism and Communications Dean’s Seed Grant Funding.
The data set from which the results of this study were derived can be obtained from the corresponding author upon request.
SRP is an employee of Johnson & Johnson.